(upbeat music) >> From theCube Studios in Palo Alto in Boston, bringing you data driven insights from theCube and ETR. This is Breaking Analysis with Dave Vellante. >> While by no means a safe haven, the cybersecurity sector has outpaced the broader tech market by a meaningful margin, that is up until very recently. Cybersecurity remains the number one technology priority for the C-suite, but as we've previously reported the CISO's budget has constraints just like other technology investments. Recent trends show that economic headwinds have elongated sales cycles, pushed deals into future quarters, and just like other tech initiatives, are pacing cybersecurity investments and breaking them into smaller chunks. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis we explain how cybersecurity trends are reverting to the mean and tracking more closely with other technology investments. We'll make a couple of valuation comparisons to show the magnitude of the challenge and which cyber firms are feeling the heat, which aren't. There are some exceptions. We'll then show the latest survey data from ETR to quantify the contraction in spending momentum and close with a glimpse of the landscape of emerging cybersecurity companies, the private companies that could be ripe for acquisition, consolidation, or disruptive to the broader market. First, let's take a look at the recent patterns for cyber stocks relative to the broader tech market as a benchmark, as an indicator. Here's a year to date comparison of the bug ETF, which comprises a basket of cyber security names, and we compare that with the tech heavy NASDAQ composite. Notice that on April 13th of this year the cyber ETF was actually in positive territory while the NAS was down nearly 14%. Now by August 16th, the green turned red for cyber stocks but they still meaningfully outpaced the broader tech market by more than 950 basis points as of December 2nd that Delta had contracted. As you can see, the cyber ETF is now down nearly 25%, year to date, while the NASDAQ is down 27% and change. Now take a look at just how far a few of the high profile cybersecurity names have fallen. Here are six security firms that we've been tracking closely since before the pandemic. We've been, you know, tracking dozens but let's just take a look at this data and the subset. We show for comparison the S&P 500 and the NASDAQ, again, just for reference, they're both up since right before the pandemic. They're up relative to right before the pandemic, and then during the pandemic the S&P shot up more than 40%, relative to its pre pandemic level, around February is what we're using for the pre pandemic level, and the NASDAQ peaked at around 65% higher than that February level. They're now down 85% and 71% of their previous. So they're at 85% and 71% respectively from their pandemic highs. You compare that to these six companies, Splunk, which was and still is working through a transition is well below its pre pandemic market value and 44, it's 44% of its pre pandemic high as of last Friday. Palo Alto Networks is the most interesting here, in that it had been facing challenges prior to the pandemic related to a pivot to the Cloud which we reported on at the time. But as we said at that time we believe the company would sort out its Cloud transition, and its go to market challenges, and sales compensation issues, which it did as you can see. And its valuation jumped from 24 billion prior to Covid to 56 billion, and it's holding 93% of its peak value. Its revenue run rate is now over 6 billion with a healthy growth rate of 24% expected for the next quarter. Similarly, Fortinet has done relatively well holding 71% of its peak Covid value, with a healthy 34% revenue guide for the coming quarter. Now, Okta has been the biggest disappointment, a darling of the pandemic Okta's communication snafu, with what was actually a pretty benign hack combined with difficulty absorbing its 7 billion off zero acquisition, knocked the company off track. Its valuation has dropped by 35 billion since its peak during the pandemic, and that's after a nice beat and bounce back quarter just announced by Okta. Now, in our view Okta remains a viable long-term leader in identity. However, its recent fiscal 24 revenue guide was exceedingly conservative at around 16% growth. So either the company is sandbagging, or has such poor visibility that it wants to be like super cautious or maybe it's actually seeing a dramatic slowdown in its business momentum. After all, this is a company that not long ago was putting up 50% plus revenue growth rates. So it's one that bears close watching. CrowdStrike is another big name that we've been talking about on Breaking Analysis for quite some time. It like Okta has led the industry in a key ETR performance indicator that measures customer spending momentum. Just last week, CrowdStrike announced revenue increased more than 50% but new ARR was soft and the company guided conservatively. Not surprisingly, the stock got absolutely crushed as CrowdStrike blamed tepid demand from smaller and midsize firms. Many analysts believe that competition from Microsoft was one factor along with cautious spending amongst those midsize and smaller customers. Notably, large customers remain active. So we'll see if this is a longer term trend or an anomaly. Zscaler is another company in the space that we've reported having great customer spending momentum from the ETR data. But even though the company beat expectations for its recent quarter, like other companies its Outlook was conservative. So other than Palo Alto, and to a lesser extent Fortinet, these companies and others that we're not showing here are feeling the economic pinch and it shows in the compression of value. CrowdStrike, for example, had a 70 billion valuation at one point during the pandemic Zscaler top 50 billion, Okta 45 billion. Now, having said that Palo Alto Networks, Fortinet, CrowdStrike, and Zscaler are all still trading well above their pre pandemic levels that we tracked back in February of 2020. All right, let's go now back to ETR'S January survey and take a look at how much things have changed since the beginning of the year. Remember, this is obviously pre Ukraine, and pre all the concerns about the economic headwinds but here's an X Y graph that shows a net score, or spending momentum on the y-axis, and market presence on the x-axis. The red dotted line at 40% on the vertical indicates a highly elevated net score. Anything above that we think is, you know, super elevated. Now, we filtered the data here to show only those companies with more than 50 responses in the ETR survey. Still really crowded. Note that there were around 20 companies above that red 40% mark, which is a very, you know, high number. It's a, it's a crowded market, but lots of companies with, you know, positive momentum. Now let's jump ahead to the most recent October survey and take a look at what, what's happening. Same graphic plotting, spending momentum, and market presence, and look at the number of companies above that red line and how it's been squashed. It's really compressing, it's still a crowded market, it's still, you know, plenty of green, but the number of companies above 40% that, that key mark has gone from around 20 firms down to about five or six. And it speaks to that compression and IT spending, and of course the elongated sales cycles pushing deals out, taking them in smaller chunks. I can't tell you how many conversations with customers I had, at last week at Reinvent underscoring this exact same trend. The buyers are getting pressure from their CFOs to slow things down, do more with less and, and, and prioritize projects to those that absolutely are critical to driving revenue or cutting costs. And that's rippling through all sectors, including cyber. Now, let's do a bit more playing around with the ETR data and take a look at those companies with more than a hundred citations in the survey this quarter. So N, greater than or equal to a hundred. Now remember the followers of Breaking Analysis know that each quarter we take a look at those, what we call four star security firms. That is, those are the, that are in, that hit the top 10 for both spending momentum, net score, and the N, the mentions in the survey, the presence, the pervasiveness in the survey, and that's what we show here. The left most chart is sorted by spending momentum or net score, and the right hand chart by shared N, or the number of mentions in the survey, that pervasiveness metric. that solid red line denotes the cutoff point at the top 10. And you'll note we've actually cut it off at 11 to account for Auth 0, which is now part of Okta, and is going through a go to market transition, you know, with the company, they're kind of restructuring sales so they can take advantage of that. So starting on the left with spending momentum, again, net score, Microsoft leads all vendors, typical Microsoft, very prominent, although it hadn't always done so, it, for a while, CrowdStrike and Okta were, were taking the top spot, now it's Microsoft. CrowdStrike, still always near the top, but note that CyberArk and Cloudflare have cracked the top five in Okta, which as I just said was consistently at the top, has dropped well off its previous highs. You'll notice that Palo Alto Network Palo Alto Networks with a 38% net score, just below that magic 40% number, is healthy, especially as you look over to the right hand chart. Take a look at Palo Alto with an N of 395. It is the largest of the independent pure play security firms, and has a very healthy net score, although one caution is that net score has dropped considerably since the beginning of the year, which is the case for most of the top 10 names. The only exception is Fortinet, they're the only ones that saw an increase since January in spending momentum as ETR measures it. Now this brings us to the four star security firms, that is those that hit the top 10 in both net score on the left hand side and market presence on the right hand side. So it's Microsoft, Palo Alto, CrowdStrike, Okta, still there even not accounting for a Auth 0, just Okta on its own. If you put in Auth 0, it's, it's even stronger. Adding then in Fortinet and Zscaler. So Microsoft, Palo Alto, CrowdStrike, Okta, Fortinet, and Zscaler. And as we've mentioned since January, only Fortinet has shown an increase in net score since, since that time, again, since the January survey. Now again, this talks to the compression in spending. Now one of the big themes we hear constantly in cybersecurity is the market is overcrowded. Everybody talks about that, me included. The implication there, is there's a lot of room for consolidation and that consolidation can come in the form of M&A, or it can come in the form of people consolidating onto a single platform, and retiring some other vendors, and getting rid of duplicate vendors. We're hearing that as a big theme as well. Now, as we saw in the previous, previous chart, this is a very crowded market and we've seen lots of consolidation in 2022, in the form of M&A. Literally hundreds of M&A deals, with some of the largest companies going private. SailPoint, KnowBe4, Barracuda, Mandiant, Fedora, these are multi billion dollar acquisitions, or at least billion dollars and up, and many of them multi-billion, for these companies, and hundreds more acquisitions in the cyberspace, now less you think the pond is overfished, here's a chart from ETR of emerging tech companies in the cyber security industry. This data comes from ETR's Emerging Technologies Survey, ETS, which is this diamond in a rough that I found a couple quarters ago, and it's ripe with companies that are candidates for M&A. Many would've liked, many of these companies would've liked to, gotten to the public markets during the pandemic, but they, you know, couldn't get there. They weren't ready. So the graph, you know, similar to the previous one, but different, it shows net sentiment on the vertical axis and that's a measurement of, of, of intent to adopt against a mind share on the X axis, which measures, measures the awareness of the vendor in the community. So this is specifically a survey that ETR goes out and, and, and fields only to track those emerging tech companies that are private companies. Now, some of the standouts in Mindshare, are OneTrust, BeyondTrust, Tanium and Endpoint, Net Scope, which we've talked about in previous Breaking Analysis. 1Password, which has been acquisitive on its own. In identity, the managed security service provider, Arctic Wolf Network, a company we've also covered, we've had their CEO on. We've talked about MSSPs as a real trend, particularly in small and medium sized business, we'll come back to that, Sneek, you know, kind of high flyer in both app security and containers, and you can just see the number of companies in the space this huge and it just keeps growing. Now, just to make it a bit easier on the eyes we filtered the data on these companies with with those, and isolated on those with more than a hundred responses only within the survey. And that's what we show here. Some of the names that we just mentioned are a bit easier to see, but these are the ones that really stand out in ERT, ETS, survey of private companies, OneTrust, BeyondTrust, Taniam, Netscope, which is in Cloud, 1Password, Arctic Wolf, Sneek, BitSight, SecurityScorecard, HackerOne, Code42, and Exabeam, and Sim. All of these hit the ETS survey with more than a hundred responses by, by the IT practitioners. Okay, so these firms, you know, maybe they do some M&A on their own. We've seen that with Sneek, as I said, with 1Password has been inquisitive, as have others. Now these companies with the larger footprint, these private companies, will likely be candidate for both buying companies and eventually going public when the markets settle down a bit. So again, no shortage of players to affect consolidation, both buyers and sellers. Okay, so let's finish with some key questions that we're watching. CrowdStrike in particular on its earnings calls cited softness from smaller buyers. Is that because these smaller buyers have stopped adopting? If so, are they more at risk, or are they tactically moving toward the easy button, aka, Microsoft's good enough approach. What does that mean for the market if smaller company cohorts continue to soften? How about MSSPs? Will companies continue to outsource, or pause on on that, as well as try to free up, to try to free up some budget? Adam Celiski at Reinvent last week said, "If you want to save money the Cloud's the best place to do it." Is the cloud the best place to save money in cyber? Well, it would seem that way from the standpoint of controlling budgets with lots of, lots of optionality. You could dial up and dial down services, you know, or does the Cloud add another layer of complexity that has to be understood and managed by Devs, for example? Now, consolidation should favor the likes of Palo Alto and CrowdStrike, cause they're platform players, and some of the larger players as well, like Cisco, how about IBM and of course Microsoft. Will that happen? And how will economic uncertainty impact the risk equation, a particular concern is increase of tax on vulnerable sectors of the population, like the elderly. How will companies and governments protect them from scams? And finally, how many cybersecurity companies can actually remain independent in the slingshot economy? In so many ways the market is still strong, it's just that expectations got ahead of themselves, and now as earnings forecast come, come, come down and come down to earth, it's going to basically come down to who can execute, generate cash, and keep enough runway to get through the knothole. And the one certainty is nobody really knows how tight that knothole really is. All right, let's call it a wrap. Next week we dive deeper into Palo Alto Networks, and take a look at how and why that company has held up so well and what to expect at Ignite, Palo Alto's big user conference coming up later this month in Las Vegas. We'll be there with theCube. Okay, many thanks to Alex Myerson on production and manages the podcast, Ken Schiffman as well, as our newest edition to our Boston studio. Great to have you Ken. