>>from around the globe. It's the Cube presenting Cuban Cloud brought to you by Silicon Angle. Welcome back to the live segment of the Cuban cloud. I'm Dave, along with my co host, John Ferrier. John Rose is here. He's the global C T o Dell Technologies. John, great to see you as always, Really appreciate >>it. Absolutely good to know. >>Hey, so we're gonna talk edge, you know, the the edge, it's it's estimated. It's a multi multi trillion dollar opportunity, but it's a highly fragmented, very complex. I mean, it comprises from autonomous vehicles and windmills, even retail stores outer space. And it's so it brings in a lot of really gnarly technical issues that we want to pick your brain on. Let me start with just what to you is edge. How do you think about >>it? Yeah, I think I mean, I've been saying for a while that edges the when you reconstitute Ike back out in the real world. You know, for 10 years we've been sucking it out of the real world, taking it out of factories, you know, nobody has an email server under their desk anymore. On that was because we could put it in data centers and cloud public clouds, and you know that that's been a a good journey. And then we realized, Wait a minute, all the data actually was being created out in the real world. And a lot of the actions that have to come from that data have to happen in real time in the real world. And so we realized we actually had toe reconstitute a nightie capacity out near where the data is created, consumed and utilized. And, you know, that turns out to be smart cities, smart factories. You know, uh, we're dealing with military apparatus. What you're saying, how do you put, you know, edges in tow, warfighting theaters or first responder environments? It's really anywhere that data exists that needs to be processed and understood and acted on. That isn't in a data center. So it's kind of one of these things. Defining edge is easier to find. What it isn't. It's anywhere that you're going to have. I t capacity that isn't aggregated into a public or private cloud data center. That seems to be the answer. So >>follow. Follow that. Follow the data. And so you've got these big issue, of course, is late and see people saying, Well, some applications or some use cases like autonomous vehicles. You have to make the decision locally. Others you can you can send back. And you, Kamal, is there some kind of magic algorithm the technical people used to figure out? You know what, the right approaches? Yeah, >>the good news is math still works and way spent a lot of time thinking about why you build on edge. You know, not all things belong at the edge. Let's just get that out of the way. And so we started thinking about what does belong at the edge, and it turns out there's four things you need. You know, if you have a real time responsiveness in the full closed loop of processing data, you might want to put it in an edge. But then you have to define real time, and real time varies. You know, real time might be one millisecond. It might be 30 milliseconds. It might be 50 milliseconds. It turns out that it's 50 milliseconds. You probably could do that in a co located data center pretty far away from those devices. One millisecond you better be doing it on the device itself. And so so the Leighton see around real time processing matters. And, you know, the other reasons interesting enough to do edge actually don't have to do with real time crossing they have to do with. There's so much data being created at the edge that if you just blow it all the way across the Internet, you'll overwhelm the Internets. We have need toe pre process and post process data and control the flow across the world. The third one is the I T. O T boundary that we all know. That was the I O t. Thing that we were dealing with for a long time. And the fourth, which is the fascinating one, is it's actually a place where you might want to inject your security boundaries, because security tends to be a huge problem and connected things because they're kind of dumb and kind of simple and kind of exposed. And if you protect them on the other end of the Internet, the surface area of protecting is enormous, so there's a big shift basically move security functions to the average. I think Gardner made up a term for called Sassy. You know, it's a pretty enabled edge, but these are the four big ones. We've actually tested that for probably about a year with customers. And it turns out that, you know, seems to hold If it's one of those four things you might want to think about an edge of it isn't it probably doesn't belong in >>it. John. I want to get your thoughts on that point. The security things huge. We talked about that last time at Del Tech World when we did an interview with the Cube. But now look at what's happened. Over the past few months, we've been having a lot of investigative reporting here at Silicon angle on the notion of misinformation, not just fake news. Everyone talks about that with the election, but misinformation as a vulnerability because you have now edge devices that need to be secured. But I can send misinformation to devices. So, you know, faking news could be fake data say, Hey, Tesla, drive off the road or, you know, do this on the other thing. So you gotta have the vulnerabilities looked at and it could be everything. Data is one of them. Leighton. See secure. Is there a chip on the device? Could you share your vision on how you see that being handled? Cause it's a huge >>problem. Yeah, this is this is a big deal because, you know, what you're describing is the fact that if data is everything, the flow of data ultimately turns into the flow of information that knowledge and wisdom and action. And if you pollute the data, if you could compromise it the most rudimentary levels by I don't know, putting bad data into a sensor or tricking the sensor which lots of people can dio or simulating a sensor, you can actually distort things like a I algorithms. You can introduce bias into them and then that's a That's a real problem. The solution to it isn't making the sensors smarter. There's this weird Catch 22 when you sense arise the world, you know you have ah, you know, finite amount of power and budget and the making sensors fatter and more complex is actually the wrong direction. So edges have materialized from that security dimension is an interesting augment to those connected things. And so imagine a world where you know your sensor is creating data and maybe have hundreds or thousands of sensors that air flowing into an edge compute layer and the edge compute layer isn't just aggregating it. It's putting context on it. It's metadata that it's adding to the system saying, Hey, that particular stream of telemetry came from this device, and I'm watching that device and Aiken score it and understand whether it's been compromised or whether it's trustworthy or whether it's a risky device and is that all flows into the metadata world the the overall understanding of not just the data itself, but where did it come from? Is it likely to be trustworthy? Should you score it higher or lower in your neural net to basically manipulate your algorithm? These kind of things were really sophisticated and powerful tools to protect against this kind of injection of false information at the sensor, but you could never do that at a sensor. You have to do it in a place that has more compute capacity and is more able to kind of enriched the data and enhance it. So that's why we think edges are important in that fourth characteristic of they aren't the security system of the sensor itself. But they're the way to make sure that there's integrity in the sense arised world before it reaches the Internet before it reaches the cloud data centers. >>So access to that metadata is access to the metadata is critical, and it's gonna be it's gonna be near real time, if not real time, right? >>Yeah, absolutely. And, you know, the important thing is, Well, I'll tell you this. You know, if you haven't figured this out by looking at cybersecurity issues, you know, compromising from the authoritative metadata is a really good compromise. If you could get that, you can manipulate things that a scale you've never imagined. Well, in this case, if the metadata is actually authoritatively controlled by the edge note the edge note is processing is determining whether or not this is trustworthy or not. Those edge nodes are not $5 parts, their servers, their higher end systems. And you can inject a lot more sophisticated security technology and you can have hardware root of trust. You can have, you know, mawr advanced. PK I in it, you can have a I engines watching the behavior of it, and again, you'd never do that in a sensor. But if you do it at the first step into the overall data pipeline, which is really where the edges materializing, you can do much more sophisticated things to the data. But you can also protect that thing at a level that you'd never be able to do to protect a smart lightbulb. A thermostat in your house? >>Uh, yes. So give us the playbook on how you see the evolution of the this mark. I'll see these air key foundational things, a distributed network and it's a you know I o t trends into industrial i o t vice versa. As a software becomes critical, what is the programming model to build the modern applications is something that I know. You guys talk to Michael Dell about this in the Cuban, everyone, your companies as well as everyone else. Its software define everything these days, right? So what is the software framework? How did people code on this? What's the application aware viewpoint on this? >>Yeah, this is, uh, that's unfortunately it's a very complex area that's got a lot of dimensions to it. Let me let me walk you through a couple of them in terms of what is the software framework for for For the edge. The first is that we have to separate edge platforms from the actual edge workload today too many of the edge dialogues or this amorphous blob of code running on an appliance. We call that an edge, and the reality is that thing is actually doing two things. It's, ah, platform of compute out in the real world and it's some kind of extension of the cloud data pipeline of the cloud Operating model. Instance, he added, A software probably is containerized code sitting on that edge platform. Our first principle about the software world is we have to separate those two things. You do not build your cloud your edge platform co mingled with the thing that runs on it. That's like building your app into the OS. That's just dumb user space. Colonel, you keep those two things separate. We have Thio start to enforce that discipline in the software model at the edges. The first principle, the second is we have to recognize that the edges are are probably best implemented in ways that don't require a lot of human intervention. You know, humans air bad when it comes to really complex distributed systems. And so what we're finding is that most of the code being pushed into production benefits from using things like kubernetes or container orchestration or even functional frameworks like, you know, the server list fast type models because those low code architectures generally our interface with via AP, eyes through CCD pipelines without a lot of human touch on it. And it turns out that, you know, those actually worked reasonably well because the edges, when you look at them in production, the code actually doesn't change very often, they kind of do singular things relatively well over a period of time. And if you can make that a fully automated function by basically taking all of the human intervention away from it, and if you can program it through low code interfaces or through automated interfaces, you take a lot of the risk out of the human intervention piece of this type environment. We all know that you know most of the errors and conditions that break things are not because the technology fails it because it's because of human being touches it. So in the software paradigm, we're big fans of more modern software paradigms that have a lot less touch from human beings and a lot more automation being applied to the edge. The last thing I'll leave you with, though, is we do have a problem with some of the edge software architectures today because what happened early in the i o t world is people invented kind of new edge software platforms. And we were involved in these, you know, edge X foundry, mobile edge acts, a crane. Oh, and those were very important because they gave you a set of functions and capabilities of the edge that you kind of needed in the early days. Our long term vision, though for edge software, is that it really needs to be the same code base that we're using in data centers and public clouds. It needs to be the same cloud stack the same orchestration level, the same automation level, because what you're really doing at the edge is not something that spoke. You're taking a piece of your data pipeline and you're pushing it to the edge and the other pieces are living in private data centers and public clouds, and you like they all operate under the same framework. So we're big believers in, like pushing kubernetes orchestration all the way to the edge, pushing the same fast layer all the way to the edge. And don't create a bespoke world of the edge making an extension of the multi cloud software framework >>even though the underlying the underlying hardware might change the microprocessor, GPU might change GP or whatever it is. Uh, >>by the way, that that's a really good reason to use these modern framework because the energies compute where it's not always next 86 underneath it, programming down at the OS level and traditional languages has an awful lot of hardware dependencies. We need to separate that because we're gonna have a lot of arm. We're gonna have a lot of accelerators a lot of deep. Use a lot of other stuff out there. And so the software has to be modern and able to support header genius computer, which a lot of these new frameworks do quite well, John. >>Thanks. Thanks so much for for coming on, Really? Spending some time with us and you always a great guest to really appreciate it. >>Going to be a great stuff >>of a technical edge. Ongoing room. Dave, this is gonna be a great topic. It's a clubhouse room for us. Well, technical edge section every time. Really. Thanks >>again, Jon. Jon Rose. Okay, so now we're gonna We're gonna move to the second part of our of our technical edge discussion. Chris Wolf is here. He leads the advanced architecture group at VM Ware. And that really means So Chris's looks >>at I >>think it's three years out is kind of his time. Arise. And so, you know, advanced architecture, Er and yeah. So really excited to have you here. Chris, can you hear us? >>Okay. Uh, >>can Great. Right. Great to see you again. >>Great >>to see you. Thanks for coming on. Really appreciate it. >>So >>we're talking about the edge you're talking about the things that you see way set it up is a multi trillion dollar opportunity. It's It's defined all over the place. Uh, Joey joke. It's Could be a windmill. You know, it could be a retail store. It could be something in outer space. Its's It's it's, you know, whatever is defined A factory, a military installation, etcetera. How do you look at the edge. And And how do you think about the technical evolution? >>Yeah, I think it is. It was interesting listening to John, and I would say we're very well aligned there. You know, we also would see the edge is really the place where data is created, processed and are consumed. And I think what's interesting here is that you have a number off challenges in that edges are different. So, like John was talking about kubernetes. And there's there's multiple different kubernetes open source projects that are trying to address thes different edge use cases, whether it's K three s or Cubbage or open your it or super edge. And I