>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> If it weren't for Pat Gelsinger, Intel's future would be a disaster. Even with his clear vision, fantastic leadership, deep technical and business acumen, and amazing positivity, the company's future is in serious jeopardy. It's the same story we've been telling for years. Volume is king in the semiconductor industry, and Intel no longer is the volume leader. Despite Intel's efforts to change that dynamic With several recent moves, including making another go at its Foundry business, the company is years away from reversing its lagging position relative to today's leading foundries and design shops. Intel's best chance to survive as a leader in our view, will come from a combination of a massive market, continued supply constraints, government money, and luck, perhaps in the form of a deal with apple in the midterm. Hello, and welcome to this week's "Wikibon CUBE Insights, Powered by ETR." In this "Breaking Analysis," we'll update you on our latest assessment of Intel's competitive position and unpack nuggets from the company's February investor conference. Let's go back in history a bit and review what we said in the early 2010s. If you've followed this program, you know that our David Floyer sounded the alarm for Intel as far back as 2012, the year after PC volumes peaked. Yes, they've ticked up a bit in the past couple of years but they pale in comparison to the volumes that the ARM ecosystem is producing. The world has changed from people entering data into machines, and now it's machines that are driving all the data. Data volumes in Web 1.0 were largely driven by keystrokes and clicks. Web 3.0 is going to be driven by machines entering data into sensors, cameras. Other edge devices are going to drive enormous data volumes and processing power to boot. Every windmill, every factory device, every consumer device, every car, will require processing at the edge to run AI, facial recognition, inference, and data intensive workloads. And the volume of this space compared to PCs and even the iPhone itself is about to be dwarfed with an explosion of devices. Intel is not well positioned for this new world in our view. Intel has to catch up on the process, Intel has to catch up on architecture, Intel has to play catch up on security, Intel has to play catch up on volume. The ARM ecosystem has cumulatively shipped 200 billion chips to date, and is shipping 10x Intel's wafer volume. Intel has to have an architecture that accommodates much more diversity. And while it's working on that, it's years behind. All that said, Pat Gelsinger is doing everything he can and more to close the gap. Here's a partial list of the moves that Pat is making. A year ago, he announced IDM 2.0, a new integrated device manufacturing strategy that opened up its world to partners for manufacturing and other innovation. Intel has restructured, reorganized, and many executives have boomeranged back in, many previous Intel execs. They understand the business and have a deep passion to help the company regain its prominence. As part of the IDM 2.0 announcement, Intel created, recreated if you will, a Foundry division and recently acquired Tower Semiconductor an Israeli firm, that is going to help it in that mission. It's opening up partnerships with alternative processor manufacturers and designers. And the company has announced major investments in CAPEX to build out Foundry capacity. Intel is going to spin out Mobileye, a company it had acquired for 15 billion in 2017. Or does it try and get a $50 billion valuation? Mobileye is about $1.4 billion in revenue, and is likely going to be worth more around 25 to 30 billion, we'll see. But Intel is going to maybe get $10 billion in cash from that, that spin out that IPO and it can use that to fund more FABS and more equipment. Intel is leveraging its 19,000 software engineers to move up the stack and sell more subscriptions and high margin software. He got to sell what he got. And finally Pat is playing politics beautifully. Announcing for example, FAB investments in Ohio, which he dubbed Silicon Heartland. Brilliant! Again, there's no doubt that Pat is moving fast and doing the right things. Here's Pat at his investor event in a T-shirt that says, "torrid, bringing back the torrid pace and discipline that Intel is used to." And on the right is Pat at the State of the Union address, looking sharp in shirt and tie and suit. And he has said, "a bet on Intel is a hedge against geopolitical instability in the world." That's just so good. To that statement, he showed this chart at his investor meeting. Basically it shows that whereas semiconductor manufacturing capacity has gone from 80% of the world's volume to 20%, he wants to get it back to 50% by 2030, and reset supply chains in a market that has become important as oil. Again, just brilliant positioning and pushing all the right hot buttons. And here's a slide underscoring that commitment, showing manufacturing facilities around the world with new capacity coming online in the next few years in Ohio and the EU. Mentioning the CHIPS Act in his presentation in The US and Europe as part of a public private partnership, no doubt, he's going to need all the help he can get. Now, we couldn't resist the chart on the left here shows wafer starts and transistor capacity growth. For Intel, overtime speaks to its volume aspirations. But we couldn't help notice that the shape of the curve is somewhat misleading because it shows a two-year (mumbles) and then widens the aperture to three years to make the curve look steeper. Fun with numbers. Okay, maybe a little nitpick, but these are some of the telling nuggets we pulled from the investor day, and they're important. Another nitpick is in our view, wafers would be a better measure of volume than transistors. It's like a company saying we shipped 20% more exabytes or MIPS this year than last year. Of course you did, and your revenue shrank. Anyway, Pat went through a detailed analysis of the various Intel businesses and promised mid to high double digit growth by 2026, half of which will come from Intel's traditional PC they center in network edge businesses and the rest from advanced graphics HPC, Mobileye and Foundry. Okay, that sounds pretty good. But it has to be taken into context that the balance of the semiconductor industry, yeah, this would be a pretty competitive growth rate, in our view, especially for a 70 plus billion dollar company. So kudos to Pat for sticking his neck out on this one. But again, the promise is several years away, at least four years away. Now we want to focus on Foundry because that's the only way Intel is going to get back into the volume game and the volume necessary for the company to compete. Pat built this slide showing the baby blue for today's Foundry business just under a billion dollars and adding in another $1.5 billion for Tower Semiconductor, the Israeli firm that it just acquired. So a few billion dollars in the near term future for the Foundry business. And then by 2026, this really fuzzy blue bar. Now remember, TSM is the new volume leader, and is a $50 billion company growing. So there's definitely a market there that it can go after. And adding in ARM processors to the mix, and, you know, opening up and partnering with the ecosystems out there can only help volume if Intel can win that business, which you know, it should be able to, given the likelihood of long term supply constraints. But we remain skeptical. This is another chart Pat showed, which makes the case that Foundry and IDM 2.0 will allow expensive assets to have a longer useful life. Okay, that's cool. It will also solve the cumulative output problem highlighted in the bottom right. We've talked at length about Wright's Law. That is, for every cumulative doubling of units manufactured, cost will fall by a constant percentage. You know, let's say around 15% in semiconductor world, which is vitally important to accommodate next generation chips, which are always more expensive at the start of the cycle. So you need that 15% cost buffer to jump curves and make any money. So let's unpack this a bit. You know, does this chart at the bottom right address our Wright's Law concerns, i.e. that Intel can't take advantage of Wright's Law because it can't double cumulative output fast enough? Now note the decline in wafer starts and then the slight uptick, and then the flattening. It's hard to tell what years we're talking about here. Intel is not going to share the sausage making because it's probably not pretty, But you can see on the bottom left, the flattening of the cumulative output curve in IDM 1.0 otherwise known as the death spiral. Okay, back to the power of Wright's Law. Now, assume for a second that wafer density doesn't grow. It does, but just work with us for a second. Let's say you produce 50 million units per year, just making a number up. That gets you cumulative output to $100 million in, sorry, 100 million units in the second year to take you two years to get to that 100 million. So in other words, it takes two years to lower your manufacturing cost by, let's say, roughly 15%. Now, assuming you can get wafer volumes to be flat, which that chart showed, with good yields, you're at 150 now in year three, 200 in year four, 250 in year five, 300 in year six, now, that's four years before you can take advantage of Wright's Law. You keep going at that flat wafer start, and that simplifying assumption we made at the start and 50 million units a year, and well, you get to the point. You get the point, it's now eight years before you can get the Wright's Law to kick in, and you know, by then you're cooked. But now you can grow the density of transistors on a chip, right? Yes, of course. So let's come back to Moore's Law. The graphic on the left says that all the growth is in the new stuff. Totally agree with that. Huge term that Pat presented. Now he also said that until we exhaust the periodic table of elements, Moore's Law is alive and well, and Intel is the steward of Moore's Law. Okay, that's cool. The chart on the right shows Intel going from 100 billion transistors today to a trillion by 2030. Hold that thought. So Intel is assuming that we'll keep up with Moore's Law, meaning a doubling of transistors every let's say two years, and I believe it. So bring that back to Wright's Law, in the previous chart, it means with IDM 2.0, Intel can get back to enjoying the benefits of Wright's Law every two years, let's say, versus IDM 1.0 where they were failing to keep up. Okay, so Intel is saved, yeah? Well, let's bring into this discussion one of our favorite examples, Apple's M1 ARM-based chip. The M1 Ultra is a new architecture. And you can see the stats here, 114 billion transistors on a five nanometer process and all the other stats. The M1 Ultra has two chips. They're bonded together. And Apple put an interposer between the two chips. An interposer is a pathway that allows electrical signals to pass through it onto another chip. It's a super fast connection. You can see 2.5 terabytes per second. But the brilliance is the two chips act as a single chip. So you don't have to change the software at all. The way Intel's architecture works is it takes two different chips on a substrate, and then each has its own memory. The memory is not shared. Apple shares the memory for the CPU, the NPU, the GPU. All of it is shared, meaning it needs no change in software unlike Intel. Now Intel is working on a new architecture, but Apple and others are way ahead. Now let's make this really straightforward. The original Apple M1 had 16 billion transistors per chip. And you could see in that diagram, the recently launched M1 Ultra has $114 billion per chip. Now if you take into account the size of the chips, which are increasing, and the increase in the number of transistors per chip, that transistor density, that's a factor of around 6x growth in transistor density per chip in 18 months. Remember Intel, assuming the results in the two previous charts that we showed, assuming they were achievable, is running at 2x every two years, versus 6x for the competition. And AMD and Nvidia are close to that as well because they can take advantage of TSM's learning curve. So in the previous chart with Moore's Law, alive and well, Intel gets to a trillion transistors by 2030. The Apple ARM and Nvidia ecosystems will arrive at that point years ahead of Intel. That means lower costs and significantly better competitive advantage. Okay, so where does that leave Intel? The story is really not resonating with investors and hasn't for a while. On February 18th, the day after its investor meeting, the stock was off. It's rebound a little bit but investors are, you know, they're probably prudent to wait unless they have really a long term view. And you can see Intel's performance relative to some of the major competitors. You know, Pat talked about five nodes in for years. He made a big deal out of that, and he shared proof points with Alder Lake and Meteor Lake and other nodes, but Intel just delayed granite rapids last month that pushed it out from 2023 to 2024. And it told investors that we're going to have to boost spending to turn this ship around, which is absolutely the case. And that delay in chips I feel like the first disappointment won't be the last. But as we've said many times, it's very difficult, actually, it's impossible to quickly catch up in semiconductors, and Intel will never catch up without volume. So we'll leave you by iterating our scenario that could save Intel, and that's if its Foundry business can eventually win back Apple to supercharge its volume story. It's going to be tough to wrestle that business away from TSM especially as TSM is setting up shop in Arizona, with US manufacturing that's going to placate The US government. But look, maybe the government cuts a deal with Apple, says, hey, maybe we'll back off with the DOJ and FTC and as part of the CHIPS Act, you'll have to throw some business at Intel. Would that be enough when combined with other Foundry opportunities Intel could theoretically produce? Maybe. But from this vantage point, it's very unlikely Intel will gain back its true number one leadership position. If it were really paranoid back when David Floyer sounded the alarm 10 years ago, yeah, that might have made a pretty big difference. But honestly, the best we can hope for is Intel's strategy and execution allows it to get competitive volumes by the end of the decade, and this national treasure survives to fight for its leadership position in the 2030s. Because it would take a miracle for that to happen in the 2020s. Okay, that's it for today. Thanks to David Floyer for his contributions to this research. Always a pleasure working with David. Stephanie Chan helps me do much of the background research for "Breaking Analysis," and works with our CUBE editorial team. Kristen Martin and Cheryl Knight to get the word out. And thanks to SiliconANGLE's editor in chief Rob Hof, who comes up with a lot of the great titles that we have for "Breaking Analysis" and gets the word out to the SiliconANGLE audience. Thanks, guys. Great teamwork. Remember, these episodes are all available as podcast wherever you listen. Just search "Breaking Analysis Podcast." You'll want to check out ETR's website @etr.ai. We also publish a full report every week on wikibon.com and siliconangle.com. You could always get in touch with me on email, david.vellante@siliconangle.com or DM me @dvellante, and comment on my LinkedIn posts. This is Dave Vellante for "theCUBE Insights, Powered by ETR." Have a great week. Stay safe, be well, and we'll see you next time. (upbeat music)