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Silicon Angle. He does some great editing for us. Thank you to all. Remember these episodes are all available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibond.com and siliconangle.com, or you can email me directly David.vellante@siliconangle.com or DM me @DVellante, or comment on our LinkedIn posts. Please do checkout etr.ai, they got the best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (upbeat music)

>> Narrator: From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hi, I'm Stuart Miniman and welcome to this CUBE Conversation. I'm in our Boston area studio and one of the things we always love to do is talk to startups and really find out they're usually on the leading edge of helping customers, new technologies, conquering challenges. And to that point, we have the co-founder and CEO of env0, that is, Ohad Maislish and we brought along with him he's got two of his investors, one of his advisors. So sitting next to Maish, we have Ed Sim, who's the founder and managing partner of Boldstart Ventures and sitting next to him is Guy Podjarny, who is the founder of Snyk. So now, you know is the acronym for Snyk and if you didn't know that, I know I'd heard about the company a couple years before that and my understanding is, Guy your the ones that connected Ohad with Ed who was the first investor. So Guy let's talk to Ohad in a second, but how the conversation started? And what what piqued your interest about what is now env0? >> Yeah, I think it started with people. I mean, I think fundamentally when you think about technology and think about startups, it needs to be an interesting market, it needs to be a good idea, but it really, first and foremost is about the people. So I've I've known Ohad from actually some work that he's done at Snyk earlier on, and was really impressed with his sharpness, his technical chops, and a lot of times the bias for feedback. And then when he presented the idea to me around kind of making Infrastructure as Code easy, and I don't want to sort of steal his thunder, talking about it and about kind of engaging with developers for it, a thought that literally resonated with me, I think, we'll probably dig into it some more. But in we live in a world in which more and more activities, more and more decisions, and really more effort is rolled on to developers. So, there's a constant need for great solutions that make on one hand make it easy for developers to embrace these solutions, on the other hand, still kind of allow the right kind of governance and controls. And I felt like Infrastructure as Code was like a great space for that, where we asked developers to do more, there's a ton of value in developers doing more around controlling these Infrastructure decisions, but it's just too hard today. So, anyways, I kind of liked the skills, I liked the idea. And I pulled in Ed, who I felt was kind of natural to kind of help introduce these experiences with other startups that share a similar philosophy to kind of help make this happen. >> Awesome, thank you Guys. So Ohad, let's let's throw it to you. Give us a little bit about your background, your team, Infrastructure as Code is not a new term. So I guess would love you to kind of weave into it. You know why now? Is it becoming more real in why your solution is positioned to help the enterprise? >> Awesome, first of all, thank you for having me. It's really exciting and again thank you for the opportunity. Regarding your question, so my background is technical. I was maybe still am a geek started University at a young age at the age of 14 in Palo Alto High School. And started my career in non technical roles very early. I have now like 21 years of experience, this is my second startup and third company, as I mentioned, my previous company is services company, provided services for Snyk and we became friends and later on partners, investors, and so on. And, we we've seen huge shift, we call the Infrastructure as Code the third data center revolution. We look at the first one being virtualization about 20 years ago led by VMware and then ZenSourcer. The second obviously, is the public cloud when companies started clicking buttons in order to get those compute resources but now nobody is clicking those buttons anymore. And instead writing, maintaining and executing that code, that Infrastructure as Code and as the Guy mentioned, it made it much more relevant for developers to influence the Infrastructure decisions and not just the app decisions. With that many challenges and opportunities around Infrastructure as Code management and automation, and that's where we focus. >> All right, so Ed I'm sure like me, you've seen a number of companies, try to climb this mountain and fall down and crash so I feel like five years ago, I would talk to a company and they say, oh, we're going to help, really help the enterprise enable developers for networking for storage, for security or anything like that. And it was like, oh, okay, good luck with that. And they just kind of crashed and burned or got acquired or did something like that. So, I feel like from our viewpoint we've seen for a long time that growth of developers and how important that is, but that gap between the enterprise and the developers feels like we're getting there. So, it gets similar what I asked Ohad why now, why this group, why the investment from you? >> Yeah, so I'll echo Guy's comment about the people. So, first and foremost, I was fortunate enough to invest in Guy back in his prior company before he started Snyk and then invested in Snyk. And there are lots of elements of env0 that remind me of Snyk the idea, for example, that developers are doing more, and that security is no longer a separate piece of developing, it's now embedded kind of in what developers and teams are doing. And I felt like the opportunity was still there for Infrastructure as Code. How do you make developers more productive, but provide that control plan or governance that's centralized so that environments can easily be reproduced. And the thing that got me so excited, was the idea that Ohad was going to tie kind of cloud costs from a proactive basis versus a reactive basis. Meaning that once we know that your environments are up and running, you could actually automatically tag it and tie the environment to the actual application. And to me, tying the business piece to the development piece was a huge, huge opportunity that hasn't been tapped yet. And so there are lots of elements of both Snyk and env0 and we're super excited to be invested in both. >> Alright, so Ohad maybe just step back for a second, give us some of the speeds and feeds we read your blog post 3.3 million dollars of the early investment, how many people you have, what is the stage of the product customer acquisition and the like? >> Sure, so we just launched our public beta and announced the funding couple of months ago led by Boldstart and another VC in Israel named Grove, and then angel investors Guy is the greatest investor among those and so we have some others as well. And now we have like 10 employees nine in Israel, one in New York City, I'm relocating after this all pandemic thing will get better. I'm moving to the Bay Area as soon as possible. That's more or less the status. And as I've mentioned, we just launched our public beta. So we have our first few design partners and early like private beta customers now starting to grow more. >> Yeah, and how would you characterize, what is the relationship between what you're doing in the public clouds. We understand, in the early days, it was like, Oh, well, cloud is going to be easy, it's going to just be enable it, it has been a wonderful tool set for developers. But simple is definitely not, I think anyone would describe the current state of environments. So, help it help us give it a little bit of what you're seeing there. And how you deal with like some very large players in ecosystem. >> Our customers are the same as the cloud vendors customers. The cloud vendors provide great value with the technical aspect with Infrastructure. But once you want to manage your organization, you want to empower your developers, you want to shift left some decisions, APM, did shift left for a performance, Snyk is doing great shift left for security. I believe that we are doing similar things to the cost. And you in the cloud vendors are in charge of you being able to do some technical orchestration. But when do you need to tear down those resources? When do you understand that there is a problematic resource or environment and what exactly made it? What is the association, how you can prevent from (mumbles) deployments from even happening at first. So all of those management information and insight ties back to your business logic and processes that's where we fit. >> I think there's actually a lot of analogy if I can chime in, on maybe an ownership aspect that happens in cloud. So we talk about the cloud and oftentimes cloud is interpreted as the technical aspect of it. So the fact that it allows you to do a bunch of things in the clouds and sort of renting someone else's hardware, and then automating a lot of it. But what cloud also does and that definitely represents what we're doing security and I think applies here, is that it moves a lot of things that used to be IT responsibility being a part of the application. So a lot of decisions, including ones really security, and including ones related cost around anywhere from provisioning of servers to, network access, to when you burst out, and to the balancing of business value to the cost involved or the risk involved. Those are no longer done by a central IT organizations, but rather, they're being done by developers day in and day out. And so I think that's really where the analogy really works with cloud is, it's not so much, like clearly there's an aspect of that that is the the technical piece of tracking how much does it cost in the on demand surrounding of cloud, but there's a lot of the ownership change, or the fact that the decisions that impact that are done by developers, and they're not yet well equipped to have the insights, to have the tools, to make the right decisions with a press of button. >> Thank you Guy and absolutely, 'cause cloud is just one of the platforms you're living on, you know well from Snyk that integration between what's happening in the platform, where open source fits into it, the various parts of the organization that are there. So, you've got some good background, I'm sure, helps you're an advisor to Ohad there to helps pull through a little bit of some of those challenges. Yeah, I mean, Ed I'd love to hear just in general your viewpoint on how startups are doing at monetizing things in the era of... You've got the massive players like Amazon and Microsoft out there. >> Look, the enterprise pain is higher than ever right now, every fortune 500 is a tech company right now and they need engineers, and they're hiring engineers. In fact, many of the largest fortune 500 have more engineers than some of the tech companies. And developer productivity is number one, front and center. And if you talk to CIOs, we just hosted a panel with the CIO of Guardian Life and the CTO of Priceline. They're all looking at how do I kind of automate my tool chain? How do I get things done faster? How do I do things more scalable? And then how do I coordinate processes amongst teams. As Guy hit upon and Ohad as well, not just security, there's product design being embedded with developers as product management being embedded with developers. There's finance now, FinOps. If you're going to spend more and more in the cloud, how do you actually control that proactively before things happen versus after or months after that happens? So I think this is going to be a huge, huge opportunity on the FinOps side. And, the final thing I would say is that winning the hearts and minds of developers to win the enterprise is a tried and trued model, and I think it's going to be even more important as we move forward in the next few years, to be honest with you. >> All right, so Ohad you know I think Ed talked about those hearts and minds of developers absolutely critical. When you look at the tooling landscape out there, the challenge of course, is there's so many tools out there, that there's platform battles, there's developers that find certain things that they love, and then there's, oh, wait, can I have a general purpose solution that can help. You talk about this being the third wave, how does this kind of tie into or potentially replace some of the last generation of automation tools. How do you see yourself getting into the accounts and growing your developer base? >> I think, I have a very