mean the list goes on and on, and the reason that you see this conflict of projects is multiple reasons. You have a platform that's not really designed to supported computing, which kubernetes is designed for data center infrastructure. Uh, first on then you have these different environments where you have some edge sites that have connectivity to the cloud, and you have some websites that just simply don't write whether it's an oil rig or a cruise ship. You have all these different use cases, so What we're seeing is you can't just say this is our edge platform and, you know, go consume it because it won't work. You actually have to have multiple flavors of your edge platform and decide. You know what? You should time first. From a market perspective, I >>was gonna ask you great to have you on. We've had many chest on the Cube during when we actually would go to events and be on the credit. But we appreciate you coming into our virtual editorial event will be doing more of these things is our software will be put in the work to do kind of a clubhouse model. We get these talks going and make them really valuable. But this one is important because one of the things that's come up all day and we kind of introduced earlier to come back every time is the standardization openness of how open source is going to extend out this this interoperability kind of vibe. And then the second theme is and we were kind of like the U S side stack come throwback to the old days. Uh, talk about Cooper days is that next layer, but then also what is going to be the programming model for modern applications? Okay, with the edge being obviously a key part of it. What's your take on that vision? Because that's a complex area certain a lot of a lot of software to be written, still to come, some stuff that need to be written today as well. So what's your view on How do you programs on the edge? >>Yeah, it's a It's a great question, John and I would say, with Cove it We have seen some examples of organizations that have been successful when they had already built an edge for the expectation of change. So when you have a truly software to find edge, you can make some of these rapid pivots quite quickly, you know. Example was Vanderbilt University had to put 1000 hospital beds in a parking garage, and they needed dynamic network and security to be able to accommodate that. You know, we had a lab testing company that had to roll out 400 testing sites in a matter of weeks. So when you can start tohave first and foremost, think about the edge as being our edge. Agility is being defined as you know, what is the speed of software? How quickly can I push updates? How quickly can I transform my application posture or my security posture in lieu of these types of events is super important. Now, if then if we walk that back, you know, to your point on open source, you know, we see open source is really, uh you know, the key enabler for driving edge innovation and driving in I S V ecosystem around that edge Innovation. You know, we mentioned kubernetes, but there's other really important projects that we're already seeing strong traction in the edge. You know, projects such as edge X foundry is seeing significant growth in China. That is, the core ejects foundry was about giving you ah, pass for some of your I o T aps and services. Another one that's quite interesting is the open source faith project in the Linux Foundation. And fate is really addressing a melody edge through a Federated M L model, which we think is the going to be the long term dominant model for localized machine learning training as we continue to see massive scale out to these edge sites, >>right? So I wonder if you could You could pick up on that. I mean, in in thinking about ai influencing at the edge. Um, how do you see that? That evolving? Uh, maybe You know what, Z? Maybe you could We could double click on the architecture that you guys see. Uh, progressing. >>Yeah, Yeah. Right now we're doing some really good work. A zai mentioned with the Fate project. We're one of the key contributors to the project. Today. We see that you need to expand the breath of contributors to these types of projects. For starters, uh, some of these, what we've seen is sometimes the early momentum starts in China because there is a lot of innovation associated with the edge there, and now it starts to be pulled a bit further West. So when you look at Federated Learning, we do believe that the emergence of five g I's not doesn't really help you to centralized data. It really creates the more opportunity to create, put more data and more places. So that's, you know, that's the first challenge that you have. But then when you look at Federated learning in general, I'd say there's two challenges that we still have to overcome organizations that have very sophisticated data. Science practices are really well versed here, and I'd say they're at the forefront of some of these innovations. But that's 1% of enterprises today. We have to start looking at about solutions for the 99% of enterprises. And I'd say even VM Ware partners such as Microsoft Azure Cognitive Services as an example. They've been addressing ML for the 99%. I say That's a That's a positive development. When you look in the open source community, it's one thing to build a platform, right? Look, we love to talk about platforms. That's the easy part. But it's the APS that run on that platform in the services that run on that platform that drive adoption. So the work that we're incubating in the VM, or CTO office is not just about building platforms, but it's about building the applications that are needed by say that 99% of enterprises to drive that adoption. >>So if you if you carry that through that, I infer from that Chris that the developers are ultimately gonna kind of win the edge or define the edge Um, How do you see that From their >>perspective? Yeah, >>I think its way. I like to look at this. I like to call a pragmatic Dev ops where the winning formula is actually giving the developer the core services that they need using the native tools and the native AP eyes that they prefer and that is predominantly open source. It would some cloud services as they start to come to the edge as well. But then, beyond that, there's no reason that I t operations can't have the tools that they prefer to use. A swell. So we see this coming together of two worlds where I t operations has to think even for differently about edge computing, where it's not enough to assume that I t has full control of all of these different devices and sensors and things that exists at the edge. It doesn't happen. Often times it's the lines of business that air directly. Deploying these types of infrastructure solutions or application services is a better phrase and connecting them to the networks at the edge. So what does this mean From a nightie operations perspective? We need tohave, dynamic discovery capabilities and more policy and automation that can allow the developers to have the velocity they want but still have that consistency of security, agility, networking and all of the other hard stuff that somebody has to solve. And you can have the best of both worlds here. >>So if Amazon turned the data center into an A P I and then the traditional, you know, vendors sort of caught up or catching up and trying to do in the same premise is the edge one big happy I Is it coming from the cloud? Is it coming from the on Prem World? How do you see that evolving? >>Yes, that's the question and races on. Yeah, but it doesn't. It doesn't have to be exclusive in one way or another. The VM Ware perspective is that, you know, we can have a consistent platform for open source, a consistent platform for cloud services. And I think the key here is this. If you look at the partnerships we've been driving, you know, we've on boarded Amazon rds onto our platform. We announced the tech preview of Azure Arc sequel database as a service on our platform as well. In addition, toe everything we're doing with open source. So the way that we're looking at this is you don't wanna make a bet on an edge appliance with one cloud provider. Because what happens if you have a business partner that says I am a line to Google or on the line to AWS? So I want to use this open source. Our philosophy is to virtualized the edge so that software can dictate, you know, organizations velocity at the end of the day. >>Yeah. So, Chris, you come on, you're you're an analyst at Gartner. You know us. Everything is a zero sum game, but it's but But life is not like that, right? I mean, there's so much of an incremental opportunity, especially at the edge. I mean, the numbers are mind boggling when when you look at it, >>I I agree wholeheartedly. And I think you're seeing a maturity in the vendor landscape to where we know we can't solve all the problems ourselves and nobody can. So we have to partner, and we have to to your earlier point on a P. I s. We have to build external interfaces in tow, our platforms to make it very easy for customers have choice around ice vendors, partners and so on. >>So, Chris, I gotta ask you since you run the advanced technology group in charge of what's going on there, will there be a ship and focus on mawr ships at the edge with that girl singer going over to intel? Um, good to see Oh, shit, so to speak. Um, all kidding aside, but, you know, patch leaving big news around bm where I saw some of your tweets and you laid out there was a nice tribute, pat, but that's gonna be cool. That's gonna be a didn't tell. Maybe it's more more advanced stuff there. >>Yeah, I think >>for people pats staying on the VMRO board and to me it's it's really think about it. I mean, Pat was part of the team that brought us the X 86 right and to come back to Intel as the CEO. It's really the perfect book end to his career. So we're really sad to see him go. Can't blame him. Of course it's it's a It's a nice chapter for Pat, so totally understand that. And we prior to pack going to Intel, we announced major partnerships within video last year, where we've been doing a lot of work with >>arm. So >>thio us again. We see all of this is opportunity, and a lot of the advanced development projects were running right now in the CTO office is about expanding that ecosystem in terms of how vendors can participate, whether you're running an application on arm, whether it's running on X 86 or whatever, it's running on what comes next, including a variety of hardware accelerators. >>So is it really? Is that really irrelevant to you? I mean, you heard John Rose talk about that because it's all containerized is it is. It is a technologies. Is it truly irrelevant? What processor is underneath? And what underlying hardware architectures there are? >>No, it's not. You know it's funny, right? Because we always want to say these things like, Well, it's just a commodity, but it's not. You didn't then be asking the hardware vendors Thio pack up their balls and go home because there's just nothing nothing left to do, and we're seeing actually quite the opposite where there's this emergence and variety of so many hardware accelerators. So even from an innovation perspective, for us. We're looking at ways to increase the velocity by which organizations can take advantage of these different specialized hardware components, because that's that's going to continue to be a race. But the real key is to make it seamless that an application could take advantage of these benefits without having to go out and buy all of this different hardware on a per application basis. >>But if you do make bets, you can optimize for that architecture, true or not, I mean, our estimate is that the you know the number of wafer is coming out of arm based, you know, platforms is 10 x x 86. And so it appears that, you know, from a cost standpoint, that's that's got some real hard decisions to make. Or maybe maybe they're easy decisions, I don't know. But so you have to make bets, Do you not as a technologist and try to optimize for one of those architectures, even though you have to hedge those bets? >>Yeah, >>we do. It really boils down to use cases and seeing, you know, what do you need for a particular use case like, you know, you mentioned arm, you know, There's a lot of arm out at the edge and on smaller form factor devices. Not so much in the traditional enterprise data center today. So our bets and a lot of the focus there has been on those types of devices. And again, it's it's really the It's about timing, right? The customer demand versus when we need to make a particular move from an innovation >>perspective. It's my final question for you as we wrap up our day here with Great Cuban Cloud Day. What is the most important stories in in the cloud tech world, edge and or cloud? And you think people should be paying attention to that will matter most of them over the next few years. >>Wow, that's a huge question. How much time do we have? Not not enough. A >>architect. Architectural things. They gotta focus on a lot of people looking at this cove it saying I got to come out with a growth strategy obvious and clear, obvious things to see Cloud >>Yeah, yeah, let me let me break it down this way. I think the most important thing that people have to focus on >>is deciding How >>do they when they build architectures. What does the reliance on cloud services Native Cloud Services so far more proprietary services versus open source technologies such as kubernetes and the SV ecosystem around kubernetes. You know, one is an investment in flexibility and control, lots of management and for your intellectual property, right where Maybe I'm building this application in the cloud today. But tomorrow I have to run it out at the edge. Or I do an acquisition that I just wasn't expecting, or I just simply don't know. Sure way. Sure hope that cova doesn't come around again or something like it, right as we get past this and navigate this today. But architect ng for the expectation of change is really important and having flexibility of round your intellectual property, including flexibility to be able to deploy and run on different clouds, especially as you build up your different partnerships. That's really key. So building a discipline to say you know what >>this is >>database as a service, it's never going to define who I am is a business. It's something I have to do is an I T organization. I'm consuming that from the cloud This part of the application sacked that defines who I am is a business. My active team is building this with kubernetes. And I'm gonna maintain more flexibility around that intellectual property. The strategic discipline to operate this way among many of >>enterprise customers >>just hasn't gotten there yet. But I think that's going to be a key inflection point as we start to see. You know, these hybrid architectures continue to mature. >>Hey, Chris. Great stuff, man. Really appreciate you coming on the cube and participate in the Cuban cloud. Thank you for your perspectives. >>Great. Thank you very much. Always a pleasure >>to see you. >>Thank you, everybody for watching this ends the Cuban Cloud Day. Volonte and John Furry. All these sessions gonna be available on demand. All the write ups will hit silicon angle calm. So check that out. We'll have links to this site up there and really appreciate you know, you attending our our first virtual editorial >>event again? >>There's day Volonte for John Ferrier in the entire Cube and Cuba and Cloud Team >>Q 3 65. Thanks >>for watching. Mhm

