(bright upbeat music) >> Hello and welcome to this Cube Conversation. I'm John Furrier, host of theCUBE. We've got a great conversation featuring Arthur AI. I'm your host. I'm excited to have Adam Wenchel who's the Co-Founder and CEO. Thanks for joining us today, appreciate it. >> Yeah, thanks for having me on, John, looking forward to the conversation. >> I got to say, it's been an exciting world in AI or artificial intelligence. Just an explosion of interest kind of in the mainstream with the language models, which people don't really get, but they're seeing the benefits of some of the hype around OpenAI. Which kind of wakes everyone up to, "Oh, I get it now." And then of course the pessimism comes in, all the skeptics are out there. But this breakthrough in generative AI field is just awesome, it's really a shift, it's a wave. We've been calling it probably the biggest inflection point, then the others combined of what this can do from a surge standpoint, applications. I mean, all aspects of what we used to know is the computing industry, software industry, hardware, is completely going to get turbo. So we're totally obviously bullish on this thing. So, this is really interesting. So my first question is, I got to ask you, what's you guys taking? 'Cause you've been doing this, you're in it, and now all of a sudden you're at the beach where the big waves are. What's the explosion of interest is there? What are you seeing right now? >> Yeah, I mean, it's amazing, so for starters, I've been in AI for over 20 years and just seeing this amount of excitement and the growth, and like you said, the inflection point we've hit in the last six months has just been amazing. And, you know, what we're seeing is like people are getting applications into production using LLMs. I mean, really all this excitement just started a few months ago, with ChatGPT and other breakthroughs and the amount of activity and the amount of new systems that we're seeing hitting production already so soon after that is just unlike anything we've ever seen. So it's pretty awesome. And, you know, these language models are just, they could be applied in so many different business contexts and that it's just the amount of value that's being created is again, like unprecedented compared to anything. >> Adam, you know, you've been in this for a while, so it's an interesting point you're bringing up, and this is a good point. I was talking with my friend John Markoff, former New York Times journalist and he was talking about, there's been a lot of work been done on ethics. So there's been, it's not like it's new. It's like been, there's a lot of stuff that's been baking over many, many years and, you know, decades. So now everyone wakes up in the season, so I think that is a key point I want to get into some of your observations. But before we get into it, I want you to explain for the folks watching, just so we can kind of get a definition on the record. What's an LLM, what's a foundational model and what's generative ai? Can you just quickly explain the three things there? >> Yeah, absolutely. So an LLM or a large language model, it's just a large, they would imply a large language model that's been trained on a huge amount of data typically pulled from the internet. And it's a general purpose language model that can be built on top for all sorts of different things, that includes traditional NLP tasks like document classification and sentiment understanding. But the thing that's gotten people really excited is it's used for generative tasks. So, you know, asking it to summarize documents or asking it to answer questions. And these aren't new techniques, they've been around for a while, but what's changed is just this new class of models that's based on new architectures. They're just so much more capable that they've gone from sort of science projects to something that's actually incredibly useful in the real world. And there's a number of companies that are making them accessible to everyone so that you can build on top of them. So that's the other big thing is, this kind of access to these models that can power generative tasks has been democratized in the last few months and it's just opening up all these new possibilities. And then the third one you mentioned foundation models is sort of a broader term for the category that includes LLMs, but it's not just language models that are included. So we've actually seen this for a while in the computer vision world. So people have been building on top of computer vision models, pre-trained computer vision models for a while for image classification, object detection, that's something we've had customers doing for three or four years already. And so, you know, like you said, there are antecedents to like, everything that's happened, it's not entirely new, but it does feel like a step change. >> Yeah, I did ask ChatGPT to give me a riveting introduction to you and it gave me an interesting read. If we have time, I'll read it. It's kind of, it's fun, you get a kick out of it. "Ladies and gentlemen, today we're a privileged "to have Adam Wenchel, Founder of Arthur who's going to talk "about the exciting world of artificial intelligence." And then it goes on with some really riveting sentences. So if we have time, I'll share that, it's kind of funny. It was good. >> Okay. >> So anyway, this is what people see and this is why I think it's exciting 'cause I think people are going to start refactoring what they do. And I've been saying this on theCUBE now for about a couple months is that, you know, there's a scene in "Moneyball" where Billy Beane sits down with the Red Sox owner and the Red Sox owner says, "If people aren't rebuilding their teams on your model, "they're going to be dinosaurs." And it reminds me of what's happening right now. And I think everyone that I talk to in the business sphere is looking at this and they're connecting the dots and just saying, if we don't rebuild our business with this new wave, they're going to be out of business because there's so much efficiency, there's so much automation, not like DevOps automation, but like the generative tasks that will free up the intellect of people. Like just the simple things like do an intro or do this for me, write some code, write a countermeasure to a hack. I mean, this is kind of what people are doing. And you mentioned computer vision, again, another huge field where 5G things are coming on, it's going to accelerate. What do you say to people when they kind of are leaning towards that, I need to rethink my business? >> Yeah, it's 100% accurate and what's been amazing to watch the last few months is the speed at which, and the urgency that companies like Microsoft and Google or others are actually racing to, to do that rethinking of their business. And you know, those teams, those companies which are large and haven't always been the fastest moving companies are working around the clock. And the pace at which they're rolling out LLMs across their suite of products is just phenomenal to watch. And it's not just the big, the large tech companies as well, I mean, we're seeing the number of startups, like we get, every week a couple of new startups get in touch with us for help with their LLMs and you know, there's just a huge amount of venture capital flowing into it right now because everyone realizes the opportunities for transforming like legal and healthcare and content creation in all these different areas is just wide open. And so there's a massive gold rush going on right now, which is amazing. >> And the cloud scale, obviously horizontal scalability of the cloud brings us to another level. We've been seeing data infrastructure since the Hadoop days where big data was coined. Now you're seeing this kind of take fruit, now you have vertical specialization where data shines, large language models all of a set up perfectly for kind of this piece. And you know, as you mentioned, you've been doing it for a long time. Let's take a step back and I want to get into how you started the company, what drove you to start it? Because you know, as an entrepreneur you're probably saw this opportunity before other people like, "Hey, this is finally it, it's here." Can you share the origination story of what you guys came up with, how you started it, what was the motivation and take us through that origination story. >> Yeah, absolutely. So as I mentioned, I've been doing AI for many years. I started my career at DARPA, but it wasn't really until 2015, 2016, my previous company was acquired by Capital One. Then I started working there and shortly after I joined, I was asked to start their AI team and scale it up. And for the first time I was actually doing it, had production models that we were working with, that was at scale, right? And so there was hundreds of millions of dollars of business revenue and certainly a big group of customers who were impacted by the way these models acted. And so it got me hyper-aware of these issues of when you get models into production, it, you know. So I think people who are earlier in the AI maturity look at that as a finish line, but it's really just the beginning and there's this constant drive to make them better, make sure they're not degrading, make sure you can explain what they're doing, if they're impacting people, making sure they're not biased. And so at that time, there really weren't any tools to exist to do this, there wasn't open source, there wasn't anything. And so after a few years there, I really started talking to other people in the industry and there was a really clear theme that this needed to be addressed. And so, I joined with my Co-Founder John Dickerson, who was on the faculty in University of Maryland and he'd been doing a lot of research in these areas. And so we ended up joining up together and starting Arthur. >> Awesome. Well, let's get into what you guys do. Can you explain the value proposition? What are people using you for now? Where's the action? What's the customers look like? What do prospects look like? Obviously you mentioned production, this has been the theme. It's not like people woke up one day and said, "Hey, I'm going to put stuff into production." This has kind of been happening. There's been companies that have been doing this at scale and then yet there's a whole follower model coming on mainstream enterprise and businesses. So there's kind of the early adopters are there now in production. What do you guys do? I mean, 'cause I think about just driving the car off the lot is not, you got to manage operations. I mean, that's a big thing. So what do you guys do? Talk about the value proposition and how you guys make money? >> Yeah, so what we do is, listen, when you go to validate ahead of deploying these models in production, starts at that point, right? So you want to make sure that if you're going to be upgrading a model, if you're going to replacing one that's currently in production, that you've proven that it's going to perform well, that it's going to be perform ethically and that you can explain what it's doing. And then when you launch it into production, traditionally data scientists would spend 25, 30% of their time just manually checking in on their model day-to-day babysitting as we call it, just to make sure that the data hasn't drifted, the model performance hasn't degraded, that a programmer did make a change in an upstream data system. You know, there's all sorts of reasons why the world changes and that can have a real adverse effect on these models. And so what we do is bring the same kind of automation that you have for other kinds of, let's say infrastructure monitoring, application monitoring, we bring that to your AI systems. And that way if there ever is an issue, it's not like weeks or months till you find it and you find it before it has an effect on your P&L and your balance sheet, which is too often before they had tools like Arthur, that was the way they were detected. >> You know, I was talking to Swami at Amazon who I've known for a long time for 13 years and been on theCUBE multiple times and you know, I watched Amazon try to pick up that sting with stage maker about six years ago and so much has happened since then. And he and I were talking about this wave, and I kind of brought up this analogy to how when cloud started, it was, Hey, I don't need a data center. 'Cause when I did my startup that time when Amazon, one of my startups at that time, my choice was put a box in the colo, get all the configuration before I could write over the line of code. So the cloud became the benefit for that and you can stand up stuff quickly and then it grew from there. Here it's kind of the same dynamic, you don't want to have to provision a large language model or do all this heavy lifting. So that seeing companies coming out there saying, you can get started faster, there's like a new way to get it going. So it's kind of like the same vibe of limiting that heavy lifting. >> Absolutely. >> How do you look at that because this seems to be a wave that's going to be coming in and how do you guys help companies who are going to move quickly and start developing? >> Yeah, so I think in the race to this kind of gold rush mentality, race to get these models into production, there's starting to see more sort of examples and evidence that there are a lot of risks that go along with it. Either your model says things, your system says things that are just wrong, you know, whether it's hallucination or just making things up, there's lots of examples. If you go on Twitter and the news, you can read about those, as well as sort of times when there could be toxic content coming out of things like that. And so there's a lot of risks there that you need to think about and be thoughtful about when you're deploying these systems. But you know, you need to balance that with the business imperative of getting these things into production and really transforming your business. And so that's where we help people, we say go ahead, put them in production, but just make sure you have the right guardrails in place so that you can do it in a smart way that's going to reflect well on you and your company. >> Let's frame the challenge for the companies now that you have, obviously there's the people who doing large scale production and then you have companies maybe like as small as us who have large linguistic databases or transcripts for example, right? So what are customers doing and why are they deploying AI right now? And is it a speed game, is it a cost game? Why have some companies been able to deploy AI at such faster rates than others? And what's a best practice to onboard new customers? >> Yeah, absolutely. So I mean, we're seeing across a bunch of different verticals, there are leaders who have really kind of started to solve this puzzle about getting AI models into production quickly and being able to iterate on them quickly. And I think those are the ones that realize that imperative that you mentioned earlier about how transformational this technology is. And you know, a lot of times, even like the CEOs or the boards are very personally kind of driving this sense of urgency around it. And so, you know, that creates a lot of movement, right? And so those companies have put in place really smart infrastructure and rails so that people can, data scientists aren't encumbered by having to like hunt down data, get access to it. They're not encumbered by having to stand up new platforms every time they want to deploy an AI system, but that stuff is already in place. There's a really nice ecosystem of products out there, including Arthur, that you can tap into. Compared to five or six years ago when I was building at a top 10 US bank, at that point you really had to build almost everything yourself and that's not the case now. And so it's really nice to have things like, you know, you mentioned AWS SageMaker and a whole host of other tools that can really accelerate things. >> What's your profile customer? Is it someone who already has a team or can people who are learning just dial into the service? What's the persona? What's the pitch, if you will, how do you align with that customer value proposition? Do people have to be built out with a team and in play or is it pre-production or can you start with people who are just getting going? >> Yeah, people do start using it pre-production for validation, but I think a lot of our customers do have a team going and they're starting to put, either close to putting something into production or about to, it's everything from large enterprises that have really sort of complicated, they have dozens of models running all over doing all sorts of use cases to tech startups that are very focused on a single problem, but that's like the lifeblood of the company and so they need to guarantee that it works well. And you know, we make it really easy to get started, especially if you're using one of the common model development platforms, you can just kind of turn key, get going and make sure that you have a nice feedback loop. So then when your models are out there, it's pointing out, areas where it's performing well, areas where it's performing less well, giving you that feedback so that you can make improvements, whether it's in training data or futurization work or algorithm selection. There's a number of, you know, depending on the symptoms, there's a number of things you can do to increase performance over time and we help guide people on that journey. >> So Adam, I have to ask, since you have such a great customer base and they're smart and they got teams and you're on the front end, I mean, early adopters is kind of an overused word, but they're killing it. They're putting stuff in the production's, not like it's a test, it's not like it's early. So as the next wave comes of fast followers, how do you see that coming online? What's your vision for that? How do you see companies that are like just waking up out of the frozen, you know, freeze of like old IT to like, okay, they got cloud, but they're not yet there. What do you see in the market? I see you're in the front end now with the top people really nailing AI and working hard. What's the- >> Yeah, I think a lot of these tools are becoming, or every year they get easier, more accessible, easier to use. And so, you know, even for that kind of like, as the market broadens, it takes less and less of a lift to put these systems in place. And the thing is, every business is unique, they have their own kind of data and so you can use these foundation models which have just been trained on generic data. They're a great starting point, a great accelerant, but then, in most cases you're either going to want to create a model or fine tune a model using data that's really kind of comes from your particular customers, the people you serve and so that it really reflects that and takes that into account. And so I do think that these, like the size of that market is expanding and its broadening as these tools just become easier to use and also the knowledge about how to build these systems becomes more widespread. >> Talk about your customer base you have now, what's the makeup, what size are they? Give a taste a little bit of a customer base you got there, what's they look like? I'll say Capital One, we know very well while you were at there, they were large scale, lot of data from fraud detection to all kinds of cool stuff. What do your customers now look like? >> Yeah, so we have a variety, but I would say one area we're really strong, we have several of the top 10 US banks, that's not surprising, that's a strength for us, but we also have Fortune 100 customers in healthcare, in manufacturing, in retail, in semiconductor and electronics. So what we find is like in any sort of these major verticals, there's typically, you know, one, two, three kind of companies that are really leading the charge and are the ones that, you know, in our opinion, those are the ones that for the next multiple decades are going to be the leaders, the ones that really kind of lead the charge on this AI transformation. And so we're very fortunate to be working with some of those. And then we have a number of startups as well who we love working with just because they're really pushing the boundaries technologically and so they provide great feedback and make sure that we're continuing to innovate and staying abreast of everything that's going on. >> You know, these early markups, even when the hyperscalers were coming online, they had to build everything themselves. That's the new, they're like the alphas out there building it. This is going to be a big wave again as that fast follower comes in. And so when you look at the scale, what advice would you give folks out there right now who want to tee it up and what's your secret sauce that will help them get there? >> Yeah, I think that the secret to teeing it up is just dive in and start like the, I think these are, there's not really a secret. I think it's amazing how accessible these are. I mean, there's all sorts of ways to access LLMs either via either API access or downloadable in some cases. And so, you know, go ahead and get started. And then our secret sauce really is the way that we provide that performance analysis of what's going on, right? So we can tell you in a very actionable way, like, hey, here's where your model is doing good things, here's where it's doing bad things. Here's something you want to take a look at, here's some potential remedies for it. We can help guide you through that. And that way when you're putting it out there, A, you're avoiding a lot of the common pitfalls that people see and B, you're able to really kind of make it better in a much faster way with that tight feedback loop. >> It's interesting, we've been kind of riffing on this supercloud idea because it was just different name than multicloud and you see apps like Snowflake built on top of AWS without even spending any CapEx, you just ride that cloud wave. This next AI, super AI wave is coming. I don't want to call AIOps because I think there's a different distinction. If you, MLOps and AIOps seem a little bit old, almost a few years back, how do you view that because everyone's is like, "Is this AIOps?" And like, "No, not kind of, but not really." How would you, you know, when someone says, just shoots off the hip, "Hey Adam, aren't you doing AIOps?" Do you say, yes we are, do you say, yes, but we do differently because it's doesn't seem like it's the same old AIOps. What's your- >> Yeah, it's a good question. AIOps has been a term that was co-opted for other things and MLOps also has people have used it for different meanings. So I like the term just AI infrastructure, I think it kind of like describes it really well and succinctly. >> But you guys are doing the ops. I mean that's the kind of ironic thing, it's like the next level, it's like NextGen ops, but it's not, you don't want to be put in that bucket. >> Yeah, no, it's very operationally focused platform that we have, I mean, it fires alerts, people can action off them. If you're familiar with like the way people run security operations centers or network operations centers, we do that for data science, right? So think of it as a DSOC, a Data Science Operations Center where all your models, you might have hundreds of models running across your organization, you may have five, but as problems are detected, alerts can be fired and you can actually work the case, make sure they're resolved, escalate them as necessary. And so there is a very strong operational aspect to it, you're right. >> You know, one of the things I think is interesting is, is that, if you don't mind commenting on it, is that the aspect of scale is huge and it feels like that was made up and now you have scale and production. What's your reaction to that when people say, how does scale impact this? >> Yeah, scale is huge for some of, you know, I think, I think look, the highest leverage business areas to apply these to, are generally going to be the ones at the biggest scale, right? And I think that's one of the advantages we have. Several of us come from enterprise backgrounds and we're used to doing things enterprise grade at scale and so, you know, we're seeing more and more companies, I think they started out deploying AI and sort of, you know, important but not necessarily like the crown jewel area of their business, but now they're deploying AI right in the heart of things and yeah, the scale that some of our companies are operating at is pretty impressive. >> John: Well, super exciting, great to have you on and congratulations. I got a final question for you, just random. What are you most excited about right now? Because I mean, you got to be pretty pumped right now with the way the world is going and again, I think this is just the beginning. What's your personal view? How do you feel right now? >> Yeah, the thing I'm really excited about for the next couple years now, you touched on it a little bit earlier, but is a sort of convergence of AI and AI systems with sort of turning into AI native businesses. And so, as you sort of do more, get good further along this transformation curve with AI, it turns out that like the better the performance of your AI systems, the better the performance of your business. Because these models are really starting to underpin all these key areas that cumulatively drive your P&L. And so one of the things that we work a lot with our customers is to do is just understand, you know, take these really esoteric data science notions and performance and tie them to all their business KPIs so that way you really are, it's kind of like the operating system for running your AI native business. And we're starting to see more and more companies get farther along that maturity curve and starting to think that way, which is really exciting. >> I love the AI native. I haven't heard any startup yet say AI first, although we kind of use the term, but I guarantee that's going to come in all the pitch decks, we're an AI first company, it's going to be great run. Adam, congratulations on your success to you and the team. Hey, if we do a few more interviews, we'll get the linguistics down. We can have bots just interact with you directly and ask you, have an interview directly. >> That sounds good, I'm going to go hang out on the beach, right? So, sounds good. >> Thanks for coming on, really appreciate the conversation. Super exciting, really important area and you guys doing great work. Thanks for coming on. >> Adam: Yeah, thanks John. >> Again, this is Cube Conversation. I'm John Furrier here in Palo Alto, AI going next gen. This is legit, this is going to a whole nother level that's going to open up huge opportunities for startups, that's going to use opportunities for investors and the value to the users and the experience will come in, in ways I think no one will ever see. So keep an eye out for more coverage on siliconangle.com and theCUBE.net, thanks for watching. (bright upbeat music)

>> Hello and welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. Got a variety of interviews across the gamut from topics, women in tech, mentoring, pipelining, developers, open source, executives. Stanford's having International Women's Day celebration with the women in data science, which we're streaming that live as well. Variety of programs. In this segment, Meagen Eisenberg, friend of theCUBE, she's the CMO of Laceworks, is an amazing executive, got a great journey story as a CMO but she's also actively advising startups, companies and really pays it forward. I want to say Meagen, thank you for coming on the program and thanks for sharing. >> Yeah, thank you for having me. I'm happy to be here. >> Well, we're going to get into some of the journey celebrations that you've gone through and best practice what you've learned is pay that forward. But I got to say, one of the things that really impresses me about you as an executive is you get stuff done. You're a great CMO but also you're advised a lot of companies, you have a lot of irons in the fires and you're advising companies and sometimes they're really small startups to bigger companies, and you're paying it forward, which I love. That's kind of the spirit of this day. >> Yeah, I mean, I agree with you. When I think about my career, a lot of it was looking to mentors women out in the field. This morning I was at a breakfast by Eileen and we had the CEO of General Motors on, and she was talking about her journey nine years as a CEO. And you know, and she's paying it forward with us. But I think about, you know, when you're advising startups, you know, I've gathered knowledge and pattern recognition and to be able to share that is, you know, I enjoy it. >> Yeah. And the startups are also fun too, but it's not always easy and it can get kind of messy as you know. Some startups don't make it some succeed and it's always like the origination story is kind of rewritten and then that's that messy middle. And then it's like that arrows that don't look like a straight line but everyone thinks it's great and you know, it's not for the faint of heart. And Teresa Carlson, who I've interviewed many times, former Amazon, now she's the president of Flexport, she always says, sometimes startups on certain industries aren't for the faint of heart so you got to have a little bit of metal, right? You got to be tough. And some cases that you don't need that, but startups, it's not always easy. What have you learned? >> Yeah, I mean, certainly in the startup world, grit, creativity. You know, when I was at TripActions travel company, pandemic hits, nobody's traveling. You cut budget, you cut heads, but you focus on the core, right? You focus on what you need to survive. And creativity, I think, wins. And, you know, as a CMO when you're marketing, how do you get through that noise? Even the security space, Lacework, it's a fragmented market. You've got to be differentiated and position yourself and you know, be talking to the right target audience and customers. >> Talk about your journey over the years. What have you learned? What's some observations? Can you share any stories and best practices that someone watching could learn from? I know there's a lot of people coming into the tech space with the generative AI things going on in Cloud computing, scaling to the edge, there's a lot more aperture for technical jobs as well as just new roles and new roles that haven't, you really don't go to college for anymore. You got cybersecurity you're in. What are some of the things that you've done over your career if you can share and some best practices? >> Yeah, I think number one, continual learning. When I look through my career, I was constantly reading, networking. Part of the journey is who you're meeting along the way. As you become more senior, your ability to hire and bring in talent matters a lot. I'm always trying to meet with new people. Yeah, if I look at my Amazon feed of books I've bought, right, it kind of chronicle of my history of things I was learning about. Right now I'm reading a lot about cybersecurity, how the, you know, how how they tell me the world ends is the one I'm reading most recently. But you've got to come up to speed and then know the product, get in there and talk to customers. Certainly on the marketing front, anytime I can talk with the customer and find out how they're using us, why they love us, that, you know, helps me better position and differentiate our company. >> By the way, that book is amazing. I saw Nicole speak on Tuesday night with John Markoff and Palo Alto here. What a great story she told there. I recommend that book to everyone. It goes in and she did eight years of research into that book around zero day marketplaces to all the actors involved in security. And it was very interesting. >> Yeah, I mean, it definitely wakes you up, makes you think about what's going on in the world. Very relevant. >> It's like, yeah, it was happening all the time, wasn't it. All the hacking. But this brings me, this brings up an interesting point though, because you're in a cybersecurity area, which by the way, it's changing very fast. It's becoming a bigger industry. It's not just male dominated, although it is now, it's still male dominated, but it's becoming much more and then just tech. >> Yeah, I mean it's a constantly evolving threat landscape and we're learning, and I think more than ever you need to be able to use the data that companies have and, you know, learn from it. That's one of the ways we position ourselves. We're not just about writing rules that won't help you with those zero day attacks. You've got to be able to understand your particular environment and at any moment if it changes. And that's how we help you detect a threat. >> How is, how are things going with you? Is there any new things you guys got going on? Initiatives or programs for women in tech and increasing the range of diversity inclusion in the industry? Because again, this industry's getting much wider too. It's not just specialized, it's also growing. >> Yes, actually I'm excited. We're launching secured by women, securedbywomen.com and it's very much focused on women in the industry, which some studies are showing it's about 25% of security professionals are women. And we're going to be taking nominations and sponsoring women to go to upcoming security events. And so excited to launch that this month and really celebrate women in security and help them, you know, part of that continual learning that I talked about, making sure they're there learning, having the conversations at the conferences, being able to network. >> I have to ask you, what inspired you to pursue the career in tech? What was the motivation? >> You know, if I think way back, originally I wanted to be on the art side and my dad said, "You can do anything as long as it's in the sciences." And so in undergrad I did computer science and MIS. Graduated with MIS and computer science minor. And when I came out I was a IT engineer at Cisco and you know, that kind of started my journey and decided to go back and get my MBA. And during that process I fell in love with marketing and I thought, okay, I understand the buyer, I can come out and market technology to the IT world and developers. And then from there went to several tech companies. >> I mean my father was an engineer. He had the same kind of thing. You got to be an engineer, it's a steady, stable job. But that time, computer science, I mean we've seen the evolution of computer science now it's the most popular degree at Berkeley we've heard and around the world and the education formats are changing. You're seeing a lot