simple answer, because, now enterprises have two options. Either they go with productivity self-service, or they go with governance, but they cannot have both. So if it's the smaller or they have less risks, so they go with the productivity and they take those risks, take the extra costs, take that potential damage that can happen. But more we see the case of I cannot allow myself this mess, so I have to block this velocity. I have to block those developers, they cannot just orchestrate cloud resources as they wish they have to open tickets, they have to go through some manual process of approval or we see more and more developers that understand there is a challenge they built in-house env0 of self-service combined with governance solution, and they always struggle doing it well, because it's not their core business. So once you see the opportunity of a more and more customers doing a lot of investment in in-house solution that do the same thing, probably a good idea to do it, as a separate product. And also the fact that we have the visibility of different customers, we can be very early but for later on adds pattern recognition, and notice what makes sense, what is problematic and give those insights and more business logic back to the customers which is impossible for them to do if they're only isolated on their cases. So as providing the same great solution to different companies, allowing them self-service combined with governance, and then additionally, add those and Smart Insights later on. >> Yeah, I think what I love about what he said is that I don't think he even sort of said finance or cost at any time of those. So really, like you said, governance and I think you can swap governance or you can swap the kind of the entity that's doing the governance for security for all of those. And that sounds awfully familiar for Snyk, which really kind of begs the answer to be the same, it's the reason that env0 approach is promising and that it would win against competition is that it tends to be that the competition or the people that are around are focused on the governance piece, they're they're focused on just sort of the entity that is the controlling entity. I like to say that it's actually not about shift left, it's about if you want to choose a direction, it's going to be the sort of the top to bottom. So it's more about, like this governance entities, whether security or finance, they need to shift from a controlling mindset that is top down that is like this dictatorship of sort of telling you what you should and shouldn't do to more of a bottom up element and allowing the teams the people in the trenches people actually make decisions to make correct decisions, and in this case, correct decisions from a financial perspective. And then alongside that, the governing entity, they need to switch to being a supportive entity an enabling entity and I think that transition will happen across many aspects of sort of software development and definitely anything that requires that type of governance from from outside of the development process today that is to change. >> Yeah, to chime in and add to Guys point, development is so important, it touches every aspect of an organization. So I always think about it as almost a collaborative workflow layer versus being reliant on kind of one control entity. Great developers always want to move fast. But, how do you kind of build that collaborative workflow and I think that Ohad in env0 is providing that for the environment and finance. Guys doing it for security. And there's lots of other opportunities out there, like privacy as well. And I wouldn't be surprised if finance folks start getting embedded with development at some point just like security is, or design is, product management is as well, because that is probably one of the highest costs around right now for many companies, and they're all trying to figure out how to stop the bleeding much earlier. >> Yeah, it's been lots of discussion, of course, we kind of go beyond DevOps, I think FinOps is in there. Ohad you have a favorite term that you've had from your advisors yet, how you categorize what you're doing. Any final words on kind of that organizational dynamic which we know so often it's the technology can be the easy part, it's getting everybody in the org, pulling in the same direction. >> Yeah, I think I'm looking at maybe a physical metaphor, or just an example, if you just enter a developer's room, you might see a screen TV there with some APM Datadog, New Relic Metrics, developers care about performance. They know very early if they did something wrong. And now they see more and more in those dashboards, in the developers rooms, things like Snyk to make sure you're not putting any bad open source package, which has security or ability. What we believe is that now they don't have the right tools, the right product that they can be part of the responsibility, of course, and that's like somebody else's problem. In other rooms, you have those TVs, those screens that show what is the cost, and maybe only later on in the waterfall kind of way you try to isolate and root cause analysis on what went wrong, but there is no good reason why those graphs of the past should be in the same rooms next to the APM and the Snyks and to prevent those as early as possible, maybe to change the discussion and build more trust between the developers that now seem not to care about the cost because they used not to care like 10 years ago when we used to have is called Apex-Cloud. The VMware or even EC2 Instances with the predicted pricing, that's all school. Now you have auto scaling Kubernetes, you have Lambda those kind of things you pay per usage. So the possibility for engineers to know how much their code is about to cost to the organization is very challenging now. If we tie from the developer up to, the financial operations, we will provide better service, and just better business value for our customer. >> Awesome, so final question I have for you, and Ohad I'm going to have you go last on this one is you kind of painted the picture of where things are going to go. So give us what success look like, Ed, start with you, give us out 12 to 24 months as to env0 in this wave as what should we be looking for? >> Success to me would be that every large enterprise has this on their budget line item as a must have. And the market is still early and evolving right now, but I have no doubt in my mind, it's going to happen. And as you hear about many large enterprises saying that we were in the second inning of cloud migration now we're in the fourth. That is what success will be and I know it's going to happen faster than we all thought. >> I'll take the developer angle to it, I think success is really when developers are delighted, or sort of they feel they're building better software by using env0 and by factoring this aspect of quality into their daily activities. And I think a lot of that comes down to ease of use. Like, I kind of encourage folks to sort of try out the env0 and see the cost calculation, it's all about making it easy. So what excites me is really around that type of success where it's so easy that it's embedded into their sort of daily activities, and that they're happy it's not a forced thing. It's something they've accepted and like having as part of their software development process. >> I fully agree with both Ed in Guy, but I want to add on on a personal note, that one of the reasons we started env0 is because we saw developers quitting jobs at some places. And the reason for that was that they didn't give them self-service, they didn't empower those developers, they were blocked by DevOps, they needed to open tickets, to do trivial things. And this frustration is just a bigger motivation for us to solve. So we want to reduce this frustration. We want developers to be happy and productive, and do what they need to do, and not getting blocked by others. So that's, I think, another way to look at it, to make sure that those developers are really making good use out of their time and going back home at the end of the day, and feeling that they did what they were paid for, not for waiting for others to locate some cloud resources for them. >> All right, well, Ohad want to wish you the best, absolutely. Some of the early things that we've seen sometimes they're the tools that help, we've been talking gosh I remember 15, 20 years about breaking down the silos between various parts of the organization, some of the tools give you different viewpoints into what you're doing, help have some of the connection and hopefully some empathy as to what the various pieces are there. You really highlighted there's nothing worse than I'm not being appreciated for the work I'm doing, or they don't understand the challenges that I'm going through. So, congratulations on env0. We look forward to following going forward and definitely hope being part your customers in the future. Thanks so much. >> Thank you, thank you very much. >> All right, and Guy really appreciate your perspectives on this thank you for joining us. >> Thanks for having them. >> All right, be sure to check out theCUBE.net where you can find all of the events we're doing online these days, of course, where there's a huge back catalog of what we have in the thousands of interviews that we've done. I'm Stuart Miniman, and thank you for watching theCUBE. (upbeat music)

>> Welcome everyone. Thank you for coming to the Intel AI lounge and joining us here for this economist world event. My name is Jack. I'm the chief architect of our autonomist driving solutions at Intel and I'm very happy to be here and to be joined by an esteemed panel of colleagues who are joining to, I hope, engage you all in a frayed dialogue and discussion. There will be time for questions as well, so keep your questions in mind. Jot them down so you ask them to us later. So first, let me introduce the panel. Next to me we have Michelle, who's the co-founder and CEO of Fine Mind. She just did an interview here shortly. Fine Mind is a company that provides a technology platform for retailers and brands that uses artificial intelligence as the heart of the experiences that her company's technology provides. Joe from Intel is the head of partnerships and acquisitions for artificial intelligence and software technologies. He participated in the recent acquisition of Movidius, a computer vision company that Intel recently acquired and is involved in a lot of smart city activities as well. And then finally, Sarush, who is data scientist by training, but now has JDA labs, which is researching emerging technologies and their application in the supply chain worldwide. So at the end of the day, the internet things that artificial intelligence really promises to improve our lives in quite incredible ways and change the way that we live and work. Often times the first thing that we think about when we think about AI is Skynet, but we at Intel believe in AI for good and that there's a lot of things that can happen to improve the way people live, work, and enjoy life. So as things in the Internet, as things become connected, smart, and automated, artificial intelligence is really going to be at the heart of those new experiences. So as I said my role is the architect for autonomous driving. It's a common place when people think about artificial intelligence, because what we're trying to do is replace a human brain with a machine brain, which means we need to endow that machine with intelligent thoughts, contexts, experiences. All of these things that sort of make us human. So computer vision is the space, obviously, with cameras in your car that people often think about, but it's actually more complicated than that. How many of us have been in a situation on a two lane road, maybe there's a car coming towards us, there's a road off to the right, and you sort of sense, "You know what? That car might turn in front of me." There's no signal. There's no real physical cue, but just something about what that driver's doing where they're looking tells us. So what do we do? We take our foot off the accelerator. We maybe hover it over the brake, just in case, right? But that's intelligence that we take for granted through years and years and years of driving experience that tells us something interesting is happening there. And so that's the challenge that we face in terms of how to bring that level of human intelligence into machines to make our lives better and richer. So enough about automated vehicles though, let's talk to our panelists about some of the areas in which they have expertise. So first for Michelle, I'll ask... Many of us probably buy stuff online everyday, every week, every hour, hourly delivery now. So a lot has been written about the death of traditional retail experiences. How will artificial intelligence and the technology that your company has rejuvenate that retail experience, whether it be online or in the traditional brick and mortar store? >> Yeah, excuse me. So one of the things that I think is a common misconception. You hear about the death of the brick and mortar store, the growth of e-commerce. It's really that e-commerce is beating brick and mortar in growth only and there's still over 90% of the world's commerce is done in physical brick and mortar store. So e-commerce, while it has the growth, has a really long way to go and I think one of the things that's going to be really hard to replace is the very human element of interaction and connection that you get by going to a store. So just because a robot named Pepper comes up to you and asks you some questions, they might get you the answer you need faster and maybe more efficiently, but I think as humans we crave interaction and shopping for certain products especially, is an experience better enjoyed in person with other people, whether that's an associate in the store or people you come with to the store to enjoy that experience with you. So I think artificial intelligence can help it be a more frictionless experience, whether you're in store or online to get you from point A to buying the thing you need faster, but I don't think that it's going to ever completely replace the joy that we get by physically going out into the world and interacting with other people to buy products. >> You said something really profound. You said that the real revolution for artificial intelligence in retail will be invisible. What did you mean by that? >> Yeah, so right now I think that