 from Las Vegas. It's theCUBE, covering AWS re-invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. Hey, welcome back everyone. Here at AWS re-invent 2018, there's 60 years of CUBE coverage, two sets, wall-to-wall coverage here, two more sets in other locations, getting all the content, bringing it in, ingesting it into our video cloud service on AWS. David, some people don't know that we have that video cloud service, but we're going to have a lot of fun. Ton of content, ton of stories, and a special analyst segment, Jerry Chen, guest here today, CUBE alumni, famous venture capitalists at Greylock Partners, partnering with Reid Hoffman, founder of LinkedIn, great set of partners at Greylock, great firm, tier one, doing a lot of great deals, rock set, recent one. Thanks, yeah. You're also, on the record, six years ago, calling the shot at Babe Ruth, predicting the future. You got a good hand on it. You got VM where you have the cloud business, now you're making investments. You're seeing a lot of stuff on the landscape, certainly as a venture capitalist, your funding projects. What better time now of innovation to actually put money to work, to take market share? And then the big guys are getting bigger, they're creating more robust platforms, the game is changing big time. I want to get your perspective. Dave, so Jerry, what's your take on the announcements, slew of announcements, which ones jumped out at you? You know, I think, so there's kind of two or three errors. There's definitely the hybrid cloud story with the outpost. There's a bunch of stuff around ML and AI services, and a bunch of stuff on data and storage. And for me, I think what they're doing around the ML services, the prediction, the personalization, the text OCR, what Amazon's doing at that app layer is now creating AI building blocks for modern applications. So, you want to do forecasting, you want to do personalization, you want to do text analysis. You now have a simple API, if you basically build this modern, A-powered app. So, he's doing to the app infrastructure layer, what he's done to the cloud infrastructure layer by deconstructing the services. And API is obviously the center, that's what web services are. So, a question for you is, do you see that the core cloud players, obviously Amazon, Big Lead, Google, Microsoft, others, it's a winner take most, you called that six years ago, and that's true. But as they grow, there's going to be now new cloudification going on for business apps, new entrepreneurs coming to market, who's vulnerable, who wins, who loses, as this evolution continues because it's going to enable a lot of opportunity. Yeah, well, I mean, Amazon and cloud in general is going to create a lot of winners and losers, like you said. So, I think you have a shift of dollars from on-prem and old legacy vendors, database storage, compute to the cloud. So, I think there's a shift of dollars for winner and losers. But I think what's going to happen is, with all these services around AI, ML, and cloud as a distribution model, a lot of applications are going to be rebuilt. So, I think the entire application stack from all the big SaaS players to small SaaS companies, you can see this kind of a long tail of new SaaS applications being built on top of the cloud that you didn't see in the past. And the ability to get to markets faster. So, the question I have for you is, if you're an entrepreneur out there looking for funding, and I can get to market quicker, what's the playbook? And two, Jassy talked on stage about a new persona, a new kind of developer. One that can rethink and reimagine and reinvent something that someone else has already done. So, if you're an entrepreneur, you got to take someone else's territory. So, how does an entrepreneur go out and identify who's lunch to eat? So, if I want to take down a company, I got to have a strategy. How do I use the cloud to? I think it's always a combination when you're, when you're a founder, you're thinking of attacking markets, combination of, where are the dollars? Where can I create some advantage IP or advantage angle? And thoroughly, where do I have a distribution advantage? How can I actually get my product in the hands of the users that differently? And so, I think those are the three things. You find intersection of a great market, you have a unique angle, and you have a unique route to market, then you have a powerful story. So, if you think about cloud change in the game, think about like the mobile app ecosystem for consumers. That's also a new platform, a new distribution method, right the mobile app stores. And so, what happened? You had a new category of developers, mobile developers, creating this long tail of 1000 apps for everything from groceries to cars like your fantasy football score. So, I think you're going to see distribution in the cloud, making it easy to get your apps out there. You're going to see a bunch of new markets open up because we're seeing