of people's self-training on YouTube. The field has really changed. What are some of the challenges you see for folks trying to get into the industry and how would you advise today if you were talking to your young self, what would you, what would be the narrative? >> Yeah, I mean my drawback then was HTML pages were coming out and I thought it would be fun to design, you know, webpages. So you find something you're passionate about in the space today, whether it's gaming or it's cybersecurity. Go and be excited about it and apply and don't give up, right? Do whatever you can to read and learn. And you're right, there are a ton of online self-help. I always try to hire women and people who are continual learners and are teaching themselves something. And I try to find that in an interview to know that they, because when you come to a business, you're there to solve problems and challenges. And the folks that can do that and be innovative and learn, those are the ones I want on my team. >> It's interesting, you know, technology is now impacting society and we need everyone involved to participate and give requirements. And that kind of leads my next question for you is, like, in your opinion, or let me just step back, let me rephrase. What are some of the things that you see technology being used for, for society right now that will impact people's lives? Because this is not a gender thing. We need everybody involved 'cause society is now digital. Technology's pervasive. The AI trends now we're seeing is clearly unmasking to the mainstream that there's some cool stuff happening. >> Yeah, I mean, I think ChatGPT, think about that. All the different ways we're using it we're writing content and marketing with it. We're, you know, I just read an article yesterday, folks are using it to write children's stories and then selling those stories on Amazon, right? And the amount that they can produce with it. But if you think about it, there's unlimited uses with that technology and you've got all the major players getting involved on it. That one major launch and piece of technology is going to transform us in the next six months to a year. And it's the ability to process so much data and then turn that into just assets that we use and the creativity that's building on top of it. Even TripActions has incorporated ChatGPT into your ability to figure out where you want when you're traveling, what's happening in that city. So it's just, you're going to see that incorporated everywhere. >> I mean we've done an interview before TripAction, your other company you were at. Interesting point you don't have to type in a box to say, I'm traveling, I want a hotel. You can just say, I'm going to Barcelona for Mobile World Congress, I want to have a good time. I want some tapas and a nice dinner out. >> Yes. Yeah. That easy. We're making it easy. >> It's efficiency. >> And actually I was going to say for women specifically, I think the reason why we can do so much today is all the technology and apps that we have. I think about DoorDash, I think about Waze you know, when I was younger you had to print out instructions. Now I get in the car real quick, I need to go to soccer practice, I enter it, I need to pick them up at someone's house. I enter it. It's everything's real time. And so it takes away all the things that I don't add value to and allows me to focus on what I want in business. And so there's a bunch of, you know, apps out there that have allowed me to be so much more efficient and productive that my mother didn't have for sure when I was growing up. >> That is an amazing, I think that actually illustrates, in my opinion, the best example of ChatGPT because the maps and GPS integration were two techs, technologies merged together that replace driving and looking at the map. You know, like how do you do that? Like now it's automatically. This is what's going to happen to creative, to writing, to ideation. I even heard Nicole from her book read said that they're using ChatGPT to write zero day exploits. So you seeing it... >> That's scary stuff. You're right. >> You're seeing it everywhere. Super exciting. Well, I got to ask you before you get into some of the Lacework things that you're involved with, cause I think you're doing great work over there is, what was the most exciting projects you've worked on in your career? You came in Cisco, very technical company, so got the technical chops, CSMIS which stands for Management of Information Science for all the young people out there, that was the state of the art back then. What are some of the exciting things you've done? >> Yeah, I mean, I think about, I think about MongoDB and learning to market to developers. Taking the company public in 2017. Launching Atlas database as a service. Now there's so much more of that, you know, the PLG motion, going to TripActions, you know, surviving a pandemic, still being able to come out of that and all the learnings that went with it. You know, they recently, I guess rebranded, so they're Navan now. And then now back in the security space, you know, 14 years ago I was at ArcSite and we were bought by HP. And so getting back into the security world is exciting and it's transformed a ton as you know, it's way more complicated than it was. And so just understanding the pain of our customers and how we protect them as is fun. And I like, you know, being there from a marketing standpoint. >> Well we really appreciate you coming on and sharing that. I got to ask you, for folks watching they might be interested in some advice that you might have for them and their career in tech. I know a lot of young people love the tech. It's becoming pervasive in our lives, as we mentioned. What advice would you give for folks watching that want to start a career in tech? >> Yeah, so work hard, right? Study, network, your first job, be the best at it because every job after that you get pulled into a network. And every time I move, I'm hiring people from the last job, two jobs before, three jobs before. And I'm looking for people that are working hard, care, you know, are continual learners and you know, add value. What can you do to solve problems at your work and add value? >> What's your secret networking hack or growth hack or tip that you can share? Because you're a great networker by the way. You're amazing and you do add a lot of value. I've seen you in action. >> Well, I try never to eat alone. I've got breakfast, I've got lunch, I've got coffee breaks and dinner. And so when I'm at work, I try and always sit and eat with a team member, new group. If I'm out on the road, I'm, you know, meeting people for lunch, going for dinner, just, you know, don't sit at your desk by yourself and don't sit in the hotel room. Get out and meet with people. >> What do you think about now that we're out of the pandemic or somewhat out of the pandemic so to speak, events are back. >> Yes. >> RSA is coming up. It's a big event. The bigger events are getting bigger and then the other events are kind of smaller being distributed. What's your vision of how events are evolving? >> Yeah, I mean, you've got to be in person. Those are the relationships. Right now more than ever people care about renewals and you are building that rapport. And if you're not meeting with your customers, your competitors are. So what I would say is get out there Lacework, we're going to be at RSA, we're going to be at re:Inforce, we're going to be at all of these events, building relationships, you know, coffee, lunch, and yeah, I think the future of events are here to stay and those that don't embrace in person are going to give up business. They're going to lose market share to us. >> And networking is obviously very key on events as well. >> Yes. >> A good opportunity as always get out to the events. What's the event networking trick or advice do you give folks that are going to get out to the networking world? >> Yeah, schedule ahead of time. Don't go to an event and expect people just to come by for great swag. You should be partnering with your sales team and scheduling ahead of time, getting on people's calendars. Don't go there without having 100 or 200 meetings already booked. >> Got it. All right. Let's talk about you, your career. You're currently at Lacework. It's a very hot company in a hot field, security, very male dominated, you're a leader there. What's it like? What's the strategies? How does a woman get in there and be successful? What are some tricks, observations, any data you can share? What's the best practice? What's the secret sauce from Meagen Eisenberg? >> Yes. Yeah, for Meagen Eisenberg. For Lacework, you know, we're focused on our customers. There's nothing better than getting, being close to them, solving their pain, showcasing them. So if you want to go into security, focus on their, the issues and their problems and make sure they're aware of what you're delivering. I mean, we're focused on cloud security and we go from build time to run time. And that's the draw for me here is we had a lot of, you know, happy, excited customers by what we were doing. And what we're doing is very different from legacy security providers. And it is tapping into the trend of really understanding how much data you have and what's happening in the data to detect the anomalies and the threats that are there. >> You know, one of the conversations that I was just having with a senior leader, she was amazing and I asked her what she thought of the current landscape, the job market, the how to get promoted through the careers, all those things. And the response was interesting. I want to get your reaction. She said interdisciplinary skills are critical. And now more than ever, the having that, having a set of skills, technical and social and emotional are super valuable. Do you agree? What's your reaction to that and what would, how would you reframe that? >> Yeah, I mean, I completely agree. You can't be a leader without balance. You've got to know your craft because you're developing and training your team, but you also need to know the, you know, how to build relationships. You're not going to be successful as a C-level exec if you're not partnering across the functions. As a CMO I need to partner with product, I need to partner with the head of sales, I need to partner with finance. So those relationships matter a ton. I also need to attract the right talent. I want to have solid people on the team. And what I will say in the security, cybersecurity space, there's a talent shortage and you cannot hire enough people to protect your company in that space. And that's kind of our part of it is we reduce the number of alerts that you're getting. So you don't need hundreds of people to detect an issue. You're using technology to show, you know, to highlight the issue and then your team can focus on those alerts that matter. >> Yeah, there's a lot of emerging markets where leveling up and you don't need pedigree. You can just level up skill-wise pretty quickly. Which brings me to the next question for you is how do you keep up with all the tech day-to-day and how should someone watching stay on top of it? Because I mean, you got to be on top of this stuff and you got to ride the wave. It's pretty turbulent, but it's still growing and changing. >> Yeah, it's true. I mean, there's a lot of reading. I'm watching the news. Anytime something comes out, you know, ChatGPT I'm playing with it. I've got a great network and sharing. I'm on, you know, LinkedIn reading articles all the time. I have a team, right? Every time I hire someone, they bring new information and knowledge in and I'm you know, Cal Poly had this learn by doing that was the philosophy at San Luis Obispo. So do it. Try it, don't be afraid of it. I think that's the advice. >> Well, I love some of the points you mentioned community and network. You mentioned networking. That brings up the community question, how could people get involved? What communities are out there? How should they approach communities? 'Cause communities are also networks, but also they're welcoming people in that form networks. So it's a network of networks. So what's your take on how to engage and work with communities? How do you find your tribe? If someone's getting into the business, they want support, they might want technology learnings, what's your approach? >> Yeah, so a few, a few different places. One, I'm part of the operator collective, which is a strong female investment group that's open and works a lot with operators and they're in on the newest technologies 'cause they're investing in it. Chief I think is a great organization as well. You've got a lot of, if you're in marketing, there's a ton of CMO networking events that you can go to. I would say any field, even for us at Lacework, we've got some strong CISO networks and we do dinners around you know, we have one coming up in the Bay area, in Boston, New York, and you can come and meet other CISOs and security leaders. So when I get an invite and you know we all do, I will go to it. I'll carve out the time and meet with others. So I think, you know, part of the community is get out there and, you know, join some of these different groups. >> Meagen, thank you so much for spending the time. Final question for you. How do you see the future of tech evolving and how do you see your role in it? >> Yeah, I mean, marketing's changing wildly. There's so many different channels. You think about all the social media channels that have changed over the last five years. So when I think about the future of tech, I'm looking at apps on my phone. I have three daughters, 13, 11, and 8. I'm telling you, they come to me with new apps and new technology all the time, and I'm paying attention what they're, you know, what they're participating in and what they want to be a part of. And certainly it's going to be a lot more around the data and AI. I think we're only at the beginning of that. So we will continue to, you know, learn from it and wield it and deal with the mass amount of data that's out there. >> Well, you saw TikTok just got banned by the European Commission today around their staff. Interesting times. >> It is. >> Meagen, thank you so much as always. You're a great tech athlete. Been following your career for a while, a long time. You're an amazing leader. Thank you for sharing your story here on theCUBE, celebration of International Women's Day. Every day is IWD and thanks for coming on. >> Thank you for having me. >> Okay. I'm John Furrier here in theCUBE Studios in Palo Alto. Thank you for watching, more to come stay with us. (bright music)

(upbeat music) >> Hello, everyone, welcome to theCUBE. I'm John Furrier, the host of theCUBE in Palo Alto, California. Also it's SiliconANGLE News. Got two great guests here to talk about AI, the impact of the future of the internet, the applications, the people. Amr Awadallah, the founder and CEO, Ed Alban is the CEO of Vectara, a new startup that emerged out of the original Cloudera, I would say, 'cause Amr's known, famous for the Cloudera founding, which was really the beginning of the big data movement. And now as AI goes mainstream, there's so much to talk about, so much to go on. And plus the new company is one of the, now what I call the wave, this next big wave, I call it the fifth wave in the industry. You know, you had PCs, you had the internet, you had mobile. This generative AI thing is real. And you're starting to see startups come out in droves. Amr obviously was founder of Cloudera, Big Data, and now Vectara. And Ed Albanese, you guys have a new company. Welcome to the show. >> Thank you. It's great to be here. >> So great to see you. Now the story is theCUBE started in the Cloudera office. Thanks to you, and your friendly entrepreneurship views that you have. We got to know each other over the years. But Cloudera had Hadoop, which was the beginning of what I call the big data wave, which then became what we now call data lakes, data oceans, and data infrastructure that's developed from that. It's almost interesting to look back 12 plus years, and see that what AI is doing now, right now, is opening up the eyes to the mainstream, and the application's almost mind blowing. You know, Sati Natel called it the Mosaic Moment, didn't say Netscape, he built Netscape (laughing) but called it the Mosaic Moment. You're seeing companies in startups, kind of the alpha geeks running here, because this is the new frontier, and there's real meat on the bone, in terms of like things to do. Why? Why is this happening now? What's is the confluence of the forces happening, that are making this happen? >> Yeah, I mean if you go back to the Cloudera days, with big data, and so on, that was more about data processing. Like how can we process data, so we can extract numbers from it, and do reporting, and maybe take some actions, like this is a fraud transaction, or this is not. And in the meanwhile, many of the researchers working in the neural network, and deep neural network space, were trying to focus on data understanding, like how can I understand the data, and learn from it, so I can take actual actions, based on the data directly, just like a human does. And we were only good at doing that at the level of somebody who was five years old, or seven years old, all the way until about 2013. And starting in 2013, which is only 10 years ago, a number of key innovations started taking place, and each one added on. It was no major innovation that just took place. It was a couple of really incremental ones, but they added on top of each other, in a very exponentially additive way, that led to, by the end of 2019, we now have models, deep neural network models, that can read and understand human text just like we do. Right? And they can reason about it, and argue with you, and explain it to you. And I think that's what is unlocking this whole new wave of innovation that we're seeing right now. So data understanding would be the essence of it. >> So it's not a Big Bang kind of theory, it's been evolving over time, and I think that the tipping point has been the advancements and other things. I mean look at cloud computing, and look how fast it just crept up on AWS. I mean AWS you back three, five years ago, I was talking to Swami yesterday, and their big news about AI, expanding the Hugging Face's relationship with AWS. And just three, five years ago, there wasn't a model training models out there. But as compute comes out, and you got more horsepower,, these large language models, these foundational models, they're flexible, they're not monolithic silos, they're interacting. There's a whole new, almost fusion of data happening. Do you see that? I mean is that part of this? >> Of course, of course. I mean this wave is building on all the previous waves. We wouldn't be at this point if we did not have hardware that can scale, in a very efficient way. We wouldn't be at this point, if we don't have data that we're collecting about everything we do, that we're able to process in this way. So this, this movement, this motion, this phase we're in, absolutely builds on the shoulders of all the previous phases. For some of the observers from the outside, when they see chatGPT for the first time, for them was like, "Oh my god, this just happened overnight." Like it didn't happen overnight. (laughing) GPT itself, like GPT3, which is what chatGPT is based on, was released a year ahead of chatGPT, and many of us were seeing the power it can provide, and what it can do. I don't know if Ed agrees with that. >> Yeah, Ed? >> I do. Although I would acknowledge that the possibilities now, because of what we've hit from a maturity standpoint, have just opened up in an incredible way, that just wasn't tenable even three years ago. And that's what makes it, it's true that it developed incrementally, in the same way that, you know, the possibilities of a mobile handheld device, you know, in 2006 were there, but when the iPhone came out, the possibilities just exploded. And that's the moment we're in. >> Well, I've had many conversations over the past couple months around this area with chatGPT. John Markoff told me the other day, that he calls it, "The five dollar toy," because it's not that big of a deal, in context to what AI's doing behind the scenes, and all the work that's done on ethics, that's happened over the years, but it has woken up the mainstream, so everyone immediately jumps to ethics. "Does it work? "It's not factual," And everyone who's inside the industry is like, "This is amazing." 'Cause you have two schools of thought there. One's like, people that think this is now the beginning of next gen, this is now we're here, this ain't your grandfather's chatbot, okay?" With NLP, it's got reasoning, it's got other things. >> I'm in that camp for sure. >> Yeah. Well I mean, everyone who knows what's going on is in that camp. And as the naysayers start to get through this, and they go, "Wow, it's not just plagiarizing homework, "it's helping me be better. "Like it could rewrite my memo, "bring the lead to the top." It's so the format of the user interface is interesting, but it's still a data-driven app. >> Absolutely. >> So where does it go from here? 'Cause I'm not even calling this the first ending. This is like pregame, in my opinion. What do you guys see this going, in terms of scratching the surface to what happens next? >> I mean, I'll start with, I just don't see how an application is going to look the same in the next three years. Who's going to want to input data manually, in a form field? Who is going to want, or expect, to have to put in some text in a search box, and then read through 15 different possibilities, and try to figure out which one of them actually most closely resembles the question they asked? You know, I don't see that happening. Who's going to start with an absolute blank sheet of paper, and expect no help? That is not how an application will work in the next three years, and it's going to fundamentally change how people interact and spend time with opening any element on their mobile phone, or on their computer, to get something done. >> Yes. I agree with that. Like every single application, over the next five years, will be rewritten, to fit within this model. So imagine an HR application, I don't want to name companies, but imagine an HR application, and you go into application and you clicking on buttons, because you want to take two weeks of vacation, and menus, and clicking here and there, reasons and managers, versus just telling the system, "I'm taking two weeks of vacation, going to Las Vegas," book it, done. >> Yeah. >> And the system just does it for you. If you weren't completing in your input, in your description, for what you want, then the system asks you back, "Did you mean this? "Did you mean that? "Were you trying to also do this as well?" >> Yeah. >> "What was the reason?" And that will fit it for you, and just do it for you. So I think the user interface that we have with apps, is going to change to be very similar to the user interface that we have with each other. And that's why all these apps will need to evolve. >> I know we don't have a lot of time, 'cause you guys are very busy, but I want to definitely have multiple segments with you guys, on this topic, because there's so much to talk about. There's a lot of parallels going on here. I was talking again with Swami who runs all the AI database at AWS, and I asked him, I go, "This feels a lot like the original AWS. "You don't have to provision a data center." A lot of this heavy lifting on the back end, is these large language models, with these foundational models. So the bottleneck in the past, was the energy, and cost to actually do it. Now you're seeing it being stood up faster. So there's definitely going to be a tsunami of apps. I would see that clearly. What is it? We don't know yet. But also people who are going to leverage the fact that I can get started building value. So I see a startup boom coming, and I see an application tsunami of refactoring things. >> Yes. >> So the replatforming is already kind of happening. >> Yes, >> OpenAI, chatGPT, whatever. So that's going to be a developer environment. I mean if Amazon turns this into an API, or a Microsoft, what you guys are doing. >> We're turning it into API as well. That's part of what we're doing as well, yes. >> This is why this is exciting. Amr, you've lived the big data dream, and and we used to talk, if you didn't have a big data problem, if you weren't full of data, you weren't really getting it. Now people have all the data, and they got to stand this up. >> Yeah. >> So the analogy is again, the mobile, I like the mobile movement, and using mobile as an analogy, most companies were not building for a mobile environment, right? They were just building for the web, and legacy way of doing apps. And as soon as the user expectations shifted, that my expectation now, I need to be able to do my job on this small screen, on the mobile device with a touchscreen. Everybody had to invest in re-architecting, and re-implementing every single app, to fit within that model, and that model of interaction. And we are seeing the exact same thing happen now. And one of the core things we're focused on at Vectara, is how to simplify that for organizations, because a lot of them are overwhelmed by large language models, and ML. >> They don't have the staff. >> Yeah, yeah, yeah. They're understaffed, they don't have the skills. >> But they got developers, they've got DevOps, right? >> Yes. >> So they have the DevSecOps going on. >> Exactly, yes. >> So our goal is to simplify it enough for them that they can start leveraging this technology effectively, within their applications. >> Ed, you're the COO of the company, obviously a startup. You guys are growing. You got great backup, and good team. You've also done a lot of business development, and technical business development in this area. If you look at the landscape right now, and I agree the apps are coming, every company I talk to, that has that jet chatGPT of, you know, epiphany, "Oh my God, look how cool this is. "Like magic." Like okay, it's code, settle down. >> Mm hmm. >> But everyone I talk to is using it in a very horizontal way. I talk to a very senior person, very tech alpha geek, very senior person in the industry, technically. they're using it for log data, they're using it for configuration of routers. And in other areas, they're using it for, every vertical has a use case. So this is horizontally scalable from a use case standpoint. When you hear horizontally scalable, first thing I chose in my mind is cloud, right? >> Mm hmm. >> So cloud, and scalability that way. And the data is very specialized. So now you have this vertical specialization, horizontally scalable, everyone will be refactoring. What do you see, and what are you seeing from customers, that you talk to, and prospects? >> Yeah, I mean put yourself in the shoes of an application developer, who is actually trying to make their application a bit more like magic. And to have that soon-to-be, honestly, expected experience. They've got to think about things like performance, and how efficiently that they can actually execute a query, or a question. They've got to think about cost. Generative isn't cheap, like the inference of it. And so you've got to be thoughtful about how and when you take advantage of it, you can't use it as a, you know, everything looks like a nail, and I've got a hammer, and I'm going to hit everything with it, because that will be wasteful. Developers also need to think about how they're going to take advantage of, but not lose their own data. So there has to be some controls around what they feed into the large language model, if anything. Like, should they fine tune a large language model with their own data? Can they keep it logically separated, but still take advantage of the powers of a large language model? And they've also got to take advantage, and be aware of the fact that when data is generated, that it is a different class of data. It might not fully be their own. >> Yeah. >> And it may not even be fully verified. And so when the logical cycle starts, of someone making a request, the relationship between that request, and the output, those things have to be stored safely, logically, and identified as such. >> Yeah. >> And taken advantage of in an ongoing fashion. So these are mega problems, each one of them independently, that, you know, you can think of it as middleware companies need to take advantage of, and think about, to help the next wave of application development be logical, sensible, and effective. It's not just calling some raw API on the cloud, like openAI, and then just, you know, you get your answer and you're done, because that is a very brute force approach. >> Well also I will point, first of all, I agree with your statement about the apps experience, that's going to be expected, form filling. Great point. The interesting about chatGPT. >> Sorry, it's not just form filling, it's any action you would like to take. >> Yeah. >> Instead of clicking, and dragging, and dropping, and doing it on a menu, or on a touch screen, you just say it, and it's and it happens perfectly. >> Yeah. It's a different interface. And that's why I love that UIUX experiences, that's the people falling out of their chair moment with chatGPT, right? But a lot of the things with chatGPT, if you feed it right, it works great. If you feed it wrong and it goes off the rails, it goes off the rails big. >> Yes, yes. >> So the the Bing catastrophes. >> Yeah. >> And that's an example of garbage in, garbage out, classic old school kind of comp-side phrase that we all use. >> Yep. >> Yes. >> This is about data in injection, right? It reminds me the old SQL days, if you had to, if you can sling some SQL, you were a magician, you know, to get the right answer, it's pretty much there. So you got to feed the AI. >> You do, Some people call this, the early word to describe this as prompt engineering. You know, old school, you know, search, or, you know, engagement with data would be, I'm going to, I have a question or I have a query. New school is, I have, I have to issue it a prompt, because I'm trying to get, you know, an action or a reaction, from the system. And the active engineering, there are a lot of different ways you could do it, all the way from, you know, raw, just I'm going to send you whatever I'm thinking. >> Yeah. >> And you get the unintended outcomes, to more constrained, where I'm going to just use my own data, and I'm going to constrain the initial inputs, the data I already know that's first party, and I trust, to, you know, hyper constrain, where the application is actually, it's looking for certain elements to respond to. >> It's interesting Amr, this is why I love this, because one we are in the media, we're recording this video now, we'll stream it. But we got all your linguistics, we're talking. >> Yes. >> This is data. >> Yep. >> So the data quality becomes now the new intellectual property, because, if you have that prompt source data, it makes data or content, in our case, the original content, intellectual property. >> Absolutely. >> Because that's the value. And that's where you see chatGPT fall down, is because they're trying to scroll the web, and people think it's search. It's not necessarily search, it's giving you something that you wanted. It is a lot of that, I remember in Cloudera, you said, "Ask the right questions." Remember that phrase you guys had, that slogan? >> Mm hmm. And that's prompt engineering. So that's exactly, that's the reinvention of "Ask the right question," is prompt engineering is, if you don't give these models the question in the right way, and very few people know how to frame it in the right way with the right context, then you will get garbage out. Right? That is the garbage in, garbage out. But if you specify the question correctly, and you provide with it the metadata that constrain what that question is going to be acted upon or answered upon, then you'll get much better answers. And that's exactly what we solved Vectara. >> Okay. So before we get into the last couple minutes we have left, I want to make sure we get a plug in for the opportunity, and the profile of Vectara, your new company. Can you guys both share with me what you think the current situation is? So for the folks who are now having those moments of, "Ah, AI's bullshit," or, "It's not real, it's a lot of stuff," from, "Oh my god, this is magic," to, "Okay, this is the future." >> Yes. >> What would you say to that person, if you're at a cocktail party, or in the elevator say, "Calm down, this is the first inning." How do you explain the dynamics going on right now, to someone who's either in the industry, but not in the ropes? How would you explain like, what this wave's about? How would you describe it, and how would you prepare them for how to change their life around this? >> Yeah, so I'll go first and then I'll let Ed go. Efficiency, efficiency is the description. So we figured that a way to be a lot more efficient, a way where you can write a lot more emails, create way more content, create way more presentations. Developers can develop 10 times faster than they normally would. And that is very similar to what happened during the Industrial Revolution. I always like to look at examples from the past, to read what will happen now, and what will happen in the future. So during the Industrial Revolution, it was about efficiency with our hands, right? So I had to make a piece of cloth, like this piece of cloth for this shirt I'm wearing. Our ancestors, they had to spend month taking the cotton, making it into threads, taking the threads, making them into pieces of cloth, and then cutting it. And now a machine makes it just like that, right? And the ancestors now turned from the people that do the thing, to manage the machines that do the thing. And I think the same thing is going to happen now, is our efficiency will be multiplied extremely, as human beings, and we'll be able to do a lot more. And many of us will be able to do things they couldn't do before. So another great example I always like to use is the example of Google Maps, and GPS. Very few of us knew how to drive a car from one location to another, and read a map, and get there correctly. But once that efficiency of an AI, by the way, behind these things is very, very complex AI, that figures out how to do that for us. All of us now became amazing navigators that can go from any point to any point. So that's kind of how I look at the future. >> And that's a great real example of impact. Ed, your take on how you would talk to a friend, or colleague, or anyone