most of the artificial intelligence that's being applied in the retail space is actually not something that shoppers like you and I see when we're on a website or when we're in the store. It's actually happening behind the scenes. It's happening to dynamically change the webpage to show you different stuff. It's happening further up the supply chain, right? With how the products are getting manufactured, put together, packaged, shipped, delivered to you, and that efficiency is just helping retailers be smarter and more effective with their budgets. And so, as they can save money in the supply chain, as they can sell more product with less work, they can reinvest in experience, they can reinvest in the brand, they can reinvest in the quality of the products, so we might start noticing those things change, but you won't actually know that that has anything to do with artificial intelligence, because not always in a robot that's rolling up to you in an aisle. >> So you mentioned the supply chain. That's something that we hear about a lot, but frankly for most of us, I think it's very hard to understand what exactly that means, so could you educate us a bit on what exactly is the supply chain and how is artificial intelligence being implied to improve it? >> Sure, sure. So for a lot of us, supply chain is the term that we picked up when we went to school or we read about it every so often, but we're not that far away from it. It is in fact a key part of what Michelle calls the invisible part of one's experience. So when you go to a store and you're buying a pair of shoes or you're picking up a box of cereal, how often do we think about, "How did it ever make it's way here?" We're the constituent components. They probably came from multiple countries and so they had to be manufactured. They had to be assembled in these plants. They had to then be moved, either through an ocean vessel or through trucks. They probably have gone through multiple warehouses and distribution centers and then finally into the store. And what do we see? We want to make sure that when I go to pick up my favorite brand of cereal, it better be there. And so, one of the things where AI is going to help and we're doing a lot of active work in this, is in the notion of the self learning supply chain. And what that means is really bringing in these various assets and actors of the supply chain. First of all, through IOT and others, generating the data, obviously connecting them, and through AI driving the intelligence, so that I can dynamically figure out the fact that the ocean vessel that left China on it's way to Long Beach has been delayed by 24 hours. What does that mean when you go to a Foot Locker to buy your new pair of shoes? Can I come up with alternate sourcing decisions, so it's not just predicting. It's prescribing and recommending as well. So behind the scenes, bringing in a lot of the, generating a lot of the data, connecting a lot of these actors and then really deriving the smarts. That's what the self learning supply chain is all about. >> Are supply chains always international or can they be local as well? >> Definitely local as well. I think what we've seen over the last decades, it's kind of gotten more and more global, but a lot of the supply chain can really just be within the store as well. You'd be surprised at how often retailers do not know where their product is. Even is it in the front of the store? Is it in the back of the store? Is it in the fitting room? Even that local information is not really available. So to have sensors to discover where things are and to really provide that efficiency, which right now doesn't exist, is a key part of what we're doing. >> So Joe, as you look at companies out there to partner or potentially acquire, do you tend to see technologies that are very domain specific for retail or supply chain or do you see technologies that could bridge multiple different domains in terms of the experiences we could enjoy? >> Yeah, definitely. So both. A lot of infant technologies start out in very niched use cases, but then there are technologies that are pervasive across multiple geographies and multiple markets. So, smart cities is a good way to look at that. So let's level set really quick on smart cities and how we think about that. I have a little sheet here to help me. Alright, so, if anybody here played Sim City before, you have your little city that's a real world that sits here, okay? So this is reality and you have little buildings and cars and they all travel around and you have people walking around with cell phones. And what's happening is as we develop smart cities, we're putting sensors everywhere. We're putting them around utilities, energies, water. They're in our phones. We have cameras and we have audio sensors in our phones. We're placing these on light poles, which is existing sustaining power points around the city. So we have all these different sensors and they're not just cameras and microphones, but they're particulate sensors. They're able to do environmental monitoring and things like that. And so, what we have is we have this physical world with all these sensors here. And then what we have is we've created basically this virtual world that has a great memory because it has all the data from all the sensors and those sensors really act as ties, if you think of it like a quilt, trying a quilt together. You bring it down together and everywhere you have a stitch, you're stitching that virtual world on top of the physical world and that just enables incredible amounts of innovation and creation for developers, for entrepreneurs, to do whatever they want to do to create and solve specific problems. So what really makes that possible is communications, connectivity. So that's where 5G comes in. So with 5G it's not just a faster form of connectivity. It's new infrastructure. It's new communication. It includes multiple types of communication and connectivity. And what it allows it to do is all those little sensors can talk to each other again. So the camera on the light pole can talk to the vehicle driving by or the sensor on the light pole. And so you start to connect everything and that's really where artificial intelligence can now come in and sense what's going on. It can then reason, which is neat, to have computer or some sort of algorithm that actually reasons based on a situation that's happening real time. And it acts on that, but then you can iterate on that or you can adapt that in the future. So if we think of an actual use case, we'll think of a camera on a light post that observes an accident. Well it's programmed to automatically notify emergency services that there's been an accident. But it knows the difference between a fender bender and an actual major crash where we need to send an ambulance or maybe multiple firetrucks. And then you can create iterations and that learns to become more smart. Let's say there was a vehicle that was in the accident that had a little yellow placard on it that said hazard. You're going to want to send different types of emergency services out there. So you can iterate on what it actually does and that's a fantastic world to be in and that's where I see AI really playing. >> That's a great example of what it's all about in terms of making things smart, connective, and autonomous. So Michelle as somebody who has founded the company and the space with technology that's trying to bring some of these experiences to market, there may be folks in the audience who have aspirations to do the same. So what have you learned over the course of starting your company and developing the technology that you're now deploying to market? >> Yeah, I think because AI is such a buzz word. You can get a dot AI domain now, doesn't mean that you should use it for everything. Maybe 7, 10, 15 years ago... These trends have happened before. In the late 90s, it was technology and there was technology companies and they sat over here and there was everybody else. Well that not true anymore. Every company uses technology. Then fast forward a little bit, there was social media was a thing. Social media was these companies over here and then there was everybody else and now every company needs to use social media or actually maybe not. Maybe it's a really bad idea for you to spend a ton of money on social media and you have to make that choice for yourself. So the same thing is true with artificial intelligence and what I tell... I did a panel on AI for Adventure Capitalists last week, trying to help them figure out when to invest and how to evaluate and all that kind of stuff. And what I would tell other aspiring entrepreneurs is "AI is means to an end. "It's not an end in itself." So unless you're a PH.D in machine learning and you want to start an AI as a service business, you're probably not going to start an AI only company. You're going to start a company for a specific purpose, to solve a problem, and you're going to use AI as a means to an end, maybe, if it makes sense to get there, to make it more efficient and all that stuff. But if you wouldn't get up everyday for ten years to do this business that's going to solve whatever problem you're solving or if you wouldn't invest in it if AI didn't exist, then adding dot AI at the end of a domain is not going to work. So don't think that that will help you make a better business. >> That's great advice. Thank you. Surash, as you talked about the automation then of the supply chain, what about people? What about the workers whose jobs may be lost or displaced because of the introduction of this automation? What's your perspective on that? >> Well, that's a great question. It's one that I'm asked quite a bit. So if you think about the supply chain with a lot of the manufacturing plants, with a lot of the distribution centers, a lot of the transportation, not only are we talking about driverless cars as in cars that you and I own, but we're talking about driverless delivery vehicles. We're talking about drones and all of these on the surface appears like it's going to displace human beings. What humans used to do, now machines will do and potentially do better. So what are the implications around human beings. So I'm asked that question quite a bit, especially from our customers and my general perception on this is that I'm actually cautiously optimistic that human beings will continue to do things that are strategic. Human beings will continue to do things that are creative and human being will probably continue to do things that are truly catastrophic, that machines simply have not been able to learn because it doesn't happen very often. One thing that comes to mind is when ATM machines came about several years ago before my time, that displaced a lot of teller jobs in the banking industry, but the banking industry did not go belly up. They found other things to do. If anything, they offered more services. They were more branches that were closed and if I were to ask any of you now if you would go back and not have 24/7 access to cash, you would probably laugh at me. So the thing is, this is AI for good. I think these things might have temporary impact in terms of what it will do to labor and to human beings but I think we as human beings will find bigger, better, different things to do and that's just in the nature of the human journey. >> Yeah, there's definitely a social acceptance angle to this technology, right? Many of us technologists in the room, it's easier for us to understand what the technology is, how it works, how it was created, but for many of our friends and family, they don't. So there's a social acceptance angle to this. So Michelle as you see this technology deployed in retail environments, which is a space where almost every person in every country goes, how do you think about making it feel comfortable for people to interact with this kind of technology and not be afraid of the robots or the machines behind the curtain. >> Yeah, that's a great question. I think that user experience always has to come first, so if you're using AI for AI's sake or for the cool factor, the wow factor, you're already doing it wrong. Again, it needs to solve a problem and what I tend to tell people who are like, "Oh my God. AI sounds so scary. "We can't let this happen." I'm like, "It's already happening "and you're already liking it. "You just don't know "because it's invisible in a lot of ways." So if you can point of those scenarios where AI has already benefited you and it wasn't scary because it was a friendly kind of interaction, you might not even have realized it was there versus something that looks so different and... Like panic driving. I think that's why the driverless car thing is a big deal because you're so used to seeing, in America at least, someone on the left side of the car in the front seat. And not seeing that is like, woah, crazy. So I think that it starts with the experience and making it an acceptable kind of interface or format that doesn't give you that, "Oh my God. Something is wrong here," kind of feeling. >> Yeah, that's a great answer. In fact, it reminds me there was this really amazing study by a Professor Nicholas Eppily that was published in the journal of social psychology and the name of this study was called A Mind In A Machine. And what he did was he took subjects and had a fully functional automated vehicle and then a second identical fully functional automated vehicle, but this one had a name and it had a voice and it had sort of a personality. So it had human anthropomorphics characteristics. And he took people through these two different scenarios and in both scenarios he's evil and introduced a crash in the scenario where it was unavoidable. There was nothing going to happen. You were going to get into an accident in these cars. And then afterwards, he pulled the subjects and said, "Well, what did you feel about that accident? "First, what did you feel about the car?" They were more comfortable in the one that had anthropomorphic features. They felt it was safer and they'd be more willing to get into it, which is not terribly surprising, but the kicker was the accident. In the vehicle that had a voice and a name, they actually didn't blame the self-driving car they were in. They blamed the other car. But in the car that didn't have anthropomorphic features, they blamed the machine. They said there's something wrong with that car. So it's one of my favorite studies because I think it does illustrate that we have