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we finally, it feels like the on prem guys are finally getting their cloud act together. Um it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean the public cloud has been around for about 10 years and still only 20% around 20% of the data in 20% of the applications are there now will be a very important ones and I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud. And I feel like when amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have a classic on, on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's, it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very, a quick way. And uh you know what they've learned, The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. Uh it just depends on what do you want to lock yourself into, but super exciting and what H. P. E. You know, when they further acts in the sea with Green Lake, I think it was four years ago, uh I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine as I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but so, but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but, but I look at it differently, I wonder what your take is. I, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here we're gonna spend $100 billion like the internet. Here you go build. And so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a Polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point. And that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp as you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody's sort of following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see. First off some of their, Um, announcements on, on how it's going and they talked about $428 billion 1200 customers over 900 partners and 95% retention. And I think that's important. Anybody who's in the lead and remember what aws I used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it is A. S. A. P. Hana. Ml apps HPC with Francis, VD. I was Citrus and video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic, with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that Western european carriers use and they're now extending that to five G. And um, so more horizontal, uh, and, and more vertical. That was the one of the big swipes, uh, that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay. Okay. So, so the other piece of that of course is standardization right there there because there was a, there was a, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse. Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way, is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say, the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say the White House customers that HP Yeah, >>Well done. So, you know, and I hear your point about we're 10 years in plus. And to me this is like a mandate. I mean, this is okay, good, good job guys about time. But if I had a, you know, sort of look at the big player, it's like we have an oligopoly here in this, in this business. It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in antony's like, okay, here's what we're going to announce that, you know, a while ago. So, and they seem to have done a good job with Wall Street and they got a simple model, you know, Dell is obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together. So they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale, codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP ES sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these players here, So Cisco, ironically has sells the most software of any of those players that you mentioned, uh with the exception of IBM um and yeah, C I >>CSDB two. Yeah, >>yeah, they're the they're the number two security player, uh Microsoft, number one, So and I think the evaluation on the street uh indicate that shows that I feel like Dell tech is a very broad play because not only do they have servers, storage, networking insecurity, but they also have Pcs and devices. So it's a it's a scale and end play with a focus on VM ware solutions, not exclusively of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table. I think with h P e, what you're bringing the table is nimble. When HP and HP split, the number one thing that I said was that ah, h P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster. And that is what I've seen as it relates to the moat, which is a unique uh competitive advantage. Quite frankly, I'm still looking for that day uh in in in what that is. And I think in this industry it's nearly impossible. And I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that as your can't if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E. When it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development. I think that is a landing place where H P. E already does pretty well can come in and expand its footprint. >>You know, that's really interesting um, observations. So, and I would agree with you. It's kind of like, this is a copycat industry. It's like the west coast offense like the NFL, >>so, >>so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer because all of a sudden you saw companies like them, you always had a long term relationship with H P E, but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really is a execution, isn't it? But go ahead please. >>Dave if I had to pick something that I think HP HPV needs to always be ahead in as a service and listen you and I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're going to have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right? Because it, it I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like Anna Quinn X play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's like you said, outpost was the sort of signal. Okay, We're coming on prem. Clearly the on prem uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere and that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding, dominating in the edge with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do >>you say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge, whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong in Mcdonald's, there's nobody there that can help uh they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road And it has a 5GV 2 x communication cameras can't see around corners. But that car communicating ahead, that ran into the stop sign can, through Vita X talked to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky, let's make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built complete architecture is to do that, putting compute into five G base stations, heck, I just, there was an announcement this week of google cloud and its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kinda whose stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we could take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba, it's fantastic and they also managed it in the right way. I mean it was part of HB but it was, it was managed a lot more loosely then, you know, a company that might get sucked into the board and I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies, but it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security, uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloaded video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion. >>Well, I have you we have a ton of time here, but I I don't pick your brain about intel the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war, you got there battling a. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean he had a great run there and I think it is a very positive move. I've never seen the energy at Intel. Probably in the last 10 years that I've seen today. I actually got a chance to talk with Pat. I visited Pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they built out there networking business, they build out a storage business um with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at A. M. B. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles they integrate into the larger chips called S. O. C. S. B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arm Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the Arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on on the planet. So here we have A and D. Who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S and then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition date. Competition is great. You know, when there's not competition in Cpus and Gpus, we know what happens, right. Uh, the B just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to, and then, oh, by the way, the custom Chip providers, WS has created no less than 15 custom semiconductors started with networking uh, and, and nitro and building out an edge that surrounded the general compute and then it moved to Inferential to for inference trainee um, is about to come out for training Graviton and gravitas to for general purpose CPU and then you've got Apple. So innovation is huge and you know, I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors, software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You've got to 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the qualcomm NXP deal. You just don't know what china is going to do. I think the Eu with some conditions is gonna let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see, wants to see this happen. Japan and Korea. I think we'll allow this china is the odd man out. >>In a word, the future of H. P. E. Is blank >>as a service >>patrick Moorehead. Always a pleasure my friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back. >>Mm.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So, you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we we finally, it feels like the on prem guys are finally getting their cloud act together. Um, it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean, the public cloud has been around for about 10 years and still only 20%. Around 20% of the data in 20% of the applications are there now, albeit very important ones. And I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud and I feel like when Amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have the classic on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very quick way. And uh, you know what they've learned. The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. It just depends on what do you want to lock yourself into, but super exciting. And what H. P. E. When they threw the acts in the sea with Green Lake, I think it was four years ago, I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine is I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but but but so but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but I look at it differently. I wonder what you're taking. I think, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here, we're going to spend $100 billion like the internet here you go build. And and so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point and that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp. As you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody started following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see, first off some of their, Um, announcements on, on how it's going. And they talked about 4, $28 billion 1200 customers over 900 partners and 95% retention. And I think that's important anybody who's in the lead and remember what Aws used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it was S. A. P. Hana Ml apps HPC with Francis V. I was Citrus in video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that western european carriers use and they're now extending that to five G. And um, so more horizontal uh and and more vertical. That was the one of the big swipes uh that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay, Okay. So, so the other piece of that of course is standardization right there there because there was a, there was, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse, Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh, is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say, the white house customers at HP. Yeah, >>Well done. So, you know, and I hear your point about 10 years in, you know, plus and to me this is like a mandate. I mean, this is okay. Good, good job guys about time. But if I had a, you know, sort of look at the big players, like, can we have an oligopoly here in this, in this business? It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in Antonio's like, okay, here's what we're going to announce that, you know, while ago, so, and they seem to have done a good job with Wall Street and they get a simple model, you know, Dell's obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together, so they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP? Es sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these these players here. So Cisco, ironically, has sells the most software of any of those players that you mentioned, uh with the exception of IBM. Um, and yeah, C >>ICSDB two. Yeah, >>yeah, they're the they're the number two security player, uh, Microsoft, number one. So and I think the evaluation on the street uh indicate that shows that I feel like uh Deltek is a is a very broad play because not only do they have servers, storage, networking and security, but they also have Pcs and devices, so it's a it's a scale and end play with a focus on VM ware solutions, not exclusively, of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table, I think with h P E, what your bring to the table is nimble. When HP and HP split, the number one thing that I said was that uh huh H P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um, and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster and that is what I've seen as it relates to the moat, which is a unique uh, competitive advantage. Quite frankly, I'm still looking for that day in, in, in what that is and I think in this industry it's nearly impossible and I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that Azure can't, if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E, when it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development, I think that is a landing place where H P E already does pretty well can come in and expand its footprint, >>you know, that's really interesting um, observations. So, and I would agree with you, it's kind of like, this is a copycat industry, it's like the west coast offense, like the NFL >>and >>so, so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer, because all of a sudden you saw companies like them, you always had a long term relationship with H P E but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really >>is an execution, >>isn't it? But go ahead, please >>Dave if I had to pick something that I think HP HPV needs to always be ahead and as a service and listen, you know, I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're gonna have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right, Because it, it, I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like ANna Quinn x play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's as you said, outpost was the sort of signal. Okay, We're coming on prem clearly the on prem, uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere. And that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding is dominating in the edge with with with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do you >>say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge. Whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, Physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong and Mcdonald's, there's nobody there that can help uh, they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road and it has a five G V two X communication cameras can't see around corners, but that car communicating ahead, that ran into the stop sign, can I through vi to X. Talk to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky to make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built Complete architectures to do that, putting compute into 5G base stations. Heck, I just, there was an announcement this week of google cloud in its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kind of who's stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we can take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba it's fantastic. And they also managed it in the right way. I mean, it was part of HB but it was it was managed a lot more loosely then, you know, a company that might get sucked into the board. And I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies. But it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, um a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloading video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion >>while I have you, we have a ton of time here, but I I don't pick your brain about intel, the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war. You got there, battling A. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean, he had a great run there and I think it is a very positive move. I've never seen the energy At Intel probably in the last 10 years that I've seen today. I actually got a chance to talk with pat. I visited pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they've built out there networking business, they build out a storage business um with with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at AMG. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles, they integrate into the larger chips called S. O. C S B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arms Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on the planet. So here we have AMG who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S. And then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition. Date. Competition is great. You know, when there's not competition in CPUs and Gpus, we know what happens right. Uh, the beach just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to and then, oh, by the way, you have the custom Chip providers. WS has created no less than 15 custom semiconductors started with networking and nitro and building out an edge that surrounded the general computer. And then it moved to Inferential for inference trainee um, is about to come out for training Graviton and Gravitas to for general purpose CPU and then you've got apple. So innovation is huge and I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You got a 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the Qualcomm NXp deal. You just don't know what china is going to do. I think the EU with some conditions is going to let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see wants to see this happen, Japan and Korea I think we'll allow this china is the odd man out. >>In a word, the future of h p. E is blank >>as a service >>patrick Moorehead. Always a pleasure. My friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back.