who asks like, "How do I make sense of the current situation? "Is it real? "What's in it for me, and what do I do?" I mean every company's rethinking their business right now, around this. What would you say to them? >> You know, I usually like to show, rather than describe. And so, you know, the other day I just got access, I've been using an application for a long time, called Notion, and it's super popular. There's like 30 or 40 million users. And the new version of Notion came out, which has AI embedded within it. And it's AI that allows you primarily to create. So if you could break down the world of AI into find and create, for a minute, just kind of logically separate those two things, find is certainly going to be massively impacted in our experiences as consumers on, you know, Google and Bing, and I can't believe I just said the word Bing in the same sentence as Google, but that's what's happening now (all laughing), because it's a good example of change. >> Yes. >> But also inside the business. But on the crate side, you know, Notion is a wiki product, where you try to, you know, note down things that you are thinking about, or you want to share and memorialize. But sometimes you do need help to get it down fast. And just in the first day of using this new product, like my experience has really fundamentally changed. And I think that anybody who would, you know, anybody say for example, that is using an existing app, I would show them, open up the app. Now imagine the possibility of getting a starting point right off the bat, in five seconds of, instead of having to whole cloth draft this thing, imagine getting a starting point then you can modify and edit, or just dispose of and retry again. And that's the potential for me. I can't imagine a scenario where, in a few years from now, I'm going to be satisfied if I don't have a little bit of help, in the same way that I don't manually spell check every email that I send. I automatically spell check it. I love when I'm getting type ahead support inside of Google, or anything. Doesn't mean I always take it, or when texting. >> That's efficiency too. I mean the cloud was about developers getting stuff up quick. >> Exactly. >> All that heavy lifting is there for you, so you don't have to do it. >> Right? >> And you get to the value faster. >> Exactly. I mean, if history taught us one thing, it's, you have to always embrace efficiency, and if you don't fast enough, you will fall behind. Again, looking at the industrial revolution, the companies that embraced the industrial revolution, they became the leaders in the world, and the ones who did not, they all like. >> Well the AI thing that we got to watch out for, is watching how it goes off the rails. If it doesn't have the right prompt engineering, or data architecture, infrastructure. >> Yes. >> It's a big part. So this comes back down to your startup, real quick, I know we got a couple minutes left. Talk about the company, the motivation, and we'll do a deeper dive on on the company. But what's the motivation? What are you targeting for the market, business model? The tech, let's go. >> Actually, I would like Ed to go first. Go ahead. >> Sure, I mean, we're a developer-first, API-first platform. So the product is oriented around allowing developers who may not be superstars, in being able to either leverage, or choose, or select their own large language models for appropriate use cases. But they that want to be able to instantly add the power of large language models into their application set. We started with search, because we think it's going to be one of the first places that people try to take advantage of large language models, to help find information within an application context. And we've built our own large language models, focused on making it very efficient, and elegant, to find information more quickly. So what a developer can do is, within minutes, go up, register for an account, and get access to a set of APIs, that allow them to send data, to be converted into a format that's easy to understand for large language models, vectors. And then secondarily, they can issue queries, ask questions. And they can ask them very, the questions that can be asked, are very natural language questions. So we're talking about long form sentences, you know, drill down types of questions, and they can get answers that either come back in depending upon the form factor of the user interface, in list form, or summarized form, where summarized equals the opportunity to kind of see a condensed, singular answer. >> All right. I have a. >> Oh okay, go ahead, you go. >> I was just going to say, I'm going to be a customer for you, because I want, my dream was to have a hologram of theCUBE host, me and Dave, and have questions be generated in the metaverse. So you know. (all laughing) >> There'll be no longer any guests here. They'll all be talking to you guys. >> Give a couple bullets, I'll spit out 10 good questions. Publish a story. This brings the automation, I'm sorry to interrupt you. >> No, no. No, no, I was just going to follow on on the same. So another way to look at exactly what Ed described is, we want to offer you chatGPT for your own data, right? So imagine taking all of the recordings of all of the interviews you have done, and having all of the content of that being ingested by a system, where you can now have a conversation with your own data and say, "Oh, last time when I met Amr, "which video games did we talk about? "Which movie or book did we use as an analogy "for how we should be embracing data science, "and big data, which is moneyball," I know you use moneyball all the time. And you start having that conversation. So, now the data doesn't become a passive asset that you just have in your organization. No. It's an active participant that's sitting with you, on the table, helping you make decisions. >> One of my favorite things to do with customers, is to go to their site or application, and show them me using it. So for example, one of the customers I talked to was one of the biggest property management companies in the world, that lets people go and rent homes, and houses, and things like that. And you know, I went and I showed them me searching through reviews, looking for information, and trying different words, and trying to find out like, you know, is this place quiet? Is it comfortable? And then I put all the same data into our platform, and I showed them the world of difference you can have when you start asking that question wholeheartedly, and getting real information that doesn't have anything to do with the words you asked, but is really focused on the meaning. You know, when I asked like, "Is it quiet?" You know, answers would come back like, "The wind whispered through the trees peacefully," and you know, it's like nothing to do with quiet in the literal word sense, but in the meaning sense, everything to do with it. And that that was magical even for them, to see that. >> Well you guys are the front end of this big wave. Congratulations on the startup, Amr. I know you guys got great pedigree in big data, and you've got a great team, and congratulations. Vectara is the name of the company, check 'em out. Again, the startup boom is coming. This will be one of the major waves, generative AI is here. I think we'll look back, and it will be pointed out as a major inflection point in the industry. >> Absolutely. >> There's not a lot of hype behind that. People are are seeing it, experts are. So it's going to be fun, thanks for watching. >> Thanks John. (soft music)

(bright upbeat music) >> Hello, everyone. Welcome to SiliconANGLE News breaking story here. Amazon Web Services expanding their relationship with Hugging Face, breaking news here on SiliconANGLE. I'm John Furrier, SiliconANGLE reporter, founder, and also co-host of theCUBE. And I have with me, Swami, from Amazon Web Services, vice president of database, analytics, machine learning with AWS. Swami, great to have you on for this breaking news segment on AWS's big news. Thanks for coming on and taking the time. >> Hey, John, pleasure to be here. >> You know- >> Looking forward to it. >> We've had many conversations on theCUBE over the years, we've watched Amazon really move fast into the large data modeling, SageMaker became a very smashing success, obviously you've been on this for a while. Now with ChatGPT OpenAI, a lot of buzz going mainstream, takes it from behind the curtain inside the ropes, if you will, in the industry to a mainstream. And so this is a big moment, I think, in the industry, I want to get your perspective, because your news with Hugging Face, I think is another tell sign that we're about to tip over into a new accelerated growth around making AI now application aware, application centric, more programmable, more API access. What's the big news about, with AWS Hugging Face, you know, what's going on with this announcement? >> Yeah. First of all, they're very excited to announce our expanded collaboration with Hugging Face, because with this partnership, our goal, as you all know, I mean, Hugging Face, I consider them like the GitHub for machine learning. And with this partnership, Hugging Face and AWS, we'll be able to democratize AI for a broad range of developers, not just specific deep AI startups. And now with this, we can accelerate the training, fine tuning and deployment of these large language models, and vision models from Hugging Face in the cloud. And the broader context, when you step back and see what customer problem we are trying to solve with this announcement, essentially if you see these foundational models, are used to now create like a huge number of applications, suggest like tech summarization, question answering, or search image generation, creative, other things. And these are all stuff we are seeing in the likes of these ChatGPT style applications. But there is a broad range of enterprise use cases that we don't even talk about. And it's because these kind of transformative, generative AI capabilities and models are not available to, I mean, millions of developers. And because either training these elements from scratch can be very expensive or time consuming and need deep expertise, or more importantly, they don't need these generic models, they need them to be fine tuned for the specific use cases. And one of the biggest complaints we hear is that these models, when they try to use it for real production use cases, they are incredibly expensive to train and incredibly expensive to run inference on, to use it at a production scale. So, and unlike web search style applications, where the margins can be really huge, here in production use cases and enterprises, you want efficiency at scale. That's where Hugging Face and AWS share our mission. And by integrating with Trainium and Inferentia, we're able to handle the cost efficient training and inference at scale, I'll deep dive on it. And by teaming up on the SageMaker front, now the time it takes to build these models and fine tune them is also coming down. So that's what makes this partnership very unique as well. So I'm very excited. >> I want to get into the time savings and the cost savings as well on the training and inference, it's a huge issue, but before we get into that, just how long have you guys been working with Hugging Face? I know there's a previous relationship, this is an expansion of that relationship, can you comment on what's different about what's happened before and then now? >> Yeah. So, Hugging Face, we have had a great relationship in the past few years as well, where they have actually made their models available to run on AWS, you know, fashion. Even in fact, their Bloom Project was something many of our customers even used. Bloom Project, for context, is their open source project which builds a GPT-3 style model. And now with this expanded collaboration, now Hugging Face selected AWS for that next generation office generative AI model, building on their highly successful Bloom Project as well. And the nice thing is, now, by direct integration with Trainium and Inferentia, where you get cost savings in a really significant way, now, for instance, Trn1 can provide up to 50% cost to train savings, and Inferentia can deliver up to 60% better costs, and four x more higher throughput than (indistinct). Now, these models, especially as they train that next generation generative AI models, it is going to be, not only more accessible to all the developers, who use it in open, so it'll be a lot cheaper as well. And that's what makes this moment really exciting, because we can't democratize AI unless we make it broadly accessible and cost efficient and easy to program and use as well. >> Yeah. >> So very exciting. >> I'll get into the SageMaker and CodeWhisperer angle in a second, but you hit on some good points there. One, accessibility, which is, I call the democratization, which is getting this in the hands of developers, and/or AI to develop, we'll get into that in a second. So, access to coding and Git reasoning is a whole nother wave. But the three things I know you've been working on, I want to put in the buckets here and comment, one, I know you've, over the years, been working on saving time to train, that's a big point, you mentioned some of those stats, also cost, 'cause now cost is an equation on, you know, bundling whether you're uncoupling with hardware and software, that's a big issue. Where do I find the GPUs? Where's the horsepower cost? And then also sustainability. You've mentioned that in the past, is there a sustainability angle here? Can you talk about those three things, time, cost, and sustainability? >> Certainly. So if you look at it from the AWS perspective, we have been supporting customers doing machine learning for the past years. Just for broader context, Amazon has been doing ML the past two decades right from the early days of ML powered recommendation to actually also supporting all kinds of generative AI applications. If you look at even generative AI application within Amazon, Amazon search, when you go search for a product and so forth, we have a team called MFi within Amazon search that helps bring these large language models into creating highly accurate search results. And these are created with models, really large models with tens of billions of parameters, scales to thousands of training jobs every month and trained on large model of hardware. And this is an example of a really good large language foundation model application running at production scale, and also, of course, Alexa, which uses a large generator model as well. And they actually even had a research paper that showed that they are more, and do better in accuracy than other systems like GPT-3 and whatnot. So, and we also touched on things like CodeWhisperer, which uses generative AI to improve developer productivity, but in a responsible manner, because 40% of some of the studies show 40% of this generated code had serious security flaws in it. This is where we didn't just do generative AI, we combined with automated reasoning capabilities, which is a very, very useful technique to identify these issues and couple them so that it produces highly secure code as well. Now, all these learnings taught us few things, and which is what you put in these three buckets. And yeah, like more than 100,000 customers using ML and AI services, including leading startups in the generative AI space, like stability AI, AI21 Labs, or Hugging Face, or even Alexa, for that matter. They care about, I put them in three dimension, one is around cost, which we touched on with Trainium and Inferentia, where we actually, the Trainium, you provide to 50% better cost savings, but the other aspect is, Trainium is a lot more power efficient as well compared to traditional one. And Inferentia is also better in terms of throughput, when it comes to what it is capable of. Like it is able to deliver up to three x higher compute performance and four x higher throughput, compared to it's previous generation, and it is extremely cost efficient and power efficient as well. >> Well. >> Now, the second element that really is important is in a day, developers deeply value the time it takes to build these models, and they don't want to build models from scratch. And this is where SageMaker, which is, even going to Kaggle uses, this is what it is, number one, enterprise ML platform. What it did to traditional machine learning, where tens of thousands of customers use StageMaker today, including the ones I mentioned, is that what used to take like months to build these models have dropped down to now a matter of days, if not less. Now, a generative AI, the cost of building these models, if you look at the landscape, the model parameter size had jumped by more than thousand X in the past three years, thousand x. And that means the training is like a really big distributed systems problem. How do you actually scale these model training? How do you actually ensure that you utilize these efficiently? Because these machines are very expensive, let alone they consume a lot of power. So, this is where SageMaker capability to build, automatically train, tune, and deploy models really concern this, especially with this distributor training infrastructure, and those are some of the reasons why some of the leading generative AI startups are actually leveraging it, because they do not want a giant infrastructure team, which is constantly tuning and fine tuning, and keeping these clusters alive. >> It sounds like a lot like what startups are doing with the cloud early days, no data center, you move to the cloud. So, this is the trend we're seeing, right? You guys are making it easier for developers with Hugging Face, I get that. I love that GitHub for machine learning, large language models are complex and expensive to build, but not anymore, you got Trainium and Inferentia, developers can get faster time to value, but then you got the transformers data sets, token libraries, all that optimized for generator. This is a perfect storm for startups. Jon Turow, a former AWS person, who used to work, I think for you, is now a VC at Madrona Venture, he and I were talking about the generator AI landscape, it's exploding with startups. Every alpha entrepreneur out there is seeing this as the next frontier, that's the 20 mile stairs, next 10 years is going to be huge. What is the big thing that's happened? 'Cause some people were saying, the founder of Yquem said, "Oh, the start ups won't be real, because they don't all have AI experience." John Markoff, former New York Times writer told me that, AI, there's so much work done, this is going to explode, accelerate really fast, because it's almost like it's been waiting for this moment. What's your reaction? >> I actually think there is going to be an explosion of startups, not because they need to be AI startups, but now finally AI is really accessible or going to be accessible, so that they can create remarkable applications, either for enterprises or for disrupting actually how customer service is being done or how creative tools are being built. And I mean, this is going to change in many ways. When we think about generative AI, we always like to think of how it generates like school homework or arts or music or whatnot, but when you look at it on the practical side, generative AI is being actually used across various industries. I'll give an example of like Autodesk. Autodesk is a customer who runs an AWS and SageMaker. They already have an offering that enables generated design, where designers can generate many structural designs for products, whereby you give a specific set of constraints and they actually can generate a structure accordingly. And we see similar kind of trend across various industries, where it can be around creative media editing or various others. I have the strong sense that literally, in the next few years, just like now, conventional machine learning is embedded in every application, every mobile app that we see, it is pervasive, and we don't even think twice about it, same way, like almost all apps are built on cloud. Generative AI is going to be part of every startup, and they are going to create remarkable experiences without needing actually, these deep generative AI scientists. But you won't get that until you actually make these models accessible. And I also don't think one model is going to rule the world, then you want these developers to have access to broad range of models. Just like, go back to the early days of deep learning. Everybody thought it is going to be one framework that will rule the world, and it has been changing, from Caffe to TensorFlow to PyTorch to various other things. And I have a suspicion, we had to enable developers where they are, so. >> You know, Dave Vellante and I have been riffing on this concept called super cloud, and a lot of people have co-opted to be multicloud, but we really were getting at this whole next layer on top of say, AWS. You guys are the most comprehensive cloud, you guys are a super cloud, and even Adam and I are talking about ISVs evolving to ecosystem partners. I mean, your top customers have ecosystems building on top of it. This feels like a whole nother AWS. How are you guys leveraging the history of AWS, which by the way, had the same trajectory, startups came in, they didn't want to provision a data center, the heavy lifting, all the things that have made Amazon successful culturally. And day one thinking is, provide the heavy lifting, undifferentiated heavy lifting, and make it faster for developers to program code. AI's got the same thing. How are you guys taking this to the next level, because now, this is an opportunity for the competition to change the game and take it over? This is, I'm sure, a conversation, you guys have a lot of things going on in AWS that makes you unique. What's the internal and external positioning around how you take it to the next level? >> I mean, so I agree with you that generative AI has a very, very strong potential in terms of what it can enable in terms of next generation application. But this is where Amazon's experience and expertise in putting these foundation models to work internally really has helped us quite a bit. If you look at it, like amazon.com search is like a very, very important application in terms of what is the customer impact on number of customers who use that application openly, and the amount of dollar impact it does for an organization. And we have been doing it silently for a while now. And the same thing is true for like Alexa too, which actually not only uses it for natural language understanding other city, even national leverages is set for creating stories and various other examples. And now, our approach to it from AWS is we actually look at it as in terms of the same three tiers like we did in machine learning, because when you look at generative AI, we genuinely see three sets of customers. One is, like really deep technical expert practitioner startups. These are the startups that are creating the next generation models like the likes of stability AIs or Hugging Face with Bloom or AI21. And they generally want to build their own models, and they want the best price performance of their infrastructure for training and inference. That's where our investments in silicon and hardware and networking innovations, where Trainium and Inferentia really plays a big role. And we can nearly do that, and that is one. The second middle tier is where I do think developers don't want to spend time building their own models, let alone, they actually want the model to be useful to that data. They don't need their models to create like high school homeworks or various other things. What they generally want is, hey, I had this data from my enterprises that I want to fine tune and make it really work only for this, and make it work remarkable, can be for tech summarization, to generate a report, or it can be for better Q&A, and so forth. This is where we are. Our investments in the middle tier with SageMaker, and our partnership with Hugging Face and AI21 and co here are all going to very meaningful. And you'll see us investing, I mean, you already talked about CodeWhisperer, which is an open preview, but we are also partnering with a whole lot of top ISVs, and you'll see more on this front to enable the next wave of generated AI apps too, because this is an area where we do think lot of innovation is yet to be done. It's like day one for us in this space, and we want to enable that huge ecosystem to flourish. >> You know, one of the things Dave Vellante and I were talking about in our first podcast we just did on Friday, we're going to do weekly, is we highlighted the AI ChatGPT example as a horizontal use case, because everyone loves it, people are using it in all their different verticals, and horizontal scalable cloud plays perfectly into it. So I have to ask you, as you look at what AWS is going to bring to the table, a lot's changed over the past 13 years with AWS, a lot more services are available, how should someone rebuild or re-platform and refactor their application of business with AI, with AWS? What are some of the tools that you see and recommend? Is it Serverless, is it SageMaker, CodeWhisperer? What do you think's going to shine brightly within the AWS stack, if you will, or service list, that's going to be part of this? As you mentioned, CodeWhisperer and SageMaker, what else should people be looking at as they start tinkering and getting all these benefits, and scale up their ups? >> You know, if we were a startup, first, I would really work backwards from the customer problem I try to solve, and pick and choose, bar, I don't need to deal with the undifferentiated heavy lifting, so. And that's where the answer is going to change. If you look at it then, the answer is not going to be like a one size fits all, so you need a very strong, I mean, granted on the compute front, if you can actually completely accurate it, so unless, I will always recommend it, instead of running compute for running your ups, because it takes care of all the undifferentiated heavy lifting, but on the data, and that's where we provide a whole variety of databases, right from like relational data, or non-relational, or dynamo, and so forth. And of course, we also have a deep analytical stack, where data directly flows from our relational databases into data lakes and data virus. And you can get value along with partnership with various analytical providers. The area where I do think fundamentally things are changing on what people can do is like, with CodeWhisperer, I was literally trying to actually program a code on sending a message through Twilio, and I was going to pull up to read a documentation, and in my ID, I was actually saying like, let's try sending a message to Twilio, or let's actually update a Route 53 error code. All I had to do was type in just a comment, and it actually started generating the sub-routine. And it is going to be a huge time saver, if I were a developer. And the goal is for us not to actually do it just for AWS developers, and not to just generate the code, but make sure the code is actually highly secure and follows the best practices. So, it's not always about machine learning, it's augmenting with automated reasoning as well. And generative AI is going to be changing, and not just in how people write code, but also how it actually gets built and used as well. You'll see a lot more stuff coming on this front. >> Swami, thank you for your time. I know you're super busy. Thank you for sharing on the news and giving commentary. Again, I think this is a AWS moment and industry moment, heavy lifting, accelerated value, agility. AIOps is going to be probably redefined here. Thanks for sharing your commentary. And we'll see you next time, I'm looking forward to doing more follow up on this. It's going to be a big wave. Thanks. >> Okay. Thanks again, John, always a pleasure. >> Okay. This is SiliconANGLE's breaking news commentary. I'm John Furrier with SiliconANGLE News, as well as host of theCUBE. Swami, who's a leader in AWS, has been on theCUBE multiple times. We've been tracking the growth of how Amazon's journey has just been exploding past five years, in particular, past three. You heard the numbers, great performance, great reviews. This is a watershed moment, I think, for the industry, and it's going to be a lot of fun for the next 10 years. Thanks for watching. (bright music)

>>from around the globe. It's the Cube covering space and cybersecurity. Symposium 2020 hosted by Cal Poly. Yeah, Lauren, Welcome to the Space and Cybersecurity Symposium 2020 put on by Cal Poly and hosted with Silicon Angle acute here in Palo Alto, California for a virtual conference. Couldn't happen in person this year. I'm John for a year. Host the intersection of space and cybersecurity. I'll see critical topics, great conversations. We got a great guest here to talk about the addressing the cybersecurity workforce gap, and we have a great guest, a feature speaker. Stewart Knox, the undersecretary with California's Labor and Workforce Development Office. Stewart Thanks for joining us today. >>Thank you so much, John. Appreciate your time today and listening to a little bit of our quandaries with making sure that we have the security that's necessary for the state of California and making sure that we have the work force that is necessary for cybersecurity in space. >>Great, I'd love to get started. I got a couple questions for you, but first take a few minutes for an opening statement to set the stage. >>Sure, realizing that in California we lead the nation in much of cybersecurity based on Department of Defense contractors within the Santa California leading the nation with over $160 billion within the industry just here in California alone and having over 800,000 bus workers. Full time employment in the state of California is paramount for us to make sure that we face, um, defense manufacturers approximate 700,000 jobs that are necessary to be filled. There's over 37,000 vacancies that we know of in California, just alone in cybersecurity. And so we look forward to making sure that California Workforce Development Agency is leading the charge to make sure that we have equity in those jobs and that we are also leading in a way that brings good jobs to California and to the people of California, a good education system that is developed in a way that those skills are necessarily met for the for the employers here in California and the nation, >>One of the exciting things about California is obviously look at Silicon Valley, Hewlett Packard in the garage, storied history space. It's been a space state. Many people recognize California. You mentioned defense contractors. It's well rooted with with history, um, just breakthroughs bases, technology companies in California. And now you've got technology. This is the cybersecurity angle. Um, take >>them into >>Gets more commentary to that because that's really notable. And as the workforce changes, these two worlds are coming together, and sometimes they're in the same place. Sometimes they're not. This is super exciting and a new dynamic that's driving opportunities. Could you share, um, some color commentary on that dynamic? >>Absolutely. And you're so correct. I think in California we lead the nation in the way that we developed programs that are companies lead in the nation in so many ways around, uh, cyberspace cybersecurity, Uh, in so many different areas for which in the Silicon Valley is just, uh, such a leader in those companies are good qualified companies to do so. Obviously, one of the places we play a role is to make sure that those companies have a skilled workforce. Andi, also that the security of those, uh, systems are in place for our defense contractors onda For the theater companies, those those outlying entities that are providing such key resource is to those companies are also leading on the cutting edge for the future. Also again realizing that we need to expand our training on skills to make sure that those California companies continue to lead is just, um, a great initiative. And I think through apprenticeship training programs on By looking at our community college systems, I think that we will continue to lead the nation as we move forward. >>You know, we've had many conversations here in this symposium, virtually certainly around. The everyday life of consumer is impacted by space. You know, we get our car service Uber lyft. We have maps. We have all this technology that was born out of defense contracts and r and D that really changed generations and create a lot of great societal value. Okay, now, with space kind of on the next generation is easier to get stuff into space. The security of the systems is now gonna be not only paramount for quality of life, but defending that and the skills are needed in cybersecurity to defend that. And the gap is there. What >>can we >>do to highlight the opportunities for career paths? It used to be the day when you get a mechanical engineering degree or aerospace and you graduated. You go get a job. Not anymore. There's a variety of of of paths career wise. What can we do to highlight this career path? >>Absolutely correct. And I think it starts, you know, k through 12 system on. I know a lot of the work that you know, with this bow and other entities we're doing currently, uh, this is where we need to bring our youth into an age where they're teaching us right as we become older on the uses of technology. But it's also teaching, um, where the levels of those education can take them k through 12. But it's also looking at how the community college system links to that, and then the university system links above and beyond. But it's also engage in our employers. You know, One of the key components, obviously, is the employers player role for which we can start to develop strategies that best meet their needs quickly. I think that's one of the comments we hear the most labor agency is how we don't provide a change as fast as we should, especially in technology. You know, we buy computers today, and they're outdated. Tomorrow it's the same with the technology that's in those computers is that those students are going to be the leaders within that to really develop how those structures are in place. S O. K. Through 12 is probably primary place to start, but also continuing. That passed the K 12 system and I bring up the employers and I bring them up in a way, because many times when we've had conversations with employers around what their skills needs were and how do we develop those better? One of the pieces that of that that I think