>> From the Silicon Angle Media office in Boston, Massachusetts, It's theCUBE. (upbeat music) Now, here's your host, Stu Miniman. >> Hi. I'm Stu Miniman, and this is theCUBE's Boston area studio; our actually brand-new studio, and I'm really excited to have I believe is a first-time guest, a long-time caller, you know, a long time listener >> Yeah, yep. first time caller, good buddy of mine Dave Graham, who is the director, is a director of emerging technologies: messaging at Dell Technologies. Disclaimer, Dave and I worked together at a company some of you might have heard on the past, it was EMC Corporation, which was a local company. Dave and I both left EMC, and Dave went back, after Dell had bought EMC. So Dave, thanks so much for joining, it is your first time on theCUBE, yes? >> It is the first time on theCUBE. >> Yeah, so. >> Lets do some, Some of the first times that I actually interacted with, with this team here, you and I were bloggers and doing lots of stuff back in the industry, so it's great to be able to talk to you on-camera. >> Yeah, same here. >> All right, so Dave, I mentioned you were a returning former EMC-er, now Dell tech person, and you spent some time at Juniper, at some startups, but give our audience a little bit about your background and your passions. >> Oh, so background-wise, yep, so started my career in technology, if you will, at EMC, worked, started in inside sales of all places. Worked my way into a consulting/engineer type position within ECS, which was, obviously a pretty hard-core product inside of EMC now, or Dell Technologies now. Left, went to a startup, everybody's got to do a start up at some point in their life, right? Take the risk, make the leap, that was awesome, was actually one of those Cloud brokers that's out there, like Nasuni, company called Sertis. Had a little bit of trouble about eight months in, so it kind of fell apart. >> Yeah, the company did, not you. >> The company did! (men laughing) I was fine, you know, but the, yeah, the company had some problems, but ended up leaving there, going to Symantec of all places, so I worked on the Veritas side, kind of the enterprise side, which just recently got bought out by Avago, evidently just. >> Broadcom >> Broadcom, Broadcom, art of the grand whole Avago. >> Dave, Dave, you know we're getting up there in years and our tech, when we keep talking about something 'cause I was just reading about, right, Broadcom, which was of course Avago bought Broadcom in the second largest tech acquisition in history, but when they acquired Broadcom, they took on the name because most people know Broadcom, not as many people know Avago, even those of us with backgrounds in the chip semiconductor and all those pieces. I mean you got Brocade in there, you've got some of the software companies that they've bought over the time, so some of those go together. But yeah, Veritas and Symantec, those of us especially with some storage and networking background know those brands well. >> Absolutely, PLX's being the PCI switched as well, it's actually Broadcom, those things. So yeah, went from Symantec after a short period of time there, went to Juniper Networks, ran part of their Center of Excellence, kind of a data center overlay team, the only non-networking guy in a networking company, it felt like. Can't say that I learned a ton about the networking side, but definitely saw a huge expansion in the data center space with Juniper, which was awesome to see. And then the opportunity came to come back to Dell Technologies. Kind of a everything old becoming new again, right? Going and revisiting a whole bunch of folks that I had worked with 13, you know, 10 years ago. >> Dave, it's interesting, you know, I think about, talk about somebody like Broadcom, and Avago, and things like that. I remember reading blog posts of yours, that you'd get down to some of that nitty-level, you and I would be ones that would be the talk about the product, all right now pull the board out, let me look at all the components, let me understand, you know, the spacing, and the cooling, and all the things there, but you know here it's 2019, Dave. Don't you know software is eating the world? So, tell us a little bit about what you're working on these days, because the high-level things definitely don't bring to mind the low-level board pieces that we used to talk about many years ago. >> Exactly, yeah, it's no longer, you know, thermals and processing power as much, right? Still aspects of that, but a lot of what we're focused on now, or what I'm focused on now is within what we call the emerging technology space. Or horizon 2, horizon 3, I guess. >> Sounds like something some analyst firm came up with, Dave. (Dave laughing) >> Yeah, like Industry 4.0, 5.0 type stuff. It's all exciting stuff, but you know when you look at technologies like five, 5G, fifth generation wireless, you know both millimeter waves, sub six gigahertz, AI, you know, everything old becoming new again, right? Stuff from the fifties, and sixties that's now starting to permeate everything that we do, you're not opening your mouth and breathing unless you're talking about AI at some point, >> Yeah, and you bring up a great point. So, we've spent some time with the Dell team understanding AI, but help connect for our audience that when you talk high AI we're talking about, we're talking about data at the center of everything, and it's those applications, are you working on some of those solutions, or is it the infrastructure that's going to enable that, and what needs to be done at that level for things to work right? >> I think it's all of the above. The beauty of kind of Dell Technologies that you sit across, both infrastructure and software. You look at the efforts and the energies, stuff like VMware buying, BitFusion, right, as a mechanism trying to assuage some of that low-level hardware stuff. Start to tap into what the infrastructure guys have always been doing. When you bring that kind of capability up the stack, now you can start to develop within the software mindset, how, how you're going to access this. Infrastructure still plays a huge part of it, you got to run it on something, right? You can't really do serverless AI at this point, am I allowed to say that? (man laughing) >> Well, you could say that, I might disagree with you, because absolutely >> Eh, that's fine. there's AI that's running on it. Don't you know, Dave, I actually did my serverless 101 article that I had, I actually had Ashley Gorakhpurwalla, who is the General Manager of Dell servers, holding the t-shirt that "there is no serverless, it's just, you know, a function that you only pay the piece that you need when you need and everything there." But the point of the humor that I was having there is even the largest server manufacturer in the world knows that underneath that serverless discussion, absolutely, there is still infrastructure that plays there, just today it tends to primarily be in AWS with all of their services, but that proliferation, serverless, we're just letting the developers be developers and not have to think about that stuff, and I mean, Dave, the stuff we've had background, you know, we want to get rid of silos and make things simpler, I mean, it's the things we've been talking about for decades, it's just, for me it was interesting to look at, it is very much a developer application driven piece, top-down as opposed to so many of the virtualization and infrastructure as a service is more of a bottom-up, let me try to change this construct so that we can then provide what you need above it, it's just a slightly different way of looking at things. >> Yeah, and I think we're really trying to push for that stuff, so you know you can bundle together hardware that makes it, makes the development platform easy to do, right? But the efforts and energy of our partnerships, Dell has engaged in a lot of partnerships within the industry, NVIDIA, Intel, AMD, Graphcore, you name it, right? We're out in that space working along with those folks, but a lot of that is driven by software. It's, you write to a library, like Kudu, or, you know pyEight, you know, PyTorch, you're using these type of elements and you're moving towards that, but then it has to run on something, right? So we want to be in that both-end space, right? We want to enable that kind of flexibility capability, and obviously not prevent it, but we want to also expose that platform to as many people within the industry as possible so they can kind of start to develop on it. You're becoming a platform company, really, when it comes down to it. >> I don't want to get down the semantical arguments of AI, if you will, but what are you hearing from customers, and what's some kind of driving some of the discussions lately that's the reality of AI as opposed to some of just the buzzy hype that everybody talks about? >> Well I still think there's some ambiguity in market around AI versus automation even, so what people that come and ask us are well, "you know, I believe in this thing called artificial intelligence, and I want to do X, Y, and Z." And these particular workloads could be better handled by a simple, not to distill it down to the barest minimum, but like cron jobs, something that's, go back in the history, look at the things that matter, that you could do very very simply that don't require a large amount of library, or sort of an understanding of more advanced-type algorithms or developments that way. In the reverse, you still have that capability now, where everything that we're doing within industry, you use chat-bots. Some of the intelligence that goes into those, people are starting to recognize, this is a better way that I could serve my customers. Really, it's that business out kind of viewpoint. How do I access these customers, where they may not have the knowledge set here, but they're coming to us and saying, "it's more than just, you know, a call, an IVR system," you know, like an electronic IVR system, right? Like I come in and it's just quick response stuff. I need some context, I need to be able to do this, and transform my data into something that's useful for my customers. >> Yeah, no, this is such a great point, Dave. The thing I've asked many times, is, my entire career we've talked about intelligence and we've talked about automation, what's different about it today? And the reality is, is it used to be all right. I was scripting things, or I would have some Bash processes, or I would put these things together. The order of magnitude and scale of what we're talking about today, I couldn't do it manually if I wanted to. And that automation is really, can be really cool these days, and it's not as, to set all of those up, there is more intelligence built into it, so whether it's AI or just machine learning kind of underneath it, that spectrum that we talk about it, there's some real-use cases, a real lot of things that are happening there, and it definitely is, order of magnitudes more improved than what we were talking about say, back when we were both at EMC and the latest generation of Symmetrix was much more intelligent than the last generation, but if you look at that 10 years later, boy, it's, it is night and day, and how could we ever have used those terms before, compared to where we are today. >> Yeah it's, it's, somebody probably at some point coined the term, "exponential". Like, things become exponential as you start to look at it. Yeah, the development in the last 10 years, both in computing horsepower, and GPU/GPGPU horsepower, you know, the innovation around, you know FPGAs are back in a big way now, right? All that brainpower that used to be in these systems now, you now can benefit even more from the flexibility of the systems in order to get specific workloads done. It's not for everybody, we all know that, but it's there. >> I'm glad you brought up FPGAs because those of us that are hardware geeks, I mean, some reason I studied mechanical engineering, not realizing that software would be a software world that we live in. I did a video with Amy Lewis and she's like, "what was your software-defined moments?" I'm like, "gosh, I'm the frog sitting in the pot, and, would love to, if I can't network-diagram it, or put these things together, networking guy, it's my background! So, the software world, but it is a real renaissance in hardware these days. Everything from the FPGAs you mentioned, you look at NVIDIA and all of their partners, and the competitors there. Anything you geeking out on the hardware side? >> I, yeah, a lot of the stuff, I mean, the era of GPU showed up in a big way, all right? We have NVIDIA to thank for that whole, I mean, the kudos to them for developing a software ecosystem alongside a hardware. I think that's really what sold that and made that work. >> Well, you know, you have to be able to solve that Bitcoin mining problem, so. >> Well, you know, depending on which cryptocurrency you did, EMD kind of snuck in there with their stuff and they did some of that stuff better. But you have that kind of competing architecture stuff, which is always good, competition you want. I think now that what we're seeing is that specific workloads now benefit from different styles of compute. And so you have the companies like Graphcore, or the chip that was just launched out of China this past week that's configurable to any type of network, enteral network underneath the covers. You see that kind of evolution in capability now, where general purpose is good, but now you start to go into reconfigurable elements so, I'll, FPGAs are some of these more advanced chips. The neuromorphic hardware, which is always, given my background in psychology, is always interesting to me, so anything that is biomorphic or neuromorphic to me is pinging around up here like, "oh, you're going to emulate the brain?" And Intel's done stuff, BraincChip's done stuff, Netspace, it's amazing. I just, the workloads that are coming along the way, I think are starting to demand different types or more effectiveness within that hardware now, so you're starting to see a lot of interesting developments, IPUs, TPUs, Teslas getting into the inferencing bit now, with their own hardware, so you see a lot of effort and energy being poured in there. Again, there's not going to be one ring to rule them all, to cop Tolkien there for a moment, but there's going to be, I think you're going to start to see the disparation of workloads into those specific hardware platforms. Again, software, it's going to start to drive the applications for how you see these things going, and it's going to be the people that can service the most amount of platforms, or the most amount of capability from a single platform even, I think are the people who are going to come out ahead. And whether it'll be us or any of our August competitors, it remains to be seen, but we want to be in that space we want to be playing hard in that space as well. >> All right Dave, last thing I want to ask you about is just career. So, it's interesting, at Vmworld, I kind of look at it in like, "wow, I'm actually, I'm sitting at a panel for Opening Acts, which is done by the VMunderground people the Sunday, day before VMworld really starts, talking about jobs and there's actually three panels, you know, careers, and financial, and some of those things, >> I'm going to be there, so come on by, >> Maybe I should join startin' at 1 o'clock Monday evening, I'm actually participating in a career cafe, talking about people and everything like that, so all that stuff's online if you want to check it out, but you know, right, you said psychology is what you studied but you worked in engineering, you were a systems engineer, and now you do messaging. The hardcore techies, there's always that boundary between the techies and the marketings, but I think it's obvious to our audience when they hear you geeking out on the TPUs and all the things there that you are not just, you're quite knowledgeable when it comes about the technology, and the good technical marketers I find tend to come from that kind of background, but give us a little bit, looking back at where you've been and where you're going, and some of those dynamics. >> Yeah, I was blessed from a really young age with a father who really loved technology. We were building