to remember the human element to these experiences and as artificial intelligence begins to replace humans, or some of us even, we need to remember that we are still social beings and how we interact with other things, whether they be human or non-human, is important. So, Joe, you talk about evaluating companies. Michelle started a company. She's gotten funding. As you go out and look at new companies that are starting up, there's just so much activity, companies that just add dot AI to the name as Michelle said, how do you cut through the noise and try to get to the heart of is there any value in a technology that a company's bringing or not? >> Definitely. Well, each company has it's unique, special sauce, right? And so, just to reiterate what Michelle was talking about, we look for companies that are really good at doing what they do best, whatever that may be, whatever that problem that they're solving that a customer's willing to pay for, we want to make sure that that company's doing that. No one wants a company that just has AI in the name. So we look for that number one and the other thing we do is once we establish that we have a need or we're looking at a company based on either talent or intellectual property, we'll go in and we'll have to do a vetting process and it takes a whole. It's a very long process and there's legal involved but at the end of the day, the most important thing for the start up to remember is to continue doing what they do best and continue to build upon their special sauce and make sure that it's very valuable to their customer. And if someone else wants to look at them for acquisition so be it, but you need to be meniacally focused on your own customer. That's my two cents. >> I'm thinking again about this concept of embedding human intelligence, but humans have biases right? And sometimes those biases aren't always good. So how do we as technologists in this industry try to create AI for good and not unintentionally put some of our own human biases into models that we train about what's socially acceptable or not? Anyone have any thoughts on that? >> I actually think that the hype about AI taking over and destroying humanity, it's possible and I don't want to disagree with Steven Hawking as he's way smarter than I am. But he kind of recognizes it could go both ways and so right now, we're in a world where we're still feeding the machine. And so, there's a bunch of different issues that came up with humans feeding the machine with their foibles of racism and hatred and bias and humans experience shame which causes them to lash out and what to put somebody else down. And so we saw that with Tay, the Microsoft chatbot. We saw that with even Google's fake news. They're like picking sources now to answer the question in the top box that might be the wrong source. Ads that Google serves often show men high paying jobs, $200,000 a year jobs, and women don't get those same ones. So if you trace that back, it's always coming back to the inputs and the lens that humans are coming at it from. So I actually think that we could be in a way better place after this singularity happens and the machines are smarter than us and they take over and they become our overlords. Because when we think about the future, it's a very common tendency for humans to fill in the blanks of what you don't know in the future with what's true today. And I was talking to you guys at lunch. We were talking about this harbored psychology professor who wrote a book and in the book he was talking about how 1950s, they were imagining the future and all these scifi stories and they have flying cars and hovercrafts and they're living in space, but the woman still stays at home and everyone's white. So they forgot to extrapolate the social things to paint the picture in, but I think when we're extrapolating into the future where the computers are our overlords, we're painting them with our current reality, which is where humans are kind of terrible (laughs). And maybe computers won't be and they'll actually create this Utopia for us. So it could be positive. >> That's a very positive view. >> Thanks. >> That's great. So do we have this all figured out? Are there any big challenges that remain in our industries? >> I want to add a little bit more to the learning because I'm a data scientist by training and a lot of times, I run into folks who think that everything's been figured out. Everything is done. This is so cool. We're good to go and one of the things that I share with them is something that I'm sure everyone here can relate to. So if a kindergartner goes to school and starts to spell profanity, that's not because the kid knows anything good or bad. That is what the kid has learned at home. Likewise, if we don't train machines well, it's training will in fact be biased to your point. So one of the things that we have to kep in mind when we talk about this is we have to be careful as well because we're the ones doing the training. It doesn't automatically know what is good or bad unless that set of data is also fed to it. So I just wanted to kind of add to your... >> Good. Thank you. So why don't we open it up a little bit for questions. Any questions in the audience for our panelists? There's one there looks like (laughs). Emily, we'll get to you soon. >> I had a question for Sarush based on what you just said about us training or you all training these models and teaching them things. So when you deploy these models to the public with them being machine learning and AI based, is it possible for us to retrain them and how do you build in redundancies for the public like throwing off your model and things like that? What are some of the considerations that go into that? >> Well, one thing for sure is training is continuous. So no system should be trained once, deployed, and then forgotten. So that is something that we as AI professionals need to absolutely, because... Trends change as well. What was optimal two years ago is no longer optimal. So that part needs to continue to happen and we're the where the whole IOT space is so important is it will continue to generate relevant consumable data that these machines can continuously learn. >> So how do you decide what data though, is good or bad, as you retrain and evolve that data over time? As a data scientist, how do you do selection on data? >> So, and I want to piggyback on what Michelle said because she's spot on. What is the problem that you're trying to solve? It always starts from there because we have folks who come in to CIOs, "Oh look. "When big data was hot, we started to collect "a lot of the data, but nothing has happened." But data by itself doesn't automatically do magic for you, so we ask, "What kind of problem are you trying to solve? "Are you trying to figure out "what kinds of products to sell? "Are you trying to figure out "the optimal assortment mix for you? "Are you trying to find the shortest path "in order to get to your stores?" And then the question is, "Do you now have the right data "to solve that problem?" A lot of times we put the science and I'm a data scientist by training. I would love to talk about the science, but really, it's the problem first. The data and the science, they come after. >> Thanks, good advice. Any other questions in the audience? Yes, one right up here. (laughing) >> Test, test. Can you hear me? >> Yep. >> So with AI machinery becoming more commonplace and becoming more accessible to developers and visionaries and thinkers alike rather than being just a giant warehouse of a ton of machines and you get one tiny machine learning, do you foresee more governance coming into play in terms of what AI is allowed to do and the decisions of what training data is allowed to be fed to Ais in terms of influence? You talk about data determining if AI will become good or bad, but humans being the ones responsible for the training in the first place, obviously, they can use that data to influence as they, just the governance and the influence. >> Jack: Who wants to take that one? >> I'll take a quick stab at it. So, yes, it's going to be an open discussion. It's going to have to take place, because really, they're just machines. It's machine learning. We teach it. We teach it what to do, how to act. It's just an extension of us and in fact, I think you had a really great conversation or a statement at lunch where you talked about your product being an extension of a designer because, and we can get into that a little bit, but really, it's just going to do what we tell it to do. So there's definitely going to have to be discussions about what type of data we feed. It's all going to be centered around the use case and what that solves the use case. But I imagine that that will be a topic of discussion for a long time about what we're going to decide to do. >> Jack: Michelle do you want to comment on this thought of taking a designer's brain and putting it into a model somehow? >> Well, actually, what I wanted to say was that I think that the regulation and the governance around it is going to be self imposed by the the developer and data science community first, because I feel like even experts who have been doing this for a long time don't rally have their arms fully around what we're dealing with here. And so to expect our senators, our congressmen, women, to actually make regulation around it is a lot, because they're not technologists by training. They have a lot of other stuff going on. If the community that's already doing the work doesn't quite know what we're dealing with, then how can we expect them to get there? So I feel like that's going to be a long way off, but I think that the people who touch and feel and deal with models and with data sets and stuff everyday are the kind of people who are going to get together and self-regulate for a while, if they're good hearted people. And we talk about AI for good. Some people are bad. Those people won't respect those convenance that we come up with, but I think that's the place we have to start. >> So really you're saying, I think, for data scientists and those of us working in this space, we have a social, ethical, or moral obligation to humanity to ensure that our work is used for good. >> Michelle: No pressure. (laughing) >> None taken. Any other questions? Anything else? >> I just wanted to talk about the second part of what she said. We've been working with a company that builds robots for the store, a store associate if you will. And one of their very interesting findings was that the greatest acceptance of it right now has been at car dealerships because when someone goes to the car dealer and we all have had terrible experiences doing that. That's why we try to buy it online, but just this perception that a robot would be unbiased, that it will give you the information without trying to push me one way or the other. >> The hard sell. >> So there's that perception side of it too that, it isn't that the governance part of your question, but more the biased perception side of what you said. I think it's fascinating how we're already trained to think that this is going to have an unbiased opinion, whether or not that true. >> That's fascinating. Very cool. Thank you Sarush. Any other questions in the audience? No, okay. Michelle, could I ask, you've got a station over there that talks a little bit more about your company, but for those that haven't seen it yet, could you tell us a little bit about what is the experience like or how is the shopping experience different for someone that's using your company's technology than what it was before? >> Oh, free advertising. I would love to. No, but actually, I started this company because as a consumer I found myself going back to the user experience piece, just constantly frustrated with the user experience of buying products one at a time and then getting zero help. And then here I am having to google how to wear a white blazer to not look like an idiot in the morning when I get dressed with my white blazer that I just bought and I was excited about. And it's a really simple thing, which is how do I use the product that I'm buying and that really simple thing has been just abysmally handled in the retail industry, because the only tool that the retailers have right now are manual. So in fashion, some of our fashion customers like John Varvatos is an example we have over there, it's like a designer for high-end men's clothing, and John Varvatos is a person, it's not just the name of the company. He's an actual person and he has a vision for what he wants his products to look like and the aesthetic and the style and there's a rockstar vibe and to get that information into the organization, he would share it verbally with PDFs, thing like that. And then his team of merchandisers would literally go manually and make outfits on one page and then go make an outfit on another page with the same exact items and then products would go out of stock and they'd go around in circles and that's a terrible, terrible job. So to the conversation earlier about people losing jobs because of artificial intelligence. I hope people do lose jobs and I hope they're the terrible jobs that no one wanted to do in the first place, because the merchandisers that we help, like the one form John Varvatos, literally said she was weeks away from quitting and she got a new boss and said, "If you don't ix this part of my job, I'm out of here." And he had heard about us. He knew about us and so he brought us in to solve that problem. So I don't think it's always a bad thing, because if we can take that route, boring, repetitive task off of human's plates, what more amazing things can we do with our brain that is only human and very unique to us and how much more can we advance ourselves and our society by giving the boring work to a robot or a machine. >> Well, that's fantastic. So Joe, when you talk about Smart Cities, it seems like people have been talking about Smart Cities for decades and often people cite funding issues, regulatory environment or a host of other reasons why these things haven't happened. Do you think we're on the cusp of breaking through there or what challenges still remain for fulfilling that vision of a smart city? >> I do, I do think we're on the cusp. I think a lot of it has to do, largely actually, with 5G and connectivity, the ability to process and send all this data that needs to be shared across the system. I also think that we're getting closer and more conscientious about