is really should be recognized that many times they recognized that they wanted a four year degree, potentially or five year, six year degree. But then, when we really looked at the skill sets, someone coming out of the community college system could meet those skill sets. And I think we need to have those conversations to make sure not that they shouldn't be continue their education. They absolutely should. Uh, but how do we get those skill sets built into this into 12 plus the two year plus the four year person? >>You know, I love the democratization of these new skills because again. There's no pattern matching because they weren't around before, right? So you gotta look at the exposure to your point K through 12 exposure. But then there's an exploration piece of whether it's community, college or whatever progression. And sometimes it's nonlinear, right? I mean, people are learning different ways, combining the exposure and the exploration. That's a big topic. Can you share your view on this because this now opens up mawr doors for people choice. You got new avenues. You got online clock and get a cloud computing degree now from Amazon and walk in and help. I could be, you know, security clearance, possibly in in college. So you know you get exposure. Is there certain things you see? Is it early on middle school? And then I'll see the exploration Those air two important concepts. Can you unpack that a little bit exposure and exploration of skills? >>Absolutely. And I think this takes place, you know, not only in in the K 12 because somebody takes place in our community colleges and universities is that that connection with those employers is such a key component that if there's a way we could build in internships where experiences what we call on the job training programs apprenticeship training pre apprenticeship training programs into a design where those students at all levels are getting an exposure to the opportunities within the Space and Cybersecurity Avenue. I think that right there alone will start to solve a problem of having 37 plus 1000 openings at any one time in California. Also, I get that there's there's a burden on employers. Thio do that, and I think that's a piece that we have to acknowledge. And I think that's where education to play a larger role That's a place we had. Labor, Workforce, Development Agency, player role With our apprenticeship training programs are pre apprenticeship training programs. I could go on all day of all of our training programs that we have within the state of California. Many of the list of your partners on this endeavor are partners with Employment Training Panel, which I used to be the director of the Brown administration of um, That program alone does incumbent worker training on DSO. That also is an exposure place where ah worker, maybe, you know, you know, use the old adage of sweeping the floors one day and potentially, you know, running a large portion of the business, you know, within years. But it's that exposure that that employee gets through training programs on band. Acknowledging those skill sets and where their opportunities are, is what's valid and important. I think that's where our students we need to play a larger role in the K 12. That's a really thio Get that pushed out there. >>It's funny here in California you're the robotics clubs in high school or like a varsity sport. You're seeing kids exposed early on with programming. But you know, this whole topic of cybersecurity in space intersection around workforce and the gaps and skills is not just for the young. Certainly the young generations gotta be exposed to the what the careers could be and what the possible jobs and societal impact and contributions what they could be. But also it's people who are already out there. You know, you have retraining re Skilling is plays an important role. I know you guys do a lot of thinking on this is the under secretary. You have to look at this because you know you don't wanna have a label old and antiquated um systems. And then a lot of them are, and they're evolving and they're being modernized by digital transformation. So what does the role of retraining and skill development these programs play? Can you share what you guys are working on in your vision for that? >>Absolutely. That's a great question. And I think that is where we play a large role, obviously in California and with Kobe, 19 is we're faced with today that we've never seen before, at least in my 27 years of running program. Similar Thio, of course, in economic development, we're having such a large number of people displaced currently that it's unprecedented with unemployment rates to where we are. We're really looking at How do we take? And we're also going to see industries not return to the level for which they stood at one point in time. Uh, you know, entertainment industries, restaurants, all the alike, uh, really looking at how do we move people from those jobs that were middle skill jobs, topper skilled jobs? But the pay points maybe weren't great, potentially, and there's an opportunity for us to skill people into jobs that are there today. It may take training, obviously, but we have dollars to do that generally, especially within our K 12 and are que 14 systems and our universities. But we really wanna look at where those skill sets are are at currently. And we want to take people from that point in time where they said today, and try to give them that exposure to your point. Earlier question is, how do we get them exposed to a system for which there are job means that pay well with benefit packages with companies that care about their employees? Because that's what our goal is. >>You know. You know, I don't know if you have some visibility on this or ah opinion, but one observation that I've had and talking to whether it's a commercial or public sector is that with co vid uh, there have been a lot of awareness of the situation. We're adequately prepared. There's, um, readiness. But as everyone kind of deals with it, they're also starting to think about what to do. Post covert as we come out of it, Ah, growth strategy for a company or someone's career, um, people starting to have that on the top of their minds So I have to ask you, Is there anything that you see that they say? Okay, certain areas, maybe not doubling down on other areas. We're gonna double down on because we've seen some best practices on a trajectory of value for coming out of co vid with, you know, well, armed skills or certain things because you because that's what a lot of people are thinking right now. It's probably cyber is I mean, how many jobs are open? So you got well, that that's kind of maybe not something double down on here are areas we see that are working. Can you share your current visibility to that dynamic? >>Absolutely. Another great question. One of the key components that we look at Labor Workforce Development Agency. And so look at industries and growth modes and ones that are in decline boats. Now Kobe has changed that greatly. We were in a growth rate for last 78 years. We saw almost every industry might miss a few. You know that we're all in growth in one way or enough, obviously, that has changed. Our landscape is completely different than we saw 67 months ago. So today we're looking at cybersecurity, obviously with 30 plus 1000 jobs cos we're looking at Defense Department contractor is obviously with federal government contracts. We were looking at the supply chains within those we're looking at. Health care, which has always been one, obviously are large one of our large entities that has has grown over the years. But it's also changed with covered 19. We're looking at the way protective equipment is manufactured in the way that that will continue to grow over time. We're looking at the service industry. I mean, it will come back, but it won't come back the way we've seen it, probably in the past, but where the opportunities that we develop programs that we're making sure that the skill sets of those folks are transferrable to other industries with one of the issues that we face constant labor and were forced moment programs is understanding that over the period of time, especially in today's world again, with technology that people skill sets way, don't see is my Parents Day that you worked at a job for 45 years and you retired out of one job. Potentially, that is, that's been gone for 25 years, but now, at the pace for which we're seeing systems change. This is going to continue to amp up. I will stay youth of today. My 12 year old nephew is in the room next door to me on a classroom right now online. And so you know, there. It's a totally different atmosphere, and he's, you know, enjoying actually being in helping learning from on all online system. I would not have been able to learn that way, but I think we do see through the K Through 12 system where we're moving, um, people's interest will change, and I think that they will start to see things in a different way than we have in the past. They were forced systems. We are an old system been around since the thirties. Some even will say prior to the thirties came out of the Great Depression in some ways, and that system we have to change the way we develop our programs are should not be constant, and it should be an evolving system. >>It's interesting a lot of the conversation between the private and public partnerships and industry. You're seeing an agile mind set where it's a growth mindset. It's also reality based mindset and certainly space kind of forces. This conversation with cyber security of being faster, faster, more relevant, more modern. You mentioned some of those points, and with co vid impact the workforce development, it's certainly going to put a lot of pressure on faster learning. And then you mentioned online learning. This has become a big thing. It's not just putting education online per se. There's new touch points. You know you got APS, you got digital. This digital transformation is also accelerating. How do you guys view the workforce development? Because it's going to be open. It's gonna be evolving. There's new data coming in, and maybe kids don't want to stare at a video conference. Is there some game aspect to it? Is there how do you integrate thes new things that are coming really fast? And it's happening kind of in real time in front of our eyes. So I love to get your thoughts on how you guys see that, because it will certainly impact their ability to compete for jobs and or to itself learn. >>I think one of the key components of California's our innovation right and So I think one of the things that we pride ourselves in California is around that, um that said, that is the piece that I think the Silicon Valley and there's many areas in California that that have done the same, um, or trying to do the same, at least in their economy, is to build in innovation. And I think that's part of the K through 12 system with our with our our state universities and our UCS is to be able to bridge that. I think that you we see that within universities, um, that really instill an innovative approach to teaching but also instill innovation within their students. I'm not sure there yet with our fully with our K 12 system. And I think that's a place that either our community colleges could be a bridge, too, as well. Eso that's one component of workforce development I think that we look at as being a key. A key piece you brought up something that's really interesting to me is when you talk about agile on day, one of the things that even in state government on this, is gonna be shocking to you. But we have not been an agile system, Aziz. Well, I think one of the things that the Newsome administration Governor Newsom's administration has brought is. And when I talk about agile systems, I actually mean agile systems. We've gone from Kobol Systems, which are old and clunky, still operating. But at the same time, we're looking at upgrading all of our systems in a way that even our technology in the state of California should be matching the technology that our great state has within our our state. So, um, there in lies. It's also challenges of finding the qualified staff that we need in the state of California for all of our systems and servers and everything that we have. Um, currently. So you know, not only are we looking at external users, users of labor, workforce development, but we're looking at internal users that the way we redevelop our systems so that we are more agile in two different ways. >>You just got me. I triggered with COBOL. I programmed in the eighties with COBOL is only one credit lab in college. Never touched it again. Thank God. But this. But this >>is the >>benefit of cloud computing. I think this is at the heart, and this is the undertone of the conference and symposium is cloud computing. You can you can actually leverage existing resource is whether there legacy systems because they are running. They're doing a great job, and they do a certain work load extremely well. Doesn't make sense to replace what does a job, but you can integrate it in this. What cloud does this is Opening up? Can mawr more and more capabilities and workloads? This is kind of the space industry is pointing to when they say we need people that can code. And that could solve data problems. Not just a computer scientist, but a large range of people. Creative, um, data, science, everything. How does California's workforce solve the needs of America's space industry? This is because it's a space state. How do you see that? Let your workforce meeting those needs. >>Yeah, I think I think it's an investment. Obviously, it's an investment on our part. It's an investment with our college partners. It's an investment from our K 12 system to make sure that that we are allocating dollars in a way through meeting the demand of industry Onda, we do look at industry specific around there needs. Obviously, there's a large one. We wanna be very receptive and work with our employers and our employee groups to make sure that we need that demand. I think it's putting our money where our mouth is and and designing and working with employer groups to make sure that the training meets their needs. Um, it's also working with our employer groups to make sure that the employees are taken care of. That equity is built within the systems, Um, that we keep people employed in California on their able to afford a home, and they're able to afford a life here in California. But it's also again, and I brought up the innovation component. I think it's building an innovation within systems for which they are employers but are also our incoming employees are incumbent workers. And you brought this up earlier. People that already employed and people that are unemployed currently with the skill set that might match up, is how do we bridge those folks into employment that they maybe have not thought about. We have a whole career network of systems out throughout the city, California with the Americans job Centers of California on day will be working, and they already are working with a lot of dislocated workers on day. One of the key components of that is to really look at how do we, um, take what their current skills that might be and then expose them to a system for which we have 37 plus 1000 job openings to Andi? How do we actually get those books employed? It's paying for potentially through those that local Workforce Innovation Opportunity Act, funding for Americans job centers, um, to pay for some on the job, training it Z to be able to pay for work experiences. It's to be able to pay for internships for students, um, to get that opportunity with our employers and also partner with our employers that they're paying obviously a percentage of that, too. >>You know, one of the things I've observed over my, um, career 54 times around the sun is you know, in the old days when I was in college in school, you had career people have longer jobs, as you mentioned. Not like that anymore. But also I knew someone I'm gonna be in line to get that job, maybe nepotism or things of that nature. Now the jobs have no historical thing or someone worked longer in a job and has more seniority. Ah, >>lot of these >>jobs. Stewart don't HAVA requirements like no one's done them before. So the ability for someone who, um, is jumping in either from any college, there's no riel. It's all level set. It's like complete upside down script here. It's not like, Oh, I went to school. Therefore I get the job you could be Anyone could walk into these careers because the jobs air so new. So it's not where you came from or what school you went to or your nationality or gender. The jobs have been democratized. They're not discriminating against people with skills. So this opens up mawr. How >>do you >>see that? Because this really is an opportunity for this next generation to be more diverse and to be mawr contributed because diversity brings expertise and different perspectives. Your thoughts on that? >>Absolutely. And that was one of the things we welcome. Obviously we want to make sure that that everybody is treated equally and that the employers view everyone as employer employer of choice but an employee of choices. Well, we've also been looking at, as I mentioned before on the COVITZ situation, looking at ways that books that are maybe any stuck in jobs that are don't have a huge career pathway or they don't have a pathway out of poverty. I mean, we have a lot of working for people in the state of California, Um, that may now do to cope and lost their employment. Uh, this, you know, Let's let's turn back to the old, you know? Let's try, eliminate, eliminate, eliminate. How do we take those folks and get them employed into jobs that do have a good career pathway? And it's not about just who you knew or who you might have an in with to get that job. It is based on skills, I think, though that said there we need to have a better way to actually match those jobs up with those employers. And I think those are the long, ongoing conversations with those employer groups to make sure that one that they see those skill sets is valid and important. Um, they're helping design this crew sets with us, eh? So that they do match up and that were quickly matching up those close skills. That so that we're not training people for yesterday skills. >>I think the employer angles super important, but also the educators as well. One of the things that was asked in another question by the gas they they said. She said The real question to ask is, how early do you start exposing the next generation? You mentioned K through 12. Do you have any data or insight into or intuition or best practice of where that insertion point is without exposure? Point is, is that middle school is a elementary, obviously high school. Once you're in high school, you got your training. Wheels are off, you're off to the races. But is there a best practice? What's your thoughts? Stewart On exposure level to these kinds of new cyber and technical careers? >>Sure, absolutely. I I would say kindergarten. We San Bernardino has a program that they've been running for a little bit of time, and they're exposing students K through 12 but really starting in kindergarten. One is the exposure Thio. What a job Looks like Andi actually have. I've gone down to that local area and I've had three opportunity to see you know, second graders in a health care facility, Basically that they have on campus, built in on dear going from one workstation as a second grader, Uh, looking at what those skills would be and what that job would entail from a nurse to a Dr Teoh physician's assistant in really looking at what that is. Um you know, obviously they're not getting the training that the doctor gets, but they are getting the exposure of what that would be. Andi, I think that is amazing. And I think it's the right place to start. Um, it was really interesting because I left. This was pre covet, but I jumped on the plane to come back up north. I was thinking to myself, How do we get this to all school district in California, where we see that opportunity, um, to expose jobs and skill sets to kids throughout the system and develop the skill set so that they do understand that they have an opportunity. >>We're here at Cal Poly Space and Cybersecurity Symposium. We have educators. We have, um, students. We have industry and employers and government together. What's your advice to them all watching and listening about the future of work. Let's work force. What can people do? What do you think you're enabling? What can maybe the private sector help with And what are you trying to do? Can you share your thoughts on that? Because we have a range from the dorm room to the boardroom here at this event. Love to get your thoughts on the workforce development view of this. >>Yeah, absolutely. I think that's the mix. I mean, I think it's going to take industry to lead A in a lot of ways, in terms of understanding what their needs are and what their needs are today and what they will be tomorrow. I think it takes education, toe listen, and to understand and labor and workforce development also listen and understand what those needs will look like. And then how do we move systems? How do we move systems quickly? How do we move systems in a way that meets those needs? How do we, uh, put money into systems where the most need is, but also looking at trends? What is that trend going to look like in two years? What does that train gonna look like in five years. But that's again listening to those employers. Um, it's also the music community based organizations. I think, obviously some of our best students are also linked to CBS. And one way or another, it may be for services. It maybe for, uh, faith based. It may be anything, but I think we also need to bring in the CBS is Well, ah, lot of outreach goes through those systems in conjunction with, but I think that's the key component is to make sure that our employers are heard on. But they sit at the table like you said to the boardroom of understanding, and I think bringing students into that so that they get a true understanding of what that looks like a well, um, is a key piece of this. >>So one of the things I want to bring up with you is maybe a bit more about the research side of it. But, um, John Markoff, who was a former New York Times reporter with author of the book What the Dormouse, said It was a book about the counter culture of the sixties and the computer revolution, and really there was about how government defense spending drove the computer revolution that we now saw with Apple and PC, and then the rest is history in California has really participated. Stanford, uh, Berkeley and the University of California School system and all the education community colleges around it. That moment, the enablement. And now you're seeing space kind of bringing that that are a lot of research coming in and you eat a lot of billionaires putting money in. You got employers playing a role. You have this new focus space systems, cybersecurity, defending and making it open and and not congested and peaceful is going to enable quickly new inflection points for opportunities. E want to get your thoughts on that? Because California is participate in drove these revolutions that created massive value This next wave seems to be coming upon us. >>Yeah, absolutely. And again, Nazis covered again as too much of ah starting point to this. But I think that is also an opportunity to actually, because I think one of the things that we were seeing seven months ago was a skill shortage, and we still see the skills shortage, obviously. But I think a key piece to that is we saw people shortage. Not only was it skills shortage, but we didn't have enough people really to fill positions in addition to and I think that people also felt they were already paying the bills and they were making ends meet and they didn't have the opportunities. Thio get additional skills This again is where we're looking at. You know that our world has changed. It changed in the sixties based on what you're you're just expressing in terms of California leading the way. Let's like California lead the way again in developing a system from which labor, workforce development with our universities are, you know, are amazing universities and community college system and structure of how do we get students back into school? You know, a lot of graduates may already have a degree, but how do they now take a skill so that they already have and develop that further with the idea that they those jobs have changed? Whales have a lot of folks that don't have a degree, and that's okay. But how do we make that connection to a system that may have failed? Ah, lot of our people over the years, um, and our students who didn't make it through the school system. How do we develop in adult training school? How do we develop contract education through our community college system with our employer sets that we developed cohorts within those systems of of workers that have amazing talents and abilities to start to fill these needs? And I think that's the key components of hearing Agency, Labor, Workforce Development Agency. We work with our community. Colleges are UCS in our state universities t develop and figure that piece out, and I think it is our opportunity for the future. >>That's such a great point. I want to call that out This whole opportunity to retrain people that are out there because these air new jobs, I think that's a huge opportunity, and and I hope you keep building and investing in those programs. That's that's really worth calling out. Thank you for doing that. And, yeah, it's a great opportunity. Thes jobs they pay well to cyber security is a good job, and you don't really need to have that classical degree. You can learn pretty quickly if you're smart. So again, great call out there question for you on geography, Um, mentioned co vid we're talking about Covic. Virtualization were virtual with this conference. We couldn't be in person. People are learning virtually, but people are starting to relocate virtually. And so one observation that I have is the space state that California is there space clusters of areas where space people hang out or space spaces and whatnot. Then you got, like, the tech community cybersecurity market. You know, Silicon Valley is a talented in these hubs, and sometimes cyber is not always in the same hubs of space. Maybe Silicon Valley has some space here, Um, and some cyber. But that's not generally the case. This is an opportunity potentially to intersect. What's your thoughts on this? Because this is This is something that we're seeing where your space has historical, you know, geography ease. Now, with borderless communication, the work boat is not so much. You have to move the space area. You know what I'm saying? So okay. What's your thoughts on this? How do you guys look at this? Is on your radar On how you're viewing this this dynamic? >>It's absolute on our radar, Like you said, you know, here we are talking virtually on and, you know, 75% of all of our staff currently in some of our department that 80% of our staff are now virtual. Um you know, seven months ago, uh, we were not were government again being slow move, we quickly transitioned. Obviously, Thio being able to have a tele work capacity. We know employers move probably even quickly, more quickly than we did, but we see that as an opportunity for our rural areas. Are Central Valley are north state um, inland Empire that you're absolutely correct. I mean, if you didn't move to a city or to a location for which these jobs were really housed, um, you didn't have an opportunity like you do today. I think that's a piece that we really need to work with our education partners on of to be able to see how much this has changed. Labor agency absolutely recognizes this. We are investing funding in the Central Valley. We're investing funding in the North State and empire to really look a youth populations of how the new capacity that we have today is gonna be utilized for the future for employers. But we also have to engage our universities around. This is well, but mostly are employers. I know that they're already very well aware. I know that a lot of our large employers with, um, Silicon Valley have already done their doing almost 100% tele work policies. Um, but the affordability toe live in rural areas in California. Also, it enables us to have, ah, way thio make products more affordable is, well, potentially in the future. But we want to keep California businesses healthy and whole in California. Of course, on that's another way we can We can expand and keep California home to our 40 plus million people, >>most to a great, great work. And congratulations for doing such a great job. Keep it up. I gotta ask about the governor. I've been following his career since he's been office. A za political figure. Um, he's progressive. He's cutting edge. He likes toe rock the boat a little bit here and there, but he's also pragmatic. Um, you're starting to see government workers starting to get more of a tech vibe. Um um just curious from your perspective. How does the governor look at? I mean, the old, almost the old guard. But like you know, used to be. You become a lawyer, become a lawmaker Now a tech savvy lawmaker is a premium candidates, a premium person in government, you know, knowing what COBOL is. A start. I mean, these are the things. As we transform and evolve our society, we need thinkers who can figure out which side the streets, self driving cars go on. I mean, who does that? I mean, it's a whole another generation off thinking. How does the Governor how do you see this developing? Because this is the challenge for society. How does California lead? How do you guys talk about the leadership vision of Why California and how will you lead the future? >>Absolutely no governor that I'm aware of that I've been around for 26 27 years of workforce development has led with an innovation background, as this governor has a special around technology and the use of technology. Uh, you know, he's read a book about the use of technology when he was lieutenant governor, and I think it's really important for him that we, as his his staff are also on the leading edge of technology. I brought a badge. I'll systems. Earlier, when I was under the Brown administration, we had moved to where I was at a time employment training panel. We moved to an agile system and deported that one of the first within within the state to do that and coming off of an old legacy system that was an antique. Um, I will say it is challenging. It's challenging on a lot of levels. Mostly the skill sets that are folks have sometimes are not open to a new, agile system to an open source system is also an issue in government. But this governor, absolutely. I mean, he has established three Office of Digital Innovation, which is part of California and department technology, Um, in partnership with and that just shows how much he wants. Thio push our limits to make sure that we are meeting the needs of Californians. But it's also looking at, you know, Silicon Valley being at the heart of our state. How do we best utilize systems that already there? How do we better utilize the talent from those those folks is well, we don't always pay as well as they dio in the state. But we do have great benefit packages. Everybody does eso If anybody's looking for a job, we're always looking for technology. Folks is well on DSO I would say that this governor, absolute leads in terms of making sure that we will be on cutting edge of technology for the nation, >>you know, and, you know, talk about pay. I mean, I know it's expensive to live in some parts of California, but there's a huge young population that wants a mission driven job and serving, um, government for the governments. Awesome. Ah, final parting question for you, Stuart, is, as you look at, um, workforce. Ah, lot of people are passionate about this, and it's, you know, you you can't go anywhere without people saying, You know, we got to do education this way and that way there's an opinion everywhere you go. Cybersecurity is a little bit peaked and focused, but there are people who are paying attention to education. So I have to ask you, what creative ways can people get involved and contribute to workforce development? Whether it's stem underrepresented minorities, people are looking for new, innovative ways to contribute. What advice would you give these people who have the passion to contribute to the next cyber workforce. >>Yeah, I appreciate that question, because I think is one of the key components. But my secretary, Julie Sue, secretary of Labor and Workforce Development Agency, talks about often, and a couple of us always have these conversations around. One is getting people with that passion to work in government one or on. I brought it up community based organizations. I think I think so many times, um, that we didn't work with our CBS to the level of in government we should. This administration is very big on working with CBS and philanthropy groups to make sure that thing engagement those entities are at the highest level. So I would say, You know, students have opportunities. Thio also engage with local CBS and be that mission what their values really drives them towards Andi. That gives them a couple of things to do right. One is to look at what ways that we're helping society in one way or another through the organizations, but it also links them thio their own mission and how they could develop those skills around that. But I think the other piece to that is in a lot of these companies that you are working with and that we work with have their own foundations. So those foundations are amazing. We work with them now, especially in the new administration. More than we ever have, these foundations are really starting to help develop are strategies. My secretary works with a large number of foundations already. Andi, when we do is well in terms of strategy, really looking at, how do we develop young people's attitudes towards the future but also skills towards the future? >>Well, you got a pressure cooker of a job. I know how hard it is. I know you're working hard, appreciate you what you do and and we wish you the best of luck. Thank you for sharing this great insight on workforce development. And you guys working hard. Thank you for what you do. Appreciate it. >>Thank you so much. Thistle's >>three cube coverage and co production of the space and cybersecurity supposed in 2020 Cal Poly. I'm John for with silicon angle dot com and the Cube. Thanks for watching