verticals like healthcare, construction, financial services that didn't have special apps beforehand be disrupted with technology, right? Autodesk just bought PlanGrid for $800 million. I mean, that's unheard of construction software company. So, you're going to see a bunch of new verticals like that be opened up. And then I think with this cloud technology with compute storage, network becomes free and have this AI layer on top of it, you can power these new applications using AI that I think is pretty damn exciting. Yeah, so you described this sort of, we went from client server to the cloud, got a whole bunch of new app providers. Obviously Salesforce was there, but Workday, Service Now. What you described as a set of composable digital services running on top of a cloud. So that's ripe for disruption. So, do I have to own my own data centers of a big SaaS company that, what happens to those big guys? I don't think you have to own your, well, you don't have to own your own, you don't have to own your own data center as a SaaS company. But you could if you wanted to, right? So, at some point in scale, a lot of the big players build their own data centers. Like Airbnb is on Amazon, but Dropbox built their own storage on Amazon early than their own data center later. Uber has their own data center, right? So you can argue that at some point in scale it makes sense to build your own. So you don't need to be on Amazon or Google or Azure Start, but it does give you a head start. Now the question is in the future, can you build a SaaS application entirely on Amazon, Azure or Google without any custom code, right? Can you hydrate what I call private SaaS? Like a single instance of my SaaS application for you, John, for you, Dave, that's your data, your workflow, your information personalized for you. So instead of this multi-tenant CRM system like Salesforce, I have a custom CRM system just for Dave, just for Jeff, just for Jerry, just for the queue, right? I think that's definitely a trend I would see happening. It's what Infor is trying to do, right? Charles Phillips, friends don't let friends build data centers, but they still got a big loss in legacy there, but it's an interesting model, focus on verticals or micro verticals or like a healthcare example that you're giving and a lot of potential. Well, here's why I think I like this, because I think, and I said this before in the queue, maybe it's not the best way to say it, is that if you look at the benefit of AI, data-driven, the quality of the data and the power of the compute has to be there. AI will work well with all that stuff, but it's also specialized around the application's use case. So you have specialism around the application, but you don't have to build a full stack to do that. You can use a horizontally-spalable cloud distribution system in your word and then only create custom work loads for the app where machine learning's involved. And AI, that's unique to the app. That's differentiation. That could be the business model or the utility. So multi-Tennessee could exist in theory at the scalable level, but unique at the top of the level. So yes, I would say I'd want that hosted in the most customized, agile, flexible way. So I would argue that that's the scenario. I think that's the future. I mean, one of my, I think we're saying today, like friends don't let friends build data centers anymore. You know? You probably don't need to build a data center anymore because you can actually build your own application on top of one of the two or three large cloud providers. So it'd be interesting to see what happens in the next three, four years. We're going to see kind of a thousand flowers bloom of different apps. Not everyone's going to make it. Not everyone's going to be a huge sales force-like outcome, but there'll be a bunch of applications out there. And the IoT stuff is interesting to me. So we're observing a lot of what the IT guys are doing. It reminds me of people trying to make the Windows mobile phone. It's just trying to force IT standards down to IoT. What I've seen from AWS today is a more of a bottoms up approach. Build applications for operations technology people, which I think is the right way to go. What are you seeing in IoT, IoT apps? What's the formula there? I think what Amazon now say with their time series database, right, their time stream prediction engine, plus their outpost offering with VMware themselves, you're really seeing a combination of IoT and Edge, right? And so the whole idea is one, there's a bunch of use cases for a time series in IoT because sensor data, cameras, self-driving cars, drones, et cetera. There's this more data coming at you. And Splunk has proven that big time. Correct, Splunk's a new 18 billion market cap company all on time series data. But number two, what's happening is it's not necessarily centralized data, right? It's happening to Edge, your self-driving car, your cell phone, et cetera. So outpost is