security, which is a major issue with IOT, making sure that our in devices or our edge devices, those things out there sensing, are secure. And I think interocular ability is something that we need to champion as well and make sure that we basically work together to enable these systems. So very, very difficult to create little, tiny walled gardens of solutions in a smart city. You may corner a certain part of the market, but you're definitely not going to have that ubiquitous benefit to society if you establish those little walled gardens, so those are the areas I think we need to focus on and I think we are making serious progress in all of them. >> Very good. Michelle, you mentioned earlier that artificial intelligence was all around us in lots of places and things that we do on a daily basis, but we probably don't realize it. Could you share a couple examples? >> Yeah, so I think everything you do online for the most part, literally anything you might do, whether that's googling something or you go to some article, the ads might be dynamically picked for you using machine learning models that have decided what is appropriate based on you and your treasure trove of data that you have out there that you're giving up all the time and not really understanding you're giving up >> The shoes that follow you around the internet right? >> Yeah, exactly. So that's basically anything online. I'm trying to give in the real-world. I think that, to your point earlier about he supply chain, just picking a box of cereal off the shelf and taking it home, there's not artificial intelligence in that at all, but the supply chain behind it. So the supply chain behind pretty much everything we do even in television, like how media gets to us and get consumed. At some point in the supply chain, there's artificial intelligence playing in there as well. >> So to start us in the supply chain where we can get the same day even within the hour delivery. How do you get better than that? What's coming that's innovative in the supply chain that will be new in the future? >> Well, so that is one example of it, but you'd be surprised at how inefficient the supply chain is, even with all the advances that have already gone in, whether it's physical advances around building modern warehouses and modern manufacturing plants, whether it's through software and others that really help schedule things and optimize things. What has happened in the supply chain just given how they've evolved is they're very siloed, so a lot of times the manufacturing plant does things that the distribution folks do not know. The distribution folks do things that the transportation folks don't know and then the store folks know nothing other than when the trucks pulls up, that's the first time they find out about things. So where the great opportunity in my mind is, in the space that I'm in, is really the generation of data, the connection of data, and finally, deriving the smarts that really help us improve efficiency. There's huge opportunity there. And again, we don't know it because it's all invisible to us. >> Good. Let me pause and see if there's any questions in the audience. There, we got one there. >> Thank you. Hi guys, you alright? I just had a question about ethics and the teaching of ethics. As you were saying, we feed the artificial intelligence, whereas in a scenario which is probably a little bit more attuned to automated driving, in a car crash scenario between do we crash these two people or three people? I would be choosing two, whereas the scenario may be it's actually better to just crash the car and kill myself. That thought would never go through my mind, because I'm human. My rule number one is self preservation. So how do we teach the computer this sort of side of it? Is there actually the AI ethic going to be better than our own ethics? How do we start? >> Yeah, that's a great question. I think the opportunity is there as Michelle was talking earlier about maybe when you cross that chasm and you get this new singularity, maybe the AI ethics will be better than human ethics because the machine will be able to think about greater concerns perhaps other than ourselves. But I think just from my point of view, working in the space of automated vehicles, I think it is going to have to be something that the industry, and societies are different, different geographies, and different countries. We have different ways of looking at the world. Cultures value different things and so I think technologists in those spaces are going to have to get together and agree amongst the community from a social contract theory standpoint perhaps in a way that's going to be acceptable to everyone who lives in that environment. I don't think we can come up with a uniform model that would apply to all spaces, but it's got to be something though that we all, as members of a community, can accept. And so yeah, that would be the right thing to do in that situation and that's not going to be an easy task by any means, which is, I think, one of the reasons why you'll continue to see humans have an important role to play in automated vehicles so that the human could take over in exactly that kind of scenario, because the machines perhaps aren't quite smart enough to do it or maybe it's not the smarts or the processing capability. It's maybe that we haven't as technologists and ethicists gotten together long enough to figure out what are those moral and ethical frameworks that we could use to apply to those situations. Any other thoughts? >> Yeah, I wanted to jump in there real quick. Absolutely questions that need to be answered, but let's come together and make a solution that needs to have those questions answered. So let's come together first and fix the problems that need to be fixed now so that we can build out those types of scenarios. We can now put our brainpower to work to decide what to do next. There was a quote I believe by Andrew Ningh Bidou and he was saying in concerning deep questions about what's going to happen in the future with AI. Are we going to have AI overlords or anything like that? And it's kind of like worrying about overpopulation at the point of Mars. Because maybe we're going to get there someday and maybe we're going to send people there and maybe we're going to establish a human population on Mars and then maybe it will get too big and then maybe we'll have problems on Mars, but right now we haven't landed on the planet and I thought that really does a good job of putting in perspective that that overall concern about AI taking over. >> So when you think about AI being applied for good and Michelle you talked about don't do AI just for AI's sake, have a problem to solve, I'll open it up to any of the three of you, what's a problem in your life or in your work experience that you'd love somebody out here would go solve with AI? >> I have one. Sorry, I wanted to do this real quick. There's roads blocked off and it's raining and I have to walk a mile to find a taxi in the rain right now after this to go home. I would love for us to have some sort of ability to manage parking spaces and determine when and who can come in to which parts of the city and when there's a spot downtown, I want my autonomous vehicle to know which one's available and go directly to that spot and I want it to be cued in a certain manner to where I'm next in line and I know. And so I would love for someone to go solve that problem. There's been some development on the infrastructure side for that kind of solution. We have a partnership Intel does with GE and we're putting sensors that have, it's an IOT sensor basically. It's called City IQ. It has environmental monitoring, audio, visual sensors and it allows this type of use case to take place. So I would love to see iterations on that. I would love to see, sorry there's another one that I'm particular about. Growing up I lived in Southern California right against the hills, a housing development, because the hills and there was not a factory, but a bunch of oil derricks back there. I would love to have sensor that senses the particulate in the air to see if there was too many fumes coming from that oil field into my yard growing up as a little kid. I would love for us to solve problems like that, so that's the type of thing that we'll be able to solve. Those are the types of innovations that will be able to take place once we have these sensors in place, so I'm going to sit down on that one and let someone else take over. >> I'm really glad you said the second one because I was thinking, "What I'm about to say is totally going to "trivialize Joe's pain and I don't want to do that." But cancer is my answer, because there's so much data in health and all these patterns are there waiting to be recognized. There's so many things you don't know about cancer and so many indicators that we could capture if we just were able to unmask the data and take a look, but I knew a brilliant company that was using artificial intelligence specifically around image processing to look at CAT scans and figure out what the leading indicators might be in a cancerous scenario. And they pivoted to some way more trivial problem which is still a problem and not to trivialize parking an whatnot, but it's not cancer. And they pivoted away from this amazing opportunity because of the privacy and the issues with HIPPA around health data. And I understand there's a ton of concern with it getting into the wrong hands and hacking and all of this stuff. I get that, but the opportunity in my mind far outweighs the risk and the fact that they had to change their business model and change their company essentially broke my heart because they were really onto something. >> Yeah that's a shame and it's funny you mention that. Intel has an effort that we're calling the cancer cloud and what we're trying to do is provide some infrastructure to help with that problem and the way cancer treatments work today is if you go to a university hospital let's say here in Texas, how you interpret that scan and how you respond and apply treatment, that knowledge is basically just kept within that hospital and within that staff. And so on the other side of the country, somebody could go in and get a scan and maybe that scan brand new to that facility and so they don't know how to treat it, but if you had an opportunity with machine learning to be able to compare scans from people, not only just in this country, but around the world and understand globally, all of the hundreds of different treatment pads that were applied to that particular kind of cancer, think how many lives could be saved, because then you're sharing knowledge with what courses of treatment worked. But it's one of those things like you say, sometimes it's the regulatory environment or it's other factors that hold us back from applying this technology to do some really good things, so it's a great example. Okay, any other questions in the audience? >> I have one. >> Good Emily. >> So this goes off of the HIPPA question, which is, and you were talking about just dynamically displaying ads earlier. What does privacy look like in a fully autonomous world? Anybody can answer that one. Are we still private citizens? What does it look like? >> How about from a supply chain standpoint? You can learn a lot about somebody in terms of the products that they buy and I think to all of us, we sort of know maybe somebody's tracking what we're buying but it's still creepy when we think about how people could potentially use that against us. So, how do you from a supply chain standpoint approach that problem? >> Yeah and it's something that comes up in my life almost every day because one of the thing's we'd like to do is to understand consumer behavior. How often am I buying? What kinds of products am I buying? What am I returning? And so for that you need transactional data. You really get to understand the individual. That then starts to get into this area of privacy. Do you know too much about me? And so a lot of times what we do is data is clearly anonymized so all we know is customer A has this tendency, customer B has this tendency. And that then helps the retailers offer the right products to these customers, but to your point, there are those privacy concerns and I think issues around governance, issues around ethics, issues around privacy, these will continue to be ironed out. I don't think there's a solid answer for any of these just yet. >> And it's largely a reflection of society. How comfortable are we with how much privacy? Right now I believe we put the individual in control of as much information as possible that they are able to release or not. And so a lot of what you said, everyone's anonymizing everything at the moment, but that may change as society's values change slightly and we'll be able to adapt to what's necessary. >> Why don't we try to stump the panel. Anyone have any ideas on things in your life you'd like to be solved with AI for good? Any suggestions out there that we could then hear from our data scientist and technologist and folks here? Any ideas? No? Alright good. Alright, well, thank you everyone. Really appreciate your time. Thank you for joining Intel here at the AI lounge at Autonomous World. We hope you've enjoyed the panel and we wish you a great rest of your event here at South by Southwest. (audience clapping) (bright music)