>> Announcer: From around the globe, it's theCUBE! Covering Space and Cybersecurity Symposium 2020. Hosted by Cal Poly. >> Hello everyone. Welcome to the Space and Cybersecurity Symposium 2020, put on by Cal Poly and hosted with SiliconANGLE theCUBE here in Palo Alto, California for a virtual conference. Couldn't happen in person this year, I'm John Furrier, your host. The intersection of space and cybersecurity, obviously critical topics, great conversations. We've got a great guest here to talk about the addressing the cybersecurity workforce gap. And we have a great guest, and a feature speaker, Stewart Knox, the undersecretary with California's Labor and Workforce Development Office. Stewart, thanks for joining us today. >> Thank you so much, John. I appreciate your time today and listening to a little bit of our quandaries with making sure that we have the security that's necessary for the state of California and making sure that we have the workforce that is necessary for cybersecurity in space. >> Great. I'd love to get started. I've got a couple of questions for you, but first take a few minutes for an opening statement to set the stage. >> Sure, realizing that in California, we lead the nation in much of cybersecurity based on Department of Defense contractors within the state of California, leading the nation with over 160 billion dollars within the industry just here in California alone and having over 800,000 plus workers full time employment in the state of California is paramount for us to make sure that we face defense manufacturers, approximately 700,000 jobs that are necessary to be filled. There's over 37,000 vacancies that we know of in California, just alone in cybersecurity. And so we look forward to making sure that California Workforce Development Agency is leading the charge to make sure that we have equity in those jobs and that we are also leading in a way that brings good jobs to California and to the people of California, a good education system that is developed in a way that those skills are necessarily met for the employers here in California, and the nation. >> One of the exciting things about California is obviously look at Silicon Valley, Hewlett Packard and the garage story, history, space, it's been a space state, many people recognize California. You mentioned defense contractors. It's well rooted with history, just breakthroughs, bases, technology companies in California. And now you've got technology. This is the cybersecurity angle. Take a minute to give some more commentary to that because that's really notable, and as the workforce changes, these two worlds are coming together and sometimes they're in the same place, sometimes they're not. This is super exciting and a new dynamic that's driving opportunities. Could you share some color commentary on that dynamic? >> Absolutely. And you're so correct. I think in California, we lead the nation in the way that we develop programs, that our companies lead in the nation in so many ways around cyberspace, cybersecurity in so many different areas, for which in the Silicon Valley is just such a leader and those companies are good, qualified companies to do so. Obviously one of the places we play a role is to make sure that those companies have a skilled workforce. And also that the security of those systems are in place for our defense contractors and for the feeder companies, those outlying entities that are providing such key resources to those companies are also leading on a cutting edge for the future. Also again, realizing that we need to expand our training and skills to make sure that those California companies continue to lead, is just such a great initiative. And I think through apprenticeship training programs, and looking at our community college systems, I think that we will continue to lead the nation as we move forward. >> You know, we've had many conversations here in this symposium virtually, certainly around the everyday life of a consumer is impacted by space. You know, we get our car service, Uber, Lyft, we have maps, we have all this technology that was born out of defense contracts and R and D that really changed generations and created a lot of great societal value. Okay, now with space kind of going to the next generation, it's easier to get stuff into space. The security of the systems is now going to be not only paramount for quality of life, but defending that, and the skills are needed in cybersecurity to defend that. And the gap is there. What can we do to highlight the opportunities for career paths? It used to be the day where you get a mechanical engineering degree or aerospace and you graduate and you go get a job, not anymore. There's a variety of paths, career-wise. What can we do to highlight this career path? >> Absolutely correct. And I think it starts, you know, K through 12 system. And I know a lot of the work that (indistinct) and other entities are doing currently. This is where we need to bring our youth into an age where they're teaching us, right, as we become older, on the uses of technology, but it's also teaching where the levels of those education can take them, K through 12, but it's also looking at how the community college system links to that. And then the university system links above and beyond, but it's also engaging our employers. You know, one of the key components, obviously as the employers play a role, for which we can start to develop strategies that best meet their needs quickly. I think that's one of the comments we hear the most, at Labor Agency is how we don't provide a change as fast as we should, especially in technology. You know, we buy computers today and they're outdated tomorrow. It's the same with the technology that's in those computers is that those students are going to be the leaders within that to really develop how those structures are in place. So K through 12 is probably our primary place to start, but also continuing that past the K-12 system. And I bring up the employers and I bring them up in a way, because many times when we've had conversations with employers around what their skills needs were and how do we develop those better? One of the pieces of that, that I think really should be recognized, many times they recognize that they wanted a four year degree, potentially, or a five year or six year degree. But then when we really looked at the skillsets, someone coming out of the community college system could meet those skillsets. And I think we need to have those conversations to make sure, not that they shouldn't be continuing their education. They absolutely should. But how do we get those skillsets built into this into a K-12 plus the two year plus the four year person? >> Yeah, I love the democratization of these new skills, because again, there's no pattern matching 'cause they weren't around before, right? So you got to look at the exposure, to your point, K through 12 exposure, but then there's an exploration piece of it, whether it's community college or whatever progression, and sometimes it's nonlinear, right? I mean, people are learning different ways, combining the exposure and the exploration. That's a big topic. Can you share your view on this? Because this now opens up more doors for people, choice, you got new avenues, you got online, I can get a cloud computing degree now from Amazon and walk in and help. I can be, you know, security clearance possibly in college. So, you know, you get exposure. Is there certain things you see, is it early on? Middle school? And then obviously the exploration, those are two important concepts. Can you unpack that a little bit, exposure and exploration of skills? >> Absolutely, and I think this takes place not only in the K-12 system, but it takes place in our community colleges and our four year universities is that, that connection with those employers is such a key component, that if there's a way we could build in internships, work experiences, what we call on the job training programs, apprenticeship training, pre-apprenticeship training programs, into a design where those students at all levels are getting an exposure to the opportunities within the space and cybersecurity avenue. I think that right there alone will start to solve a problem of having 37 plus thousand openings at any one time in California. Also, I get that there's a burden on employers to do that. And I think that's a piece that we have to acknowledge, and I think that's where education can play a larger role. That's a place we at Labor Workforce Development Agency play a role with our apprenticeship training programs, our pre-apprenticeship training programs. I could go on all day of all of our training programs that we have within the state of California. Many of the list of your partners on this endeavor are partners with Employment Training Panel, which I used to be the director of the Brown administration of. That program alone does incumbent worker training. And so that also is an exposure place where a worker may be, you know, I use the old adage of sweeping the floors one day and potentially writing a large portion of the business, within years. But it's that exposure that that employee gets through training programs, and acknowledging those skill sets and where their opportunities are, is what's valid and important. I think that's where our students, we need to play a larger role than the K-12 system, really, to get that pushed out there. >> It's funny, here in California, you were the robotics clubs in high school are like a varsity sport, you're seeing kids exposed early on with programming, but it's, you know, this whole topic of cybersecurity and space intersection around workforce, and the gaps in the skills, it's not just for the young, certainly the young generation's got to be exposed to what the careers could be and what the possible jobs and societal impact and contributions, what they could be, but also it's people who are already out there. You know, you have retraining, re-skilling, this plays an important role. I know you guys do a lot of thinking on this as the undersecretary, you have to look at this because you know, you don't want to have a label "old and antiquated" systems. And a lot of them are, and they're evolving and they're being modernized by digital transformation. So what does the role of retraining and skill development for these programs play? Can you share what you guys are working on and your vision for that? >> Absolutely. That's a great question. 'Cause I think that is where we play a large role, obviously in California and with COVID-19 is we are faced with today that we've never seen before. At least in my 27 years of running programs, similar to all workforce and economic development, we are having such a large number of people displaced currently that it's unprecedented, we've got employment rates to where we are. We're really looking at how do we take, and we're also going to see industries not return to the level for which they stood at one point in time, you know, entertainment industries, restaurants, all of the alike, really looking at how do we move people from those jobs that were middle skill jobs to upper skill jobs, but the pay points maybe weren't great, potentially. And there's an opportunity for us to skill people into jobs that are there today. It may take training, obviously, but we have dollars to do that, generally, especially within our K-12 and our K-14 systems and our universities. But we really want to look at where those skillsets are at, currently. And we want to take people from that point in time where they sit today, and try to give them that exposure to your point earlier question is how do we get them exposed to a system for which there are job with means that pay well, with benefit packages, with companies that care about their employees. 'Cause that's what our goal is. >> You know, I don't know if you have some visibility on this or an opinion, but one of the observations that I've had and talk to whether it's a commercial or public sector, is that with COVID, there's been a lot of awareness of the situation. We're adequately prepared. There's some readiness, but as everyone kind of deals with it, they're also starting to think about what to do post-COVID as we come out of it, a growth strategy for a company or someone's career. People are starting to have that on the top of their minds. So I have to ask you, is there anything that you see that they say, "Okay, certain areas, maybe not doubling down on other areas, we're going to double down on because we've seen some best practices on a trajectory of value for coming out of COVID with, you know, well-armed skills or certain things." 'Cause that's what a lot of people are thinking right now. And certainly cyber is, I mean, how many jobs are open? So you got "Well that that's kind of maybe not something to double down on, here are areas we see that are working." Can you share your current visibility into that dynamic? >> Absolutely. Another great question. One of the key components that we look at at Labor Workforce Development Agency is to look at the industries in growth modes and ones that are in decline modes. Now COVID has changed that greatly. We were in a growth mode for the last seven, eight years. We saw almost every industry, minus a few, that were all in growth in one way or another, but obviously that has changed. Our landscape is completely different than we saw six, seven months ago. So today we're looking at cybersecurity, obviously with 30 plus thousand job openings, we are looking at Defense Department contractors, obviously, with federal government contracts. We are looking at the supply chains within those. We are looking at healthcare, which has always been one of obviously our large, one of our large entities that has grown over the years. But it's also changed with COVID-19. We're looking at the way protective equipment is manufactured and the way that that will continue to grow over time, we're looking at the service industry. I mean, it will come back, but it won't come back the way we've seen it probably in the past, but where are the opportunities that we develop programs that we are making sure that the skill sets of those folks are transferable to other industries. We have one of the issues that we face constantly in Labor and Workforce Development programs is understanding that over the period of time, especially in today's world, again, with technology, that people's skillsets, we don't see as in my parents' day that you worked at a job for 45 years and you retired at one job potentially. That's been gone for 25 years, but now at the pace for which we are seeing systems change, this is going to continue to amp up, and I will say, youth of today, my 12 year old nephew is in the room next door to me, in a classroom right now online. And so, you know, it's a totally different atmosphere and he's enjoying actually being at home and learning from an all online system. I would not have been able to learn that way, but I think we do see through the K through 12 system, the way we're moving, people's interests will change. And I think that they will start to see things in a different way than we have in the past. They were forced systems. We are an old system, been around since the 30s. Some even we'll say prior to the 30s, came out of the Great Depression in some ways. And that system, we have to change the way we develop our programs. It should not be constant and it should be an evolving system. >> It's interesting. A lot of the conversations between the private and public partnerships and industry, you're seeing an agile mindset where it's a growth mindset, it's also a reality-based mindset and certainly space kind of forces this conversation with cybersecurity of being faster, faster, more relevant, more modern. And you mentioned some of those points, and with COVID impact, the workforce development is certainly going to put a lot of pressure on faster learning. And then you mentioned online learning. This has become a big thing. It's not just putting education online per se. There's new touchpoints. You know, you've got apps, you've got digital. This digital transformation is also accelerating. How do you guys view the workforce development? Because it's going to be open. It's going to be evolving. There's new data coming in and maybe kids don't want to stare at a video conference. Is there some game aspect to it? Is there, how do you integrate these new things that are coming really fast, and it's happening kind of in real time in front of our eyes. So I'd love to get your thoughts on how you guys see that because it'll certainly impact their ability to compete for jobs and/or to self-learn. >> Well, I think one of the key components of California is our innovation, right? And so I think one of the things that we pride ourselves in California is around that. That said, that is the piece that I think the Silicon Valley, and then there's many areas in California that have done the same, or tried to do the same, at least in their economy is to build in innovation. And I think that's part of the K through 12 system, with our state universities and our UCs is to be able to bridge that. I think that you, we see that within universities that really instill an innovative approach to teaching, but also instill innovation within their students. I'm not sure we're there yet fully, with our K-12 system, and I think that's a place that either our community colleges could be a bridge to as well. So that's one component of workforce development I think that we look at as being a key piece. You brought up something that's really interesting to me is when you talk about agile, and one of the things that even in state government, this is going to be shocking to you, but we have not been an agile system as well. I think one of the things that the Newsom administration, Governor Newsom's administration has brought is, and when I talk about agile systems, I actually mean agile systems. We've gone from COBOL systems, which are old and clunky, still operating, but at the same time, we're looking at upgrading all of our systems in a way that even in our technology, in the state of California should be matching, the technology that our great state has within our state. So therein lies, it's also challenges of finding the qualified staff that we need in the state of California for all of our systems and servers and everything that we have currently. So, you know, not only are we looking at external users of labor workforce development, but we're looking at internal users, that the way we redevelop our systems so that we are more agile in two different ways. >> You just got me triggered with COBOL. I programmed in the 80s with COBOL, only one credit lab in college. Never touched it again, thank God. But this is the benefit of cloud computing. I think this is at the heart and this is the undertone of the conference and symposium is cloud computing, you can actually leverage existing resources, whether they're legacy systems, because they are running, they're doing a great job and they do a certain workload extremely well. Doesn't make sense to replace if it does a job. You can integrate it and that's what cloud does. This is opening up more and more capabilities and workloads. This is kind of what the space industry is pointing to when they say "We need people that can code and that can solve data problems," not just the computer scientists, but a large range of people, creative, data, science, everything. How does California's workforce solve the needs of America's space industry? This is because it's a space state. How do you see the labor workforce meeting those needs? >> Yeah, I think it's an investment. Obviously it's an investment on our part. It's an investment with our college partners. It's an investment from our K-12 system to make sure that we are allocating dollars in a way through meeting the demand of industry. And we do look at industry-specific around their needs, obviously this is a large one. We want to be very receptive, and work with our employers and our employee groups to make sure that we meet that demand. I think it's putting our money where our mouth is and designing and working with employer groups to make sure that the training meets their needs. It's also working with our employer groups to make sure that the employees are taken care of and that equity is built within the systems, that we keep people employed in California, and they're able to afford a home and they're able to afford a life here in California, but it's also again and I brought up the innovation component. I think it's building an innovation within systems for which they are employers, but are also our incoming employees and our incumbent workers. And you brought those up earlier, people that are already employed and people that are unemployed currently with a skill set that might match up is how do we bridge those folks into employment that they maybe have not thought about? We have a whole career network of systems out throughout The City of California with the America's Job Centers of California, and they will be working, and they already are working with a lot of dislocated workers. And one of the key components of that is to really look at how do we take what their current skillset might be, and then expose them to a system for which we have 37 plus thousand job openings, too, and how do we actually get those folks employed? It's paid for potentially through that local Workforce Innovation and Opportunity Act funding through our America's Job Centers, to pay for some on the job training. It's to be able to pay for work experiences, it's to be able to pay for internships for students to get that opportunity with our employers and also partnering with our employers that they're paying, obviously a percentage of that too. >> You know, one of the things I've observed over my career, 54 times around the sun is, you know, in the old days, when I was in college and school, you had career, people had the longer jobs, as you mentioned it's not like that anymore. But also I knew someone I'm going to to be in line to get that job, maybe nepotism or things of that nature. Now the jobs have no historical thing or someone worked longer in a job and has more seniority. A lot of these jobs, Stewart, don't have requirements, like no one's done them before. So the ability for someone who is jumping in, either from any college, there's no real, it's all level set, it's a complete upside down script here. It's not like, "Oh, I went to school, therefore I get the job." It can be, anyone can walk into these careers because the jobs are so new. So it's not where you came from or what school you went to or your nationality or gender. The jobs have been democratized. They're not discriminating against people with skills. This opens up more. How do you see that? Because this really is an opportunity for this next generation to be more diverse and to be more contributive because diversity brings expertise and different perspectives. Your thoughts on that. >> Absolutely, and that was one of the things we welcome, obviously. We want to make sure that that everybody is treated equally and that the employers view everyone as an employer of choice, but an employee of choice as well. We've also been looking at, as I mentioned before on the COVID situation, looking at ways that folks that are maybe stuck in jobs that don't have a huge career pathway, or they don't have a pathway out of poverty. I mean, we have a lot of working poor people in the state of California that may now due to COVID lost their employment. This, you know, let's turn back to the old adage, let's turn lemons into lemonade. How do we take those folks and get them employed into jobs that do have a good career pathway? And it's not about just who you knew, or who you might have an in with to get that job. It is based on skills. I think though, that said, we need to have a better way to actually match those jobs up with those employers. And I think those are the ongoing conversations with those employer groups to make sure that, one, that they see those skill sets as valid and important. They're helping design those career sets with us so that they do match up and that we're quickly matching up those close skillsets so that we're not training people for yesterday's skills. >> I think the employer angle's super important, but also the educators as well. One of the things that was asked in another question by the guest, they said, she said, the real question to ask is, how early do you start exposing the next generation? You mentioned K through 12, do you have any data or insight into or intuition or best practice of where that insertion point is, that exposure point? Is it middle school? Is it elementary, honestly, high school, once you're in high school, you got your training wheels are off, you're off to the races, but is there a best practice? What's your thoughts, Stewart, on exposure level to these kinds of new cyber and technical careers? >> Sure, absolutely. I would say kindergarten. We, San Bernardino has a program that they've been running for a little bit of time, and they're exposing students K through 12, but really starting in kindergarten. One is the exposure to what a job looks like. And then actually I've gone down to that local area and I've had the opportunity to see, you know, second graders in a healthcare facility, basically, that they have on campus built-in. And they're going from one workstation as a second grader, looking at what those skills would be and what that job would entail from a nurse to a doctor, to a physician's assistant, and really looking at what that is. You know, obviously they're not getting the training that a doctor gets, but they are getting the exposure of what that would be. And I think that is amazing. And I think it's the right place to start. It was really interesting 'cause as I left, this was pre-COVID, but as I jumped on the plane to come back up north, I was thinking to myself, "How do we get this to all school districts in California where we see that opportunity to expose jobs and skill sets to kids throughout the system and develop those skill sets so that they do understand that they have an opportunity?" >> We are here at Cal Poly Space and Cybersecurity Symposium. We have educators, we have students, we have industry and employers and government together. What's your advice to them all watching and listening about the future of work, this workforce, what can people do? What do you think you're enabling? What can maybe the private sector help with and what are you trying to do? Can you share your thoughts on that? Because we have a range from the dorm room to the boardroom here at this event. I'd love to get your thoughts on the workforce development view of this. >> Yeah, absolutely. And I think that's the mix. I mean, I think it's going to take industry to lead, in a lot of ways in terms of understanding what their needs are and what their needs are today and what they will be tomorrow. I think it takes education to listen, and to understand, and labor and workforce development to also listen and understand what those needs will look like. And then how do we move systems? How do we move systems quickly? How do we move systems in a way that meets those needs? How do we put money into systems where the most need is, but also looking at trends? What is that trend going to look like in two years? What is that trend going to look like in five years, (indistinct), again, listening to those employers, it's also listening to the community-based organizations. I think obviously some of our best students are also linked to CBOs in one way or another. It may be for services, it may be for faith-based, it may be anything, but I think we also need to bring in the CBOs as well. A lot of outreach goes through those systems in conjunction with, but I think that's the key component is to make sure that our employers are heard and that they sit at the table, like you said, to the boardroom of understanding, and I think bringing students into that so that they get a true understanding of what that looks like as well, is a key piece of this. >> Stu, one of the things I want to bring up with you is maybe a little bit more about the research side of it, but John Markoff, who was a former New York times reporter, but author of the book, "What the Dormouse Said," it was a book about the counterculture of the 60s and the computer revolution. And really it was about how government defense spending drove the computer revolution that we now saw with Apple and PC. And then the rest is history in California, has really participated, Stanford, the Berkeley, and the University of California school system, and all the education community colleges around it. That moment, the enablement, and now you're seeing space kind of bringing that, a lot of research coming in, need a lot of billionaires putting money in, you've got employers playing a role. You have this new focus, space systems, cybersecurity defending and making it open and, not congested and peaceful, is going to enable quickly, new inflection points for opportunities. I want to get your thoughts on that because California's participated and drove those revolutions, that's created massive value. This next wave seems to be coming upon us. >> Yeah, absolutely. And again, not to use COVID again as too much of a starting point to this, but I think that is also an opportunity to actually, 'cause I think one of the things that we were seeing seven months ago was a skill shortage, and we still see the skill shortage, obviously. But I think a key piece to that is we saw a people shortage. Not only was it skill shortage, but we didn't have enough people really to fill positions in addition, too, and I think that people also felt they were already paying the bills and they were making ends meet and they didn't have the opportunities to get additional skills. This again is where we're looking at, you know, our world has changed. It changed in the 60s based on what you're just expressing in terms of California leading the way. Let's let California lead the way again in developing a system for which labor workforce development with our universities, our amazing universities and community college system structure, of how do we get students back into school? You know, a lot of graduates may already have a degree, but how do they now take a skill set that they already have and develop that further with the idea that those jobs have changed? We also have a lot of folks that don't have a degree, and that's okay, but how do we make that connection to a system that may have failed a lot of our people over the years, and our students who didn't make it through the school system, how do we develop an adult training school? How do we develop contract education through our community college system with our employer sets, that we develop cohorts within the systems of workers that have amazing talents and abilities to start to fill these needs. And I think that's the key components that here at Labor Workforce Development Agency, we work with our community colleges, our UCs and our state universities to develop and figure that piece out. And I think it is our opportunity for the future. >> That's such a great point. I want to call that out, this whole opportunity to retrain people that are out there because these are new jobs. I think that's a huge opportunity and, I hope you keep building and investing in those programs. That's really worth calling out. Thank you for doing that. And yeah, it's a great opportunity to gain these jobs. They pay well, too, cybersecurity's a good job and you don't really need to have that classical degree. You can learn pretty quickly if you're smart. So again, great call out there. A question for you on geography. You mentioned COVID, we're talking about COVID, virtualization, we're virtual with this conference. We couldn't be in person. People are learning virtually, but people are starting to relocate virtually. And so one observation that I have is the space state that California is, there's space clusters of areas where space people hang out, or space spaces and whatnot. Then you got like the tech community, the cybersecurity market, you know, Silicon Valley, you know, the talent is in these hubs. And sometimes cyber's not always in the same hubs as space. Maybe Silicon Valley has some space here, and some cyber, but that's not generally the case. This is an opportunity potentially to intersect. What's your thoughts on this? Because this is something that we're seeing, where space has historical, you know, geographies. Now with borderless communication, the work mode is not so much "You have to move to this space area." You know what I'm saying? So what's your thoughts on this? How do you guys look at, this is on your radar, and how you're viewing this dynamic. >> It's absolutely on our radar. Like you said, you know, here we are, talking virtually, and you know, 75% of all of our staff currently, in some of our departments, it's 80% of our staff, are now virtual. Seven months ago, we were not. Government, again, being slow move, we quickly transitioned, obviously, to being able to have a telework capacity. We know employers moved probably even more quickly than we did, but we see that as an opportunity for our rural areas, our Central Valley, our Northstate, Inland Empire. That you're absolutely correct. I mean, if you didn't move to a city or to a location for which these jobs were really housed, you didn't have an opportunity like you do today. I think that's a piece that we really need to work with our education partners on, to be able to see how much this has changed. Labor Agency absolutely recognizes this. We are investing funding in the Central Valley. We're investing funding in the Northstate and Inland Empire to really look at youth populations, of how the new capacity that we have today is going to be utilized for the future for employers. But we also have to engage our universities around this as well, but mostly our employers. I know that they're already very well aware. I know that a lot of our large employers within Silicon Valley have already done it. They're doing almost 100% telework policies, but the affordability to live in rural areas in California, also enables us to have a way to make products more affordable as well, potentially in the future. But we want to keep California businesses healthy and whole in California, of course. And that's another way we can expand and keep California home to our 40 plus million people. >> Well Stewart, great work and congratulations for doing such a great job. Keep it up. I got to ask you about the governor. I've been following