>>From the cube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cute conversation. Welcome to this cube conversation. I'm Lisa Martin pleased to be joined once again by the co CEO of mem sequel, Raj Verma, Raj, welcome back to the program. >>Thank you very much, Lisa. Great to see you as always. >>It's great to see you as well. I always enjoy our conversations. So why don't you start off because something that's been in the news the last couple of months besides COVID is one of your competitors, snowflake confidentially filed IPO documents with the sec a couple months ago. Just wanted to get your perspective on from a market standpoint. What does that signify? >>Yeah. Firstly, congratulations to the snowflake team. Uh, you know, I've, I have a bunch of friends there, you know, John McMahon, my explosives on the board. And I remember having a conversation with him about seven years ago and it was just starting off and I'm just so glad for him and Bob Mobileye. And, and as I said, a bunch of my friends who are there, um, they're executed brilliantly and, uh, I'm thrilled for that. So, um, we are hearing as to what the outcomes are likely to be. And, uh, it just seems like, uh, you know, it's going to be a great help. Um, and I think what it signifies is firstly, if you have a bit technology and if you execute well, good things happen and there's enough room for innovation here. So that is one, the second aspect is I think, and I think more importantly, what it signifies is a change of thought in the database market. >>If you really see, um, and know if my memory serves me right in the last two decades or probably two and a half buckets, we just had one company go public in the database space and that was Mongo. And, um, and that was in, I think October, 2017 and then, uh, two and a half years. So three years we've seen on other ones and uh, from the industry that we know, um, you know, there are going to be a couple that are going to go out in the next 18 months, 24 months as well. So the fact is that we had a, the iron grip on the database market for almost, you know, more than two decades. It was Oracle, IBM that a bit of Sybase and SAP HANA. And now there are a bunch of companies which are helping solve the problems of tomorrow with the technology of the month. >>And, uh, and that is, um, that is snowflake is a primary example of that. Um, so that's a, that's good change. God is good. I do think the incumbents are gonna find it harder and harder going forward. And also if you really see the evolution of the database market, the first sort of workloads that moved to the cloud with the developer workloads and the big benefactor that that was the no secret movement and one company that executed in my opinion, the best was Mongol. And they were the big benefactor of that, that sort of movement to the cloud. The second was the very large, but Moisey database data warehouse market, and a big benefactor of that has been snowflake big queries, the other one as well. However, the biggest set of tsunami of data that's we are seeing move to the cloud is the operational data, which is the marriage of historical data with real time data to give you real time insights as, or what we call the now are now. >>And that's going to be much, much bigger than, uh, than both the, you know, sequel or the developer data movement and the data warehouse. And we hope to be a benefactor of that. And then the shake up that happens in the database market and the change that's happening there, isn't a vendor take on market anymore, and that's good because you don't then have the stranglehold that Oracle had and you know, some of the ways that are treated as customers and help them to run some, et cetera, um, yeah. And giving customers choice so that they can choose what's best for the business is going to be, it's going to be great. And me are going to see seven to 10 really good database companies in large, in the next decade. And we surely hope them secret as one of them of, we definitely have the, have the potential to be one of them. >>You have the market, we have the product, we have the customers. So, you know, as I tell my team, it's up to us as to what we make of it. And, um, you know, we don't worry that much about competition. You did mention snowflake being advantage station. We, yeah, sure. You know, we do compete on certain opportunities. However, their value proposition is a little more single-threaded than ours. So they are more than the Datavail house space are. Our vision of the board is that, uh, you know, you should have a single store for data, whether it's database house, whether it's developer data or whether it's operational data or DP data. And, uh, you know, watch this space from orders. We make somebody exciting announcements. >>So dig into that a little bit more because some of the news and the commentary Raj in the last, maybe six weeks since the snowflake, um, IPO confidential information was released was, is the enterprise data warehouse dead. And you just had a couple of interesting things we're talking about now, we're seeing this momentum, huge second database to go public in two and a half bigots. That's huge, but that's also signifying to a point you made earlier. There's, there's a shift. So memes SQL isn't, we're not talking about an EDW. We're talking about operational real time. How do you see that if you're not looking in the rear view mirror, those competitors, how do you see that market and the opportunities? >>Yeah, I, I don't think the data warehouse market is dead at thought. I think the very fact that, you know, smoke makers going out at whatever valuation they go out, which is, you know, tens of billions of dollars is, um, is a testimony to the fact that, you know, it's a fancy ad master. This is what it is. I mean, data warehouses have existed for decades and, uh, there is a better way of doing it. So it's a fancy of mousetrap and, and that's great. I mean, that's way to money and it's clearly been demonstrated. Now what we are saying is that I think that is a better way to manage the organization's data rather than having them categorized in buckets of, you know, data warehouse, data developer, data DP, or transactional data, you know, uh, analytical data. Is there a way to imagine the future where there is one single database that you can quit eat, or data warehouse workloads for operational workloads, for OLTB work acknowledge and gain insights. And that's not a fancier mousetrap that is a data strategy reimagine. And, uh, and that's our mission. That's our purpose in life right now and are very excited about it's going to be hard. It's not, it's not a given it's a hard problem to solve. Otherwise, if you can solve it before we have the, uh, we have the goods to deliver and the talent, the deliberate, and, um, we are, we are trying it out with some very, very marquee customers. So we've been very excited about, >>Well, changing of the guard, as you mentioned, is hard. The opposite is easy, the opposite, you know, ignoring and not wanting to get out of that comfort zone. That's taken the easy route in my opinion. So it seems like we've got in the market, this, this significant changing of the guard, not just in, you know, what some of your competition is doing, but also from a customer's perspective, how do you help customers, especially institutions that have been around for decades and decades and decades pivot quickly so that the changing of the guard doesn't wipe them out. >>Yeah. Um, I actually think slightly differently. I think changing of the guard, um, wiping out a customer is if they stick or are resistant to the fact that there is a change of God, you know, and if they, if they hold on to, as we said in our previous conversation, if you stick onto the decisions of yesterday, you will not see the Sundays of tomorrow. So I do think that, uh, you know, change, you have a, God is a, is a symbolism, not even a symbolism as a statement to our customers to say, there is a better way of doing, uh, what you are doing to solve tomorrow's problem. And then doesn't have to be the Oracles and the BB tools and the psychosis of the world. So that's, that's one aspect of it. The second thing is, as I've always said, you're not really that obsessed about, uh, competition. >>The competition will do what they do. Uh, we are really very focused on having an impact in the shortest period of time on our customers and, uh, hopefully a positive impact. And if you can't do it, then, you know, I've had conversations with a few of them saying, maybe be not the company for you. Uh, it's not as if I have to sort of, software's a good one. I supply to the successful customers in the bag to do the unsuccessful with customers. The fact is that, you know, in certain, certain places there isn't an organizational alignment and you don't succeed. However, we do have young, we have in the last 14 months or so made tremendous investments into really ease of use of flexibility of architecture, which is hybrid and tactile, and that shrinking the total time to value for our customers. Because if I, if I believe you, if you do these three things, you will have an impact, a positive impact on the customer, in the sharpest, uh, amount of time and your Lindy or yourself. And I think that is more important than worrying needlessly about competition. And then the competition will do what they do. But if you keep your customers happy by having a positive impact, um, successes, only amount of time, >>Customers and employees are essential to that. But I like that you talked about customer obsession because you see it all over the place. Many people use it as descriptors of themselves and their LinkedIn profiles, for example, but for it actually to be meaningful, you talked about the whole objective is to make an impact for your customers. How do you define that? So that it's not just, I don't want to say marketing term, but something that everyone says they're customer obsessed showing it right within the pudding. >>It's easy to say we are customer obsessed. I mean, this organization is going to say we don't care about our customer. So, you know, of course we all want our customers to be successful. How do you, that's easy, you know, having a cultural value that we put our customers first is, was easy, but we didn't choose to do that. What we said is how do you have an impact on your customer in the shortest amount of time, right? That is, that is what you have. I'm sequel and Lee have now designed every process in mem sequel to align with that word. If, if that is a decision that we have to make a B essentially lenses through the fact of what is in the best interest of our customer and what will get us to have an impact, a positive impact on the customer in the shortest amount of time, that is a decision, which is a buy decision for us to make. >>A lot of times it's more expensive. It's a, a lot duffel. It stresses the, um, the, the, the organization, um, and the people in it. But that's, uh, that's what you have to do if you are. Um, if you are, you know, as, as they say, customer obsessed, um, it is, it's just a term which is easy to use, but very difficult to put here too. And we want to be a tactic. It right to be, we are going to continue to learn. It's a, it's not a destination, it's a journey. And we continue to take decisions and refine our processes do, as I said, huh, impact on our customers in the shortest amount of time. Now, obsessiveness, a lot of times is seen as a negative in the current society that we live in. And there's a reason for that because the, they view view obsession, but I view obsession and aggression is that is a punishing expression, which is really akin to just being cruel, you know, leading by fear and all the rest of it, which is as no place in any organization. >>And I actually think that in society at large, nothing, I believe that doesn't have any place in society. And then there's something which I dumb as instrumentalists, which is, this is where we were. This is where we are. This is where we are going and how do we track our progress on a daily, weekly, monthly basis? And if we, aren't sort of getting to that level that we believe we should get to, if our customers, aren't seeing the value of dramas in the shortest amount of time, what is it that we need to do better? Um, is that obsession, our instrumental aggression is, is, is what we are all about. And that brings with it a level of intensity, which is not what everyone, but then when you are, you know, challenging the institutions which have, uh, you know, the also has to speak for naked, it's gonna take a Herculean effort to ask them. And, uh, you know, the, the basically believed that instrumental aggression in terms of the, uh, you know, having an impact on customer in the shop to smile at time is gonna get us there. And a, and B are glad to have people who actually believe in that. And, uh, and that's why we've made tremendous progress over the course of last, uh, two years. >>So instrumental aggression. Interesting. How you talked about that, it's a provocative statement, but the way that you talk about it almost seems it's a prescriptive, very strategic, well thought out type of moving the business forward, busting through the old guard. Cause let's face it, you know, the big guys, the Oracles they're there, they're not easy for customers to rip and replace, but instrumental aggression seems to kind of go hand in hand with the changing of the guard. You've got to embrace one to be able to deliver the other, right. >>Yeah. So ducks, I think even a fever inventing something new. Um, I mean, yeah, it just requires instrumental aggression, I believe is a, uh, uh, anchor core to most successful organizations, whether in IP or anywhere else. That is a, that is a site to that obsession. And not, I'm not talking about instrumental aggression here, but I'm really talking about the obsession to succeed, uh, which, uh, you know, gave rise to what I think someone called us brilliant jerks and all the rest of it, because that is the sort of negative side of off obsession. And I think the challenge of leadership in our times is how do you foster the positivity of obsession, which needs to change a garden? And that's the instrumental aggression as a, as a tool to, to go there. And how do you prevent the negative side of it, which says that the end justifies the means and, and that's just not true. >>Uh, there is, there is something that's right, and there's something that's wrong. And, uh, and if that is made very clear that the end does not justify the meanings, it creates a lot of trust between, um, Austin, our customers, also not employees. And when their inherent trust, um, happens, then you foster, as I said, the positive side of obsession and, um, get away from the negative side of obsession that you've seen in certain very, very large companies. Now, the one thing that instrumental aggression and obsession brings to a company is that, uh, it makes a lot of people uncomfortable, and this is what I continue to tell. Um, our, our employees and my audience is, um, you know, be comfortable being uncomfortable because what you're trying to do is odd. And it's going to take a, as I say, a Herculean effort. So let's, uh, let's be comfortable being uncomfortable, uh, and have fun doing it. If there's, uh, how many people get a chance to change, uh, industry, which was dominated by a few bears and have such a positive impact, not only on our estimates, but society at large. And, uh, I think it's a privilege. Pressure is a privilege. And, uh, I'm grateful for the opportunity that's been afforded to me and to my colleagues. And, uh, >>It's a great way. Sorry. That's a great way of looking at it. Pressure is a privilege. If you think about, I love what you said, I always say, get, you know, get comfortably uncomfortable. It is a heart in any aspect, whether it's your workouts or your discipline, you know, working from home, it's a hard thing to do to your point. There's a lot of positivity that can come from it. If we think of what's happening this week alone and the U S political climate changing of the old guard, we've got Kamala Harris as our first female VP nominee and how many years, but also from a diversity angle, from a women leadership perspective, blowing the door wide open. >>It's great to see that, um, you know, we have someone that my daughter's going to look up to and say that, uh, you know, yes, there is, there is a place for us in society and we can have a meaningful contribution to society. So I actually think that San Antonio versus nomination is, um, you know, it's a simple ism of change of God, for sure. Um, I have no political agendas, um, at all. Then you can see how it pans out in November, but the one thing is for sure, but it's going to make a lot of people uncomfortable, a change of God, or this makes a lot of people. And, and, uh, and you know, I was reflecting back on something else and in everything that I've actually achieved, which is, is something I'm proud of. I had to go through a zone, but I was extremely uncomfortable. >>Uh, Gould only happens when you have uncomfortable, um, girl to happens in your conference room. And, um, whether it's, um, you know, running them sequel, uh, or are having a society change, uh, if you stick to your comfort zone, you stick to your prejudices and viruses because it's just comfortable there, there's a, uh, wanting to be awkward. And, uh, and, and I think that that's that essential change of God. As I said, at the cost of repeating myself will make a lot of people uncomfortable, but I honestly believe will move the society forward. And, uh, yeah, I, um, I couldn't be more proud of, uh, having a California San Diego would be nominated and it's a, she brings diversity multicultural. And what I loved about it was, you know, we talk about culture and all the rest of it. And she, she was talking about how our parents who were both, uh, uh, at the Berkeley when she was growing up, we were picking up from and she be, you know, in our, in our prime going to protests and Valley. >>And so it was just, uh, it was ingrained in her to be able to challenge the status school and move the society forward. And, uh, you know, she was comfortable being uncomfortable when she was in that, you know, added that. And that's good. Maybe not. I think we sort of, uh, yeah, I, yeah, let's see, let's see what November brings to us, but, um, I think just a nomination has, uh, exchanged a lot of things and, uh, if it's not this time, it can be the next time, but at the time off the bat, but you're going to have a woman by woman president in my lifetime. Um, that's um, I minced about them, uh, and that's just great. >>Well, I should hope so too. And there's so many, I know we've got to wrap here, but so many different data points that show that that technology company actually, companies, excuse me, with women in leadership position are significantly 10, 20% more profitable. So the changing of the guard is hard as you said, but it's time to get uncomfortable. And this is a great example of that as well as the culture that you have at mem sequel Raja. It's always a pleasure and a philosophical time talking with you. I thank you for joining me on the cube today. >>Thank you me since I'm just stay safe, though. >>You as well for my guest, Raj Burma, I'm Lisa Martin. Thank you for watching this cube conversation.