PCs, like back in the eighties, right, when that was a thing, you know, "I built my AMD 386 DX box" >> Have you watched the AMC show, "Halt and Catch Fire," when that was on? >> Yeah, yeah, yeah, so there was that kind of, always interesting to me, and I, with the way my mind works, I can't code to save my life, that's my brother's gift, not mine. But being able to kind of assemble things in my head was kind of always something that stuck in the back. So going through college, I worked as a lab resident as well, working in computer labs and doing that stuff. It's just been, it's been a passion, right? I had the education, was very, you know, that was my family, was very hard on the education stuff. You're going to do this. But being able to follow that passion, a lot of things fell into place with that, it's been a huge blessing. But even in grad school when I was getting my Masters in clinical counseling, I ran my own consulting business as well, just buying and selling hardware. And a lot of what I've done is just I read and ask a ton of questions. I'm out on Twitter, I'm not the brightest bulb in the, of the bunch, but I've learned to ask a lot of questions and the amount of community support in that has gotten me a lot of where I am as well. But yeah, being able to come out on this side, marketing is, like you're saying, it's kind of an anathema to the technical guys, "oh those are the guys that kind of shine the, shine the turd, so to speak," right? But being able to come in and being able to kind of influence the way and make sure that we're technically sound in what we're saying, but you have to translate some of the harder stuff, the more hardcore engineering terms into layman's terms, because not everybody's going to approach that. A CIO with a double E, or an MS in electrical engineering are going on down that road are very few and far between. A lot of these folks have grown up or developed their careers in understanding things, but being able to kind of go in and translate through that, it's been a huge blessing, it's nice. But always following the areas where, networking for me was never a strong point, but jumping in, going, "hey, I'm here to learn," and being willing to learn has been one of the biggest, biggest things I think that's kind of reinforced that career process. >> Yeah, definitely Dave, that intellectual curiosity is something that serves anyone in the tech industry quite well, 'cause, you know, nobody is going to be an expert on everything, and I've spoken to some of the brightest people in the industry, and even they realize nobody can keep up with all of it, so that being able to ask questions, participate, and Dave, thank you so much for helping me, come have this conversation, great as always to have a chat. >> Ah, great to be here Stu, thanks. >> Alright, so be sure to check out the theCUBE.net, which is where all of our content always is, what shows we will be at, all the history of where we've been. This studio is actually in Marlborough, Massachusetts, so not too far outside of Boston, right on the 495 loop, we're going to be doing lot more videos here, myself and Dave Vellante are located here, we have a good team here, so look for more content out of here, and of course our big studio out of Palo Alto, California. So if we can be of help, please feel free to reach out, I'm Stu Miniman, and as always, thanks for watching theCUBE. (upbeat electronic music)

>> from Cambridge, Massachusetts. It's the Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back >> to M I. T. Everybody watching the Cube, The leader in live tech coverage. My name is Dave Volonte here with Paul Guillen. My co host, Tom Davenport, is here is the president's distinguished professor at Babson College. Huebel? Um, good to see again, Tom. Thanks for coming on. Glad to be here. So, yeah, this is, uh let's see. The 13th annual M I t. Cdo lucky. >> Yeah, sure. As this year. Our seventh. I >> think so. Really? Maybe we'll offset. So you gave a talk earlier? She would be afraid of the machines, Or should we embrace them? I think we should embrace them, because so far, they are not capable of replacing us. I mean, you know, when we hit the singularity, which I'm not sure we'll ever happen, But it's certainly not going happen anytime soon. We'll have a different answer. But now good at small, narrow task. Not so good at doing a lot of the things that we do. So I think we're fine. Although as I said in my talk, I have some survey data suggesting that large U. S. Corporations, their senior executives, a substantial number of them more than half would liketo automate as many jobs as possible. They say. So that's a little scary. But unfortunately for us human something, it's gonna be >> a while before they succeed. Way had a case last year where McDonald's employees were agitating for increasing the minimum wage and tThe e management used the threat of wrote of robotics sizing, hamburger making process, which can be done right to thio. Get them to back down. Are you think we're going to Seymour of four that were maybe a eyes used as a threat? >> Well, I haven't heard too many other examples. I think for those highly structured, relatively low level task, it's quite possible, particularly if if we do end up raising the minimum wage beyond a point where it's economical, pay humans to do the work. Um, but I would like to think that, you know, if we gave humans the opportunity, they could do Maur than they're doing now in many cases, and one of the things I was saying is that I think companies are. Generally, there's some exceptions, but most companies they're not starting to retrain their workers. Amazon recently announced they're going to spend 700,000,000 to retrain their workers to do things that a I and robots can't. But that's pretty rare. Certainly that level of commitment is very rare. So I think it's time for the companies to start stepping up and saying, How can we develop a better combination of humans and machines? >> The work by, you know, brain Nelson and McAfee, which is a little dated now. But it definitely suggests that there's some things to be concerned about. Of course, ultimately there prescription was one of an optimist and education, and yeah, on and so forth. But you know, the key point there is the machines have always replace humans, but now, in terms of cognitive functions, but you see it everywhere you drive to the airport. Now it's Elektronik billboards. It's not some person putting up the kiosks, etcetera, but you know, is you know, you've you've used >> the term, you know, paid the cow path. We don't want to protect the past from the future. All right, so, to >> your point, retraining education I mean, that's the opportunity here, isn't it? And the potential is enormous. Well, and, you know, let's face it, we haven't had much in the way of productivity improvements in the U. S. Or any other advanced economy lately. So we need some guests, you know, replacement of humans by machines. But my argument has always been You can handle innovation better. You can avoid sort of race to the bottom at automation sometimes leads to, if you think creatively about humans and machines working as colleagues. In many cases, you remember in the PC boom, I forget it with a Fed chairman was it might have been, Greenspan said, You can see progress everywhere except in the product. That was an M. I. T. Professor Robert Solow. >> OK, right, and then >> won the Nobel Prize. But then, shortly thereafter, there was a huge productivity boom. So I mean is there may be a pent up Well, God knows. I mean, um, everybody's wondering. We've been spending literally trillions on I t. And you would think that it would have led toe productivity, But you know, certain things like social media, I think reduced productivity in the workplace and you know, we're all chatting and talking and slacking and sewing all over the place. Maybe that's is not conducive to getting work done. It depends what you >> do with that social media here in our business. It's actually it's phenomenal to see political coverage these days, which is almost entirely consist of reprinting politicians. Tweets >> Exactly. I guess it's made life easier for for them all people reporters sitting in the White House waiting for a press conference. They're not >> doing well. There are many reporters left. Where do you see in your consulting work your academic work? Where do you see a I being used most effectively in organizations right now? And where do you think that's gonna be three years from now? >> Well, I mean, the general category of activity of use case is the sort of someone's calling boring I. It's data integration. One thing that's being discussed a lot of this conference, it's connecting your invoices to your contracts to see Did we actually get the stuff that we contracted for its ah, doing a little bit better job of identifying fraud and doing it faster so all of those things are quite feasible. They're just not that exciting. What we're not seeing are curing cancer, creating fully autonomous vehicles. You know, the really aggressive moonshots that we've been trying for a while just haven't succeeded at what if we kind of expand a I is gonna The rumor, trawlers. New cool stuff that's coming out. So considering all these new checks with detective Aye, aye, Blockchain new security approaches. When do you think that machines will be able to make better diagnoses than doctors? Well, I think you know, in a very narrow sense in some cases, that could do it now. But the thing is, first of all, take a radiologist, which is one of the doctors I think most at risk from this because they don't typically meet with patients and they spend a lot of time looking at images. It turns out that the lab experiments that say you know, these air better than human radiologist say I tend to be very narrow, and what one lab does is different from another lab. So it's just it's gonna take a very long time to make it into, you know, production deployment in the physician's office. We'll probably have to have some regulatory approval of it. You know, the lab research is great. It's just getting it into day to day. Reality is the problem. Okay, So staying in this context of digital a sort of umbrella topic, do you think large retail stores roll largely disappeared? >> Uh, >> some sectors more than others for things that you don't need toe, touch and feel, And soon before you're to them. Certainly even that obviously, it's happening more and more on commerce. What people are saying will disappear. Next is the human at the point of sale. And we've been talking about that for a while. In In grocery, Not so not achieve so much yet in the U. S. Amazon Go is a really interesting experiment where every time I go in there, I tried to shoplift. I took a while, and now they have 12 stores. It's not huge yet, but I think if you're in one of those jobs that a substantial chunk of it is automata ble, then you really want to start looking around thinking, What else can I do to add value to these machines? Do you think traditional banks will lose control of the payment system? Uh, No, I don't because the Finn techs that you see thus far keep getting bought by traditional bank. So my guess is that people will want that certainty. And you know, the funny thing about Blockchain way say in principle it's more secure because it's spread across a lot of different ledgers. But people keep hacking into Bitcoin, so it makes you wonder. I think Blockchain is gonna take longer than way thought as well. So, you know, in my latest book, which is called the Aye Aye Advantage, I start out talking by about Tamara's Law, This guy Roy Amara, who was a futurist, not nearly as well known as Moore's Law. But it said, You know, for every new technology, we tend to overestimate its impact in the short run and underestimated Long, long Ryan. And so I think a I will end up doing great things. We may have sort of tuned it out of the time. It actually happens way finally have autonomous vehicles. We've been talking about it for 50 years. Last one. So one of the Democratic candidates of the 75 Democratic ended last night mentioned the chief manufacturing officer Well, do you see that automation will actually swing the pendulum and bring back manufacturing to the U. S. I think it could if we were really aggressive about using digital technologies in manufacturing, doing three D manufacturing doing, um, digital twins of every device and so on. But we are not being as aggressive as we ought to be. And manufacturing companies have been kind of slow. And, um, I think somewhat delinquent and embracing these things. So they're gonna think, lose the ability to compete. We have to really go at it in a big way to >> bring it. Bring it all back. Just we've got an election coming up. There are a lot of concern following the last election about the potential of a I chatbots Twitter chat bots, deep fakes, technologies that obscure or alter reality. Are you worried about what's coming in the next year? And that that >> could never happen? Paul. We could never see anything deep fakes I'm quite worried about. We don't seem. I know there's some organizations working on how we would certify, you know, an image as being really But we're not there yet. My guess is, certainly by the time the election happens, we're going to have all sorts of political candidates saying things that they never really said through deep fakes and image manipulation. Scary? What do you think about the call to break up? Big check. What's your position on that? I think that sell a self inflicted wound. You know, we just saw, for example, that the automobile manufacturers decided to get together. Even though the federal government isn't asking for better mileage, they said, We'll do it. We'll work with you in union of states that are more advanced. If Big Tak had said, we're gonna work together to develop standards of ethical behavior and privacy and data and so on, they could've prevented some of this unless they change their attitude really quickly. I've seen some of it sales force. People are talking about the need for data standard data protection standards, I must say, change quickly. I think they're going to get legislation imposed and maybe get broken up. It's gonna take awhile. Depends on the next administration, but they're not being smart >> about it. You look it. I'm sure you see a lot of demos of advanced A I type technology over the last year, what is really impressed you. >> You know, I think the biggest advances have clearly been in image recognition looking the other day. It's a big problem with that is you need a lot of label data. It's one of the reasons why Google was able to identify cat photos on the Internet is we had a lot of labeled cat images and the Image net open source database. But the ability to start generating images to do synthetic label data, I think, could really make a big difference in how rapidly image recognition works. >> What even synthetic? I'm sorry >> where we would actually create. We wouldn't have to have somebody go around taking pictures of cats. We create a bunch of different cat photos, label them as cat photos have variations in them, you know, unless we have a lot of variation and images. That's one of the reasons why we can't use autonomous vehicles yet because images differ in the rain and the snow. And so we're gonna have to have synthetic snow synthetic rain to identify those images. So, you know, the GPU chip still realizes that's a pedestrian walking across there, even though it's kind of buzzed up right now. Just a little bit of various ation. The image can throw off the recognition altogether. Tom. Hey, thanks so much for coming in. The Cube is great to see you. We gotta go play Catch. You're welcome. Keep right. Everybody will be back from M I t CDO I Q In Cambridge, Massachusetts. Stable, aren't they? Paul Gillis, You're watching the Cube?