his career since he's been in office as a political figure. He's progressive, he's cutting edge. He likes to rock the boat a little bit here and there, but he's also pragmatic. You're starting to see government workers starting to get more of a tech vibe. Just curious from your perspective, how does the governor look at, I mean, the old, I won't say "old guard," but like, you know, it used to be, you become a lawyer, you become a lawmaker. Now a tech savvy lawmaker is a premium candidate, is a premium person in government. Knowing what COBOL is, is a start. I mean, these are the things that as we transform and evolve our society, we need thinkers who can figure out which side of the streets self driving cars go on. I mean, who does that? It's a whole nother generation of thinking. How does the governor, how do you see this developing? Because this is the challenge for society. How does California lead? How do you guys talk about the leadership vision of why California and how will you lead the future? >> Absolutely. No governor that I'm aware of, and I've been around for 26, 27 years of workforce development, has led with an innovation background as this governor has, especially around technology and the use of technology. You know, he's wrote a book about the use of technology when he was lieutenant governor. And I think it's really important for him that we, as his staff are also on the leading edge of technology. I brought up agile systems earlier. When I was under the Brown administration, we had moved to where I was at the time, Employment Training Panel, we moved to an agile system and deployed that. One of the first within the state to do that and coming off of an old legacy system that was an antique. I will say it is challenging. It's challenging on a lot of levels. Mostly the skill sets that our folks have, sometimes are not open to a new agile system, to an open source system is also an issue in government. But this governor absolutely, I mean, he has established the Office of Digital Innovation, which is part of California Department of Technology, in partnership with, and that just shows how much he wants to push our limits to make sure that we are meeting the needs of Californians. But it's also looking at, you know, Silicon Valley being at the heart of our state, how do we best utilize systems that are already there? How do we better utilize the talent from those folks as well? We don't always pay as well as they do in the state, but we do have great benefit packages, everybody knows. So if anybody's looking for a job, we're always looking for technology folks as well. And so I would say that this governor absolutely leads in terms of making sure that we will be on cutting edge technology for the nation. >> And, you know, talk about pay, I mean, I know it's expensive to live in some parts of California, but there's a huge young population that wants a mission-driven job, and serving the government for the government, it's awesome. A final parting question for you, Stewart, is as you look at the workforce, a lot of people are passionate about this and it's, you know, you can't go anywhere without people saying, you know, "We've got to do education this way, and that way," there's an opinion everywhere you go. Cybersecurity, obviously a little bit peaked and focused, but there are people who are paying attention to education. So I have to ask you what creative ways can people get involved and contribute to workforce development, whether it's STEM, underrepresented minorities, people are looking for new, innovative ways to contribute. What advice would you give these people who have the passion to contribute to the next cyber workforce? >> Yeah, I appreciate that question because I think it's one of the key components that my secretary, Julie Su, secretary of Labor and Workforce Development Agency, talks about often. And a couple of us always have these conversations around one is getting people with that passion to work in government, one, or, and I brought it up community-based organizations. I think so many times that we didn't work with our CBOs to the level that in government, we should, this administration is very big on working with CBOs and philanthropy groups to make sure that the engagement of those entities are at the highest level. So I would say, students have opportunities to also engage with local CBOs and be that mission, what their values really drives them towards. And that gives them a couple of things to do, right? One is to look at ways that we're helping society in one way or another through those organizations, but it also links them to their own mission and how they can develop those skills around that. But I think the other piece to that is in a lot of these companies that you are working with and that we work with, have their own foundations. So those foundations are amazing. We work with them now, especially in the Newsom administration, more than we ever have. These foundations are really starting to help develop our strategies. My secretary works with a large number of foundations already, and we do as well in terms of strategy, really looking at how do we develop young people's attitudes towards the future, but also skills towards the future? >> Well, you got a pressure cooker of a job. I know how hard it is. I know you're working hard and appreciate what you do. And, and we wish you the best of luck, thank you for sharing this great insight on workforce development. And you guys are working hard. Thank you for what you do. Appreciate it. >> Great. Thank you so much. I appreciate it. >> This is theCUBE coverage and co-production of the Space and Cybersecurity Symposium 2020 with Cal Poly. I'm John Furrier with siliconangle.com and theCUBE. Thanks for watching. (calm music)

>> Live from Washington DC, it's theCUBE, covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to AWS Public Sector Summit here in our nation's capital, Washington DC. I'm your host, Rebecca Knight, along with my cohost, John Furrier. We are joined by Daniel Castro. He is the Vice President Information Technology and Innovation Foundation, a think tank based here in town. Welcome, Daniel. >> Thanks for having me. >> So, the theme of this conference is all about modernizing government IT. I want to just start by asking a think tank analyst, how do you define IT modernization, particularly as it relates to the public sector? >> Yeah, I mean, I think a lot about how we've had this evolution, and how we do egovernment, right? And we've talked about the stages of egovernment before, for a long time, and it used to be that you had this very basic model. You put some information online, and then you had the transactional model, so you have some communication. Then you'd have something that was a little more interactive. So, maybe you get some more back and forth there. And now I think we're getting into this new model of egovernment. This next stage where we can possibly start automating a lot of more. We can start using AI. We can use IoT, and I think that's where there's a lot of excitement now because there's so much possibility with what we can do with government that didn't exist before, even five years ago. And so, to me, it's exciting to see things like where you can ask Alexa to do something with government, and you can start seeing this next wave that didn't exist even a few years ago. >> What kind of efficiencies do you see, because that seems to be a theme, using data, undifferienciated heavy-lifting tasks, where do you see the use cases in government for being more efficient with cloud and data? >> Well, I have a little bit of experience in government. I used to work in government, and one thing that a lot of people will tell you is that there's a lot of really boring things that you have to do when you're in government. There's a lot of really exciting things, really great things you can do when you're in government that's what attracts, I think, great people. But what I see is the possibility to take a lot of those boring activities out of government. The paperwork associated with your leave, and filing a claim, or all these things that people don't like, to me, that's the possibility. Can we get rid of the boring part of government and just have the really value-added part. And with data, I think that's where we're moving 'cause it's not about moving papers around and tracking. Government has a big information problem, it's can we really get to the core problem, which is the analytics, the decision-making, the problem solving. And that to me, you see so many companies on the floor that are saying, we'll take care of the security problem for you. We'll take care of the storage problem for you. we'll take care of the applications, and leave you to do that you actually wanted to do when you came to government. >> Get rid of the manual tasks, and leaving more room for the creative. And as you said, the analytical, the problem-solving. >> Right. >> Well the thing I want to ask you is that I'm old enough to see the original internet wave. And the US did a great job under the Department of Commerce when the internet came out, the domain name system. They worked internationally with ICANN, variety of other organizations, and so you had this nice growth of the internet. Now it just seems like it's highly accelerated, you got Facebook, you got YouTube. You got all these things going on. You have Amazon, these big whales of tech companies. There's a huge tech-lash going on. There's a lot of tech for good as well. So, we were just talking in our last segment, the pile for tech for good opportunities is a lot higher than the tech for bad, but everyone's focused on the bad actors right now. These are private companies. These aren't public entities, Facebook, YouTube, Amazon so they can't arrest anyone. They can't, they do what they do, right? >> Right. >> So where's the new way to get this under control? What's the think tank's perspectve? What's the community perspective in DC around this? >> What strikes me is the level of optism we see around technology has changed significantly, and part of that's driven by the tech-lash. If you go back to the '90s, people were excited about the potential of the internet, and what it could mean. We've done some analysis looking at even just the reporting in the media. We did sentiment anaylysis of how technology's being described, not just IT, but technology overall and innovation overall. You see a downward trend in the last 20 years. It's been steady, and it's been faster in the last 10 years. That affects, I think, the ability to get the public on board with new technology. It affects the ability of government to say, we're using technology for these new purposes. And it affects the policies. When you mentioned ICANN, the Departmemt of Commerce said We're going to do something fundamentally different with the internet, we're going to help create it, but keep our hands off it That idea was radical and new and exciting and innovative. Now we have all these new technologies like whether it's Jones or IoT or AI, but we don't have government necessarily saying, this is exciting and new and maybe we should do things different this time. We should think about a creative way of ensuring that we are not in the way of innovation. That we're putting in good guard rails to protect people, and instead they want to do kind of the old model, of let's regulate the technology, or focus on how it can go wrong instead of really focusing on how it might go right. >> Well, I got to say, we need more think tanks like what you guys are doing because my personal feeling, not being a very political person, and being from California, is you can't regulate what you don't understand. So if you don't understand it, then get out of the way, and a lot of people that I see in DC, certainly in elected official sides, they really don't know what they're talking about. They're mostly either lawyers or not tech savvy. And the ones that are tech savvy seem to be kind of oppressed, like where are they? Where's the revolution? >> So what's the answer then? I mean they... (laughs) >> Well, I think we have to educate more about what the potential is. When you see people start to understand, here's the technology, here's the benefits. But these are the 10 things we need to do to get there. They understand they need to do more. The problem is, some of the technology, it is kind of confusing to policy makers. Do you try to explain what machine learning is to a 70 year old elected official, and not all of them are familiar with it. Some of them are, but you look at the, Congress has an AI caucus. Congress also has a blockchain caucus, which do you think is bigger? >> Blockchain. >> Blockchain, of course, right? Because people think there's money there, it's immutable. But AI's going to be the one-- >> Infrastructure dynamic around supply chain. >> Yeah. >> Which is a data challenge because now you got encryption, and you have all kinds of immutability. So again, this is an exciting time but what do you do? Do you jump in? Nurture it? Regulate it? >> I think government, what traditionally people think about government is the lag around technology. What I like about this conference is, I think it'll show that government can be the leader in technology. When government's the leader in technology, it de-risks it for both the private sector and the rest of government. So it can say, we're going to be on the cutting edge. We're going to show how it can be done, and by being an early adopter, we can also help shape the technology. So when people are concerned about bias in AI or something, if government's an early adopter, they can help address some of those problems whether it's by making their own data sets available or showing-- >> When government is experimenting with the algorithms and then makes some mistakes, it builds more bias into it. It has more consequences, it feels like that at least. >> I think that's true, but I think the difference is nobody expects the private sector to necessarily put citizen's interest first, but that is government's role. Government's role is to say, how can we make our community better? So when it has a primary seat at the table, it can help shape the technology to get to those types of concerns. Now, of course you have to have a good government. So it's also important that we elect people who are excited about technology and protecting all people. The CIA, and now the DoD with Jedi, and a variety of other contracts going on, I think can be that leader again. If you look at the CIA is done, I think that is a great use case example, a leader gestating since 2013. DoD now on it. My friend, John Markoff, former New York Times columnist, wrote a book, What the Door Mouse Said. It's about how the hippy counter culture created the computer revolution, really from the build-up of technology around government funding to institutions and academic institutions. The counterculture developed, aka, the computer revolution. So I see a similar thing kind of happening now. It feels like you have all this tech out there. You've got this counterculture of people saying, why is there all this red tape? Why can't we use this data? Why is LinkedIn a site load of data? Why is Facebook doing what they're doing? So, I think the question should be asked, the question is, how should we take that position as the government to foster innovation, curb the bad, accelerate good, reward good. So the incentives could be digital I'd love to get your reaction to that. >> Yeah, I think that's a good point. What I see, we had a panel this morning on open data, and one of the big themes there was around the idea of collaboration. It's about partnerships between government and industry whether it's government providing the data, or industry providing the data, and also focusing on specific problems. I think that's how you get out of the siloed approach which is the concern that you have one federal agency, for example, focusing on, this is my problem. And I have the blinders on and not looking how it affects everyone else, and arguably that's the critique that a lot of people have about companies, that they're focused on one problem. They're not looking at the effects they have on the rest of the economy or society. I think you have collaberation on specific problems whether it's the opioid crisis or health care, or energy, then you start getting people from lots of different backgrounds saying, here's the resources we can bring to bear on these problems, and here's how we're going to fix it, and here's how we're going to do things differently. A lot of that gets to, do you have data that you can share? Do you have IT infrastructure that's interoperable? And do you have just kind of an organizational structure, that allows and encourages that type of collaboration? So I think when you keep kind of pushing it then, saying this is the future we want. These are the problems we're going to solve. Then it forces, even governments that are traditionally rigid to start re-orienting around new ways of solving problems. >> Well you know, open source software really could be an indicator of where this could go because you look at the generations of evolution in open source software. Collaberation that come out of that could be applied to data. >> Absolutely, and it forced second government agencies to rethink how they operate. It forced them to say, well maybe this traditional procurement model doesn't work. How else can we do things? How can we move to more service support? Those types of changes came about from a change in licensing the software. (laughs) >> Exactly. Well, Daniel, thank you so much for coming on theCUBE. It's been a pleasure, and we look forward to having you on again soon. >> Thanks for having me. >> Thanks for coming on. >> I'm Rebecca Knight, for John Furrier, we will have much more from AWS Public Sector Summit, here on theCUBE Teresa Carlson is coming up next. Stay tuned.

>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCube! (funky electronic music) Now, here's your host, Dave Vellante! >> Welcome, everybody, to this Cube conversation here in our Marlborough offices. I am very excited today, I spent a number of years at IDC, which, of course, is owned by IDG. And there's a new book out, relatively new, called Future Forward: Leadership Lessons from Patrick McGovern, the Visionary Who Circled the Globe and Built a Technology Media Empire. And it's a great book, lotta stories that I didn't know, many that I did know, and the author of that book, Glenn Rifkin, is here to talk about not only Pat McGovern but also some of the lessons that he put forth to help us as entrepreneurs and leaders apply to create better businesses and change the world. Glenn, thanks so much for comin' on theCube. >> Thank you, Dave, great to see ya. >> So let me start with, why did you write this book? >> Well, a couple reasons. The main reason was Patrick McGovern III, Pat's son, came to me at the end of 2016 and said, "My father had died in 2014 and I feel like his legacy deserves a book, and many people told me you were the guy to do it." So the background on that I, myself, worked at IDG back in the 1980s, I was an editor at Computerworld, got to know Pat during that time, did some work for him after I left Computerworld, on a one-on-one basis. Then I would see him over the years, interview him for the New York Times or other magazines, and every time I'd see Pat, I'd end our conversation by saying, "Pat, when are we gonna do your book?" And he would laugh, and he would say, "I'm not ready to do that yet, there's just still too much to do." And so it became sort of an inside joke for us, but I always really did wanna write this book about him because I felt he deserved a book. He was just one of these game-changing pioneers in the tech industry. >> He really was, of course, the book was even more meaningful for me, we, you and I started right in the same time, 1983-- >> Yeah. >> And by that time, IDG was almost 20 years old and it was quite a powerhouse then, but boy, we saw, really the ascendancy of IDG as a brand and, you know, the book reviews on, you know, the back covers are tech elite: Benioff wrote the forward, Mark Benioff, you had Bill Gates in there, Walter Isaacson was in there, Guy Kawasaki, Bob Metcalfe, George Colony-- >> Right. >> Who actually worked for a little stint at IDC for a while. John Markoff of The New York Times, so, you know, the elite of tech really sort of blessed this book and it was really a lot to do with Pat McGovern, right? >> Oh, absolutely, I think that the people on the inside understood how important he was to the history of the tech industry. He was not, you know, a household name, first of all, you didn't think of Steve Jobs, Bill Gates, and then Pat McGovern, however, those who are in the know realize that he was as important in his own way as they were. Because somebody had to chronicle this story, somebody had to share the story of the evolution of this amazing information technology and how it changed the world. And Pat was never a front-of-the-TV-camera guy-- >> Right. >> He was a guy who put his people forward, he put his products forward, for sure, which is why IDG, as a corporate name, you know, most people don't know what that means, but people did know Macworld, people did know PCWorld, they knew IDC, they knew Computerworld for sure. So that was Pat's view of the world, he didn't care whether he had the spotlight on him or not. >> When you listen to leaders like Reed Hoffman or Eric Schmidt talk about, you know, great companies and how to build great companies, they always come back to culture. >> Yup. >> The book opens with a scene of, and we all, that I usually remember this, well, we're just hangin' around, waitin' for Pat to come in and hand out what was then called the Christmas bonus-- >> Right. >> Back when that wasn't politically incorrect to say. Now, of course, it's the holiday bonus. But it was, it was the Christmas bonus time and Pat was coming around and he was gonna personally hand a bonus, which was a substantial bonus, to every single employee at the company. I mean, and he did that, really, literally, forever. >> Forever, yeah. >> Throughout his career. >> Yeah, it was unheard of, CEOs just didn't do that and still don't do that, you were lucky, you got a message on the, you know, in the lunchroom from the CEO, "Good work, troops! Keep up the good work!" Pat just had a really different view of the culture of this company, as you know from having been there, and I know. It was very familial, there was a sense that we were all in this together, and it really was important for him to let every employee know that. The idea that he went to every desk in every office for IDG around the United States, when we were there in the '80s there were probably 5,000 employees in the US, he had to devote substantial amount-- >> Weeks and weeks! >> Weeks at a time to come to every building and do this, but year after year he insisted on doing it, his assistant at the time, Mary Dolaher told me she wanted to sign the cards, the Christmas cards, and he insisted that he ensign every one of them personally. This was the kind of view he had of how you keep employees happy, if your employees are happy, the customers are gonna be happy, and you're gonna make a lot of money. And that's what he did. >> And it wasn't just that. He had this awesome holiday party that you described, which was epic, and during the party, they would actually take pictures of every single person at the party and then they would load the carousel, you remember the 35-mm. carousel, and then, you know, toward the end of the evening, they would play that and everybody was transfixed 'cause they wanted to see their, the picture of themselves! >> Yeah, yeah. (laughs) >> I mean, it was ge-- and to actually pull that off in the 1980s was not trivial! Today, it would be a piece of cake. And then there was the IDG update, you know, the Good News memos, there was the 10-year lunch, the 20-year trips around the world, there were a lot of really rich benefits that, you know, in and of themselves maybe not a huge deal, but that was the culture that he set. >> Yeah, there was no question that if you talked to anybody who worked in this company over, say, the last 50 years, you were gonna get the same kind of stories. I've been kind of amazed, I'm going around, you know, marketing the book, talking about the book at various events, and the deep affection for this guy that still holds five years after he died, it's just remarkable. You don't really see that with the CEO class, there's a couple, you know, Steve Jobs left a great legacy of creativity, he was not a wonderful guy to his employees, but Pat McGovern, people loved this guy, and they st-- I would be signing books and somebody'd say, "Oh, I've been at IDG for 27 years and I remember all of this," and "I've been there 33 years," and there's a real longevity to this impact that he had on people. >> Now, the book was just, it was not just sort of a biography on McGovern, it was really about lessons from a leader and an entrepreneur and a media mogul who grew this great company in this culture that we can apply, you know, as business people and business leaders. Just to give you a sense of what Pat McGovern did, he really didn't take any outside capital, he did a little bit of, you know, public offering with IDG Books, but, really, you know, no outside capital, it was completely self-funded. He built a $3.8 billion empire, 300 publications, 280 million readers, and I think it was almost 100 or maybe even more, 100 countries. And so, that's an-- like you were, used the word remarkable, that is a remarkable achievement for a self-funded company. >> Yeah, Pat had a very clear vision of how, first of all, Pat had a photographic memory and if you were a manager in the company, you got a chance to sit in meetings with Pat and if you didn't know the numbers better than he did, which was a tough challenge, you were in trouble! 'Cause he knew everything, and so, he was really a numbers-focused guy and he understood that, you know, his best way to make profit was to not be looking for outside funding, not to have to share the wealth with investors, that you could do this yourself if you ran it tightly, you know, I called it in the book a 'loose-tight organization,' loose meaning he was a deep believer in decentralization, that every market needed its own leadership because they knew the market, you know, in Austria or in Russia or wherever, better than you would know it from a headquarters in Boston, but you also needed that tightness, a firm grip on the finances, you needed to know what was going on with each of the budgets or you were gonna end up in big trouble, which a lot of companies find themselves in. >> Well, and, you know, having worked there, I mean, essentially, if you made your numbers and did so ethically, and if you just kind of followed some of the corporate rules, which we'll talk about, he kind of left you alone. You know, you could, you could pretty much do whatever you wanted, you could stay in any hotel, you really couldn't fly first class, and we'll maybe talk about that-- >> Right. >> But he was a complex man, I mean, he was obviously wealthy, he was a billionaire, he was very generous, but at the same time he was frugal, you know, he drove, you know, a little, a car that was, you know, unremarkable, and we had buy him a car. He flew coach, and I remember one time, I was at a United flight, and I was, I had upgraded, you know, using my miles, and I sat down and right there was Lore McGovern, and we both looked at each other and said right at the same time, "I upgraded!" (laughs) Because Pat never flew up front, but he would always fly with a stack of newspapers in the seat next to him. >> Yeah, well, woe to, you were lucky he wasn't on the plane and spotted you as he was walking past you into coach, because he was not real forgiving when he saw people, people would hide and, you know, try to avoid him at all cost. And, I mean, he was a big man, Pat was 6'3", you know, 250 lbs. at least, built like a linebacker, so he didn't fit into coach that well, and he wasn't flying, you know, the shuttle to New York, he was flyin' to Beijing, he was flyin' to Moscow, he was going all over the world, squeezing himself into these seats. Now, you know, full disclosure, as he got older and had, like, probably 10 million air miles at his disposal, he would upgrade too, occasionally, for those long-haul flights, just 'cause he wanted to be fresh when he would get off the plane. But, yeah, these are legends about Pat that his frugality was just pure legend in the company, he owned this, you know, several versions of that dark blue suit, and that's what you would see him in. He would never deviate from that. And, but, he had his patterns, but he understood the impact those patterns had on his employees and on his customers. >> I wanna get into some of the lessons, because, really, this is what the book is all about, the heart of it. And you mentioned, you know, one, and we're gonna tell from others, but you really gotta stay close to the customer, that was one of the 10 corporate values, and you remember, he used to go to the meetings and he'd sometimes randomly ask people to recite, "What's number eight?" (laughs) And you'd be like, oh, you'd have your cheat sheet there. And so, so, just to give you a sense, this man was an entrepreneur, he started the company in 1964 with a database that he kind of pre-sold, he was kind of the sell, design, build type of mentality, he would pre-sold this thing, and then he started Computerworld in 1967, so it was really only a few years after he launched the company that he started the Computerworld, and other than Data Nation, there was nothing there, huge pent-up demand for that type of publication, and he caught lightning in a bottle, and that's really how he funded, you know, the growth. >> Yeah, oh, no question. Computerworld became, you know, the bible of the industry, it became a cash cow for IDG, you know, but at the time, it's so easy to look in hindsight and say, oh, well, obviously. But when Pat was doing this, one little-known fact is he was an editor at a publication called Computers and Automation that was based in Newton, Massachusetts and he kept that job even after he started IDC, which was the original company in 1964. It was gonna be a research company, and it was doing great, he was seeing the build-up, but it wasn't 'til '67 when he started Computerworld, that he said, "Okay, now this is gonna be a full-time gig for me," and he left the other publication for good. But, you know, he was sorta hedging his bets there for a little while. >> And that's where he really gained respect for what we'll call the 'Chinese Wallet,' the, you know, editorial versus advertising. We're gonna talk about that some more. So I mentioned, 1967, Computerworld. So he launched in 1964, by 1971, he was goin' to Japan, we're gonna talk about the China Stories as well, so, he named the company International Data Corp, where he was at a little spot in Newton, Mass.