(upbeat music) >> Hi, and welcome to theCUBE, the leading source for insights into the world of technology and innovation. I'm your host Donald Klein, and today's topic is the market for autonomous vehicles and the ecosystem suppliers looking to tap into this brave new world of autonomous capabilities in our daily commute. To have this conversation I'm joined by Rudy Burger, managing partner at Woodside Capital. Rudy, welcome to the show. >> Thanks Don, it's great to be here. >> Great, so look, why don't we start off Rudy, why don't you tell us a little bit about Woodside Capital and your role there? >> Great, so I founded Woodside Capital about 20 years ago having started five different companies of my own, one of which I took public. We are a specialist M&A advisor. We work with so-called growth stage often venture-backed companies and help them find buyers that are usually much larger public companies. Our clients are usually US or European companies and we find buyers in the US, Europe, or Asia. >> Excellent, excellent, okay. And why don't you talk a little bit about your kind of specialty areas? >> So I focused my career, and certainly the work at Woodside Capital, on imaging technologies and as an enabling technology, and the products and markets that are enabled by imaging and increasingly computer vision. So nowadays that is autonomous vehicles, consumer technology, security surveillance, and digital health. So enabling technologies, the computer vision is the theme that binds those together. >> Okay, well, the thing that's on everybody's mind these days is autonomous vehicles, when are we going to get them? Very high profile for sure. Before the show we talking about the kind of two key ingredients to making this happen, the AI software which is kind of the brains of the operation and then also the sensors which enable all of the AI. So why don't we talk about the sensor world first, okay? Lot of discussion about there, so sort of does the brave new world of vehicles need lidar? Does it not need lidar? Are there other types of sensors coming along? What's your sense of that market and how it's looking for all of the different players in it? >> So, Don, I look at it from a sort of fairly basic standpoint. Humans have two very capable image sensors and a very powerful processor, and the degree to which the automotive manufacturers and so-called Robo-Taxi developers have decided it's necessary to sprinkle every sensor known to man, and I'm talking lidar, radar, ultrasound, thermal, and of course cameras, is to some extent a degree to which, you know, image sensors are not as good as our eyes today. Now, there are some areas in which we will probably always have technology as a help. For example, humans are not very good at seeing in the dark whereas a thermal technology can do that very well. But my overall belief is that it's never a good idea to bet against an incumbent technology, and in this case I'm talking about so-called CMOS image sensors which are the sensor that goes into pretty much every camera in the world now. It's never a good idea to bet against the incumbent technology being able to scale into a new market. Every time people have done that, they've been wrong. Back in the early days the debate was whether CMOS image sensors would ever be good enough to replace CCDs as the sensor technology, and of course now, you know, everything uses CMOS image sensors. In other markets there was a long period of time in which people were thinking that LCD panels would never be large enough to replace, you know, for television, for example, 50 inch and so forth. It was never going to happen, so we needed plasma TVs, we needed rear-projection TVs. But slowly but surely the incumbent technology, LCDs, expanded to that market. So my belief is that CMOS image sensors will evolve to a point at which they will replace the need for lidar in most applications. >> Interesting, so that's a very controversial statement, right? Because you've certainly seen a lot of emphasis on the development of new generation lidar capability. >> Over 100 lidar companies started over the last three, four years, and of course many of them will not be happy to hear me say that. There are two distinct markets and one is the so-called Robo-Taxi market, and the other is more of the consumer vehicle ADAS market, and I think we need to think about those separately because the economics behind both are very different. If you look at the Robo-Taxi market, those vehicles tend to be much more expensive and are relatively price-insensitive. So if they can improve safety a little bit by putting a lidar on there, you know, great, let's do it, multiple lidars because these vehicles will be in operation 24 by seven, and if each vehicle costs 200,000, $250,000, fine. When we talk about the mass market for automobiles, type of car that you and I might go down and buy, very different thing. And, you know, auto makers sweat the pennies, and so putting a one or $200 lidar in a vehicle, big decision. And to the extent that they can replace the need for that lidar with a much less expensive camera system, that's what they'll do. Bear in mind that Mobileye, which has been the biggest success story, acquired by Intel for $13.5 billion, second largest acquisition Intel ever made, they for the most part still run on one camera, forward-looking camera. That's it, no radar, no lidar, no thermal, one camera. So the clever use of image processing, computer vision, and one image sensor can do a great deal. >> Interesting, okay. Well, so I want to talk about the software in just a second, but just to kind of finish this point, so if you were advising a sensor company that's developing some next gen capabilities, whether lidar or other related technologies, is the point you're making here that there are certain segments of this industry which are going to be more attractive to your technology than others? >> Absolutely, yes. I mean, the first thing to recognize is that the automotive industry has never really been a particularly comfortable fit with the economics and timeline of venture capital. VCs need to invest and recoup and redeploy back to their LPs on an eight-year cycle. But the automotive industry moves quite slowly, perhaps Tesla are excepted, and what the first piece of advice I would give these companies is it's probably going to be three, four, five years before, even if you have the right technology, before that technology really starts generating any significant volume and revenue. So for many venture-backed companies, that's too long. So the first piece of advice is find pockets of revenue, right, beachheads if you will, where you can land your technology and start generating revenue before you get to the automotive market. And many of these lidar companies we just talked about are not going to last long enough to get to the automotive market because not only does the automotive market move slowly but the autonomous vehicle market keeps on getting pushed out to the right as the industry realizes that this is a big, hairy problem. And so I would say, what is it that your technology can do an order of magnitude better than any other technology? Focus on that and find some opportunities for revenue outside the automotive industry that will sustain the company on its way to the holy grail. >> Interesting, yeah, so find that alternative revenue source to get you to base camp, and then when the market's ready, climb that Everest to-- >> I've seen so many companies basically go out of business because they've set their sights on either the automotive market, and it's go for broke. We're not interested in, all these other things are distractions. You know, entrepreneurs don't have a plan B. Or this. We're going to get our technology into a smartphone, that's it. And there are possibly some other opportunities but it takes so long and it's so difficult to get your technology into a smartphone that they go out of business before they ever get to that point. >> Interesting, okay. So good advice for people looking to kind of apply their technology in this kind of a very difficult market, right, very complicated market. All right, well, then let's switch to the other side of it. So we were kind of talking about the key ingredients, right? Sensors but also AI and the software around that, okay, and there are some very big players developing the software. Tesla's had their Autonomy Day where they've showcased their technology. You've obviously got Google with their capabilities developing software. How do you make sense of this overall landscape because we do see a lot of smaller providers also trying to develop software here. >> So the first thing that I find fascinating about the automotive industry is that for the most part there is no software market. There's perhaps one exception of any scale, that's BlackBerry that sells the QNX software. They found a point within the entertainment console where they can license their software. But for all of the development and capital invested into automotive software, nobody is actually generating revenue, making a living, by licensing software. And one of the main reasons for that is that, you know, the automotive market, really since inception, has been a hardware business. This is a business of bending sheet metal, internal combustion engines, and software has really not played that big a role up until relatively recently. So even those companies that do have software technology have ended up selling it into the automotive supply chain as a piece of silicon, embedded on a piece of silicon, not as, you know, here's my software on a USB stick, right? I think that the whole software licensing model hasn't so far fit well, fit comfortably, with the automotive industry. And the other reason is that there's no standard platform. If I were to develop a piece of software, I can, in the PC industry, I can develop for Windows, I can develop for Mac, I can develop for an iPhone. There's no such thing in the automotive industry, and particularly in this new world of autonomous vehicles there is no standard platform. There are many different processors, Nvidia has staked an early claim there. And the reason that most of the companies developing autonomous vehicle technology have developed the so-called full-stack solution, everything from code running on the processor, integrated through the sensors and so forth, is for that reason, there is no standard platform. So each company has developed the whole solution for themselves, and there are many of them around here that have raised hundreds of millions of dollars, some cases billions of dollars, for that purpose. So there is, today, no software market for automotive in the same way that we think about it in other industries. >> Understood, understood. But in terms of the companies that are actually pushing the envelope on these kind of capabilities, right, so we're taking the best of AI, we're applying it to big data sets, and then hopefully being able to extract that to create capabilities for these vehicles, right? What's your sense of how far that's come along in-- >> Well, it's come a long way but, here I'm going to push the boat out a little bit. I don't believe that the so-called deep learning technology, which is the current state of the art for AI, it's the technology that has allowed computers to beat humans at chess, at Go, I don't think that that flavor of AI, that approach to AI, is ever going to get us to safe enough autonomous vehicles. And that's because it works extremely well in fairly well-bounded rules, rule-bounded games or any scenario like that, but can you imagine trying to teach your 16-year-old how to drive by showing them images of every situation that they might encounter, right? Impossible. It's an infinite, it's not a well-bounded set. And that's so difficult because we really haven't developed the technology to allow computers to learn, to have things like common sense, to infer, you know, well, this happened, so this is likely to happen. So I think we are going to need a whole new breakthrough in AI before we get to what is generally considered safe enough vehicles. >> Interesting, well then, maybe if we kind of apply your previous thought about sort of Robo-Taxis as maybe being the segment where you're going to see the most use of these newer sensor technologies. >> Rudy: Near term, yes. >> Exactly, what about maybe, is that sort of the same rules apply there for maybe the AI providers, that they're-- >> I think so and that's why they're all focused on that. I mean, from Uber to Waymo, they've all made the same calculation which is if you're running a fleet of vehicles, and so for example in Uber's case, the driver takes 80% of the fare and only 20% goes back to Uber, but if you can replace the driver with a computer, you can keep that vehicle on the road 24 by seven and you can keep 100% of the revenue. You don't need to pay the computer. So that's the calculus that they're all going through. But I think that many of them are making a fundamental mistake and I predicted recently that I think Uber, my prediction for 2020 is that Uber is going to divest its autonomous vehicle business and get back to the business that it should be focused on. Uber generates about $14 billion a year in gross revenue, so 20% of that, which is the piece that Uber keeps after the drivers take their 80, is what, 2.8 billion. Uber should be able to be an extremely profitable business on 2.8 billion of net revenue, but they're spending a huge chunk of money every year on R&D. Now, I would argue that Hertz and Avis have successful businesses. They're in the service, they're in the transportation business, but they didn't decide that they had to build their own cars in order to be in that business. My view, personal view, is that what Uber should be doing is saying, that's not our business, right? We are the world's best at managing this sort of peer-to-peer network crowdsourced transportation, if you will. And when some company, some Silicon Valley startup, comes out with safe enough technology, great, we'll use it, but we don't have to develop that ourselves. >> Well then, maybe just to play devil's advocate here for a second, what about it's a Robo-Taxi-type technologies being applied in bounded areas within metropolitan