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBEConversation. >> Hi everyone, welcome to the special CUBEConversation. We're in Palo Alto, California, at theCUBE studio. I'm John Furrier, co-host of the CUBE. We're here with Chris Yeh. He's the co-founder and general partner of Blitzscaling Ventures, author of the book Blitzscaling with Reid Hoffman, founder of LinkedIn and a variety of other ventures, also a partner at Greylock Partners. Chris, great to see you. I've known you for years. Love the book, love Reid. You guys did a great job. So congratulations. But the big news is you're now a TV star as one of the original inaugural contestants on the Mental Samurai, just premiered on Fox, was it >> On Fox. >> On Fox, nine o'clock, on which days? >> So Mental Samurai is on Fox, Tuesdays at 9 p.m. right after Master Chef Junior. >> Alright. So big thing. So successful shows. Take us through the journey. >> Yeah. >> It's a new show, so it's got this kind of like Jeopardy vibe where they got to answer tough questions in what looks like a roller coaster kind of arm that moves you around from station to station, kind of jar you up. But it's a lot of pressure, time clock and hard questions. Tell us about the format. How you got that. Gives all the story. >> So the story behind Mental Samurai is it's from the producers of American Ninja Warrior, if you've ever seen that show. So American Ninja Warrior is a physical obstacle course and these incredible athletes go through and the key is to get through the obstacle course. If you miss any of the obstacles, you're out. So they took that and they translated it to the mental world and they said, okay, we're going to have a mental obstacle course where you going to have different kinds of questions. So they have memory questions, sequence questions, knowledge questions, all these things that are tapping different elements of intelligence. And in order to win at the game, you have to get 12 questions right in five minutes or less. And you can't get a single question wrong. You have to be perfect. >> And they do try to jar you up, to kind of scrabble your brain with those devices, it makes it suspenseful. In watching last night at your watch party in Palo Alto, it's fun to watch because yeah, I'm like, okay, it's going to be cool. I'll support Chris. I'll go there, be great and on TV, and oh my, that's pretty interesting. It was actually riveting. Intense. >> Yeah. You have that element of moving around from station to station and it's dramatic. It's kind of a theater presence. But what's it like in there? Give us some insight. You're coming on in April 30th so you're yet to come on. >> Yes. >> But the early contestants, none of them made it to the 100,000. Only one person passed the first threshold. >> Right >> Take us through the format. How many thresholds are there? What's the format? >> Perfect, so basically when a competitor gets strapped into the chair, they call it Ava, it's like a robot, and basically they got it from some company in Germany and it has the ability to move 360 degrees. It's like an industrial robot or something. It makes you feel like you're an astronaut or in one those centrifugal force things. And the idea is they're adding to the pressure. They're making it more of a challenge. Instead of just Jeopardy where you're sitting there, and answering questions and bantering with Alex Trebek, you're working against the clock and you're being thrown around by this robot. So what happens is first you try to answer 12 questions correctly in less than five minutes. If you do that, then you make it through to the next round, what they call the circle of samurai and you win $10,000. The circle of samurai, what happens is there are four questions and you get 90 seconds plus whatever you have left over from your first run, to answer those four questions. Answer all four questions correctly, you win $100,000 and the official title of Mental Samurai. >> So there's only two levels, circle of samurai but it gets harder. Now also I noticed that it's, their questions have certain puzzles and there's certain kinds of questions. What's the categories, if you will, what's the categories they offer? >> Yes, so the different categories are knowledge, which is just classic trivia, it's a kind of Jeopardy stuff. There's memory, where they have something on screen that you have to memorize, or maybe they play an audio track that you have to remember what happened. And then there's also sequence where you have to put things in order. So all these different things are represented by these different towers which are these gigantic television screens where they present the questions. And the idea is in order to be truly intelligent, you have to be able to handle all of these different things. You can't just have knowledge. You can't just have pop culture. You got to have everything. >> So on the candidates I saw some from Stanford. >> Yeah. >> I saw an athlete. It's a lot of diversity in candidates. How do they pick the candidates? How did you get involved? Did your phone ring up one day? Were you identified, they've read your blog. Obviously they've, you're smart. I've read your stuff on Facebook. How did you get in there? (laughs) >> Excellent question. So the whole process, there's a giant casting department that does all these things. And there's people who just cast people for game shows. And what happened with me is many years ago back in 2014, my sister worked in Hollywood when I was growing up. She worked for ER and Baywatch and other companies and she still keeps track of the entertainment industry. And she sent me an email saying, hey, here's a casting call for a new show for smart people and you should sign up. And so I replied to the email and said hey I'm Chris Yeh. I'm this author. I graduate from Stanford when I was 19, blah blah blah blah. I should be on your show. And they did a bunch of auditions with me over the phone. And they said we love you, the network loves you. We'll get in touch and then I never heard. Turns out that show never got the green light. And they never even shot that show. But that put me on a list with these various casting directors. And for this show it turns out that there was an executive producer of the show, the creator of the show, his niece was the casting director who interviewed me back in 2014. And she told her uncle, hey, there's this guy, Chris Yeh, in Palo Alto. I think would be great for this new show you're doing. Why don't you reach out to him. So they reached out to me. I did a bunch of Skype auditions. And eventually while I was on my book tour for Blitzscaling, I got the email saying, congratulations, you're part of the season one cast. >> And on the Skype interviews, was it they grilling you with questions, or was it doing a mock dry run? What was some of interview vetting questions? >> So they start off by just asking you about yourself and having you talk about who you are because the secret to these shows is none of the competitors are famous in advance, or at least very few of them are. There was a guy who was a major league baseball pitcher, there's a guy who's an astronaut, I mean, those guys are kind of famous already, but the whole point is, they want to build a story around the person like they do with the Olympics so that people care whether they succeed or not. And so they start off with biographical questions and then they proceed to basically use flash cards to simulate the game and see how well you do. >> Got it, so they want to basically get the whole story arc 'cause Chris, obviously Chris is smart, he passed the test. Graduate when he's 19. Okay, you're book smart. Can you handle the pressure? If you do get it, there's your story line. So they kind of look from the classic, kind of marketing segmentation, demographics is your storylines. What are some of the things that they said to you on the feedback? Was there any feedback, like you're perfect, we like this about you. Or is it more just cut and dry. >> Well I think they said, we love your energy. It's coming through very strongly to the screen. That's fantastic. We like your story. Probably the part I struggle the most with, was they said hey, you know, talk to us about adversity. Talk to us about the challenges that you've overcome. And I tell people, listen, I'm a very lucky guy. A lot of great things have happened to me in life. I don't know if there's that much adversity that I can really complain about. Other people who deal with these life threatening illnesses and all this stuff, I don't have that. And so that was probably the part I struggled the most with. >> Well you're certainly impressive. I've known you for years. You're a great investor, a great person. And a great part of Silicon Valley. So congratulations, good luck on the show. So it's Tuesdays. >> 9 p.m. >> 9 p.m. >> On fox. >> On Fox. Mental Samurai. Congratulations, great. Great to be at the launch party last night. The watch party, there'll be another one. Now your episode comes out on April 30th. >> Yes. So on April 30th we will have a big Bay area-wide watch party. I'm assuming that admission will be free, assuming I find the right sponsors. And so I'll come back to you. I'll let you know where it's going to be. Maybe we should even film the party. >> That's, well, I got one more question on the show. >> Yeah. >> You have not been yet on air so but you know the result. What was it like sitting in the chair, I mean, what was it personally like for you? I mean you've taken tests, you've been involved with the situation. You've made some investments. There's probably been some tough term sheets here and there, board meetings. And all that experience in your life, what was it compared to, what was it like? >> Well, it's a really huge adrenaline rush because if you think about there's so many different elements that already make it an adrenaline rush and they all combine together. First of all, you're in this giant studio which looks like something out of a space-age set with this giant robotic arm. There's hundreds of people around cheering. Then you're strapped into a robotic arm which basically makes you feel like an astronaut, like every run starts with you facing straight up, right? Lying back as if you're about to be launched on a rocket. And then you're answering these difficult questions with time pressure and then there's Rob Lowe there as well that you're having a conversation with. So all these things together, and your heart, at least for me, my heart was pounding. I was like trying very hard to stay calm because I knew it was important to stay clam, to be able to get through it. >> Get that recall, alright. Chris, great stuff. Okay, Blitzscaling. Blitzscaling Ventures. Very successful concept. I remember when you guys first started doing this at Stanford, you and Reid, were doing the lectures at Stanford Business School. And I'm like, I love this. It's on YouTube, kind of an open project initially, wasn't really, wasn't really meant to be a book. It was more of gift, paying it forward. Now it's a book. A lot of great praise. Some criticism from some folks but in general it's about scaling ventures, kind of the Silicon Valley way which is the rocket ship I call. The rocket ship ventures. There's still the other venture capitals. But great book. Feedback from the book and the original days at Stanford. Talk about the Blitzscaling journey. >> And one of the things that happened when we did the class at Stanford is we had all these amazing guests come in and speak. So people like Eric Schmidt. People like Diane Greene. People like Brian Chesky, who talked about their experiences. And all of those conversations really formed a key part of the raw material that went into the book. We began to see patterns emerge. Some pretty fascinating patterns. Things like, for example, a lot of companies, the ones that'd done the best job of maintaining their culture, have their founders involved in hiring for the first 500 employees. That was like a magic number that came up over and over again in the interviews. So all this content basically came forward and we said, okay, well how do we now take this and put it into a systematic framework. So the idea of the book was to compress down 40 hours of video content, incredible conversations, and put it in a framework that somebody could read in a couple of hours. >> It is also one of those things where you get lightning in a ball, the classic and so then I'd say go big or go home. But Blitzscaling is all about something new and something different. And I'm reading a book right now called Loonshots, which is a goof on moonshots. It's about the loonies who start the real companies and a lot of companies that are successful like Airbnb was passed over on and they call those loonies. Those aren't moonshots. Moonshots are well known, build-outs. This is where the blitzscaling kind of magic happens. Can you just share your thoughts on that because that's something that's not always talked about in the mainstream press, is that a lot of there blitzscaling companies, are the ones that don't look good on paper initially. >> Yes. >> Or ones that no one's talking about is not in a category or herd mentality of investors. It's really that outlier. >> Yes. >> Talk about that dynamic. >> Yeah, and one of the things that Reid likes to say is that the best possible companies usually sound like they're dumb ideas. And in fact the best investment he's been a part of as a venture capitalist, those are the ones where there's the greatest controversy around the table. It's not the companies that come in and everyone's like this is a no-brainer, let's do it. It's the companies where there's a big fight. Should we do this, should we not? And we think the reason is this. Blitzscaling is all about being able to be the first to scale and the winner take most or the winner take all market. Now if you're in a market where everyone's like, this is a great market, this is a great idea. You're going to have huge competition. You're going to have a lot of people going after it. It's very difficult to be the first to scale. If you are contrarian and right you believe something that other people don't believe, you have the space to build that early lead, that you can then use to leverage yourself into that enduring market leadership. >> And one of the things that I observed from the videos as well is that the other fact that kind of plays into, I want to get your reaction, this is that there has to be a market shift that goes on too because you have to have a tailwind or a wave to ride because if you can be contrarian if there's no wave, >> Right. >> right? so a lot of these companies that you guys highlight, have the wave behind them. It was mobile computing, SaaSification, cloud computing, all kind of coming together. Talk about that dynamic and your reaction 'cause that's something where people can get confused on blitzscaling. They read the book. Oh I'm going to disrupt the dry cleaning business. Well I mean, not really. I mean, unless there's something different >> Exactly. >> in market conditions. Talk about that. >> Yeah, so with blitzscaling you're really talking about a new market or a market that's transforming. So what is it that causes these things to transform? Almost always it's some new form of technological innovation, or perhaps a packaging of different technological innovations. Take mobile computing for example. Many of the components have been around for a while. But it took off when Apple was able to combine together capacitative touchscreens and the form factor and the processor strength being high enough finally. And all these things together created the technological innovation. The technological innovation then enables the business model innovation of building an app store and creating a whole new way of thinking about handheld computing. And then based on that business model innovation, you have the strategy innovation of blitzscaling to allow you to grow rapidly and keep from blowing up when you grow. >> And the spirit of kind of having, kind of a clean entrepreneurial segmentation here. Blitzscaling isn't for everybody. And I want you to talk about that because obviously the book's popular when this controversy, there's some controversy around the fact that you just can't apply blitzscaling to everything. We just talk about some of those factors. There are other entrepreneurialship models that makes sense but that might not be a fit for blitzscaling. Can you just unpack that and just explain, a minute to explain the difference between a company that's good for blitzscaling and one that isn't. >> Well, a key thing that you need for blitzscaling is one of these winner take most or winner take all markets that's just enormous and hugely valuable, alright? The whole thing about blitzscaling is it's very risky. It takes a lot of effort. It's very uncomfortable. So it's only worth doing when you have those market dynamics and when that market is really large. And so in the book we