>> Announcer: Live from Las Vegas, Nevada it's theCube. Covering, Accelerate 2017. Brought to you by Fortinet. Now, here are your hosts, Lisa Martin, and Peter Buress. (tech music) >> Lisa: Hi, welcome back to theCube. We are Silicon Angle's Flagship Program, where we go out to the events and extract the signal to the noise, bringing it directly to you. Today, we are in beautiful Las Vegas with Fortinet. It's their Accelerate 2017 Event. I'm your host, Lisa Martin, joined by my cohost, Peter Buress. And we're very excited to be joined by a Technology Alliance Partner, Nozomi Networks, Edgard Capdevielle. You are the CEO? >> Yes, that's right. >> And, welcome to theCube. >> Thank you, happy to be here. >> So, a couple of great things that Nozomi announced, just a couple of months ago, one was, they just secured fantastic $7.5 million in Series A Funding. And the second thing they announced was you, as the new CEO, so congratulations on your new post. >> Thank you very much, thank you. >> So, Nozomi is focused on the Industrial Control Systems Industry. What was it about this particular opportunity, that attracted you to want to lead Nozomi? >> Yeah, great question. Two things mainly. One, is the team. The two founders are truly rock stars, they have a great background in Cyber Security, and how do we apply Artificial Intelligence to Industrial Cyber Security. And two was, I had been working with the founders for a little bit, and I saw, with my own eyes, how the customers adopted the technology, how easy it was to deploy in an industrial setting, which tends to have a lot of friction. Not a lot of equipment gets into those networks. And the ease of proof of concepts, I saw it with my own eyes. And the frictionless interactions, made me join. >> So Nozomi was started in 2013, you're already monitoring over 50,000 industrial installations. >> That's right. >> Some of the themes that we've talked about, at the event today, so far, with Fortinet's senior leaders, is the evolution of security, where they're positioning, really at this third generation of that. As we're seeing that, and we're seeing that in order for businesses to digitalize successfully, they have to have trust in that data. What is Nozomi seeing, in terms of your industrial customers? What are some of the biggest concerns that they have, regarding security? And how are you working with Fortinet, to help mitigate or limit damage from cyber attacks? >> A lot of our customers in our space, are going through what's called IT/OT Conversions. OT networks, have traditionally been serial, point to point, run over two step para copper and they've recently adopted ethernet. When you adopt ethernet, you have a gravitational force, which is to connect. So these OT networks used to be air gaps, segregated, and now they're being converged with IT technology, under sometimes, IT operation. And therefore, they start suffering the traditional IT attacks. Those traditional IT attacks, are particularly harmful when it comes to industrial, critical infrastructure. And they require special technology that understands those protocols, to be able to detect anomalies, and white list or black list, certain activities. >> Give some example, of an IOT network. So, what is, you say critical infrastructure, gives us some examples, what are we talking about? >> IOT's a very broad term. We focus very specifically on industrial IOT. >> Or, industrial IOT. >> Industrial IOT, could be a network that controls a refining, so the refining process in a refinery. It could be electrical distribution, any form of electrical generation, oil and gas, upstream or downstream. Manufacturing, everything that moves in manufacturing, is controlled by an industrial control networks. Pharma, in the same subsegment, if you will. Some transportation, we're based in San Francisco, so our barge system is controlled with industrial control systems. >> So, we're talking about, as you say critical infrastructure, we're talking about things that, where getting control of some element of that critical infrastructure, >> Correct. >> Especially in the process manufacturing businesses, can have enormously harmful effects? >> Correct. >> On not only business, but an entire community? >> The disruption that it can cause is tremendous. From lights out in a city, to harm to people, in a transportation case, oil and gas case. Environmental damage, leakage. The damage can be tremendous. And that's basically, one of the huge differences between IT and OT. In IT, if your network blinks, your email may be two seconds late, my print job may need to be resent. In OT, you may not be able to turn off that valve, or stop this process from happening, or receive an alarm in time. >> Right, so like, I live in Palo Alto. Not too from me is, some of the big refineries up in Richmond, California. And not too long ago, they had an OT outage, and it led to nearly a billion dollars worth of damage, to that plant, and to the local environment. >> Correct. >> So this is real serious stuff. >> So with a product like Nozomi, you can detect anomalies. Anomalies come in three flavors. One could be equipment damage, malfunction. The other one could be human error, which is very very common. And the other one could be cyber. Any one of those could be an anomaly, and if it tries to throw the process into a critical state, we would detect that, and that's where ... >> Talking about cyber, from a cyber attack perspective, what is it about industrial control systems that makes them such a target? >> Yeah. It is that they had been used to be isolated networks, just like I said. When IT and OT converges, are taking networks that used to be serial security was not really a concern, in industrial control networks, you don't really have identity, you don't have authentication. You're just starting to have encryption. Basically, if you drop a command in the network, that command will get executed. So, it's about the vulnerability of those. >> Vulnerability, maybe it's an easy target? And then from a proliferation perspective, we mentioned the evolution of security. But, the evolution of cyber attacks, the threat surface is increasing. What is the potential, give us some examples, some real world examples, of the proliferation that a cyber attack, >> That is a great question. >> And an industrial control system, can have on a retailer or a bank, energy company? >> The industry was put in the map in 2010, with Stuxnet. Stuxnet was the first attack, everybody talked about Stuxnet for a while. And it was very hard to create a market out of that, because it was done really by a nation's state, and it was done like once. Since then, 2010, 2013 and now 'til today, attacks have increased in frequency dramatically, and in use cases. Not only are nation states attacking each other, like in the case now of the Ukraine, but now you have traditional security use cases, your malicious insider, you're compromised insiders, doing industrial cyber attacks. In 2015, the Department of Homeland Security reported 295, industrial cyber attacks, in our nation's critical infrastructure. And those are not mandated, they don't have a reporting mandate, so those are voluntary reports. >> Wow. >> So that number, could be two or three times as big. If you think about it, from 2010, we've gone from once a year, to 2015 once per day. So, it's happening. It's happening all the time. And it's increasing not only in frequency, but in sophistication. >> So, it's 295 reported. But there's a bunch of unreported, >> Correct. >> That we know about, and then there's a bunch that we don't know about? >> Correct. >> So, you're talking about potentially thousands of efforts? And you're trying with Fortinet and others, to bring technology, as well as, a set of best practices and thought leadership, for how to mitigate those problems? >> That's right. With Fortinet, we have a very comprehensive solution. We basically combine Fortinet's sophistication or robustness from a cyber security platform, with Nozomi's industrial knowledge. Really, we provide anomaly detection, we detect, like I said, any sort of anomaly, when it comes to error, cyber, or malfunction. And we feed it to Fortinet. Fortinet can be our enforcement arm if you will, to stop, quarantine, block, cyber attacks. >> So, Nozomi's building models, based on your expertise of how industrial IOT works, >> That's right. >> And you're deploying those models with clients, but integrating the back into the Fortinet sandbox, and other types of places. So, when problems are identified, it immediately gets published, communicated to Fortinet, and then all Fortinet customers get visibility into some of those problems? >> We connect with Fortinet in two ways. One, is we have 40 SIM, so we alert everybody. We become part of the information, security information environment. But we also used Nozomi Fortigates, to block, to become active in the network. Our product is 100% passive. We have to be passive to be friendly deployed in industrial networks. But, for the level of attack or the level or risk is very high, you can actually configure Fortinet to receive a command from Fortinet, and from Nozomi, and actually block or quarantine a particular contaminated node, or something like that. Does that make sense? >> Oh, totally. Makes 100%, because as you said, so you let Fortinet do the active work, of actually saying yes or no, something can or cannot happen, based on the output of your models? >> That's right. Yep. >> So, when you think about IOT, or industrial IOT, there's an enormous amount of investment being made of turning all these analog feeds, into digital signals, that then can be modeled. Tell us a little bit about how your customers are altering their perspective on, what analog information needs to be captured, so that your models can get smarter and smarter, and better and better at predicting and anticipating and stopping problems. >> When it comes to industrial models, you need to pretty much capture all the data. So, we size the deployment of our product based on the number of nodes or PLC's that exist in an industrial network. We have designed our product to scale, so the more information or the more number of nodes, the better our models are going to be, and our products will scale to build those models. But, capturing all the data is required. Not only capturing, but parsing all the data, and extracting the insides and the correlations between all the data, is a requirement for us to have the accuracy in anomaly detection that we have. >> What is the customer looking at in terms of going along that, that seems like an arduous task, a journey. What does, and you don't have to give us a customer name, but what does that journey look like, working together with Nozomi, and Fortinet, to facilitate that transformation, from analog to digital, if all the information is critical? >> That transformation is happening already. A lot of these industrial networks are already working on top of ethernet, a standard DCPIP. The way the journey works for us, is we provide, as soon as we show up, an immediate amount of visibility. These networks don't have the same tool sets from a visibility and asset management perspective that IT networks have. So, the first value add is visibility. We capture an incredible amount of information. And the first and best way to deploy it initially, is with, let me look at my network, understand how many PLC's do I have, how the segmentation should be properly done. And then, during all this time, our model building is happening, we're learning about the physical process and about the network. After we've done with the learning our system, determines that now it's ready to enforce, or detect anomalies, and we become at that point, active in anomaly detection. At that point, the customer may connect us with Fortinet, and we may be able to enforce quarantine activities, or blocking activities, if the problem requires it. >> Is there any one particular, use case that sticks out in your mind, as a considerable attack, that Nozomi has helped to stop? >> We obviously can't name any one in particular, but when it comes to defending yourself against cyber criminals, we have defended companies against malicious insiders. Sometimes, an employee didn't like how something may have happened, with them or with somebody else, and that person leaves the company, but nobody removed their industrial credentials. And they decide to do something harmful, and it's very hard. Industrial malicious insider activity, is extremely hard to pinpoint, extremely hard to troubleshoot. Industrial issues in general, are very hard to troubleshoot. So, one of the things that Nozomi adds a lot of value is, is allowing troubleshooting from the keyboard, without eliminating trucks and excel sheets, you quickly can pinpoint a problem, and stop the bad things before they happen. >> One more quick question for you. With the announcements that Fortinet has made today, regarding, you mentioned some of the products, what are you looking forward to most in 2017, in terms of being able to take it to the next level with your customers? To help them, help themselves? >> Listen, the solution works amazingly well. We have to tell more people about it. I think the critical infrastructure has not had the attention in prior years, and I think this year's going to be a year where, ICS security is going to be, and Fortinet of course, is very aware of this, is going to be a lot more relevant for a lot more people. The number of attacks, and the you know, the attacks surface that will never be, it's all playing so that, this year's going to be a big year. >> Yeah, I think we were talking, before we started, that the U.S. Department of Homeland Security, has just identified the U.S. Election System, as a critical infrastructure. >> That's right. >> So maybe it's going to take more visible things, that have global implications, to really help move this forward. >> I think the one point I would make when it comes to government, government has been great, if you make an analogy, this is an analogy that I have on the top of my head, if you look at cars in the automotive industry, seat belts and airbags have saved a lot of lives. We don't have that in industrial cyber security. And we need the government to tell us, what are the seat belts? And what are the minimum set of requirements that are electrical, infrastructures should be able to sustain? And that way, it makes the job easier for a lot of us, because nobody can tell you today, how much security to invest, and what's the mix of security solutions that you should have. And therefore, in the places where you don't have a lot of investment, you don't have none. And you become very vulnerable. Today, if you want to ship a car, and you want your car to be driven on the road, it has to have airbags, and it has to have seat belts, and that makes it a minimum bar for proper operation, if you will. >> But the proper, the way it typically works, is government is going to turn to folks like yourself, to help advise and deliver visibility, into what should be the appropriate statements about regulation, and what needs to be in place. So, it's going to be interesting because you and companies like you, will in fact be able to generate much of the data, that will lead to hopefully, less ambiguous types of regulations. >> Yes, that's right. That's right. I agree 100%. >> Wow, it's an exciting prospect. Edgard Capdevielle, thank you so much. CEO of Nozomi Networks, it's been a pleasure to have you on the program today. >> Thank you. >> On behalf of my cohost Peter Buress, Peter, thank you. We thank you for watching theCube, but stick around, we've got some more up, so stay tuned. (tech music)