areas where the rules-- >> That's where it will start. >> Could be more-- >> I think that's where it will start, but I think part of the problem is that we have, perhaps in part due to all of the media hype around autonomous vehicles, we've been misdirected to thinking about autonomous vehicles as a replacement for the car we drive to work every day and I think that's the wrong way to think about it. I think that autonomous vehicles are going to show up in the market as an extension of public transportation. Right, you know, I get off the train and there's an autonomous vehicle waiting to take me for the last couple of miles to my office. >> And those last couple of miles would be sort of a regulated space. >> Rudy: May well be. >> Where the AI is more than capable of functioning. >> Right, and that, you know, yes. And so it's better to think about autonomous vehicles as not being a revolutionary technology but much more of an evolutionary technology. And in fact, most of these technologies are showing up in so-called ADAS technologies which are designed to make driving your regular car safer, lane assist, keeping you a safe distance. >> Donald: Maybe just explain that word, ADAS, and what that means. >> So ADAS stands for automated driver-assistance systems. So one of the first was cruise control, right, everybody's familiar with cruise control. And so to some extent ADAS is just building on cruise control. In addition to maintaining a constant speed, you can now stay in the lane. In addition to maintaining a constant speed, it will now automatically slow down if you get too close to the car in front. And so you can see ADAS as, you know, collision avoidance and so forth, not full autonomy, still have to have a driver in the driver's seat, but evolving year by year until one year we wake up and, yep, my car will actually drive me all the way from home to work without me intervening. Right, it's going to happen in that way. >> So incremental improvements. >> Incremental improvement. >> To ADAS as opposed to kind of revolution of autonomy. >> An overnight sensation. >> Yeah, right, coming from nowhere. Okay, understood. Well then, let's pivot from that then, okay. So let's talk about the automotive industry as a whole and sort of your thoughts on how this is all going to play out. >> Yeah, so there are some very interesting dynamics playing out in the automotive industry. Firstly, as good news, as a result of all of this money and innovation in the automotive industry, Detroit's actually coming back. I go there once or twice a year and you can feel the economy coming back in Detroit, but it's not going to come back around, you know, bending sheet metal. And the challenge that the automotive companies have is so much of their infrastructure and expertise has been built on construction, building a car, production lines to bend the metal, install the engine, and the internal combustion engine itself. And by complete coincidence, to some extent, we've got this confluence of all of these autonomous technologies and electric vehicles happening at the same time. Electric vehicles are much easier to make than internal combustion engines. Far fewer parts. It's one of the reasons that China has spun up about 20 different electric vehicle companies recently. So I think that long term, my prediction is that the automobile industry will go the same way that the personal computer industry went. When the PC first, you know, it was born by IBM, or Apple in some sense before that. There were dozens of companies producing different PCs and it was very much, they were expensive products, and, you know, relatively unusual. As the industry matured, the supply chains matured, and it became apparent there were really only two companies that were making a lot of money out of the PC industry. The companies that developed the software, operating system, and the companies that developed the processor, and all of the manufacturing went over to, in the PC's case, in Taiwan, right? And I think that exactly the same thing is going to happen with the automotive industry. Tesla today still actually makes cars, but I don't see them long term being in the car business because they're really a technology company. It's the reason I don't think Apple is ever going to get into the car industry. They make fantastic margins selling computer products. The gross margin selling a car, it's miserable. It can be single digits or teens. That would completely tank Apple's blended gross margin. So my prediction for the industry is there will be a few small pockets of very profitable businesses, particularly around the operating system, by which I mean the intelligence or the AI intelligence, and then the processor, whether it's a Qualcomm processor or a Nvidia processor or an Intel processor. And as with the PC industry, most of the profit will go there and most of the manufacturing will end up getting outsourced because that's not the value-add, you know, bending metal and so forth. >> Interesting, well, so in the kind of compute market today, right, we have this notion of sort of cloud-native, right, okay, and that many of the companies that are developing apps as relying on cloud-native infrastructure have a kind of technology lead that's going to be hard for some of the legacy providers to actually catch up on. Now, other people say that that's not necessarily the case and et cetera, right? Can you make the same argument for the electric car market, that some of the electric-natives might have a kind of sustainable advantage here? >> I should've added, today the cloud infrastructure companies, cloud services, SaaS companies, in the PC world, you know, very profitable, and I can see a similar cloud services model developing for the automotive industry. However, other than Tesla, it's very difficult to change the automotive channel to support that. I'll give you one example. Everyone that owns a Tesla is very used to the idea that, sometimes on a daily basis, a new bunch of software, operating system software, is downloaded overnight to your vehicle. You wake up in the morning and some new feature's been turned on, right? Tesla can do that because they bypass the entire dealership channel that has a complete lock on the rest of the industry. So for example, if GM wants to do the same thing as Tesla and do sort of what's called over-the-air, OTA, updates, software updates, they can't do that because their contract with the dealership network states that if there is service to be done on the vehicle, the vehicle has to be brought back to the dealership, and the dealerships consider updating the software on the vehicle as service. So their contract with the dealers actually prevent them from doing something that basic. So it's not just a technology issue. The whole channel and way vehicles get sold is going to have to change. >> Interesting, so that's the advantage that some of the new generation of vehicle manufacturers-- >> I would say that Tesla has a five year lead, technology lead, because they, like Apple, are vertically integrated. They're doing everything from user interface, fit and function, all the way down to the semiconductor. They're developing their own semiconductors now. So they have become a fearsome competitor in the electronic vehicle space because they've been doing it for longer than the other major auto companies. They've figured out a lot of the, you know, tricks and techniques of how to extend mileage and so forth. And so they have a substantial lead in the industry at this point, despite the fact that over the next 12, 18 months, every automotive company is going to be coming out with their own flavor of electronic vehicle. >> So then it's more than just about having electric drivetrains, et cetera, right? It's about the whole suite of capabilities. >> It's a systems engineering challenge. >> Interesting, okay. All right, well Rudy, we're going to have to leave it there, okay, but I think everything you've told us is, it sounds like some good news for some of the Tesla stock holders at the moment. >> I think so. >> Okay, well. (laughs) We'll pass on making an opinion about that, but great conversation, thank you for your insights. Okay, this is Donald Klein, host of theCUBE, here with Rudy Burger, managing partner at Woodside Capital. >> Rudy: Great, thank you, Don. (upbeat music)

(upbeat music) >> Hi, and welcome to theCUBE, the leading source for insights into the world of technology and innovation. I'm your host Donald Klein, and today's topic is the market for autonomous vehicles and the ecosystem suppliers looking to tap into this brave new world of autonomous capabilities in our daily commute. To have this conversation I'm joined by Rudy Burger, managing partner at Woodside Capital. Rudy, welcome to the show. >> Thanks Don, it's great to be here. >> Great, so look, why don't we start off Rudy, why don't you tell us a little bit about Woodside Capital and your role there? >> Great, so I founded Woodside Capital about 20 years ago having started five different companies of my own, one of which I took public. We are a specialist M&A advisor. We work with so-called growth stage often venture-backed companies and help them find buyers that are usually much larger public companies. Our clients are usually US or European companies and we find buyers in the US, Europe, or Asia. >> Excellent, excellent, okay. And why don't you talk a little bit about your kind of specialty areas? >> So I focused my career, and certainly the work at Woodside Capital, on imaging technologies and as an enabling technology, and the products and markets that are enabled by imaging and increasingly computer vision. So nowadays that is autonomous vehicles, consumer technology, security surveillance, and digital health. So enabling technologies, the computer vision is the theme that binds those together. >> Okay, well, the thing that's on everybody's mind these days is autonomous vehicles, when are we going to get them? Very high profile for sure. Before the show we talking about the kind of two key ingredients to making this happen, the AI software which is kind of the brains of the operation and then also the sensors which enable all of the AI. So why don't we talk about the sensor world first, okay? Lot of discussion about there, so sort of does the brave new world of vehicles need lidar? Does it not need lidar? Are there other types of sensors coming along? What's your sense of that market and how it's looking for all of the different players in it? >> So, Don, I look at it from a sort of fairly basic standpoint. Humans have two very capable image sensors and a very powerful processor, and the degree to which the automotive manufacturers and so-called Robo-Taxi developers have decided it's necessary to sprinkle every sensor known to man, and I'm talking lidar, radar, ultrasound, thermal, and of course cameras, is to some extent a degree to which, you know, image sensors are not as good as our eyes today. Now, there are some areas in which we will probably always have technology as a help. For example, humans are not very good at seeing in the dark whereas a thermal technology can do that very well. But my overall belief is that it's never a good idea to bet against an incumbent technology, and in this case I'm talking about so-called CMOS image sensors which are the sensor that goes into pretty much every camera in the world now. It's never a good idea to bet against the incumbent technology being able to scale into a new market. Every time people have done that, they've been wrong. Back in the early days the debate was whether CMOS image sensors would ever be good enough to replace CCDs as the sensor technology, and of course now, you know, everything uses CMOS image sensors. In other markets there was a long period of time in which people were thinking that LCD panels would never be large enough to replace, you know, for television, for example, 50 inch and so forth. It was never going to happen, so we needed plasma TVs, we needed rear-projection TVs. But slowly but surely the incumbent technology, LCDs, expanded to that market. So my belief is that CMOS image sensors will evolve to a point at which they will replace the need for lidar in most applications. >> Interesting, so that's a very controversial statement, right? Because you've certainly seen a lot of emphasis on the development of new generation lidar capability. >> Over 100 lidar companies started over the last three, four years, and of course many of them will not be happy to hear me say that. There are two distinct markets and one is the so-called Robo-Taxi market, and the other is more of the consumer vehicle ADAS market, and I think we need to think about those separately because the economics behind both are very different. If you look at the Robo-Taxi market, those vehicles tend to be much more expensive and are relatively price-insensitive. So if they can improve safety a little bit by putting a lidar on there, you know, great, let's do it, multiple lidars because these vehicles will be in operation 24 by seven, and if each vehicle costs 200,000, $250,000, fine. When we talk about the mass market for automobiles, type of car that you and I might go down and buy, very different thing. And, you know, auto makers sweat the pennies, and so putting a one or $200 lidar in a vehicle, big decision. And to the extent that they can replace the need for that lidar with a much less expensive camera system, that's what they'll do. Bear in mind that Mobileye, which has been the biggest success story, acquired by Intel for $13.5 billion, second largest acquisition Intel ever made, they for the most part still run on one camera, forward-looking camera. That's it, no radar, no lidar, no thermal, one camera. So the clever use of image processing, computer vision, and one image sensor can do a great deal. >> Interesting, okay. Well, so I want to talk about the software in just a second, but just to kind of finish this point, so if you were advising a sensor company that's developing some next gen capabilities, whether lidar or other related technologies, is the point you're making here that there are certain segments of this industry which are going to be more attractive to your technology than others? >> Absolutely, yes. I mean, the first thing to recognize is