talk about there being many businesses that this doesn't apply to. And we use the example of two companies that were started at the same time. One company is Amazon, which is obviously a blitzscaling company and a dominant player and a great, great company. And the other is the French Laundry. In fact, Jeff Bezos started Amazon the same year that Thomas Keller started the French Laundry. And the French Laundry still serves just 60 people a day. But it's a great business. It's just a very different kind of business. >> It's a lifestyle or cash flow business and people call it a lifestyle business but mainly it's a cash flow or not a huge growing market. >> Yeah. >> Satisfies that need. What's the big learnings that you learned that was something different that you didn't know coming out of blitzscaling experience? Something that surprised you, something that might have shocked you, something that might have moved you. I mean you're well-read. You're smart. What was some learnings that you learned from the journey? >> Well, one of the things that was really interesting to me and I didn't really think about it. Reid and I come from the startup world, not the big company world. One of the things that surprised me is the receptivity of big companies to these ideas. And they explained it to me and they said, listen, you got to understand with a big company, you think it's just a big company growing at 10, 15% a year. But actually there's units that are growing at 100% a year. There's units that are declining at 50% a year. And figuring out how you can actually continue to grow new businesses quicker than your old businesses die is a huge thing for the big, established companies. So that was one of the things that really surprised me but I'm grateful that it appears that it's applicable. >> It's interesting. I had a lot of conversations with Michael Dell before, and before they went private and after they went private. He essentially was blitzscaling. >> Yeah. >> He said, I'm going to winner take most in the mature, somewhat declining massive IT enterprise spend against the HPs of the world, and he's doing it and VMware stock went to an all time high. So big companies can blitz scale. That's the learning. >> Exactly. And the key thing to remember there is one of the reasons why somebody like Michael Dell went private to do this is that blitzscaling is all about prioritizing speed over efficiency. Guess who doesn't like that? Wall street doesn't like because you're taking a hit to earnings as you invest in a new business. GM for example is investing heavily in autonomous vehicles and that investment is not yet delivering cash but it's something that's going to create a huge value for General Motors. And so it's really tough to do blitzscaling as a publicly traded company though there are examples. >> I know your partner in the book, Reid Hoffman as well as in the blitzscaling at Stanford was as visible in both LinkedIn and as the venture capitalist of Greylock. But also he was involved with some failed startups on the front end of LinkedIn. >> Yeah. >> So he had some scar tissue on social networking before it became big, I'll say on the knowledge graph that he's building, he built at LinkedIn. I'm sure he had some blitzscaling lessons. What did he bring to the table? Did he share anything in the classes or privately with you that you can share that might be helpful for people to know? >> Well, there's a huge number of lessons. Obviously we drew heavily on Reid's life for the book. But I think you touched on something that a lot of people don't know, which is that LinkedIn is not the first social network that Reid created. Actually during the dot-com boom Reid created a company called SocialNet that was one of the world's first social networks. And I actually was one of the few people in the world who signed up and was a member of SocialNet. I think I had the handle, net revolutionary on that if you can believe that. And one of the things that Reid learned from his SocialNet experience turned into one of his famous sayings, which is, if you're not embarrassed by your first product launch, you've launched too late. With SocialNet they spent so much time refining the product and trying to get it perfectly right. And then when they launched it, they discovered what everyone always discovers when they launch, which is the market wants something totally different. We had no idea what people really wanted. And they'd wasted all this time trying to perfect something that they've theoretically thought was what the market wanted but wasn't actually what the market wanted. >> This is what I love about Silicon Valley. You have these kind of stories 'cause that's essentially agile before agile came out. They're kind of rearranging the deck chairs trying to get the perfect crafted product in a world that was moving to more agility, less craftsmanship and although now it's coming back. Also I talked to Paul Martino, been on theCUBE before. He's a tribe with Pincus. And it's been those founding fathers around these industries. It's interesting how these waves, they start off, they don't get off the ground, but that doesn't mean the category's dead. It's just a timing issue. That's important in a lot of ventures, the timing piece. Talk about that dynamic. >> Absolutely. When it comes to timing, you think about blitzscaling. If you start blitzscaling, you prioritize speed over efficiency. The main question is, is it the right time. So Webvan could be taken as an example of blitzscaling. They were spending money wildly inefficiently to build up grocery delivery. Guess what? 2000 was not the right time for it. Now we come around, we see Instacart succeeding. We see other delivery services delivering some value. It just turns out that you have to get the timing right. >> And market conditions are critical and that's why blitzscaling can work when the conditions are right. Our days back in the podcast, it was, we were right but timing was off. And this brings up the question of the team. >> Yeah. >> You got to have the right team that can handle the blitzscaling culture. And you need the right investors. You've been on both sides of the table. Talk about that dynamic because I think this is probably one of the most important features because saying you going to do blitzscaling and then getting buy off but not true commitment from the investors because the whole idea is to plow money into the system. You mentioned Amazon, one of Jeff Bezos' tricks was, he always poured money back into his business. So this is a capital strategy, as well financial strategy capital-wise as well as a business trait. Talk about the importance of having that stomach and the culture of blitzscaling. >> Absolutely. And I think you hit on something very important when you sort of talk about the importance of the investors. So Reid likes to refer to investors as financing partners. Or financing co-founders, because really they're coming on with you and committing to the same journey that you're going on. And one of the things I often tell entrepreneurs is you really have to dig deep and make sure you do more due diligence on your investors than you would on your employees. Because if you think about it, if you hire an employee, you can actually fire them. If you take money from an investor, there's no way you can ever get rid of them. So my advice to entrepreneurs is always, well, figure out if they're going to be a good partner for you. And the best way to do that is to go find some of the entrepreneurs they backed who failed and talked to those people. >> 'Cause that's where the truth will come out. >> Well, that's right. >> We stood by them in tough times. >> Exactly. >> I think that's classic, that's perfect but this notion of having the strategies of the elements of the business model in concert, the financial strategy, the capital strategy with the business strategy and the people strategy, all got to be pumping that can't be really any conflict on that. That's the key point. >> That's right, there has to be alignment because again, you're trying to go as quickly as possible and if you're running a race car and you have things that are loose and rattling around, you're not going to make it across the finish line. >> You're pulling for a pit stop and the guys aren't ready to change the tires, (snapping fingers) you know you're out of sync. >> Bingo. >> Chris, great stuff. Blitzscaling is a great book. Check it out. I recommend it, remember blitz scale is not for anyone, it's for the game changers. And again, picking your investors is critical on this. So if you picked the wrong investors, blitzscaling will blow up in a bad way. So don't, don't, pick properly on the visa and pick your team. Chris, so let's talk about you real quick to end the segment and the last talk track. Talk about your background 'cause I think you have a fascinating background. I didn't know that you graduated when you're 19, from Stanford was it? >> Yes. >> Stanford at 19, that's a great accomplishment. You've been an entrepreneur. Take us through your journey. Give us a quick highlight of your career. >> So the quick highlight is I grew up in Southern California and Santa Monica where I graduated from Santa Monica High School along with other luminaries such as Rob Lowe, Robert Downey, Jr., and Sean Penn. I didn't go at the same time that they did. >> They didn't graduate when they were 17. >> They did not, (John laughing) and Charlie Sheen also attended Santa Monica High School but dropped out or was expelled. (laughing) Go figured. >> Okay. >> I came up to Stanford and I actually studied creative writing and product design. So I was really hitting both sides of the brain. You could see that really coming through in the rest of my career. And then at the time I graduated which was the mid-1990s that was when the internet was first opening up. I was convinced the internet was going to be huge and so I just went straight into the internet in 1995. And have been in the startup world ever since. >> Must love that show, Halt and Catch Fire a series which I love reminiscing. >> AMC great show. >> Just watching that my life right before my eyes. Us old folks. Talk about your investment. You are at Wasabi Ventures now. Blitzscaling Ventures. You guys looks like you're going to do a little combination bring capital around blitzscaling, advising. What's Blitzscaling Ventures? Give a quick commercial. >> So the best way to think about it is for the entrepreneurs who are actually are blitzscaling, the question is how are you going to get the help you need to figure out how to steer around the corners to avoid the pitfalls that can occur as you're growing rapidly. And Blitzscaling Ventures is all about that. So obviously I bring a wealth of experience, both my own experience as well as everything I learned from putting this book together. And the whole goal of Blitzscaling Ventures is to find those entrepreneurs who have those blitzscalable opportunities and help them navigate through the process. >> And of course being a Mental Samurai that you are, the clock is really important on blitzscaling. >> There are actually are a lot of similarities between the startup world and Mental Samurai. Being able to perform under pressure, being able to move as quickly as possible yet still be accurate. The one difference of course is in our startup world you often do make mistakes. And you have a chance to recover from them. But in Mental Samurai you have to be perfect. >> Speed, alignment, resource management, capital deployment, management team, investors, all critical factors in blitzscaling. Kind of like entrepreneurial going to next level. A whole nother lesson, whole nother battlefields. Really the capital markets are flush with cash. Post round B so if you can certainly get altitude there's a ton of capital. >> Yeah. And the key is that capital is necessary for blitzscaling but it's not sufficient. You have to take that financial capital and you have to figure out how to combine it with the human capital to actually transform the business in the industry. >> Of course I know you've got to catch a plane. Thanks for coming by in the studio. Congratulations on the Mental Samurai. Great show. I'm looking forward to April 30th. Tuesdays at 9 o'clock, the Mental Samurai. Chris will be an inaugural contestant. We'll see how he does. He's tight-lipped, he's not breaking his disclosure. >> I've got legal requirements. I can't say anything. >> Just say he's sticking to his words. He's a man of his words. Chris, great to see you. Venture capitalist, entrepreneur, kind of venture you want to talk to Chris Yeh, co-founder, general partner of blitzscaling. I'm John Furrier for theCUBE. Thanks for watching. (upbeat music)

>> Announcer: Live from Orlando, Florida. It's the CUBE. Covering Grace Hopper Celebration of Women in Computing. Brought to you by Silicon Angle Media. >> Welcome back everybody. Jeff Frick here with the Cube. We are winding down day three of the Grace Hopper Celebration of Women in Computing in Orlando. It's 18,000, mainly women, a couple of us men hangin' out. It's been a phenomenal event again. It always amazes me to run into first timers that have never been to the Grace Hopper event. It's a must do if you're in this business and I strongly encourage you to sign up quickly 'cause I think it sells out in about 15 minutes, like a good rock concert. But we're excited to have our next guest. She's Rachel Faber Tobac, UX Research at Course Hero. Rachel, great to see you. >> Thank you so much for having me on. >> Absolutely. So, Course Hero. Give people kind of an overview of what Course Hero is all about. >> Yup. So we are an online learning platform and we help about 200 million students and educators master their classes every year. So we have all the notes, >> 200 million. >> Yes, 200 million! We have all the notes, study guides, resources, anything a student would need to succeed in their classes. And then anything an educator would need to prepare for their classes or connect with their students. >> And what ages of students? What kind of grades? >> They're usually in college, but sometimes we help high schoolers, like AP students. >> Okay. >> Yeah. >> But that's not why you're here. You want to talk about hacking. So you are, what you call a "white hat hacker". >> White hat. >> So for people that aren't familiar with the white hat, >> Yeah. >> We all know about the black hat conference. What is a white hat hacker. >> So a "white hat hacker" is somebody >> Sounds hard to say three times fast. >> I know, it's a tongue twister. A white hat hacker is somebody who is a hacker, but they're doing it to help people. They're trying to make sure that information is kept safer rather than kind of letting it all out on the internet. >> Right, right. Like the old secret shoppers that we used to have back in the pre-internet days. >> Exactly. Exactly. >> So how did you get into that? >> It's a very non-linear story. Are you ready for it? >> Yeah. >> So I started my career as a special education teacher. And I was working with students with special needs. And I wanted to help more people. So, I ended up joining Course Hero. And I was able to help more people at scale, which was awesome. But I was interested in kind of more of the technical side, but I wasn't technical. So my husband went to Defcon. 'cause he's a cyber security researcher. And he calls me at Defcon about three years ago, and he's like, Rach, you have to get over here. I'm like, I'm not really technical. It's all going to go over my head. Why would I come? He's like, you know how you always call companies to try and get our bills lowered? Like calling Comcast. Well they have this competition where they put people in a glass booth and they try and have them do that, but it's hacking companies. You have to get over here and try it. So I bought a ticket to Vegas that night and I ended up doing the white hat hacker competition called The Social Engineering Capture the Flag and I ended up winning second, twice in a row as a newb. So, insane. >> So you're hacking, if I get this right, not via kind of hardcore command line assault. You're using other tools. So like, what are some of the tools that are vulnerabilities that people would never think about. >> So the biggest tool that I use is actually Instagram, which is really scary. 