-- >> Right, right. >> So, he had a vision. You said in your book, you mention, how did this gentleman get it so right for so long? And that really leads to some of the leadership lessons, and one of them in the book was, sort of, have a mission, have a vision, and really, Pat was always talking about information, about information technology, in fact, when Wine for Dummies came out, it kind of created a little friction, that was really off the center. >> Or Wine for Dummies, or Sex for Dummies! >> Yeah, Sex for Dummies, boy, yeah! >> With, that's right, Ruth Westheimer-- >> Dr. Ruth Westheimer. >> But generally speaking, Glenn, he was on that mark, he really didn't deviate from that vision. >> Yeah, no, it was very crucial to the development of the company that he got people to, you know, buy into that mission, because the mission was everything. And he understood, you know, he had the numbers, but he also saw what was happening out there, from the 1960s, when IBM mainframes filled a room, and, you know, only the high priests of data centers could touch them. He had a vision for, you know, what was coming next and he started to understand that there would be many facets to this information about information technology, it wasn't gonna be boring, if anything, it was gonna be the story of our age and he was gonna stick to it and sell it. >> And, you know, timing is everything, but so is, you know, Pat was a workaholic and had an amazing mind, but one of the things I learned from the book, and you said this, Pat Kenealy mentioned it, all American industrial and social revolutions have had a media company linked to them, Crane and automobiles, Penton and energy, McGraw-Hill and aerospace, Annenberg, of course, and TV, and in technology, it was IDG. >> Yeah, he, like I said earlier, he really was a key figure in the development of this industry and it was, you know, one of the key things about that, a lot publications that came and went made the mistake of being platform or, you know, vertical market specific. And if that market changed, and it was inevitably gonna change in high tech, you were done. He never, you know, he never married himself to some specific technology cycle. His idea was the audience was not gonna change, the audience was gonna have to roll with this, so, the company, IDG, would produce publications that got that, you know, Computerworld was actually a little bit late to the PC game, but eventually got into it and we tracked the different cycles, you know, things in tech move in sine waves, they come and go. And Pat never was, you know, flustered by that, he could handle any kind of changes from the mainframes down to the smartphone when it came. And so, that kind of flexibility, and ability to adjust to markets, really was unprecedented in that particular part of the market. >> One of the other lessons in the book, I call it 'nation-building,' and Pat shared with you that, look, that you shared, actually, with your readers, if you wanna do it right, you've gotta be on the ground, you've gotta be there. And the China story is one that I didn't know about how Pat kind of talked his way into China, tell us, give us a little summary of that story. >> Sure, I love that story because it's so Pat. It was 1978, Pat was in Tokyo on a business trip, one of his many business trips, and he was gonna be flying to Moscow for a trade show. And he got a flight that was gonna make a stopover in Beijing, which in those days was called Peking, and was not open to Americans. There were no US and China diplomatic relations then. But Pat had it in mind that he was going to get off that plane in Beijing and see what he could see. So that meant that he had to leave the flight when it landed in Beijing and talk his way through the customs as they were in China at the time with folks in the, wherever, the Quonset hut that served for the airport, speaking no English, and him speaking no Chinese, he somehow convinced these folks to give him a day pass, 'cause he kept saying to them, "I'm only in transit, it's okay!" (laughs) Like, he wasn't coming, you know, to spy on them on them or anything. So here's this massive American businessman in his dark suit, and he somehow gets into downtown Beijing, which at the time was mostly bicycles, very few cars, there were camels walking down the street, they'd come with traders from Mongolia. The people were still wearing the drab outfits from the Mao era, and Pat just spent the whole day wandering around the city, just soaking it in. He was that kind of a world traveler. He loved different cultures, mostly eastern cultures, and he would pop his head into bookstores. And what he saw were people just clamoring to get their hands on anything, a newspaper, a magazine, and it just, it didn't take long for the light bulb to go on and said, this is a market we need to play in. >> He was fascinated with China, I, you know, as an employee and a business P&L manager, I never understood it, I said, you know, the per capita spending on IT in China was like a dollar, you know? >> Right. >> And I remember my lunch with him, my 10-year lunch, he said, "Yeah, but, you know, there's gonna be a huge opportunity there, and yeah, I don't know how we're gonna get the money out, maybe we'll buy a bunch of tea and ship it over, but I'm not worried about that." And, of course, he meets Hugo Shong, which is a huge player in the book, and the home run out of China was, of course, the venture capital, which he started before there was even a stock market, really, to exit in China. >> Right, yeah. No, he was really a visionary, I mean, that word gets tossed around maybe more than it should, but Pat was a bonafide visionary and he saw things in China that were developing that others didn't see, including, for example, his own board, who told him he was crazy because in 1980, he went back to China without telling them and within days he had a meeting with the ministry of technology and set up a joint venture, cost IDG $250,000, and six months later, the first issue of China Computerworld was being published and within a couple of years it was the biggest publication in China. He said, told me at some point that $250,0000 investment turned into $85 million and when he got home, that first trip, the board was furious, they said, "How can you do business with the commies? You're gonna ruin our brand!" And Pat said, "Just, you know, stick with me on this one, you're gonna see." And the venture capital story was just an offshoot, he saw the opportunity in the early '90s, that venture in China could in fact be a huge market, why not help build it? And that's what he did. >> What's your take on, so, IDG sold to, basically, Chinese investors. >> Yeah. >> It's kind of bittersweet, but in the same time, it's symbolic given Pat's love for China and the Chinese people. There's been a little bit of criticism about that, I know that the US government required IDC to spin out its supercomputer division because of concerns there. I'm always teasing Michael Dow that at the next IDG board meeting, those Lenovo numbers, they're gonna look kinda law. (laughs) But what are your, what's your, what are your thoughts on that, in terms of, you know, people criticize China in terms of IP protections, etc. What would Pat have said to that, do you think? >> You know, Pat made 130 trips to China in his life, that's, we calculated at some point that just the air time in planes would have been something like three and a half to four years of his life on planes going to China and back. I think Pat would, today, acknowledge, as he did then, that China has issues, there's not, you can't be that naive. He got that. But he also understood that these were people, at the end of the day, who were thirsty and hungry for information and that they were gonna be a player in the world economy at some point, and that it was crucial for IDG to be at the forefront of that, not just play later, but let's get in early, let's lead the parade. And I think that, you know, some part of him would have been okay with the sale of the company to this conglomerate there, called China Oceanwide. Clearly controversial, I mean, but once Pat died, everyone knew that the company was never gonna be the same with the leader who had been at the helm for 50 years, it was gonna be a tough transition for whoever took over. And I think, you know, it's hard to say, certainly there's criticism of things going on with China. China's gonna be the hot topic page one of the New York Times almost every single day for a long time to come. I think Pat would have said, this was appropriate given my love of China, the kind of return on investment he got from China, I think he would have been okay with it. >> Yeah, and to invoke the Ben Franklin maxim, "Trading partners seldom wage war," and so, you know, I think Pat would have probably looked at it that way, but, huge home run, I mean, I think he was early on into Baidu and Alibaba and Tencent and amazing story. I wanna talk about decentralization because that was always something that was just on our minds as employees of IDG, it was keep the corporate staff lean, have a flat organization, if you had eight, 10, 12 direct reports, that was okay, Pat really meant it when he said, "You're the CEO of your own business!" Whether that business was, you know, IDC, big company, or a manager at IDC, where you might have, you know, done tens of millions of dollars, but you felt like a CEO, you were encouraged to try new things, you were encouraged to fail, and fail fast. Their arch nemesis of IDG was Ziff Davis, they were a command and control, sort of Bill Ziff, CMP to a certain extent was kind of the same way out of Manhasset, totally different philosophies and I think Pat never, ever even came close to wavering from that decentralization philosophy, did he? >> No, no, I mean, I think that the story that he told me that I found fascinating was, he didn't have an epiphany that decentralization would be the mechanism for success, it was more that he had started traveling, and when he'd come back to his office, the memos and requests and papers to sign were stacked up two feet high. And he realized that he was holding up the company because he wasn't there to do this and that at some point, he couldn't do it all, it was gonna be too big for that, and that's when the light came on and said this decentralization concept really makes sense for us, if we're gonna be an international company, which clearly was his mission from the beginning, we have to say the people on the ground in those markets are the people who are gonna make the decisions because we can't make 'em from Boston. And I talked to many people who, were, you know, did a trip to Europe, met the folks in London, met the folks in Munich, and they said to a person, you know, it was so ahead of its time, today it just seems obvious, but in the 1960s, early '70s, it was really not a, you know, a regular leadership tenet in most companies. The command and control that you talked about was the way that you did business. >> And, you know, they both worked, but, you know, from a cultural standpoint, clearly IDG and IDC have had staying power, and he had the three-quarter rule, you talked about it in your book, if you missed your numbers three quarters in a row, you were in trouble. >> Right. >> You know, one quarter, hey, let's talk, two quarters, we maybe make some changes, three quarters, you're gone. >> Right. >> And so, as I said, if you were makin' your numbers, you had wide latitude. One of the things you didn't have latitude on was I'll call it 'pay to play,' you know, crossing that line between editorial and advertising. And Pat would, I remember I was at a meeting one time, I'm sorry to tell these stories, but-- >> That's okay. (laughs) >> But we were at an offsite meeting at a woods meeting and, you know, they give you a exercise, go off and tell us what the customer wants. Bill Laberis, who's the editor-in-chief at Computerworld at the time, said, "Who's the customer?" And Pat said, "That's a great question! To the publisher, it's the advertiser. To you, Bill, and the editorial staff, it's the reader. And both are equally important." And Pat would never allow the editorial to be compromised by the advertiser. >> Yeah, no, he, there was a clear barrier between church and state in that company and he, you know, consistently backed editorial on that issue because, you know, keep in mind when we started then, and I was, you know, a journalist hoping to, you know, change the world, the trade press then was considered, like, a little below the mainstream business press. The trade press had a reputation for being a little too cozy with the advertisers, so, and Pat said early on, "We can't do that, because everything we have, our product is built, the brand is built on integrity. And if the reader doesn't believe that what we're reporting is actually true and factual and unbiased, we're gonna lose to the advertisers in the long run anyway." So he was clear that that had to be the case and time and again, there would be conflict that would come up, it was just, as you just described it, the publishers, the sales guys, they wanted to bring in money, and if it, you know, occasionally, hey, we could nudge the editor of this particular publication, "Take it a little bit easier on this vendor because they're gonna advertise big with us," Pat just would always back the editor and say, "That's not gonna happen." And it caused, you know, friction for sure, but he was unwavering in his support. >> Well, it's interesting because, you know, Macworld, I think, is an interesting case study because there were sort of some backroom dealings and Pat maneuvered to be able to get the Macworld, you know, brand, the license for that. >> Right. >> But it caused friction between Steve Jobs and the writers of Macworld, they would write something that Steve Jobs, who was a control freak, couldn't control! >> Yeah. (laughs) >> And he regretted giving IDG the license. >> Yeah, yeah, he once said that was the worst decision he ever made was to give the license to Pat to, you know, Macworlld was published on the day that Mac was introduced in 1984, that was the deal that they had and it was, what Jobs forgot was how important it was to the development of that product to have a whole magazine devoted to it on day one, and a really good magazine that, you know, a lot of people still lament the glory days of Macworld. But yeah, he was, he and Steve Jobs did not get along, and I think that almost says a lot more about Jobs because Pat pretty much got along with everybody. >> That church and state dynamic seems to be changing, across the industry, I mean, in tech journalism, there aren't any more tech journalists in the United States, I mean, I'm overstating that, but there are far fewer than there were when we were at IDG. You're seeing all kinds of publications and media companies struggling, you know, Kara Swisher, who's the greatest journalist, and Walt Mossberg, in the tech industry, try to make it, you know, on their own, and they couldn't. So, those lines are somewhat blurring, not that Kara Swisher is blurring those lines, she's, you know, I think, very, very solid in that regard, but it seems like the business model is changing. As an observer of the markets, what do you think's happening in the publishing world? >> Well, I, you know, as a journalist, I'm sort of aghast at what's goin' on these days, a lot of my, I've been around a long time, and seeing former colleagues who are no longer in journalism because the jobs just started drying up is, it's a scary prospect, you know, unlike being the enemy of the people, the first amendment is pretty important to the future of the democracy, so to see these, you know, cutbacks and newspapers going out of business is difficult. At the same time, the internet was inevitable and it was going to change that dynamic dramatically, so how does that play out? Well, the problem is, anybody can post anything they want on social media and call it news, and the challenge is to maintain some level of integrity in the kind of reporting that you do, and it's more important now than ever, so I think that, you know, somebody like Pat would be an important figure if he was still around, in trying to keep that going. >> Well, Facebook and Google have cut the heart out of, you know, a lot of the business models of many media companies, and you're seeing sort of a pendulum swing back to nonprofits, which, I understand, speaking of folks back in the mid to early 1900s, nonprofits were the way in which, you know, journalism got funded, you know, maybe it's billionaires buying things like the Washington Post that help fund it, but clearly the model's shifting and it's somewhat unclear, you know, what's happening there. I wanted to talk about another lesson, which, Pat was the head cheerleader. So, I remember, it was kind of just after we started, the Computerworld's 20th anniversary, and they hired the marching band and they walked Pat and Mary Dolaher walked from 5 Speen Street, you know, IDG headquarters, they walked to Computerworld, which was up Old, I guess Old Connecticut Path, or maybe it was-- >> It was actually on Route 30-- >> Route 30 at the time, yeah. And Pat was dressed up as the drum major and Mary as well, (laughs) and he would do crazy things like that, he'd jump out of a plane with IDG is number one again, he'd post a, you know, a flag in Antarctica, IDG is number one again! It was just a, it was an amazing dynamic that he had, always cheering people on. >> Yeah, he was, he was, when he called himself the CEO, the Chief Encouragement Officer, you mentioned earlier the Good News notes. Everyone who worked there, at some point received this 8x10" piece of paper with a rainbow logo on it and it said, "Good News!" And there was a personal note from Pat McGovern, out of the blue, totally unexpected, to thank you and congratulate you on some bit of work, whatever it was, if you were a reporter, some article you wrote, if you were a sales guy, a sale that you made, and people all over the world would get these from him and put them up in their cubicles because it was like a badge of honor to have them, and people, I still have 'em, (laughs) you know, in a folder somewhere. And he was just unrelenting in supporting the people who worked there, and it was, the impact of that is something you can't put a price tag on, it's just, it stays with people for all their lives, people who have left there and gone on to four or five different jobs always think fondly back to the days at IDG and having, knowing that the CEO had your back in that manner. >> The legend of, and the legacy of Patrick J. McGovern is not just in IDG and IDC, which you were interested in in your book, I mean, you weren't at IDC, I was, and I was started when I saw the sort of downturn and then now it's very, very successful company, you know, whatever, $3-400 million, throwin' off a lot of profits, just to decide, I worked for every single CEO at IDC with the exception of Pat McGovern, and now, Kirk Campbell, the current CEO, is moving on Crawford del Prete's moving into the role of president, it's just a matter of time before he gets CEO, so I will, and I hired Crawford-- >> Oh, you did? (laughs) >> So, I've worked for and/or hired every CEO of IDC except for Pat McGovern, so, but, the legacy goes beyond IDG and IDC, great brands. The McGovern Brain Institute, 350 million, is that right? >> That's right. >> He dedicated to studying, you know, the human brain, he and Lore, very much involved. >> Yup. >> Typical of Pat, he wasn't just, "Hey, here's the check," and disappear. He was goin' in, "Hey, I have some ideas"-- >> Oh yeah. >> Talk about that a little. >> Yeah, well, this was a guy who spent his whole life fascinated by the human brain and the impact technology would have on the human brain, so when he had enough money, he and Lore, in 2000, gave a $350 million gift to MIT to create the McGovern Institute for Brain Research. At the time, the largest academic gift ever given to any university. And, as you said, Pat wasn't a guy who was gonna write a check and leave and wave goodbye. Pat was involved from day one. He and Lore would come and sit in day-long seminars listening to researchers talk about about the most esoteric research going on, and he would take notes, and he wasn't a brain scientist, but he wanted to know more, and he would talk to researchers, he would send Good News notes to them, just like he did with IDG, and it had same impact. People said, "This guy is a serious supporter here, he's not just showin' up with a checkbook." Bob Desimone, who's the director of the Brain Institute, just marveled at this guy's energy level, that he would come in and for days, just sit there and listen and take it all in. And it just, it was an indicator of what kind of person he was, this insatiable curiosity to learn more and more about the world. And he wanted his legacy to be this intersection of technology and brain research, he felt that this institute could cure all sorts of brain-related diseases, Alzheimer's, Parkinson's, etc. And it would then just make a better future for mankind, and as corny as that might sound, that was really the motivator for Pat McGovern. >> Well, it's funny that you mention the word corny, 'cause a lot of people saw Pat as somewhat corny, but, as you got to know him, you're like, wow, he really means this, he loves his company, the company was his extended family. When Pat met his untimely demise, we held a crowd chat, crowdchat.net/thankspat, and there's a voting mechanism in there, and the number one vote was from Paul Gillen, who posted, "Leo Durocher said that nice guys finish last, Pat McGovern proved that wrong." >> Yeah. >> And I think that's very true and, again, awesome legacy. What number book is this for you? You've written a lot of books. >> This is number 13. >> 13, well, congratulations, lucky 13. >> Thank you. >> The book is Fast Forward-- >> Future Forward. >> I'm sorry, Future Forward! (laughs) Future Forward by Glenn Rifkin. Check out, there's a link in the YouTube down below, check that out and there's some additional information there. Glenn, congratulations on getting the book done, and thanks so much for-- >> Thank you for having me, this is great, really enjoyed it. It's always good to chat with another former IDGer who gets it. (laughs) >> Brought back a lot of memories, so, again, thanks for writing the book. All right, thanks for watching, everybody, we'll see you next time. This is Dave Vellante. You're watchin' theCube. (electronic music)

>> Over and welcome to this special cube conversation here in the Palo Alto Studios of Cube. Part of our People. First project with Mayfield Fund and Co creation with Cuban John Very your host. Very special guest. Judy Estrin. She's the CEO of J Labs and author of the book Closing the Innovation Gap. She's also well known for being an Internet entrepreneur. Pioneer worked on the initial TCP IP protocol with Vin Cerf from When the A Stanford Great History Computer Science. You have computer systems in your blood, and now you're mentoring a lot of companies. Author you a lot of work, and you're lending your voice to some cutting edge issues here in Silicon Valley and around the world. Thanks for joining me today for the conversation. >> Thank you. It's fun to be here, >> So I love the fact that you're here. You're a celebrity in the commute computer industry circles. You were there at the beginning, when the computer systems or the Internet were being connected as they built out of stone of the whole system's revolution in the eighties, and the rest is history. Now we have cloud computing, and now we're seeing a whole nother level step function of scale. And so you've kind of seen it all. You've seen all all the waves. Actually, something like make is they have seen some of the ways, but you've seen all of them. The most compelling thing I think that's happening now is the convergence of social science and computer science. Kind of our motto. Silicon Angle. You recently wrote to Post on Medium that that has been kind of trending and going viral. I want to get your perspective on that. And they're They're interesting because they they bring a little bit of computer science called the authoritative Authority Terrian Technology Reclaiming Control far too attention, part one. We go into great detail to lay out some big picture computer industry discussions. What's it all about? What's what's the What's the idea behind these stories? >> So let me back up a little bit in that, a Sze Yu said. And we can go into this if you want. I was very involved in a lot of thie, ah, innovation that happened in the Village Valley in terms of microprocessors, the Internet, networking, everything that laid the foundation for a lot of the things we see today incredible opportunities for my career for problems we solved over the last ten years. Ten, twelve years. Um, I began to see a shift and a shift in the culture and a shift in the way technology was impacting us. And it's not all good or bad. It's that it felt like we were out of balance and that we were becoming shorter and shorter, term focused and actually my book in two thousand eight closing the innovation gap. The main message there is let's not forget about the seeds you plant that all of this comes from because we're reaping the benefit of those seeds. We're not planning new seats and that we were becoming in the Valley in the nation the way we thought about things more and more short term focused and technology was causing some of that and benefitting and not been and at a disadvantage because of that. So that started with my book in two thousand eight and then in twenty fourteen, I think it was I did a Ted talk a Ted X talk called Balancing our Digital Diets, and I was even Mohr concerned that we were out of whack in terms of the consequences of innovation, and I drew an analogy to our food's systems, where so much innovation and creating cheap calories and energy and things like high fructose corn syrup that it took years to realize that, Oh, there's some negative consequences of that innovation. And so that was kind of a warning that, um, we weren't thinking enough about the consequences of at that point. Social media. That was before fake news, and I talked about tweets and how truth that lies went faster than truth, not knowing how bad that situation was going to be and then leading up to the election and after the election. We all know and have all learned now about the impacts of these technologies on our democracy, and I believe on our society and humanity. And I don't think it's just about our election system. I think it's about our psyches and how the technology's air impacting the way we think our fear and anxiety level of our kids and us is adults. So I been talking to people about it and advising, and I finally decided as, uh, I was collaborating with people that I felt that a lot of the awareness was in pockets that we talked about data privacy or we talked about addiction. But these air things were all interrelated, and so I wanted to one ad. My voices is technologists because I think a lot of the people who are writing the building, the awareness and talking about it if you are in government or a journalist's or even a social scientist people, it's really easy to say, Yeah, you say that, but you don't understand. It's more complicated than that. You don't understand the technology. So one, I do understand that technology. So I felt adding my voice as a technologist. But I'm also, uh, just increasingly concerned about what we do about it and that we take a more holistic view. So that's what, what what the pieces are about. And the reason I broke it into two pieces is because they're too long for most people, even the way they are. But the first is to build awareness of the problems which we can dig into it a high level if you want. And then the second is to throw out ideas as we move towards discussing solutions. So let me take a breath because you were goingto jump in, and then I can. >> No, it's just because you're connecting the foundational of technology foundation technology, identifying impact, looking at pockets of awareness and then looking at how it's all kind of coming together when you talk like that The first time I saw O subsystem interrupt us connection so someone could get like a operating system. And I think the society that you're pointing out in the article, the first one intention was there only to relate. And I think that's the key part. I think that's interesting because we run into people all the time when we do our cue broadcasts that have awareness here and don't know what's going on this. So this context that's highly cohesive. But there's no connection, right? So the decoupled right but highly cohesive, That's kind of systems. Architecture concept. So how do we create a robust technology's society system where technology and I think that's a threat that we're seeing this? What I cleaned out of the articles was your kind of raising the flag a little bit to the notion of big picture right system, kind of a foundational, but let's look at consequences and inter relationships, and how can we kind of orchestrate and figure out solutions? So what was the reaction to expand on that concept? Because this is where I was. It was provocative to me, >> right? So I think there are two thought trains that I just went down. One is that one of the problems we have that has been created by technology and technology is suffering from again. It's causing both cause and effect is not enough seats, system thinking and so one issue, which is not just this is not just about social media and not just about a I, but over the last twenty years we've increasingly trained, I think, are, Ah, engineers and computer scientists in Mohr transactional thinking. And as we move quicker and quicker to solve problems, we are not training our leaders or training our technologist to think in terms of systems. And so what I mean by systems is two things that you can break, that any problems have pieces. But those pieces air inter connected. We are interconnected, and that you, if you don't keep those things in mind, then you will not design things in a way, I believe that have the longevity and make the right type decisions. The second is the law of consequences when you have a system, if you do something here, it's going to impact something here. And so that whole notion of taking was thinking through consequences. I'm afraid that we're training people as we are focusing on being more and more agile, moving more and more quickly that it's in technology and in society that we're losing some of that system, thinking >> that they kind of think that's the trade off is always around. Whenever he had systems conversations in the past, but my old systems had on trade offs, we have overhead, so we have more memory. How do we handle things? So this is kind of That's just what happens. You tell about consequence, but >> we don't have all those we I'm older than you. But we started at a time when that we were limited. We were limited by memory. We were limited by processing. We were limited by band with and a different times. As thie industry emerged, the constraints were in different areas. Today, you don't have any of those constraints. And so, if you don't have any of those constraints. You don't get trained in thinking about trade offs and thinking about consequences. So when when we come into just what drove me to write, this one set of things are foundational issues and what I mean by foundational it's it's our relationship to technology. And the fact of the matter is, as a society, um, we put technology on a pedestal, and we have, uh, this is not to be taken out of Cut is not to be taken the extreme of talking about people, but overall, our relationship with technology is a bullying, controlling relationship. That's why I called it authoritarianism. >> Upgrade your iPhone to the new version. >> Well, whether it's as a user that you're giving up your your your authority to all these notifications and to your addiction, whether it is the fact that it is the control with the data, whether it is predictive ai ai algorithms that are reading your unconscious behaviors and telling you what you think, because if it's suggesting what you by putting things in front of you. So there are all of these behaviors that our relationship with technology is not a balanced relationship and you could one. You have a culture where the companies that are that have that power are driving towards. It's a culture of moving fast growth only don't think about the consequences. It's not just the unintended consequences, but it's the consequences of intended use. So the business models and at which we don't need to go into, because I think a lot of other people talk about that all end up with a situation which is unhealthy for us as people and humanity and for us as a society. So you take that part and it is. There's a parallel here, and we should learn from what happened with industrial Ah, the industrial revolution. We want progress. But if we don't pay attention to the harm, the harmful byproducts and trade offs of progress, it's why we have issues with climate. It's why we have plastic in our oceans. It's because you, you judge everything by progresses just growth and industrialization without thinking about well being or the consequences. Well, I believe we now face a similar challenge of digitization, so it's not industrialization. But it's digitalization that has byproducts in a whole number of areas. And so what the the article does is get into those specifics, whether it's data or anxiety, how we think our cognitive abilities, our ability to solve problems, All of those things are byproducts of progress. And so we should debate um, where we what we're willing to give up one last thing. And then I'll have to come in, which is one of the problems with both of these is is humans value convenience. We get addicted to convenience, and if somebody gives us something that is going to make things more convenient, it sure is held to go backward. And that's one of the reasons the combination of measuring our goodness as a country or a CZ. Globalization by economic growth and measuring our personal wellness by convenience, if something is more convenient, were happier. Take those two together, and it makes a dangerous cop combination because then our need for community convenience gets manipulated for continued economic growth. And it doesn't necessarily end up in, Ah, progress from, ah, well being perspective. >> It's interesting point about the digitization, because the digital industrial revolution, when the digital revolution is happening, has consequences. We're seeing them and you point them out in your post Facebook and fake news. There's also the global landscape is the political overlay. There's societal impact. There's not enough scholars that I've been trained in the art of understanding into relationships of technology, and Peg used to be a nerd thing. And now my kids are growing up. Digital natives. Technology is mainstreams, and there it is. Politics. You know, the first hack collection, Some of the control, The first president actually trolled his way. That president, I said that I'm the kid. That was my position. He actually was a successful troll and got everyone he trolled the media and you got the attention. These air new dynamics, This is reality. So is you look forward and bring these ideas, and I want to get your thoughts on ideas on how to bring people together. You've been on a CTO Cisco Systems. I know you've been sleeping on a board. This is a cross pollination opportunity. Bring people together to think about this. How do you do You look at that? How do you view how to take the next steps as a as an industry, as a society and as a global nations? It eventually, because cyber security privacy is becoming polarized. Also on a geography bases in China they have. GPR is hard core there. In Europe, he got Asia. With Chinese. You got America being American. It's kind of complicated as a system architecture thinking. How do you look at this? What is the playing field where the guard rails? What's your thoughts on this? Because it's a hard one, >> right? So it is a hard one and it isn't. It isn't easy to pave out a path that says it's solvable. Um, nor does Climate right now. But you have to believe we're going to figure it out because we have to figure it out. So I think there are a lot of pieces that we need to start with, and then we need to adjust along the way. And, um, one piece is and let me back up. I am not. I don't believe we can leave this up to the industry to solve the incentives and the value systems and the understanding of the issues. The industry is coming from an industry perspective, and you can't also. You also can't leave it just two technologists because technologists have a technology person perspective. I don't believe that you just can have government solve it for a variety of reasons. One is, if it takes a spectrum of things to legislation, tends to be retroactive, not forward looking. And you need to be really careful not to come up with regulation that actually reinforces the status quo as opposed to making something better. But I think we need to. We do need to figure out how to govern in a way that includes all of these things. So once >> it's running, it's clear that watching the Facebook hearing and watching soon dark sky in front of the house. Our current elected officials actually don't even know how the Internet works, so that's one challenge. So you have a shift in its every beat >> and it and it's actually, if you think about the way legislation often gets made one of the problems with our democracy right now, I'm not going to put it in quotes. But I want to put it >> out. >> Is that the influence of money on our democracy means that so often the input toe legislation comes from industry. So whether it's again big tech, big pharma, big Oil, big. That's the way this cycle works in places where we have had successful legislation that industry input, what you need industry input. You just don't want industry to be the on ly input that is balanced with other