>> Narrator: Live from Las Vegas, Nevada, it's The Cube, covering Accelerate 2017. Brought to you by Fortinet. Now, here's your host, Lisa Martin. >> Hi, welcome back to The Cube. We are Silicon Angle's flagship live streaming program, where we go out to the events and we extract the signal from the noise, and we bring it right to you. We are in beautiful Las Vegas with Fortinet. Today, or this week is their Accelerate 2017 event, and we've been excited to be chatting with a lot of their folks and technology partners. Today we are joined by two gentlemen from Fortinet. First, we have John Maddison. You are the Senior Vice President of Products and Solutions. >> Indeed. >> Lisa: Hey John. >> Hi. >> Lisa: Thanks for joining us. We've got Joe Sykora who is the Vice President of America's Channels. >> Thanks Lisa. >> So guys, a lot of exciting stuff going on today. I wanted to give the viewers here who haven't had a chance to meet you guys yet, what you're both doing. John, you have a veteran. You're a veteran of over 20 years experience at telecom >> At least. >> At least 20 in IT infrastructure, security industries, you've lived in Europe and Asia and the U.S. and worked in those. Joe, you oversee quite a big channel of over 7400 America's partners and the entire channel strategy. So you guys are kind of busy. >> A little bit. >> Joe, you're probably pretty proud of this. You were named, in 2015, by CRN as one of the 50 Most Influential Channel Chiefs. >> Yes I was. >> Did you get like a button or hat? >> No, I think it's a t-shirt. >> Oh, t-shirt. >> Absolutely. >> Outstanding, so speaking of t-shirts, I have no segue there, wanted to understand, we've been talking to a lot of your folks today, as I mentioned. We talked to your CEO who was talking about this third generation of security and kind of where we are today with that. And then we talked to Drew, the CFO, who was really talking about the criticalness of trusting data. With the announcement today, maybe John I'll throw this to you, the announcement today of the new products and technologies, how are they going to continue to facilitate or enable your customers, direct or indirect to be able to trust their data? >> Yeah, so we announced the fabric last year. Today, we announced our operating system Fi.6, which is extension of the fabric. We also announced something called intent-based network security, which is the next generation of network security that Ken Xie, our founder, talked about. And then we also announced, the third thing is our new security operations solution, which brings together several products for the infosec world. So I think all of these come together to make sure that we're continuing the effort to make sure our customers are safer, that they can integrate the fabric into their infrastructure and obviously, that's very important to their brand. >> That was going to be one of the things I was going to talk about is are you seeing that you're making a difference in the brand of a customer? We were talking, before we started today, and a lot of you are familiar with some of the the big breaches, I mean, breaches are a common, daily occurrence, but when when they start happening in brands it's the consumers know who aren't in technology becomes a suddenly, can I trust this particular brand where I normally go and buy household products. So it sounds like the announcements today are really next generation leading you guys to continue to be able to deliver, not just that comfort level that your customers need in terms of we can trust our data, but also helping them improve their brand so that their customers trust their brand. >> Exactly and so, you know, the fabric has expanded in that we've expanded it across multiple now attack vectors so what used to be really focused on the core network, we can now cover email, we can now cover the web, endpoint and also, you can see some of our partners around here, we've also expanded our fabric-ready so the fabric here has several APIs, multiple APIs that allow different partners to connect into it. And so, we haven't announced it totally yet but we've got six new partners, some big companies like Cisco and HBE, actually joining our fabric-ready program to be part of the fabric. So we can cover the entire infrastructure of any company. >> Fantastic, so speaking, we'll get to that in a minute but one of the topics that's also come out today, as we've seen the evolution of security from perimeter based security in the 90s to you know, web security, cloud security. Moving towards 2020 and the fact that it's 2017, a little scary, we're pretty close to that and we're seeing this explosion and proliferation of mobile devices, of IOT devices, lot of lack of security there. As we get to that point, one of the other themes that we're hearing a lot about here today is that there is a gap in terms of of resources. What is Fortinet doing to help bridge that gap, that your customers are facing? Where it comes to, specifically, network security programs? >> So one of the programs we launched again, a couple of years ago was the Network Security Expert program, NSE, in 2016, we had over 30,000 certificates issued on NSE. It's probably one of the largest security programs, 'cause one of the big issues for customers and our partners is just the skills gap, cybersecurity. We also, actually, use a lot of those materials and assets and give them to Universities who are starting to do their programs as well. That's really essential for our partners to be trained at the lowest level in terms of the basics, but also, we've had about 40 people take part in our Network Security Eight architecture program. You can see them, these are the pins, actually, we have, which are NSE one to seven, but the NSE eight are the red ones and there's about 40 now of what we call security solution architects, who can go into companies and look at their complete infrastructure and give them an update in terms of security. >> Excellent, so want to touch on the channel, for a moment. Ken talked about the security fabric architecture, you mentioned that it was launched last year. What has been the reaction of the channel? >> Oh, it's been absolutely great. It's about mid-year last year's when we announced that. Embraced by the channel, in fact, CRN named it the security product of the year, for 2016. >> Lisa: Oh, fantastic, congratulations. >> Very proud of that. And that's actually the feedback of the channel partners. It resonates. It's creating new opportunities for our partners. Combine that with the training that John just talked about, I mean, they're armed to really just go out there and help solve all those end user programs, problems. >> Thank you, and sorry for interrupting. What are some of the main pain points that you're hearing through the channel, that customers are experiencing as we start to see big attacks have become more and more prevalent, the Dyn attack recently, DdOS being common types of attacks. As more and more things, like critical infrastructures are becoming plugged into corporate networks, and more mobile and more IOT, what are some of the pain points that your customers are experiencing, and how are they, looking to resolve and mitigate some of the challenges that they have leveraging the security fabric architecture? >> Sure, well attacks are going to happen, right. We know they're going to happen. It's how fast can you react to those attacks. And the fabric actually enarms our partners to just have intelligence on what is actionable and what's not actionable. So we're tryin' to automate that. Some of the future stuff that we're going to be doing later in the year is going to even enable them more. But it's all about simplifying it for our partners to react to what needs to be reacted to. >> Are you seeing, from an industry perspective, we were talking with Derek Menke, excuse me, about healthcare really being at the top of the at risk from an industry perspective. But in the general session today, there was a CSO panel and there was Verizon was there, Levi's was there, as well as Lazard. We saw Telefonica throughout the event today, the Steelers. Are you seeing through the channel, and maybe this is a question for both of you, are you seeing particular industries at more risk coming to you through your customers' needs or is it fairly agnostic from a security perspective? >> Yeah, I think on the channel side, obviously, everyone's at risk, right. So I think it's the value of those of the incidences is really more highlighted. So when Derek talks about healthcare, for example, dealing with people's lives is important along with you health records. So that's much more valuable than say, at the Steelers, not being able to get on the guest wifi. So I think everyone's at risk. All of our channel partners have different verticals that they go after, and it's all the same, it really is. >> Yeah, I would say the risk is pretty broad across every vertical, I mean, yes healthcare, the healthcare records are extremely valuable, but also the financial industry. You've also got industrial controls systems, for example. You've also got retail and so, I think every vertical, every industry is taking security very, very seriously. And back to your previous question about how is the fabric helping partners, I think, previously, they had to kind of stitch together a lot of point solutions themselves. I think with the fabric, it gives them an architecture or a framework. It could be mostly Fortinet gear. It could be Fortinet plus some of their other partners. It helps them put that in place across the entire infrastructure. >> You bring up a good point, John, that that was brought up a number of times today and that is the role of the CSO now being, you know, kind of think, is that guy or girl at the lead of the digital army? But that person is inheriting, we were seeing a couple of different reports, North of 25 different security technology, really kind of a patchwork environment. In that kind of situation, where now security is a board level conversation, how is Fortinet direct, and through the channel, helping that CSO? Is that a key buyer for you that you're helping to figure out, I've got this patchwork here, how do I build it into a fabric or a fabric around it? >> What we've seen, what I've experienced in the last 10 plus years in security is, I'd often go into a room and there'll be the network security people on one side of the table, and the security people on the other side of the table with the CSO and the CIO and I think, that gradually over the last three years, I've seen more cooperation. So now, when we have briefings with customers and partners, you'll see both teams together. You'll see a new role inside customers called the Security Architect, that's looking holistically longer term over the security architecture. And one of our announcements today around the security operations center is to do, just do that, bring together the SOC and the infosec world, together with the network security world. We did a demo today on stage showing that bringing together our Forti SIM, our Forti analyzer with our fabric to bring those two worlds together, because as Joe says, you know, there's a report done by Verizon on the breach report that says, within 60 seconds, you can be compromised. You've got basically 60 seconds to stop that threat and so speed is very important. So giving our partners this ability to bring together a fabric, with Fortinet gear, with our partners' gear, that provides very fast protection is very important. >> Excellent, one of the things, too, that I found interesting today was learning about what FortiGuard Labs is doing. I read over the weekend what Derek Menke's team published, the 2017 predictions. Really quite frightening. And he was on the show earlier and saying, that they're already seeing a number of these things already in play. How much more intelligent malware is getting, and the pervasiveness of the threats there. How are some of the new technologies announced today, maybe enhancing or what FortiLabs is doing from a threat intelligence perspective, is that something that was part of? >> Yeah, that's a really important area. I think the vendor community needs to do better in sharing the threat intelligence. I think, today, it's in pockets, but I think long term, it's absolutely essential that threat intelligence get shared across the whole community because, with some of the new threats coming, the machine to machine threats, the scale and the speed's going to be even more. You saw the Dyn attack last year on Ddos. That's going to be small compared to some things coming up. So I think, longer term, the fabric across the infrastructure, and then the security vendors getting together and sharing that threat intelligence so you've got a bigger view of the attack surface is absolutely essential to stop the new type of threats. >> Exactly, and as that attack surface is growing by the day. So last question, before we wrap up here, give you guys both a chance to answer. At the beginning of your fiscal year, here we are in January, what are you most excited about for the channel in 2017, for example? >> Sure, opportunity, right. For our channel partners, we've got probably one of the strongest channel partners just the overall. We're aligning, realigning with our field teams, so just the resources that all of these partners have. I think the opportunity's great, the market's great, like you said, you open up anything now, and you see, okay, it's been infiltrated, it's been hacked. So I think we're all going to have a really good 2017. >> Fantastic, John, what about you? What are you most excited for? >> I was most excited about this interview, actually, that's what I was looking forward to. >> Wow, fantastic, we'll close there. (laughter). >> No, I think it's obviously, rolling out more of our technology, integrating more of our partners, training more of our partners and helping them with their customers. >> Fantastic, well the buzz and the momentum here and also, the passion for both yourselves and your roles and your peers and your colleagues is really palpable. So I want to thank you both for joining us on the Cube today. >> Thank you. >> And we wish you the best of luck at the rest of the event. >> Thanks Lisa. >> Alright, for John and Joe, I'm Lisa Martin. You've been watching the Cube, but stick around, we'll be right back.