that the automotive industry has never really been a particularly comfortable fit with the economics and timeline of venture capital. VCs need to invest and recoup and redeploy back to their LPs on an eight-year cycle. But the automotive industry moves quite slowly, perhaps Tesla are excepted, and what the first piece of advice I would give these companies is it's probably going to be three, four, five years before, even if you have the right technology, before that technology really starts generating any significant volume and revenue. So for many venture-backed companies, that's too long. So the first piece of advice is find pockets of revenue, right, beachheads if you will, where you can land your technology and start generating revenue before you get to the automotive market. And many of these lidar companies we just talked about are not going to last long enough to get to the automotive market because not only does the automotive market move slowly but the autonomous vehicle market keeps on getting pushed out to the right as the industry realizes that this is a big, hairy problem. And so I would say, what is it that your technology can do an order of magnitude better than any other technology? Focus on that and find some opportunities for revenue outside the automotive industry that will sustain the company on its way to the holy grail. >> Interesting, yeah, so find that alternative revenue source to get you to base camp, and then when the market's ready, climb that Everest to-- >> I've seen so many companies basically go out of business because they've set their sights on either the automotive market, and it's go for broke. We're not interested in, all these other things are distractions. You know, entrepreneurs don't have a plan B. Or this. We're going to get our technology into a smartphone, that's it. And there are possibly some other opportunities but it takes so long and it's so difficult to get your technology into a smartphone that they go out of business before they ever get to that point. >> Interesting, okay. So good advice for people looking to kind of apply their technology in this kind of a very difficult market, right, very complicated market. All right, well, then let's switch to the other side of it. So we were kind of talking about the key ingredients, right? Sensors but also AI and the software around that, okay, and there are some very big players developing the software. Tesla's had their Autonomy Day where they've showcased their technology. You've obviously got Google with their capabilities developing software. How do you make sense of this overall landscape because we do see a lot of smaller providers also trying to develop software here. >> So the first thing that I find fascinating about the automotive industry is that for the most part there is no software market. There's perhaps one exception of any scale, that's BlackBerry that sells the QNX software. They found a point within the entertainment console where they can license their software. But for all of the development and capital invested into automotive software, nobody is actually generating revenue, making a living, by licensing software. And one of the main reasons for that is that, you know, the automotive market, really since inception, has been a hardware business. This is a business of bending sheet metal, internal combustion engines, and software has really not played that big a role up until relatively recently. So even those companies that do have software technology have ended up selling it into the automotive supply chain as a piece of silicon, embedded on a piece of silicon, not as, you know, here's my software on a USB stick, right? I think that the whole software licensing model hasn't so far fit well, fit comfortably, with the automotive industry. And the other reason is that there's no standard platform. If I were to develop a piece of software, I can, in the PC industry, I can develop for Windows, I can develop for Mac, I can develop for an iPhone. There's no such thing in the automotive industry, and particularly in this new world of autonomous vehicles there is no standard platform. There are many different processors, Nvidia has staked an early claim there. And the reason that most of the companies developing autonomous vehicle technology have developed the so-called full-stack solution, everything from code running on the processor, integrated through the sensors and so forth, is for that reason, there is no standard platform. So each company has developed the whole solution for themselves, and there are many of them around here that have raised hundreds of millions of dollars, some cases billions of dollars, for that purpose. So there is, today, no software market for automotive in the same way that we think about it in other industries. >> Understood, understood. But in terms of the companies that are actually pushing the envelope on these kind of capabilities, right, so we're taking the best of AI, we're applying it to big data sets, and then hopefully being able to extract that to create capabilities for these vehicles, right? What's your sense of how far that's come along in-- >> Well, it's come a long way but, here I'm going to push the boat out a little bit. I don't believe that the so-called deep learning technology, which is the current state of the art for AI, it's the technology that has allowed computers to beat humans at chess, at Go, I don't think that that flavor of AI, that approach to AI, is ever going to get us to safe enough autonomous vehicles. And that's because it works extremely well in fairly well-bounded rules, rule-bounded games or any scenario like that, but can you imagine trying to teach your 16-year-old how to drive by showing them images of every situation that they might encounter, right? Impossible. It's an infinite, it's not a well-bounded set. And that's so difficult because we really haven't developed the technology to allow computers to learn, to have things like common sense, to infer, you know, well, this happened, so this is likely to happen. So I think we are going to need a whole new breakthrough in AI before we get to what is generally considered safe enough vehicles. >> Interesting, well then, maybe if we kind of apply your previous thought about sort of Robo-Taxis as maybe being the segment where you're going to see the most use of these newer sensor technologies. >> Rudy: Near term, yes. >> Exactly, what about maybe, is that sort of the same rules apply there for maybe the AI providers, that they're-- >> I think so and that's why they're all focused on that. I mean, from Uber to Waymo, they've all made the same calculation which is if you're running a fleet of vehicles, and so for example in Uber's case, the driver takes 80% of the fare and only 20% goes back to Uber, but if you can replace the driver with a computer, you can keep that vehicle on the road 24 by seven and you can keep 100% of the revenue. You don't need to pay the computer. So that's the calculus that they're all going through. But I think that many of them are making a fundamental mistake and I predicted recently that I think Uber, my prediction for 2020 is that Uber is going to divest its autonomous vehicle business and get back to the business that it should be focused on. Uber generates about $14 billion a year in gross revenue, so 20% of that, which is the piece that Uber keeps after the drivers take their 80, is what, 2.8 billion. Uber should be able to be an extremely profitable business on 2.8 billion of net revenue, but they're spending a huge chunk of money every year on R&D. Now, I would argue that Hertz and Avis have successful businesses. They're in the service, they're in the transportation business, but they didn't decide that they had to build their own cars in order to be in that business. My view, personal view, is that what Uber should be doing is saying, that's not our business, right? We are the world's best at managing this sort of peer-to-peer network crowdsourced transportation, if you will. And when some company, some Silicon Valley startup, comes out with safe enough technology, great, we'll use it, but we don't have to develop that ourselves. >> Well then, maybe just to play devil's advocate here for a second, what about it's a Robo-Taxi-type technologies being applied in bounded areas within metropolitan areas where the rules-- >> That's where it will start. >> Could be more-- >> I think that's where it will start, but I think part of the problem is that we have, perhaps in part due to all of the media hype around autonomous vehicles, we've been misdirected to thinking about autonomous vehicles as a replacement for the car we drive to work every day and I think that's the wrong way to think about it. I think that autonomous vehicles are going to show up in the market as an extension of public transportation. Right, you know, I get off the train and there's an autonomous vehicle waiting to take me for the last couple of miles to my office. >> And those last couple of miles would be sort of a regulated space. >> Rudy: May well be. >> Where the AI is more than capable of functioning. >> Right, and that, you know, yes. And so it's better to think about autonomous vehicles as not being a revolutionary technology but much more of an evolutionary technology. And in fact, most of these technologies are showing up in so-called ADAS technologies which are designed to make driving your regular car safer, lane assist, keeping you a safe distance. >> Donald: Maybe just explain that word, ADAS, and what that means. >> So ADAS stands for automated driver-assistance systems. So one of the first was cruise control, right, everybody's familiar with cruise control. And so to some extent ADAS is just building on cruise control. In addition to maintaining a constant speed, you can now stay in the lane. In addition to maintaining a constant speed, it will now automatically slow down if you get too close to the car in front. And so you can see ADAS as, you know, collision avoidance and so forth, not full autonomy, still have to have a driver in the driver's seat, but evolving year by year until one year we wake up and, yep, my car will actually drive me all the way from home to work without me intervening. Right, it's going to happen in that way. >> So incremental improvements. >> Incremental improvement. >> To ADAS as opposed to kind of revolution of autonomy. >> An overnight sensation. >> Yeah, right, coming from nowhere. Okay, understood. Well then, let's pivot from that then, okay. So let's talk about the automotive industry as a whole and sort of your thoughts on how this is all going to play out. >> Yeah, so there are some very interesting dynamics playing out in the automotive industry. Firstly, as good news, as a result of all of this money and innovation in the automotive industry, Detroit's actually coming back. I go there once or twice a year and you can feel the economy coming back in Detroit, but it's not going to come back around, you know, bending sheet metal. And the challenge that the automotive companies have is so much of their infrastructure and expertise has been built on construction, building a car, production lines to bend the metal, install the engine, and the internal combustion engine itself. And by complete coincidence, to some extent, we've got this confluence of all of these autonomous technologies and electric vehicles happening at the same time. Electric vehicles are much easier to make than internal combustion engines. Far fewer parts. It's one of the reasons that China has spun up about 20 different electric vehicle companies recently. So I think that long term, my prediction is that the automobile industry will go the same way that the personal computer industry went. When the PC first, you know, it was born by IBM, or Apple in some sense before that. There were dozens of companies producing different PCs and it was very much, they were expensive products, and, you know, relatively unusual. As the industry matured, the supply chains matured, and it became apparent there were really only two companies that were making a lot of money out of the PC industry. The companies that developed the software, operating system, and the companies that developed the processor, and all of the manufacturing went over to, in the PC's case, in Taiwan, right? And I think that exactly the same thing is going to happen with the automotive industry. Tesla today still actually makes cars, but I don't see them long term being in the car business because they're really a technology company. It's the reason I don't think Apple is ever going to get into the car industry. They make fantastic margins selling computer products. The gross margin selling a car, it's miserable. It can be single digits or teens. That would completely tank Apple's blended gross margin. So my prediction for the industry is there will be a few small pockets of very profitable businesses, particularly around the operating system, by which I mean the intelligence or the AI intelligence, and then the processor, whether it's a Qualcomm processor or a Nvidia processor or an Intel processor. And as with the PC industry, most of the profit will go there and most of the manufacturing will end up getting outsourced because that's not the value-add, you know, bending metal and so forth. >> Interesting, well, so in the kind of compute market today, right, we have this notion of sort of cloud-native, right, okay, and that many of the companies that are developing apps as relying on cloud-native infrastructure have a kind of technology lead that's going to be hard for some of the legacy providers to actually catch up on. Now, other people say that that's not necessarily the case and et cetera, right? Can you make the same argument for the electric car market, that some of the electric-natives might have a kind of sustainable advantage here? >> I should've added, today the cloud infrastructure companies, cloud services, SaaS companies, in the PC world, you know, very profitable, and I can see a similar cloud services model developing for the automotive industry. However, other than Tesla, it's very difficult to change the automotive channel to support that. I'll give you one example. Everyone that owns a Tesla is very used to the idea that, sometimes on a daily basis, a