60% of the information that I need to hack a company, I find on Instagram via geolocation. So people are taking pictures of their computers, their work stations. I can get their browser, their version information and then I can help infiltrate that company by calling them over the phone. It's called vishing. So I'll call them and try and get them to go to a malicious link over the phone and if I can do that, I can own their company, by kind of presenting as an insider and getting in that way. (chuckling) It's terrifying. >> So we know phishing right? I keep wanting to get the million dollars from the guy in Africa that keeps offering it to me. >> (snickers) Right. >> I don't whether to bite on that or. >> Don't click the link. >> Don't click the link. >> No. >> But that interesting. So people taking selfies in the office and you can just get a piece of the browser data and the background of that information. >> Yep. >> And that gives you what you need to do. >> Yeah, so I'll find a phone number from somebody. Maybe they take a picture of their business card, right? I'll call that number. Test it to see if it works. And then if it does, I'll call them in that glass booth in front of 400 people and attempt to get them to go to malicious links over the phone to own their company or I can try and get more information about their work station, so we could, quote unquote, tailor an exploit for their software. >> Right. Right. >> We're not actually doing this, right? We're white hat hackers. >> Right. >> If we were the bad guys. >> You'd try to expose the vulnerability. >> Right. The risk. >> And what is your best ruse to get 'em to. Who are you representing yourself as? >> Yeah, so. The representation thing is called pre-texting. It's who you're pretending to be. If you've ever watched like, Catch Me If You Can. >> Right. Right. >> With Frank Abagnale Jr. So for me, the thing that works the best are low status pretext. So as a woman, I would kind of use what we understand about society to kind of exploit that. So you know, right now if I'm a woman and I call you and I'm like, I don't know how to trouble shoot your website. I'm so confused. I have to give a talk, it's in five minutes. Can you just try my link and see if it works on your end? (chuckling) >> You know? Right? You know, you believe that. >> That's brutal. >> Because there's things about our society that help you understand and believe what I'm trying to say. >> Right, right. >> Right? >> That's crazy and so. >> Yeah. >> Do you get, do you make money white hacking for companies? >> So. >> Do they pay you to do this or? Or is it like, part of the service or? >> It didn't start that way. >> Right. >> I started off just doing the Social Engineering Capture the Flag, the SECTF at Defcon. And I've done that two years in a row, but recently, my husband, Evan and I, co-founded a company, Social Proof Security. So we work with companies to train them about how social media can impact them from a social engineering risk perspective. >> Right. >> And so we can come in and help them and train them and understand, you know, via a webinar, 10 minute talk or we can do a deep dive and have them actually step into the shoes of a hacker and try it out themselves. >> Well I just thought the only danger was they know I'm here so they're going to go steal my bike out of my house, 'cause that's on the West Coast. I'm just curious and you may not have a perspective. >> Yeah. >> 'Cause you have niche that you execute, but between say, you know kind of what you're doing, social engineering. >> Yeah. >> You know, front door. >> God, on the telephone. Versus kind of more traditional phishing, you know, please click here. Million dollars if you'll click here versus, you know, what I would think was more hardcore command line. People are really goin' in. I mean do you have any sense for what kind of the distribution of that is, in terms of what people are going after? >> Right, we don't know exactly because usually that information's pretty confidential, >> Sure. when a hack happens. But we guess that about 90% of infiltrations start with either a phishing email or a vishing call. So they're trying to gain information so they can tailor their exploits for your specific machine. And then they'll go in and they'll do that like actual, you know, >> Right. >> technical hacking. >> Right. >> But, I mean, if I'm vishing you right and I'm talking to you over the phone and I get you to go to a malicious link, I can just kind of bypass every security protocol you've set up. I don't even a technical hacker, right? I just got into your computer because. >> 'Cause you're in 'Cause I'm in now, yup. >> I had the other kind of low profile way and I used to hear is, you know, you go after the person that's doin' the company picnic. You know Wordpress site. >> Yes. >> That's not thinking that that's an entry point in. You know, kind of these less obvious access points. >> Right. That's something that I talk about a lot actually is sometimes we go after mundane information. Something like, what pest service provider you use? Or what janitorial service you use? We're not even going to look for like, software on your machine. We might start with a softer target. So if I know what pest extermination provider you use, I can look them up on LinkedIn. See if they've tagged themselves in pictures in your office and now I can understand how do they work with you, what do their visitor badges look like. And then emulate all of that for an onsite attack. Something like, you know, really soft, right? >> So you're sitting in the key note, right? >> Yeah. >> Fei-Fei Li is talking about computer visualization learning. >> Right. >> And you know, Google running kagillions of pictures through an AI tool to be able to recognize the puppy from the blueberry muffin. >> Right. >> Um, I mean, that just represents ridiculous exploitation opportunity at scale. Even you know, >> Yeah. >> You kind of hackin' around the Instagram account, can't even begin to touch, as you said, your other thing. >> Right. >> You did and then you did it at scale. Now the same opportunity here. Both for bad and for good. >> I'm sure AI is going to impact social engineering pretty extremely in the future here. Hopefully they're protecting that data. >> Okay so, give a little plug so they'll look you up and get some more information. But what are just some of the really easy, basic steps that you find people just miss, that should just be, they should not be missing. From these basic things. >> The first thing is that if they want to take a picture at work, like a #TBT, right? It's their third year anniversary at their company. >> Right. Right. >> Step away from your work station. You don't need to take that picture in front of your computer. Because if you do, I'm going to see that little bottom line at the bottom and I'm going to see exactly the browser version, OS and everything like that. Now I'm able to exploit you with that information. So step away when you take your pictures. And if you do happen to take a picture on your computer. I know you're looking at computer nervously. >> I know, I'm like, don't turn my computer on to the cameras. >> Don't look at it! >> You're scarin' me Rachel. >> If you do take a picture of that. Then you don't want let someone authenticate with that information. So let's say I'm calling you and I'm like, hey, I'm with Google Chrome. I know that you use Google Chrome for your service provider. Has your network been slow recently? Everyone's network's been slow recently, right? >> Right. Right. >> So of course you're going to say yes. Don't let someone authenticate with that info. Think to yourself. Oh wait, I posted a picture of my work station recently. I'm not going to let them authenticate and I'm going to hang up. >> Interesting. All right Rachel. Well, I think the opportunity in learning is one thing. The opportunity in this other field is infinite. >> Yeah. >> So thanks for sharing a couple of tips. >> Yes. >> And um. >> Thank you for having me. >> Hopefully we'll keep you on the good side. We won't let you go to the dark side. >> I won't. I promise. >> All right. >> Rachel Faber Tobac and I'm Jeff Frick. You're watchin the Cube from Grace Hopper Celebration Women in Computing. Thanks for watching. (techno music)

okay we're back at vmworld twenty twelve i'm john fairy with SiliconANGLE calm this is the cube this is our flagship telecast we go out to the events extract a signal from the noise and share that with you i'm joe and stu miniman my co-host with this segment and martine casado the co-founder of nicera you guys are ranking number one on our trending tool that we built under networking because it moved up to the top of the list because of vmworld company had spent a billion dollars for you guys jaishree from Arista called you guys the Instagram of networking kind of tongue-in-cheek on the huge buyout but hey congratulations great wired story today SR with you guys we've done about the talent you have and you brought over the vmworld and you're the top story here so congratulations thank you welcome to the cube thank you so take us through the logic and your motion around past year okay up until the buyout what a roller coaster so just share with us personally from Europe as an entrepreneur what was it like what highlights of what happened well I guess I've been very focused on changing networking right so for me it's been largely a technical ride and since we started the company five years ago we've been focusing on developing core technology and we did that for the first three years and then the last year to us was primarily about execution and customer engagement and so you know we've spent a lot of time proving the technology getting into production doing the support and fixing out that model and so it turned out is a very natural transition point when the acquisition happened because we had gotten traction we had starting to realize how difficult it is to address a market as large as this within a small start-up and so it was very welcome to come join a much larger company where we can kind of provide this as a much box so you guys have some big backers obviously you know they're all it's all well documented in the valley but every entrepreneur has that moments like wait a minute is this what I wanted is this tea but the dollars was so good and vmware's asti growing company what clicked for you what made you go is this the right thing take us through that decision you know absolutely so I mean like to me business guides behavior and at the end of the day the goal is is how do you change networking and have a very very firm belief that the access layer to that network is moving from within the network towards the edge and so we wanted to develop technologies that can use this position to re-implement networking and software and so once you get the core technology done once you prove it out with large customers once you prove out the market the question is is kind of what is the best way to have the biggest impact and I think in some respects you can look at vmware is one of the largest networking companies in the in the world just based on port count right the number of virtual ports that they control is as large as any large networking vendor so this is the opportunity of a lifetime to change in industry so like I've been doing this now you know sdn since those doing my PhD at stanford for so going on 10 years now and this is the the opportunity of a lifetime to actually have broad broad like planet scale impact well congratulations certainly you disrupted the market not only in the validation of the acquisition but as you guys were moving out and talking about some of the deployments you guys were doing it just came out of left field for most people but in the inside baseball sure people knew it was going on in terms of like how you guys are disrupting so so congratulations thank you here I want to talk about is also the messaging here at vmworld very solid around suffered to find datacenter sure and that really kind of brings you into a whole nother beyond networking so you know we've been covering converged infrastructure that's looking a look upon you know around house storage servers and networking so its bigger now than just networking right so now you're taking it to a whole nother leg of the journey so connect the dots out there for the folks between software virtualization and software-defined networking to this to the data center help them understand what is going to happen under that next leg of the journey yeah of course so we're all familiar with compute virtualization right I mean this is how vmware initially changed the world where the time it takes to provision a workload when from weeks to literally minutes like two minutes however I t isn't about single workloads ideas about applications and all the network services that those applications require for example firewalling or security or or monitoring debugging and so even though we reduce the time it took to provisional workload from weeks two minutes you still took days to do everything else that was required so if we take a broad scope if we take a broad look at a thai tea we still realize it still takes days to provision new applications and to provision new workloads and so the only way to get past this the next step that we want to take is to virtualize every aspect of infrastructure and so there's three of those there's there's compute which is virtualized their storage which we're making good progress on and there's network and network really is a pivot piece right it's the one piece that touches everything right it is between the compute in the storage it is between the different types of compute and so if you look at large data centers even cloud data centers the long pole in the tent and provisioning is the network so we must must virtualize that so the goal is the software-defined data center that's like everything's in software everything's totally dynamic you create it on demand you can move it its liquid it's like water it'll go anywhere but in order for this dream to be realized we've got to get the network out of the way and that's what the sierra does we've been talking about going to go and Wikibon we've just kicked up a whole kind of research section on what we're calling data infrastructure and really highlighting this modern era right and we kind of use a lot of sports analogies but you know a modern era meaning the new way not the old way right so you're a classic example of disruption in a new way so talk about the enablement that you see happening from a from a marker play standpoint just you know open your mind and share the crowds and vision around what you will enable with this because networking is has to be dynamic it has that makes total sense you guys have done it what's going to happen next in your mind's eye in terms of what the possibilities are yeah yeah absolutely so I think ultimately this is where we want to get to we want to build a platform that will provide that will recreate you know every Network Service and functionality in a virtualized manner in software from the edge and that means that there can be any service available anywhere over any type of hardware at any scale that's needed and it can be done all at virtualization timeframe so this is like you do an API call you get a virtual network abstraction you add a firewall to it you you configure ackles to it and so all of network configuration all of network services all of network operations become soft state it becomes like a VM image and it's available anywhere that you want it to and so that is the first step so I believe these transformations and systems and this happened many times in the past happen in two steps the first one is you virtualize and when you virtualize you offer the same thing but in a more flexible manner like when you virtualize compute you offered an x86 cpu but you did it in software after you virtualize you can actually change the operational paradigm like when you when they created compute virtualization they didn't immediately get to migration or snapshot or rewind all these other kind of operational benefits these came later so the first step is any networking anywhere you want at any scale automatically and then the second step is like drastically changing the operational paradigm so you can do things like better security so you can rewind configuration state I mean things that we can't even think about today because now we have this ultimate point of indirection that's virtualized this virtualized layer and who's the candidate for these developers just admins net admins all the above is it going to be software programmatic I mean how does that it takes DevOps right to a level of functionality that is just mind-boggling so yeah who's the new personnel yeah it was like who's life does this impact think what happens called a CI easy out there well I mean it's a good question whose life does this impact I mean I mean immediately anybody that's building out a data center like a cloud architect is going to have this this primitive that that they can use to architect better system just like you gave them a virtual machine they use that as a primitive for building better data centers now we're giving them virtual networks as a primitive build virtual data centers so the cloud architects job gets easier application developers don't have to worry about the basics of you know the way networks work our network configuration operations will have a lot more flexibility and the virtual layer of where they can move things around as far as the physical networking layer the problem actually becomes