input. And so we need infrastructure in the world. In the country that has policy ideas, technology. This needs to come from civil society, from the academy from non profits. So you need the same way we have environmental sciences. We need to fund from government, not just industry funded that science. That's number one. And then we need ways to have conversations about influencing companies to do the right thing. Some of it is going to be through legislation some of it is going to be for through pressure. This, in some ways is like tobacco in some ways, like it's like food. In some ways, it's like climate on DH. It's so and an underlying any of this to happen. We need people to understand and to speak up because awareness amongst whether it's individuals, parents, teachers, we need to give people the information to protect themselves and to push back on companies and to rally pushback on government. Because if if there's not an awareness of people are walking around saying, Don't take away my service, don't make this less convenient don't tax my soda. Don't tell me my text messages. That's right, so and I'm not saying taxes of the way. But if there isn't what what I'm focused on is, how do we build awareness? How do we get information out? How do we get companies like yours and others that this becomes part of >> our >> messaging of understanding so we can be talking about I >> think it's, you know back, Teo, The glory days of the TCP epi Internet revolution. He sent a package from here to there. It's a step. Take a first step. I personally listening to you talk feel and I said, It's on The Cuban people know that. You know, my my rap know that I've been pounding this. There's a counter culture in there somewhere. Counter culture's is where action happens, and I think you know, tax regulation and, you know, the current generations inherited. It is what it is we have. You're laying out essentially the current situation. John Markoff wrote a great book, What the door Mail said, talking about how the sixties counterculture influence the computer industry from breaking in for getting computer time for time sharing, too hippy revolution question I have for you put you on the spot. Is Is there a counterculture in your mind? Coming a digital hippie quotes is because I feel it. I feel that that let the air out of the balloon before it pops. Something has to happen and I think has to be a counterculture. I yet yet can't put my finger on it. Maybe it's a digital kind of a revolution, something compelling that says Whoa time out. >> All right? I think we need a couple of counter culture's in that in layers of it, because, um, I think there is going to be or is starting to be a counterculture amongst technologist and the technology industry and entrepreneurs who are some it's still small who are saying, You know what? This chasing unicorns and fastest growth and scale, you know, move faxed and break things. But, um, we want to move fast, but we want to think about whether we're breaking what we're breaking is really dangerous, you know, move fast and break things is fine, but if it's oops, we broke democracy. That isn't something that, uh that is I'm sorry you have to think about and adapt more quickly. So I think there is Are people who are talking about let's talk openly about the harm. Let's not just be tech optimists. Let's understand that it's small, but it's beginning and you're seeing it in a I for instance, the people who are saying Look, were technologists, we want to be responsible. This is a powerful weapon or tool. And let's make sure we think about how we use it. Let me just say one thing, which is, I think we needed another kind of counterculture, which I'm hoping is happing in a number of areas, which is societally saying, You know, we have a slow food movement. Maybe we just need a slow down, a little bit movement. So if you look at mindfulness, if you look at kids who are starting to say, You know what? I want to talk to someone in person, I don't. So we we need some of that counter movement where I'm hoping the pedestal starts to come back. In terms of people looking for real connectivity and not just numbers of connections, >> it's interesting, You know, everything has a symmetrical, responsible thing about it. For every fake news payload and network effect is potentially an opposite reaction of quality network effect. It's interesting, and I don't know where it is, but I think that's got it could be filled, certainly on the economic side, by new entrepreneurial thinking, like one observation I'm making is you know this. Remember, they'll bad boys of tech and he's smiling. Now It's bad gals, too, which is growing still lower numbers. So I think there's gonna be a shift to the good, the good folks right moment. But she's a she's a good entrepreneur. She's not just out there to make a quick buck or hey, mission driven za signal we're seeing. So you start to see a little bit more of a swing to Whoa, hey, let's recognize that it's not about, you know, could Buck or >> so, yes, but between you and I, it's teeny compared to the other forces. So that's what those of us who believe that needs to happen need to continue to >> one of those forces money making. >> I think it's a combination of, Ah, money and how much money, Dr. Celebrity culture, um, the forces, the power that's in place is so strong that it's hard to break through, um, short term thinking, not even being trained. So like so many things in our culture, where you have entrenched power and then you see uprising and you get hope and that's where you need the hope. But, um, we've seen it so often in so many movements, from race to gender, where you think, Oh, that's solved, it's not solved and then you come back in and come back at it. So I just I would argue that there is little bits of it, but it needs fuel. It needs continuity. It it. And the reason I think we need some government regulation is it needs help because it's not gonna >> happen. You should question, you know, some successes that I point out Amazon Web services, Google even having a long game kind of narrative they're always kind of were misunderstood at first. Remember, Google was loud by search is not doing too well. Then the rest is history. Amazon was laughed. Amazon Web services was laughed at. So people who have the long game seemed to be winning in these transitions. And that's kind of what you're getting at. You think long term, the long game. If you think in terms of the long term vision, you then going look at consequences differently. How many people do you run in? The valleys actually think like that. Okay, >> so we're talking about two different things. One is long term thinking, and I do think that apple, Google, Amazon have taken long term thinking's. So there are a good example. But if you look at them, if we look at the big companies in terms of the way they approached the market and competition and their potential negative impacts on overall society, they're part of the power. They're not doing anything to change the systems, to not >> have good and continue to benefit. The rich get richer. >> So there this This is why it's complicated. There are not good guys and bad guys there are. These people are doing this and that. So do I think overall dough? I see more long term thinking. Um, not really. I think that the incentives in the investment community, the incentives in the stock market. The incentives culturally are still very much around shorter term thinking. Not that there aren't any, but >> yeah, I would agree. I mean, it tends to be, you know, Hey, we're crushing it. We're winning, you know? Look at us. Growth hack. I mean, just the languages. Semantics. You look at that. I think it's changed. I think Facebook is, I think, the poster child of short term thinking growth hacks move fast, break stuff and look where they are, you know, they can't actually sustaining and brand outside of Facebook, they have to buy Instagram and these other companies to actually get the kind of growth. But certainly Facebook is dominate on the financial performance, but they're kind of sitting in their situation. I think you know the bro Grammer movement, I think is kind of moving through the white common ear culture of Okay, let's get some entrepreneurship going. Great. Rod. I think that's stabilising. I think we're seeing with cloud really science and thinking for good. That's a positive sign. >> Well, I'm I'm glad to hear that from you, you know, and all >> you're probably going with. >> No, no, no, I'll take that and take that into feeding my hope because I hope, >> well, the movement is classic. Look, we're not gonna tolerate this anymore. I think transparency in my final question to you before you get to some of the more entrepreneur Question says, If you look at the role of community on data, science and connectedness, one of the things about being connected is you got potential potential for collective intelligence. So if you look at data, as I said, networks, what if there was a way to kind of hone that network to get to the truth fast? Esther, something we've been working on here, and I think that's something that, you know changes media. It changes the game. But collective intelligent, the role of the community now becomes a stakeholder and potentially laying out. So his problems and you're part of the Mayfield community was co created this video with roll community, super important people. The rule of the of the person your thoughts on >> so I community is a word that is has takes on a lot of meetings, and the problem is when you mean it one way and use it the other way, the same as data driven. So I think there's at one level which is community and conductivity that has to do with collecting input from lots of sources. And when you talk about investigative journalism or they're in environmental situations or all sorts of areas where the ability to collect information from lots of sources that air interested and analyze that information that is one level of community and connectivity and networking because of people you know which is great, there's another type. When people talk about community, they mean a sense of community in terms of what humans need and what that connectivity is. And most online networks don't give you that level. The online needs to be augmented by, Ah, inter personal understanding. And one of the problems. I think with today's technology is we're fitting humans into bits that technology Khun Support, as opposed to recognizing what are our human needs that we want to hold on to and saying There are some things that are not going to fit into somebody's data set. So in that first type of community than absolutely, I think there's lots of benefits of the cloud and wisdom of the crowd. But if you're talking about humans connecting in people. You don't have the same type of, uh, that that really community online tools can help. But we should never confuse what happens in our online world >> with your final question for, you know, we got We're pushing the time here. Thank you for spending time. First of all, it's great conversation. You've seen the movie with venture capital from the beginning. You know, all the original players seeing what is now just where's that come from? Where are we? What's the state of VC? Then? He hope to the future, they all adding value. How do you see that evolving and where are we with? >> You know, I would. I think venture capital has gone through a lot of different phases. And like so many things, especially those of us who want computers, we liketo lump them all together. They're not altogether. There are some small, Yes, like they field. And the I do think, though, that something shifted in the lead up to the dot com. Ah, and later the burst. And what shifted is venture capitalists. Before that time were company builders. They were the financiers, but they saw themselves with the entrepreneur building companies because of the expansion leading up to two thousand, and the funds grew and the people coming into the field were, they became more bankers and they took more financial supposed to balancing financing and entrepreneurship. It felt like it moved. Maurin toe. This is a private equity play, Um, and I think the dynamic with entrepreneurs and the methodology overall shifted, and I don't know that that's changed Now again, not across the board. I think there are some, uh, those firms that have identified our partners within firms who still very much want Teo filled companies and partner with entrepreneurs. But I think the dynamic shifted, and if you view them as that's what they are, is private equity investors. And don't expect something else. If people need money, that's a good pick. Ones that are the best partner >> is your partner. If you want a banker, go here. If you want Builder, go their key distinction. Judy. Thanks for sharing that insight. We're Judy Estrin. Sea of Jail as author of Closing Innovation. Gabbas Wellman's well known entrepreneur advisor board member formally CTO of Cisco. And again, Great gas. Thanks for coming on I'm John for Herewith. Cube conversation. Part ofmy Mayfield. People first with the Cube. Thanks for watching.

Zay California in the heart of Silicon Valley. It's the cube covering Hadoop summit 2016 brought to you by Hortonworks. Here's your host, John furrier. >>Okay, we'll come back here and we are here live in Silicon Valley for the cube. This is our flagship program. We go out to the events and extract the cylinders. Of course. We're here at the big data event. Hadoop summit 2016 have a special guest celebrity now, author of the bestselling book magical at Virginia Heffernan magic and loss rising on the bestseller lists. Welcome to the cube. Thanks in our show, you are my internet friend and now you're my real life friend. You're my favorite Facebook friend that I just now met for the first time. Great to meet you. We had never met and now we, but we know each other of course intimately through the interwebs. So I've been following your writing your time. Send you do some stuff on medium and then you, you kind of advertise. You're doing this book. I saw you do the Google glasses experiment in. >>It was Brooklyn and it might, it was so into Google glass and I will admit it, I fought for everything. I fell for VR and all its incarnations and um, and the Google last year, it was like that thing that was supposed to put the internet all voice activated, just put the internet always in front of your face. So I started to wear it around in Brooklyn, my prototype. I thought everyone would stop me and say how cool it was. In fact they didn't think it was pull it off new Yorkers. That's how you would, how they really feel. Got a problem with that. Um, your book magic and loss is fantastic and I think it really is good because uh, Dan Lyons wrote, disrupted, loved, which was fantastic. Dan lies big fan of him and his work, but it really, it wasn't a parody of civil rights for Silicon Valley. >>The show that's kinda taken that culture and made it mainstream. I had people call me up and say, Hey, you live in Callow Alto. My God, do you live near the house? Something like it's on Newell, which is one of my cross streets. But the point is tech culture now is kind of in a native, my youngest is 13 and you know, we're in an iPad generation for the youth and we're from the generation where there was no cell phones. And Mike, I remember when pages were the big innovation and internet. But I think, I think when I'm telling you, I think, I know I'm talking to a fellow traveler when I say that there was digital culture before the advent of the worldwide web in the early nineties you know, I, I'm sure you did too. Got electronic games like crazy. I would get any Merlin or Simon or whatever that they, they introduced. >>And then I also dialed into a mainframe in the late seventies and the early eighties to play the computer as we call it. We didn't even call it the internet. And the thing about the culture too was email was very, you know, monochrome screens, but again, clunky but still connected. Right? So we were that generation of, you know, putting that first training wheels on and now exposed to you. So in the book, your premise is, um, there's magical things happening in the internet and art countering the whole trolling. Uh, yeah, the Internet's bad. And we know recently someone asked me, how can the internet be art when Twitter is so angry? What do you think art is? You know, this is an art. Art is emotional. Artists know powerful >>emotions represented in tranquility and this is, you know, what you see on the internet all the time. Of course the aid of course are human. It needs a place to live and call it Twitter. For now it used to be YouTube comments. So, but we are always taking the measure of something we've lost. Um, I get the word loss from lossy compression, you know, the engineering term that, how does, how MP3 takes that big broad music signal and flattens it out. And something about listening to music on MP3, at least for me, made me feel a sense that I was grieving for something. It was missing something from my analog life. On the other hand, more than counterbalanced by the magic that I think we all experienced on the internet. We wouldn't have a friendship if it weren't for social media and all kinds of other things. And strange serendipity happens not to mention artistic expression in the form of photography, film, design of poetry and music, which are the five chapters of the book. >>So the book is fantastic. The convergence and connection of people, concepts, life with the internet digitally is interesting, right? So there's some laws with the MP3. Great example, but have you found post book new examples? I'm sure the internet culture, geese like Mia, like wow, this is so awesome. There's a cultural aspect of it is the digital experience and we see it on dating sites. Obviously you see, you know Snapchat, you know, dating sites like Tinder and other hookups apps and the real estate, everything being Uberized. What's the new things that you've, that's coming out and you must have some >>well this may be controversial, but one thing I see happening is anti digital culture. Partly as an epi phenomenon of side effect of digitization. We have a whole world of people who really want to immerse themselves in things like live music maker culture, things made by hand, vinyl records, vinyl records, which are selling more than ever in the days of the rolling stones. Gimme shelter less they sold less than than they do now. The rolling stones makes $1 billion touring a year. Would we ever have thought that in the, in the, you know, at the Genesis of the iPod when it seemed like, you know, recorded music represented music in that MP3 thing that floated through our, our phones was all we needed. No, we want to look in the faces of the rolling stones, get as close as we can to the way the music is actually made and you know, almost defiantly, and this is how the culture works. This is how youth culture works. Um, reject, create experiences that cannot be digitized. >>This is really more of a counter culture movement on the overt saturation of digital. >>Yes. Yes. You see the first people to scale down from, you know, high powered iPhones, um, when we're youth going to flip phones. You know, it's like the greatest like greatest punk, punk, punk tech. Exactly. It's like, yeah, I'm going to use these instruments, but like if I break a string, who cares on a PDs? The simplest one, right? >>My mom made me use my iPhone. Are we going to, how are we going to have that? it'd >>be like, Oh, look at you with your basic iPhone over there. And I've got my just like hack down, downscale, whatever. And you know what, I don't spend the weekends, don't pick up my phone on the weekends. But you know, there are interesting markets there. And interesting. I mean, for instance, the, you know, the live phenomenon, I know that, you know, there's this new company by one of the founders of Netflix movie pass, which um, for a $30 subscription you've seen movies in the theater as much as you want and the theaters are beautiful. And what instead of Netflix and chill, you know, the, the, the contemporary, you know, standard date, it's dinner and movie. You're out again. You're eating food, which can't be digitized with in-company, which can't be digitized. And then sitting in a theater, you know, a public experience, which is, um, a pretty extraordinary way that the culture and business pushes back on digital. >>Remember I was a comma on my undergraduate days in computer science in the 80s. And before when it was nerdy and eh, and there was a sociology class at Hubba computers and social change. And the big thing was we're going to lose social interactions because of email. And if you think about what you're talking about here is that the face to face presence, commitment of being with somebody right now is a scarce resource. You have an abundance of connections. >>I mean, take the fact what has happened is digital culture has jacked up the value of undigital culture. So for instance, you know, I've, I've met on Facebook, we talk on Facebook messenger, we notice that we're, you know, like kindred spirits in a certain way and we like each other's posts and so forth. Then we have an, a more extensive talk in messenger when we meet in person for the first time. Both of us are East coast people, but we hugged tele because it's like, Oh wow, like you in the flesh. You know it's something exciting. >>Connection virtually. That's right. There's a synchronous connection presence, but we're not really, we haven't met face to face. >>Yeah, there's this great as a great little experiment going on, set group of kids and Silicon Valley have decided they're too addicted to their phones and Facebook. Now I am not recommending for your viewers and listeners that anybody do what these kids sounds good, are ready. Go. Hey, all right, so what they do is take an LSD breakfast. Now I don't take drugs. I think you can do this without the LSD, but they put a little bit of a hallucinogen under their skin in the morning and what they find is they lost interest in the boring interface in their phones because people on the bus suddenly looked so fascinating to them. The human face is an ratable interface. It can't be reproduced anywhere, Steve. You know, Johnny ive can't make it. They can't make it at Google. And that I think is something we will see young markets doing, which is this renewed appreciation for nature and analog for humans and for analog culture. >>That's right. The Navy is going to sextants and compasses. You may have seen training, they're training sailors on those devices because of the fear that GPS might be hacked. So you know, the young kids probably don't even know what a cup is is, well, I bought myself a compass recently because I suddenly was like, you know, we talk a lot about digital technology, but what the heck, this thing you can point toward the poles, right in my hands. You know, I was suddenly like, we are this floating ball with these poles with different magnetic charges. And I think it's time. I appreciate it. >>Okay, so I've got to ask the, um, the, the feedback that you've gotten from the book, um, again, we hear that every Geneva magic and loss, great, great book. Go by. It's fantastic and open your mind up. It's a, it's a thought provoking, but really specific good use cases. I got a think that, you know, when you talk at Google and when you talk to some of the groups that you're talking to, certainly book clubs and other online that there must be like, Oh my God, you hit the cultural nerve. What have you heard from some of these, um, folks from my age 50 down to the 20 something year olds? Have you had any aha moments where you said, Oh my God, I hit a nerve here. >>Did not want to, I mean, I didn't want to write one of those books. That's like the one thing you need to know to get your startup to succeed or whatever. You know, I was at the airport and every single one of them is like, pop the only thing you need to do to save this or whatever. And they, they do take a very short view. Now if you're thinking about, you know, whether if you're thinking about your quarterly return or your, you know, what you're going to do this quarter and when you're going to be profitable or user acquisition, those books are good manuals. But if you're going to buy a hardcover book and you're going to really invest in reading every page, not just the bolded part, not just the put, you know, the two points that you have to know. I really wanted readers and at what I had found on the internet, people like you, we have an interest in a long view. You know what, I need a really long view >>in a prose that's not for listicle or you know, shorts. It's like it's just a thought provoker but somebody can go, Hey, you know, at the beach on the weekend say, Hey wow, this is really cool. What F you know, we went analog for awhile or what if, what's best for my kids to let my kids play multiplayer games more Zika simulate life. That was my, so these are the kinds of questions that the digital parents are asked. >>Yeah. So you know, like let's take the parents question, which is, is, you know, a, surprisingly to me it's a surprisingly pressing question. I am a parent, but my kids' digital habits are not, you know, of obsessive interest to me. Sometimes I think the worry about our kids is a proxy for how we worry about ourselves. You know, it's funny because they're the, you know, the model of the parent saying my kid has attention deficit order, zero order. My kid has attention deficit disorder. The kids over here, the parents here, you know, who has the attention deficit disorder. But in any case I have realized that parents are talking about uh, computers on the internet as though something kids have to have a very ambivalent relationship with and a very wary relationship with. So limit the time, and it sounds a little bit like the abstinence movement around sexuality that like, you know, you only dip in, it's very, you know, they're only date, right, right, right. >>Instead of joining sides with their kids and helping to create a durable, powerful, interesting online avatar, which is what kids want to do. And it's also what we want to do. So like in your Facebook profile, there are all kinds of strategic groups you can make as a creator of that profile. We know it as adults. Like, do you, some people put up pictures of their kids, some people don't vacation pictures. Some people promote the heck out of themselves. Some people don't do so much of that. Um, do you put up a lot of photographs? Do whatever. Those are the decisions we started to make when went on Facebook at kitchen making the two small armor to have on their gaming profile. That's kind of how they want to play, you know, play for you, going to wear feathers. These are important things. Um, but the uh, you know, small questions like talking to your kids and I don't mean a touchy feely conversation, but literally during the write in all lower case commit, you know, Brighton, all lower case, you're cute and you're this and that means a certain thing and you should get it and you're going to write in all caps and you're going to talk about white nationalist ideology. >>Well that also has a set of consequences. What have you learned in terms of the virtual space? Actually augmented reality, virtual reality, these promise to be virtual spaces. What, what is one of them? They always hope to replicate the real world. The mean, yes. Will there be any parallels of the kind of commitment in the moment? Gives you one thing. I say kids that, you know, the subtitle of the book is the internet as art, magic and loss. The internet is art and the kind of art, the internet is, is what I think of as real estate art. It purports to be reality. You know, every technology pick a photography film says or think of even the introduction of a third dimension in painting, you know, in Renaissance painting perspective for ports to represent reality better than it's been represented before. And if you're right in sync with the technology, you're typically fooled by it. >>I mean, this is a seductive representation of reality. You know, people watching us now believe they're seeing us flush of let us talk. You know, they don't think they're seeing pixels that are designed in certain ways and certainly it's your ways. So trying to sort out the incredibly interesting immersive, artful experience of being online that has some dangers and has some emotions to do it from real life is a really important thing. And you know, for us to learn first and then a model for our kids. So I had a horrible day on Twitter one day, eight 2012 213 worst day ever on Twitter. It was a great day for me. I spent the day at the beach, my Twitter avatar took sniper fire for me all day. People called her an idiot separated amount. I separated them out. And anyone who like likes roleplay and games knows that like I'm not a high priestess in Dentons and dragons. >>You know, I'm a much smaller person than that. And in, in, you know, in the case of this Twitter battle, I'm a less embattled person than the one that takes your armor from me on Twitter. That's my art. Your armor. So let's talk about poetry. Twitter, you mentioned poetry, Twitter, 140 characters. I did 40 characters is a lot. If like a lot of internet users your to have pictographic language like Chinese. So 140 characters is a novel by, well not a novel, but it's a short story for, you know, a writer of short form, short form Chinese aphorisms like Confucius. So one of the things I wanted to say is there's nothing about it being short that makes it low culture. You know, there's, I mean it takes a second to take, to take an a sculpture or to take an a painting and yet like the amount of craft that went into that might be much more good tweeting and you're excellent at it, um, is not easy. You know, I know that times I've been like, I tagged the wrong person and then I have to delete it. Like, because the name didn't come up or you know, I get the hashtags wrong and then I'm like, Oh, it would have been better this other way or I don't have a smart enough interject >>it's like playing sports. Twitter's like, you know, firing under the tennis ball baseline rallies with people. I mean, it's like, it's like there's a cultural thing. And this is the thing that I love about your book is you really bring in the metaphors around art and the cultural aspect. Have you had any, have you found that there's one art period that we represent right now? That it could be a comparison? >>I mean, you know, it's always tempting to care everything to the Renaissance. But you know, obviously in the Italian Renaissance there was so much technological innovation and so much, um, and so much, uh, so much artistic innovation. But, um, you know, the other thing are the Dawn of it's might be bigger than that, which it sounds grounds grandiose, but we're talking about something that nearly 6 billion people use and have access to. So we're talking about something bigger than we've ever seen is the Donovan civilization. So like, we pay a lot of attention to the Aqua docks and Rome and, and you know, later pay to touch it to the frescoes. I attend in this book to the frescoes, to the sculpture, to the music, to the art. So instead of talking about frescoes as an art historian, might I talk about Instagram? Yeah. >>And you, and this thing's all weave together cause we can back to the global fabric. If you look at the civilization as you know you're not to use the world is flat kind of metaphor. But that book kind of brings out that notion of okay if you just say a one global fabric, yes you have poetry, you have photography of soiling with a Johnny Susana ad in London. He says, you know, cricket is a sport in England, a bug and a delicacy depending on where in the world you are. >>Love that is that, I wonder if that's the HSBC had time to actually a beautiful HSBC job has done a beautiful campaign. I should find out who did it about perspective. And that is also a wonderful way to think about the internet because you know, I know a lot of people who don't like Twitter, who don't like YouTube comments. I do like them because I am perpetually surprised at what people bring to their interpretation. Insights in the comments can be revealing. You know, you know, you don't wanna get your feelings hurt. Sometimes you don't want that much exposure to the micro flora and fauna of ideas that could be frightening. But you know, when you're up for it, it's a really nice test of your immune system, you know. All right. So what's next for you? Virginia Heffernan magic and last great book. I think I will continue to write the tech criticism, which is just this growing field. I at Sarah Watson had a wonderful piece today in the Columbia journalism review about how we really need to bring all our faculties to treat, treating to tech criticism meant and treating tech with, um, with Karen, with proper off. Um, and the next book is on anti digital culture. Um, I will continue writing journalism and you'll see little previews of that book in the next work. >>Super inspirational. And I think the culture needs this kind of rallying cry because you know, there is art and science and all this beautiful beauty in the internet and it's not about mutually exclusive analog world. You can look and take, can come offline. So it's interesting case study of this, this revolution I think, and I think the counter culture, if you'd go back and Southern John Markoff about this, when he wrote his first book, the Dormouse wander about the counter culture in Silicon Valley is what's your grade book? And counter cultures usually create a another wave of innovation. So the question that comes out of this one is there could, this could be a seminal moment in history. I mean, I think it absolutely is. You know, in some ways, every moment is a great moment if you know what to make of it. But I am just tired of people telling us that we're ruining our brands and that this is the end of innovation and that we're at some low period. >>I think we will look back and think of this as an incredibly fertile time for our imaginations. If we don't lose hope, if we keep our creativity fired and if we commit to this incredible period we're in Virginia. Thanks for spending the time here in the queue. Really appreciate where you're live at. Silicon Valley is the cube with author Virginia Heffernan magic. And loss. Great book. Get it. If you don't have it, hard copies still available, get it. We'll be right back with more live coverage here. This is the cube. I'm John furry right back with more if the short break.