new bunch of software, operating system software, is downloaded overnight to your vehicle. You wake up in the morning and some new feature's been turned on, right? Tesla can do that because they bypass the entire dealership channel that has a complete lock on the rest of the industry. So for example, if GM wants to do the same thing as Tesla and do sort of what's called over-the-air, OTA, updates, software updates, they can't do that because their contract with the dealership network states that if there is service to be done on the vehicle, the vehicle has to be brought back to the dealership, and the dealerships consider updating the software on the vehicle as service. So their contract with the dealers actually prevent them from doing something that basic. So it's not just a technology issue. The whole channel and way vehicles get sold is going to have to change. >> Interesting, so that's the advantage that some of the new generation of vehicle manufacturers-- >> I would say that Tesla has a five year lead, technology lead, because they, like Apple, are vertically integrated. They're doing everything from user interface, fit and function, all the way down to the semiconductor. They're developing their own semiconductors now. So they have become a fearsome competitor in the electronic vehicle space because they've been doing it for longer than the other major auto companies. They've figured out a lot of the, you know, tricks and techniques of how to extend mileage and so forth. And so they have a substantial lead in the industry at this point, despite the fact that over the next 12, 18 months, every automotive company is going to be coming out with their own flavor of electronic vehicle. >> So then it's more than just about having electric drivetrains, et cetera, right? It's about the whole suite of capabilities. >> It's a systems engineering challenge. >> Interesting, okay. All right, well Rudy, we're going to have to leave it there, okay, but I think everything you've told us is, it sounds like some good news for some of the Tesla stock holders at the moment. >> I think so. >> Okay, well. (laughs) We'll pass on making an opinion about that, but great conversation, thank you for your insights. Okay, this is Donald Klein, host of theCUBE, here with Rudy Burger, managing partner at Woodside Capital. >> Rudy: Great, thank you, Don. (upbeat music)

>> Narrator: From Denver, Colorado, it's theCUBE. Covering Super Computing 17. Brought to you by Intel. (techno music) Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in Denver, Colorado at the Super Computing Conference 2017. About 12 thousand people, talking about the outer edges of computing. It's pretty amazing. The keynote was huge. The square kilometer array, a new vocabulary word I learned today. It's pretty exciting times, and we're excited to have our next guest. He's Bill Jenkins. He's a Product Line Manager for AI on FPGAs at Intel. Bill, welcome. Thank you very much for having me. Nice to meet you, and nice to talk to you today. So you're right in the middle of this machine-learning AI storm, which we keep hearing more and more about. Kind of the next generation of big data, if you will. That's right. It's the most dynamic industry I've seen since the telecom industry back in the 90s. It's evolving every day, every month. Intel's been making some announcements. Using this combination of software programming and FPGAs on the acceleration stack to get more performance out of the data center. Did I get that right? Sure, yeah, yeah. Pretty exciting. The use of both hardware, as well as software on top of it, to open up the solution stack, open up the ecosystem. What of those things are you working on specifically? I really build first the enabling technology that brings the FPGA into that Intel ecosystem. Where Intel is trying to provide that solution from top to bottom to deliver AI products. >> Jeff: Right. Into that market. FPGAs are a key piece of that because we provide a different way to accelerate those machine-learning and AI workloads. Where we can be an offload engine to a CPU. We can be inline analytics to offload the system, and get higher performance that way. We tie into that overall Intel ecosystem of tools and products. Right. So that's a pretty interesting piece because the real-time streaming data is all the rage now, right? Not in batch. You want to get it now. So how do you get it in? How do you get it written to the database? How do you get it into the micro-processor? That's a really, really important piece. That's different than even two years ago. You didn't really hear much about real-time. I think it's, like I said, it's evolving quite a bit. Now, a lot of people deal with training. It's the science behind it. The data scientists work to figure out what topologies they want to deploy and how they want to deploy 'em. But now, people are building products around it. >> Jeff: Right. And once they start deploying these technologies into products, they realize that they don't want to compensate for limitations in hardware. They want to work around them. A lot of this evolution that we're building is to try to find ways to more efficiently do that compute. What we call inferencing, the actual deployed machine-learning scoring, as they will. >> Jeff: Right. In a product, it's all about how quickly can I get the data out. It's not about waiting two seconds to start the processing. You know, in an autonomous-driven car where someone's crossing the road, I'm not waiting two seconds to figure out it's a person. Right, right. I need it right away. So I need to be able to do that with video feeds, right off a disk drive, from the ethernet data coming in. I want to do that directly in line, so that my processor can do what it's good at, and we offload that processor to get better system performance. Right. And then on the machine-learning specifically, 'cause that is all the rage. And it is learning. So there is a real-time aspect to it. You talked about autonomous vehicles. But there's also continuous learning over time, that's not necessarily dependent on learning immediately. Right. But continuous improvement over time. What are some of the unique challenges in machine-learning? And what are some of the ways that you guys are trying to address those? Once you've trained the network, people always have to go back and retrain. They say okay, I've got a good accuracy, but I want better performance. Then they start lowering the precision, and they say well, today we're at 32-bit, maybe 16-bit. Then they start looking into eight. But the problem is, their accuracy drops. So they retrain that into eight topology, that network, to get the performance benefit, but with the higher accuracy. The flexibility of FPGA actually allows people to take that network at 32-bit, with the 32-bit trained weights, but deploy it in lower precision. So we can abstract away the fact that the hardware's so flexible, we can do what we call floating point 11-bit floating point. Or even 8-bit floating point. Even here today at the show, we've got a binary and ternary demo, showcasing the flexibility that the FPGA can provide today with that building block piece of hardware that the FPGA can be. And really provide, not only the topologies that people are trying to build today, but tomorrow. >> Jeff: Right. Future proofing their hardware. But then the precisions that they may want to do. So that they don't have to retrain. They can get less than a 1% accuracy loss, but they can lower that precision to get all the performance benefits of that data scientist's work to come up with a new architecture. Right. But it's interesting 'cause there's trade-offs, right? >> Bill: Sure. There's no optimum solution. It's optimum as to what you're trying to optimize for. >> Bill: Right. So really, the ability to change the ability to continue to work on those learning algorithms, to be able to change your priority, is pretty key. Yeah, a lot of times today, you want this. So this has been the mantra of the FPGA for 30 plus years. You deploy it today, and it works fine. Maybe you build an ASIC out of it. But what you want tomorrow is going to be different. So maybe if it's changing so rapidly, you build the ASIC because there's runway to that. But if there isn't, you may just say, I have the FPGA, I can just reprogram it to do what's the next architecture, the next methodology. Right. So it gives you that future proofing. That capability to sustain different topologies. Different architectures, different precisions. To kind of keep people going with the same piece of hardware. Without having to say, spin up a new ASIC every year. >> Jeff: Right, right. Which, even then, it's so dynamic it's probably faster then, every year, the way things are going today. So the other thing you mentioned is topography, and it's not the same topography you mentioned, but this whole idea of edge. Sure. So moving more and more compute, and store, and smarts to the edge. 'Cause there's just not going to be time, you mentioned autonomous vehicles, a lot of applications to get everything back up into the cloud. Back into the data center. You guys are pushing this technology, not only in the data center, but progressively closer and closer to the edge. Absolutely. The data center has a need. It's always going to be there, but they're getting big. The amount of data that we're trying to process every day is growing. I always say that the telecom industry started the Information Age. Well, the Information Age has done a great job of collecting a lot of data. We have to process that. If you think about where, maybe I'll allude back to autonomous vehicles. You're talking about thousands of gigabytes, per day, of data generated. Smart factories. Exabytes of data generated a day. What are you going to do with all that? It has to be processed. We need that compute in the data center. But we have to start pushing it out into the edge, where I start thinking, well even a show like this, I want security. So, I want to do real-time weapons detection, right? Security prevention. I want to do smart city applications. Just monitoring how traffic moves through a mall, so that I can control lighting and heating. All of these things at the edge, in the camera, that's deployed on the street. In the camera that's deployed in a mall. All of that, we want to make those smarter, so that we can do more compute. To offload the amount of data that needs to be sent back to the data center. >> Jeff: Right. As much as possible. Relevant data gets sent back. No shortage of demand for compute store networking, is there? No, no. It's really a heterogeneous world, right? We need all the different compute. We need all the different aspects of transmission of the data with 5G. We need disk space to store it. >> Jeff: Right. We need cooling to cool it. It's really becoming a heterogeneous world. All right, well, I'm going to give you the last word. I can't believe we're in November of 2017. Yeah. Which is bananas. What are you working on for 2018? What are some of your priorities? If we talk a year from now, what are we going to be talking about? Intel's acquired a lot of companies over the past couple years now on AI. You're seeing a lot of merging of the FPGA into that ecosystem. We've got the Nervana. We've got Movidius. We've got Mobileye acquisitions. Saffron Technologies. All of these things, when the FPGA is kind of a key piece of that because it gives you that flexibility of the hardware, to extend those pieces. You're going to see a lot more stuff in the cloud. A lot more stuff with partners next year. And really enabling that edge to data center compute, with things like binary neural networks, ternary neural networks. All the different next generation of topologies to kind of keep that leading edge flexibility that the FPGA can provide for people's products tomorrow. >> Jeff: Exciting times. Yeah, great. All right, Bill Jenkins. There's a lot going on in computing. If you're not getting your computer science degree, kids, think about it again. He's Bill Jenkins. I'm Jeff Frick. You're watching theCUBE from Super Computing 2017. Thanks for watching. Thank you. (techno music)