really a way for Amazon to get closer to the Edge by pushing their compute towards your data center, towards remote office branch office, and get closer to where the data is. So I think that'll be super interesting. Well, the elastic inference engine is critical. Now we got elasticity around inference, and then they got the chip set that worked in Ferencia that can work with the elastic service. That's a powerful combination. The AI plumbing war between Google and TensorFlow as technology versus like PyTorch, Google TPUs versus what Amazon is doing with inference chips today, which is what I'm sorry, Microsoft for analysis is doing, is fascinating to watch in terms of how you had a kind of an Intel NVIDIA duopoly for a long time, and now we have Intel NVIDIA, and then everyone from Amazon, Google, and Microsoft doing their own silicon. It's pretty fast. What was the stat? He said 85% of the TensorFlow, Cloud TensorFlow's running on AWS? Makes a lot of sense. Big numbers. Aurora's customers logo slide doubled. But let's break down real quick to end the segment with the key areas that we see going on, at least in my perspective, I want to get your reaction. Storage, major disruption. He emphasized a lot of that in the keynote. He spent a lot of time on stores. Actually, I think more than EC2, if you look at it. Two, databases, database war, storage reconfiguration, at a Holy Trinity networking storage and compute that's evolving. Databases, SageMaker, machine learning, all there, and then over the top, yesterday's announcement of satellite as a service. That essentially kills the edge of the network because there is no edge if we have space satellites shooting connectivity to any device, the world is no more edge. It's everywhere. Your thoughts, those are areas. Which one pops out as the most surprising or most relevant? I think it's consistent Amazon strategy. On the lowest layer, they're trying to draw the cost of zero. So on storage, cheaper, cheaper, cheaper, they're driving the bottom layer to zero to get all your data. I think the second thing in the database layer, it makes sense, it's not open source, right? Time scale or time series is not, time stream is not, their open source database is their own. So open source, low cost, the lowest layer, their database stuff is mostly their own. Aurora, Dynamo, time stream, right? Because there's some level lock in there, which I think customers are worried about. So that's clever, it's not by accident, that's all proprietary. And then ML services on top of that, that's all cares for developers and it's API locking. So clearly, low cost, open source at the bottom. Proprietary data sources that they're trying to own and then API's on top of it. And so the higher up in the stack, the more and more Amazon you look, the more and more Amazon you have to adopt as kind of a lock in stack. So it's a brilliant strategy that you guys have been executing for the past six, seven years as you guys have seen firsthand. I think the most exciting thing and the most shocking thing to me is this move towards this battle for the AI front, this ML AI front. I think we saw like ML's the new sequel, right? That's the new war, right? It gets Amazon, Google, on top. And that's going to be the future of applications because this is a table thing. But you're right on it. It's a knife fight for the data and then you layer on machine intelligence on top of that and you get cloud scale and that's the innovation engine in the next 10 years. All right, Jerry Chen just unpacked the state of the union of cloud. Of course, as an investor, I got to ask the final question, how are you investing to take advantage of this wave versus being on the wrong side of history? Um, you know, I have frameworks for everything. There's a framework on how to attack the cloud vendors. And so I'm looking at a couple of things. One, a seams in between the cloud, right? Or in between services because they can't do everything well and they're kind of these large continents, right? Amazon, Google, Azure. So I'm looking for seams between the three of them. I'm looking for two deep areas of IP that they're not going into that you actually have proprietary tap. And then verticals of data, like source of the data or workflows that these guys are in great. And then finally kind of cross data, cross cloud solutions. So something that gives you the ability to run on-prem, off-prem, Microsoft, Google, Azure. Yeah, fill in the white spaces that are big white spaces. They're big white. And then hope that could develop into good. Jerry Chen, partner at Greylock Partners, formerly VMware, part of the V-Mafia, friend of theCUBE, great guest analysis here with Dave Vellante and John Furrier. Thanks for watching us. Stay with us, more live coverage. Day two of three days of wall-to-wall coverage at ReInvent, 52,000 people. The whole industry's here. You can see the formations. We're getting all the data. We're bringing it to you. Stay with us.