quite a bit simpler but you still have to focus the on the problem of building a physical network so for example when server virtualization came around you didn't like reduce the need for servers you needed more servers and just like the same thing will happen with with network virtualization which is you'll still need physical networks and they're going to probably have to be better physical networks but the problem now is more of how do you build a physical network with high capacity that can support any workload and less about doing all the operational stuff you do today how does an impact we just had chris hoffman from juniper who's now a worker he's been a big security buff a great guest for us but we just were just riffing on the security problems right so give us your perspective on how this new canvas of software-defined virtualization is gonna impact security paradise yeah so I mean I think there are a couple of answers i actually think ultimately the security model is improved honestly so yeah the original work was done with the intelligence community actually the the original funding for nasira came from the intelligence community my background I used to work for the intelligence agencies and when you move everything to software we already have a fundamental security paradigm which is crust consolidation in the hypervisor right and with network virtualization you follow the same paradigm which is you you entrust the hypervisor to enforce things like isolation enforce the security but now you've got a strongly authenticated endpoint there you're not guessing about things but but it requires the security community to evolve with the virtualization community so I think that there's much more of a socialization hurdle more of a social hurdle than a technical hurdle like all of the technology is there to do good security in the cloud I think getting the traditional vendors to evolve their tools into of all they're thinking it's much more difficult so I've got one more thing to add I actually think there's an opportunity to do security in entirely new ways ones that again can transform the industry so for example with virtualization you've got deep semantics into the workloads I mean you're in the hypervisor you can look inside the VMS you know who's using them know what applications they're using guy you could even know what the documents are being sent or or read or passed around and because you have this information at the edge if you virtualize the network as well you can pass this context into the network so now instead of like looking at packets and kind of trying to guess what application there is by looking at traffic you can actually get past like the ground truth information from the hypervisor so I think we have the potential so it's like drastically improved security that's Martine if you look at the networking industry there's lots of companies that have tried to change it in the past when you talk about innovation standards have a lot of times slow things down yep you know there's the legacy thought set you know great respect for ccie s but you know they have their install base in their way of doing things so you know there's there's so many pieces that make up networking and even the first time I saw your solution there's multiple standards and open you know groups working on this so you know how do you guys tease through and work through all of these issues yeah so clearly a very complex and multifarious question so I'm going to I'm going to attack one piece of it and we can go from there one of the primary benefits of actual virtualization like actual virtualization is that what you end up with should look like what you started with right so like if you're fundamentally changing an operational paradigm you're probably not doing virtualization so for example in a network virtualization solution the physical network is still a physical Network and it needs to be managed like a physical network with physical networking tools and in order to be fully virtualized the virtual abstraction I give you if I give you a virtual network that should also look like the networks that you've kind of grown to love as a child right they should have all the counters all the debugging the ability to interpose services right and so from from that standpoint you're still preserving the interfaces that people are used to it says there's more of them so like for example when I talk to a network operator today they're like oh this is confusing I've got virtualization I say actually instead of having one network that's really complicated you've got em and simple networks now you've got a very simple physical Network and if you got any virtual networks and they all all of the same interfaces that you use to manage it however there's one catch and that one catch is is there's an additional bit of information which is how do you map this virtual world to the physical world which happened in compute virtualization as well so like everybody understood a virtual machine everybody understood the physical machine but people weren't entirely sure how you debug the mapping between the two and that's incumbent as US is software providers and solution providers to provide that to provide the ability to to map from this kind of you know like platonic virtual reality down to this kind of gritty physical reality okay so from a standard standpoint you I mean you guys helped invent OpenFlow you guys created the open V switch you're heavily involved in OpenStack Andy there's been a lot of buzz since the acquisition about you know the involvement in OpenStack and yeah yeah kind of God how many people today everything in what's your thoughts on it yeah so let me also teach a tease apart you know two things before I get to that one so in networking standards are really important and like in the way standards work he's got a bunch of people that kind of go and talk about things and they design things they agree on them that's actually quite different than open source right and like their different processes different communities different rules of engagement so let me focus on the open source first then we'll go back to the standards thank you because I perfect just to give you a little bit foreshadowing like I hope the world goes open source not open Stan so can we do to it so but we'll get there right so as far as open source yes so I wrote the first version of open flow I mean it came out of my thesis right the first three employees of nicera created the first craft of open flow and it was it was just something that we wanted to use to control switches right i mean we wrote the first reference implementation the first open flow controller you know we seeded the stanford stuff of course i'm a consulting a faculty at stanford so i was involved there we also are the primary developers behind open V switch it's in the linux kernel you know we've probably put you know many millions of dollars in developing that it's used by competitors and partners alike that's used in many clouds and then we've heavily participated in an OpenStack in particular you know where the Delete on quantum which is the networking portion of OpenStack we've done a lot of development bear so as far as the merger is concerned the acquisitions concerned none of that will change we're fully committed to open V switch to OpenStack will continue and even escalate our contribution there quick quick note on OpenStack i was told that something for folks have actually entered some code into the OpenStack of storage just kind of curious about that so and we touched many areas of OpenStack and again the the networking piece touches everything and you know we do a lot of the development on quantum and we run actually nasira internally randa an openstack cloud for internal dev cloud and we've got thousands of VMs on it that we use it and so we're heavily we're like heavy users and contributors to both OpenStack and linux I mean if you look in Linux we've actually fixed a lot of the veal and issues in the kernel right so like and we're very very involved in open source but we're involved as users right like we don't sell you know linux we don't sell OpenStack but we do believe for to have a vibrant ecosystem is nice to have these tools out there and as we use the tools we fix them and we contribute it back okay what about multi hypervisor environments because that was one of the things that really impressed me about like the open D switch is it really doesn able kind of that that multi hypervisor even more than kind of heterogeneous switches it's the multi hypervisor piece yeah that's right so if you kind of zoom away like I think we've had like a fairly myopic focus in the industry on servers over the last 10 years and it's like if you zoom away from the server to a data center you end up in this realm of heterogeneous technologies multiple cloud management systems multiple hypervisors and so when we came up with our our initial strategy of building a network virtualization layer we knew networks touch everything we must support all of those technologies and so it was like a fundamental tenant of the technology that we might support all hypervisors and physical hardware switches as well because there are workloads that are not july's and so you know open V switch itself which is the V switch that we use it's in sports in kvm bare metal linux it's been ported to bsd it's been ported to other operating systems it's been ported to top-of-rack hardware switches so we can use all of them to do to do network virtualization so mark can I want to ask you about the sufferer define partnering strategy from a technical perspective obviously we're really big believers in open source as well they love that we'd love to think it's great and it's now a business model in the industry so it's great to see all that work as vmware now with you guys in the family there go to other unifying clouds so they took a multiple clouds at this point so you know what would you bring to the table from hyper Microsoft hyper-v environment and other big vendors HP Dell yeah Microsoft what can you bring to the table in working with those guys or are you outgoing are you talking to them and and if you were having those conversations what does what would those conversations be well so the product itself that we're developing and we we do bring to market now we will continue is a network virtualization platform that's multi hypervisor right and so the goal is to have something that you can deploy into any cloud environment regardless of what CMS are running and regardless of what of what hypervisors they're using now we have many many partners whether their system integrators with the solution partners and so you know we don't have any religion on on the type of technologies in play we want to provide the best virtual networking solution in the industry and that's really our primary our primary focus let me ask you about it Trent some trends in the in the tech community in in academia and the research areas obviously at this example just randomly low-level virtual machines that kind of those kinds of shifts are happening could you talk about just what you're tracking right now that your get your eye on in terms of what's going on at some of the top university obviously low-level virtual machines at the University of Illinois and in Chicago so what other areas can you share with us that you monitoring listen this is a great question to ask a nap academic and I'm going to totally disappoint you in that I you know I i I'm on a lot of pcs and I follow a lot of research I mean you know I submit papers you know all the time and like I've mostly lost faith in the academic process on the research side lately which i haven't relevant so in terms of trends no but that's exactly the point I think that there's enough vision to last for a century and like now it's time to do work and if it were up to me we would all be taking these ideas that we've come up with over the last 10 years there's very few new ones in my opinion and we'd be executing like crazy and so well again while i'm on the pcs and while i do review the papers i do submit the papers i think we should all focus on like changing infrastructure into software executing like hell and changing the world that way and so and I don't have a really bad attitude about this especially as abuse or but it's a bad attitude okay we say it we hit it all hang out so final question for me and if she wants to get one more in and don't you can't say the acquisition as the answer what is the biggest surprise that that that you fell out of your chair over the past 24 months around you in the industry in your entrepreneurial venture here now at VMware and it could be like a surprise and this trend didn't happen that happened that you know these are the things that happened it could be good or bad what's the biggest surprise that caught you off guard this year that's 24 months yeah it's a good question I think the one that actually been a little the most shocking is how how difficult is being just very honest is how difficult to manage perception in the industry and if you look at kind of social media and you look at a lot of the buzz in the rags so much of it is generated by non disinterested parties so invested parties and so I think it's possible to be a perfectly good citizen and then get paint in a very negative light or be a very negative citizen and be painted in a very good light and it's been counterintuitive to me how you manage this effectively like almost a dynamic feedback system so for example this year has been an enormous contributor to open source I think we've contributed more than anybody in our space by you know factor of 10 or more we contributed most of the core technologies and often people like well but it's a proprietary solution on the other hand there sometimes we're like okay this is a closer source product people like we should use this here because it's the open solution and so well I think that definitely felt on both sides you know being both open source and close or sometimes it's worked for us and for the wrong reasons sometimes it's not worked for us for the right reasons and so that dynamic has been the least intuitive to me so I'm not sure I fell off my chair but definitely it's been the most surprising yeah and you know and that's what we're trying to solve a SiliconANGLE as we say we're agile media and ultimately with social media the whole media business is changing so we know one of the things that we care about here so that's why we have the qubits we just this is raw data we want to share be provocative be edgy is too it's a data-driven world and we believe the media business is absolutely screwed up beyond all recognition so so because of just lack of fact-checking just old techniques aren't working and but it's the same game right so it's just so things circulate things get branded and we've seen a time and time again I've seen great people show up as like almost painted as criminals yeah so it's just a sad state of reporting and media so would agree with you there okay John so if I if I can have that one last question your machine you know the networking industries is a big community and when you talk about kind of the jobs that people are doing today what's your recommendation to folks out there in the networking industry what should what should they start to you know we'd or you know start playing with to kind of understand where things are going down the line honestly I don't want to say a cliche but I actually really believe this one I think I think networking networks are evolving to become proper systems and proper systems in an end-to-end manner meaning that goes a very well-defined hardware a software layer they all work together and I think the data center is is becoming a large computer and I think the most important thing is to view the industry and that lens meaning you know I would get as much information as I could on how guys like Google or Amazon or Facebook build their data centers and you realize that if you do a cross-section of these things like the Capital savings the operational savings the flexibility of the software like that's changing the world and if it's not changing the world directly by changing infrastructure it's changing the world to the surfaces they deliver and understanding that model in your bones I think is the beacon going forward so if it were me the first thing I do is I really understand why they make those decisions what the benefits are and I would use that to guide my learning going forward okay Martinez out of this co-founder of this year now at do you have a title at VMware yet or do you I mean did i do I don't know my head honcho of the Sierra am where Thanks coming inside the cube really preciate it we right back with our next guest we're going to wrap up try to wrap up the day as they start to bon jovi soundcheck here at V emerald 2012 this is SiliconANGLE calm and Wikibon doors continues coverage at vmworld great thank you