>> Announcer: Live from Silicon Valley, it's theCUBE, covering Mobile World Congress 2017. Brought to you by Intel. >> Okay, welcome back, everyone. We're live here in Palo Alto, California for SiliconANGLE Media's theCUBE special two-day coverage of Mobile World Congress in Barcelona, Spain. As people starting to get ready to take that nap to go out all night in Barcelona after they've had their tapas and wine we're here in California breaking it all down. Two days of coverage, this is end of day two in Spain. We're in the middle of it here, and breaking down the analysis, covering all the news, commentary, identifying the trends and talking to the folks here in the Bay Area that can add value to the conversation, and our next guest is Bob Stefanski, who's the managing director of eLab, located in Palo Alto, a venture capitalist making investments and really a key player bridging Silicon Valley with Michigan Motor City here bringing the two worlds together as the autonomous vehicles and the automotive industry's under massive disruption and change, and the car companies know about it and they're not afraid of it. Ford's here, GM's here, they're all here, and now we have Bob Stefanski here in theCUBE. Bob, good to see ya, thanks for coming in. >> John, thanks for having me on. It's good to be here. >> I love this story, and I think this is not really well documented, but this is the beginning of what's been happening for a while, kind of as an outpost to Michigan and Motor City, you have some satellite offices in Palo Alto or Silicon Valley. They're close to Stanford, close to Cal, close to a lot of the research, but now it's a change where you're starting to see Ford, GM, all the car companies, BMW, big venture fund as well, all here in Silicon Valley because the software defined blank is everything, so software-defined radios in 5G, big story at Mobile World Congress, software-defined networks, the world is software-driven, so they're here. You're bridging the investments, trying to identify the key trends. >> Bob: You bet. >> To help identify this new game-changing technology that's going to bring a whole new world together, and certainly Intel and others are changing the networks, creating an end-to-end architecture digitally to bring autonomous vehicles, media entertainment, smart cities, the smart home, and we're seeing Alexa, Google's got their device, and you're seeing smart cities. What's the big bridge being built around? I mean, obviously, the cars themselves are changing. What is this bridge between Silicon Valley and Michigan Motor City? Obviously, that's a big part of Uber and whatnot. >> Absolutely, John, you know, I grew up in Michigan, I grew up in the days before there was a single chip, I think, in cars. I worked for General Motors when I was a summer intern in the early '80s in the engineering group there. There was a very distinct automotive culture. I then fast forward 20 years, and I'm in Silicon Valley. I've spent the majority of my career here in Silicon Valley doing Silicon Valley things, so software, enterprise software was where I spent most of my career with TIBCO software. We are now bridging these two things. We're bridging, the automotive industry is, I think we all know, anyone who's paying attention, the car now has a lot of chips in it, and it's about to have a lot more, the car is becoming a data center on wheels. It's becoming another mobile device, a very big mobile device, and the really neat thing is with, we're the only venture fund with offices and partners located in both places. We have fairly deep networks and connections into the whole Michigan ecosystem back there in automotive, and of course, we're out here in Silicon Valley as well. It's been fascinating to see after spending, after having that early childhood experience, young adult experience as I was growing up in the auto industry, and really kind of the heyday of the auto industry, maybe the beginning of the decline in the '70s and early '80s, and then having sort of spent the career working on the latest, greatest, newest technologies as they've come along out here in Silicon Valley. This is a fascinating time to see these two now finally merging together with autonomous vehicles. >> One of the things that we're seeing in Intel, obviously the bellwether, and they always have the long game going and make the big bets, and autonomous vehicles and virtual reality is that showcase, but what I find interesting and I want to get your thoughts on and reaction to is that I shared on my Facebook feed a post by autoblog.com that says, "Race for autonomous cars is over in Silicon Valley." And they were kind of pointing to the obvious things that people are seeing today, which is myopic and narrow in my opinion, but obviously Apple kind of tapped out of building a car, and I think a lot of people thought, "Oh, Apple should build a car. "They built a watch, why not build a car?" Obviously, they forgot about Teslas here, so I'm not sure what they're thinking, but I think they missed the point that it's bigger than the actual car. Could you share some color commentary around the mindset of Detroit? Because we're seeing that certainly Ford's not lookin' the other way, they have their finger on the pulse. Others do as well. What is the general mindset for the folks in both ecosystems and how are they working together right now? >> Sure, that's a great question, John. And you said it right at the outset, look, all the autos are here, and they're here in our backyard in Palo Alto. They've really sort of migrated here over the last five, seven years probably. GM is here, Ford is here in a big way, BMW's here, Mercedes' here. So they all obviously recognize that the car's becoming all about technology, and they need to be, if they're going to be a key part of that in the future, they need to be out here, and they need to be understanding that, on the other hand, making cars is hard. Making cars is not a simple thing, and this is where 70% of auto research in the U.S. is still happening in Michigan in the Detroit area. Michigan has a very high density of automotive engineers, and integration engineers and integrating IT with the autos and so forth. There's a lot of talent there, there's a lot of experience there. I think, you know, frankly probably the biggest and most interesting thing in this bridge is going to be to watch the cultures either integrate or not, and there's a lot of talk about who wins and the autos can't move fast enough, and that may be the case, but we'll find out. I'm not so sure. They know how to compete and there's a lot of smart people. >> There's no way that Detroit's going away. >> Bob: Not at all. >> My view is they're very solid, and I think they got good self-awareness, and I think if you look at the signals, I would say that I'm pretty confident it's just a matter of how they get reconfigured in this new value-creation model around 5G and whatnot. But I want to get your thoughts on another point, which is if you look at what the iPhone did, that created a new class of app developer and that, I would call them, on one hand artisan developers, people who are composing much more design-centric, obviously, and then, you still had the hardcore developers, and that was lower in the stack, but also other harder problems. But when you talk about automotive, there are some serious technology challenges that require, I won't say old-school engineering, but really hardcore engineering. You're talking about wireless, which is a physics issue, you have all kinds of policy challenges, but really hardcore engineering and software development. I'm not discounting what the app guys are doing, but certainly there will be plenty of apps like all that more the finishing touches in, say, cars for instance. What are some of those technologies because that's really where you need to see the classic double-E, computer science, physics gurus, the real PhD kind of guys. What's your thoughts and what trends do you see in that hardcore area? >> Absolutely, you know, I mean, look, we all know that cars are no longer about just axles and engines, and those hard things. But I think when we make this transition to highly automated, to fully autonomous vehicles, the technologies that are driving that, the fundamental technologies and the really hard stuff are around sensors, right. We're constantly developing newer, faster, better, further range, more precise sensors, so we're talking about Lidar, we're talking about of course, Mobileye and what's happening with the camera and vision processing. We're talking about even radar, a 1940s technology that actually is changing very fast. There's a lot of interesting things happening. >> AI's an old technology coming back now and getting rebooted with cloud computing and whatnot. >> Yeah, absolutely, and then, connecting all that to the cloud, right. I think the hardest, and I think we talked about this before, probably still the single hardest piece and the point of this fear on this is artificial intelligence at the end of the day. It's the same stuff that's driving virtual reality, it's the same stuff that's driving a lot of different things right now, but it's also true in self-driving cars. These things, when you make a car, first of all, it's got to be safe. It has got to be safe. The Department of Transportation, the government regulatory interest is in safety. To make a car safe, they have to be tested, tested, tested, tested, what's that about? Well, when autonomous takes over, it's no long John Furrier driving that car, it's the AI driving the car, right? How do you make it AI smart? >> The crash test dummy's inside AI. >> Right, this is fundamental deep learning. This is fundamental deep learning that the guys at Google know as much as anybody in the world and Facebook and all, you know, that we all know about the arms race in artificial intelligence, but that's at the core of what's happening in self-driving vehicles, and most of that talent, the talent is spread out, it's all over the world, but there's a lot of it out here. And they know they need to have those engineers here. >> What's interesting about your background, you mentioned when we started this segment, you have an enterprise software background in Silicon Valley and you've been very successful, it's interesting, we were talking yesterday and we kind of validated this morning on our opening segment around Mobile World Congress, it's a two-show game right now. It's kind of a bipolar show. You got devices, the new phones, the glam and the sizzle, Samsung and so on, so forth, LG. >> Bob: Can't wait. >> And then you got the TelCo show, which is, TelCo's trying to figure things out, but what's interesting is what we noticed is that there's really a trend between enterprise computing concepts, network data center with consumer clash, so there's a direct collision course between the TelCos which serve as consumers, but the infrastructure challenges are all enterprise. >> Bob: Right, right. >> And the number one thing that's key there is integration and ecosystems. So, you kind of have the right background for this, so we want to get your thoughts on ecosystem integration concepts where a lot of boats in the harbor, so rising tide will float all boats, we see that as a trend, but also integrating. You mentioned the testing, so it's not one company's going to do all this. >> It's not one company that's going to do all this, and in fact, it's going to one of the more complex integrations we've ever undertaken because we're going to have to have those automotive engineers, we're going to have to have those, the software developers, we're going to have to have the AI guys, we're going to have to have the sensor guys, and it's all going to the cloud ultimately. And don't forget GPS, you got GPS. You got a lot. >> Connectivity challenges. Mobility. >> Connectivity challenges, and of course, 5G when 5G comes down the line is going to be a critical part of this as well. You're also going to have smart cities, you're going to have infrastructure embedded in the environment, and in particular, the highly dense areas is where it'll happen first. It's not going to, rural America and so forth, they're going to be probably driving their cars without the embedded sensor for a while, but there are a lot of different components to integrate. >> We had a CTO on earlier before, Val Bercovici, he was talking about the cloud native architecture really plays well in this market because it's not so much about the one car, it's about the one cars in relations to thousands of other cars that are self-driving. It's a multi-touch data equation. Alright, Bob, final question I want to get to you is what are you investing in? What are some of the things that you're looking at? Can you share? I know some of the stuff is pretty stealthy on your end, 'cause it's pretty high end, but can you share any, show a little leg on investments you've made? >> You bet, you bet. Yeah, John, we're, some of the, probably the coolest stuff I can't talk about right now, you're right. Hint hint, it's in some of the things I've already talked about. We're certainly in artificial intelligence. We have a portfolio company in that. We're looking at others. In better sensors, some of the sensor areas I talked about, we are in the process of looking at companies. We have investments in the connected space, not autonomous, but connected space, which is also going to be a very big and important part of this. Company called Aperia right up here that is, at the end of the day, they're tire inflation, but it's all about data. They do automated tire inflation, connected, they'll be connecting every fleet in America. And so we're-- >> It's those boring little efficiency areas that really yield a lot of cash. We just talked about a guest about waste optimize, waste disposal industries. >> Absolutely. >> Little things that are luring billion dollar innovations. >> Little things, very big problems, right, and it's where you can marry things like tire inflation on commercial fleets with data, with lots of data that we never had before. And then apply artificial intelligence to that to learn what's happening and map an entire fleet or multiple fleets nationwide, worldwide, collect all that data and start to correlate and understand what. Those are the problems that are, where a lot of value can be added actually with these technologies. >> It's super interesting, and I think you got a great opportunity, congratulations. Great to see the bridge between Silicon Valley and Michigan Motor City, and I think that's anecdotally means automotive, but there's probably other bridges your connecting, too. Bob, thanks for coming in and sharing. Final question for you while we got you, got a little bit more time. What premises would you, are you betting on? I mean, everyone has a premise, and you mentioned before you came on-camera that one of your premises is that automotive won't miss mobility. What other premises are you investing, what thesises are you building around? >> Well, look, for the, are you talking about autonomous vehicles or much--? >> For the bridge fund and how you're looking at the future of autonomous driving in the connected ecosystem, what are the premise, what's on the premise? >> The premise there is that we're in for what I think is going to be the biggest change in the biggest thing to happen in transportation ever, but it's not just transportation, so we're looking at areas that are not autonomous per se, but that are going to be fundamentally impacted, so services. We're talking about things like insurance, we're talking about all the shared services that are going to come out of this. Medicine is going to probably change, and there's some interesting plays there. And so all of this sort of periphery that is going to be disrupted, we're trying to look five years, 10 years ahead and look at how life is going to change, people's individual experiences are going to change, and how new services, in particular shared services, are going to be enabled by autonomy. >> Bob Stefanski here inside theCUBE, breaking down his commentary and direction of his investments bridging Silicon Valley with Michigan Motor City, or really looking at the autonomous future of vehicles and transportation. This is theCUBE, I'm John Furrier. We'll be back with more coverage and analysis of Mobile World Congress 2017 after this short break. (upbeat electronic music)