 Welcome back, everyone, to SuperCloud 4's episode four, JVAI, I'm John Roy, Dave Vellante. We've got, wrapping up day one, you've got two closing sessions. First, we're interviewing Howie Shue, Cube alumni. Now, Cube host, as of today, also senior executive at Palo Alto Networks, heading up the AI machine learning team over there. Howie, great to have you back, and congratulations on a great panel. Thank you. It's a lot of fun. It was really good. You were nervous, where you did great. You did a poll, you did some prep work, get all your ducks lined up. I did all the homework. You did your homework. The key is the guests, though, right? I mean, the guests, you did a great job asking the question, but having a great guest from Salesforce, Google, and Microsoft, that they're so articulate, and so technically oriented, but can talk in business terms, makes for a great panel. Yeah. So, well done. So, the panel we want to review real quick with you is AI, Enterprise AI, Hyper Reality, did a poll. You had VJ from Microsoft, laid out great commentary there. We had Warren from Google, and Jay Ash from Salesforce, all senior executives. Really interesting perspective. Enterprise sees great hope, but it's here. And we had Intel's executive just commenting like, one comment is like, why don't I give up my co-pilot? It's just, they didn't have co-pilot last year. So, what's your takeaway as looking at now, zooming out and looking at yourself in the panel, what was the big takeaway? Because you had some serious hitters there. Big names, a lot of projects, all legit AI going on and all those companies. So, zoom out a little bit, right? Everyone is asking, hey, this enterprise, software, adoption of the general AI, is that a hype or reality? What is the killer applications? Because we all talk about it, but how many are in production and then are there any killer applications? My one liner takeaway on this one question is, it's really about giving super power to everyone from all walks of life. That's actually pretty amazing, right? Because whether you are doing programmer, product manager, whatever the things you are doing, you are going to get super power and then do something fundamentally quite different on top of what you have been doing. Some of what you have been doing may be replaced by co-pilot, but you are suddenly actually empowered to do a lot more things. That is my one liner takeaway because it's not just the killer applications, it's actually giving super power to everyone. But that's what it was, the killer app was accessed for all, right? To drive productivity. It's interesting in tech and business schools, you hear terms like competitive strategy, competitive advantage. The word that I always love was disruptive enabler. And with the consumerization of AI, what's coming out of day one here, Dave, and how I would say is that you're seeing the consumerization of AI in the hands of people where they go, oh, magic, or I like this, I can feel the benefit, I can see some future, but how your point about that enablement, that's a disruptive enablement because the creativity, even Warren said it on the cute beer, he said he sees more creativity coming, more you say productivity, a room from Intel said knowledge workers. All the same language for enablement. This is like the, this is the key thing, the enablement, what will AI enable? And enablement not just for incrementally better, incrementally productivity, right? It's actually, think out of the box, step-function improvement, right? Something very different. I've been having conversations with some of my friends, they are the, whether the MLE, machine learning engineer, or data scientists in some big companies, right? The boundary between data scientists and then machine learning engineers are kind of getting, the boundary is getting blurry. So you need to rethink about. You don't need to have ADHDs on staff. I heard one of your comments on your panel is interesting. What would you give a bunch of PhD students or experts? Imagine having that capability, so that step-function change is interesting. I guess my next question is, where are we in your mind, okay? Enterprise always feel a little bit behind because there's so much to going on, data, governance, security, consumer, that starts just slinging code, trying to launch a company. Then you got the big hyperscalers with the cloud scale out there. How do you see the interplay between, say, the hot startup, you know, throwing the arrows at the big guys, trying to, David versus Goliath, the big whales, and then the, I won't say slow-moving enterprise, but traditionally slow-moving to implement. You know, look, you know, the technology is amazing, right? All of us have the consensus at this point. The question is, can we land this technology so that it can be, you know, useful at scale? And then, you know, people can consume that. I think there's still a long way to go on that one, right? You know, I think Warren mentioned that. We have all the pieces, but when you piece them together, you know, it takes a lot of effort. What I would have called it, I think some of the people, you know, at this super cloud, also mentioned that there is a last mile thing, right? You know, all the technology is good. How do you connect that technology with the data you have? You know, if I were to start a company, you know, tomorrow, I would have called it lastmile.ai. The domain name may be too expensive to get, right? Because, you know, fundamentally, there's still a last mile thing, right? You know, all the technology is good. You know, how do I actually attach my data with it, right? Is it easy, right? You know, sure, I have the fine tuning, I have the rag, you know, on the paper, but when you actually do it, there are a lot of details. And also your LinkedIn poll showed 63% said biggest shift but takes time. There were some skeptics, about 20% of the people said, oh, it's peak cycle. But so what is that last mile? What are those last mile? Is it data privacy? Is it data quality? So I did a two poll. You know, one is, you know, how big is the technology shift, right? The other one is, what are the number one challenge? It's actually all over the place. There's no one place, right? Well, the model can be better. We all know that, right? You know, less hallucination, you know, so on and so on. And then there is also a kind of a data side, right? Data could be data retrieval, right? The accuracy or that sort of thing. And then there is a compliance security, governance, right? So. All of the above. All of the above. All of the above. That's the last mile. So the last one mile is not just the one thing. It was the last mile of a number. We got to dig the trench. We have to get the cable. Hold on, hold on. I want to tee into this because Brotton Saha, this AWS VP was on our keynote. He was our opening presentation. You had Google, Microsoft. We had all the hyperscales here in SuperCloud 4, as well as the CTO of SaaS, an older company that has modernized their game. Then we had a panel of founders. I call them the senior founders. I won't say senior, I didn't call them that, but experienced founders. Piyush Sharma and Vikram Yoshi, one's a compute guy, one's a security guy. Both. Serial entrepreneur. Serial entrepreneur. You are an entrepreneur as well. And you know, you work for the big company. You think like one, you've been one. You've been an EIR at Greylock. So I have to ask you the question I asked those guys. As an experienced founder that's seen the cycles before, I'll see you're well articulated what you're looking at, killer app, infrastructure, game changing, step function. If you were going to start a company today, what would you, how would you do it? Like, I mean, obviously the cloud was great because you didn't have to provision any hardware to get going. So you're in the market quick. What's that feature of AI that makes it better now to do a startup? And what would you do? How would you execute? Not the idea, but like take us through the mindset. If you're going to start a company tomorrow, say take the cube and turn it into it. Right. So the mindset of us, right? There are a number of things, right? You know, we already talked about there are multiple last mile issues, right? I would say solving any one of them is a big deal, right? You know, big company will solve those problem, but you know, big company, it's harder for them to be super focused, they're super laser focused to solve one problem super well, right? So that's sort of the one thing. The other thing is, I think, you know, I mentioned this at a super cloud three, you know, the future of entrepreneur, they are facing a very different environment because of the power, because of the superpower they have, you know, we'll probably, we'll see a lot more solopreneur. Now by solopreneur, I do not mean single, I mean a lot less resources, right? We used to be kind of a 20 people, 30 people team. Today you should think about it, can you do this, you know, with five people? I was actually having lunch with a VJ, you know, today before the panel. And he mentioned that, hey, you know, anyone can start a GNAI project, you know, with real sort of a budget, right? A lifestyle business could pick one little thing in a vertical and be big, and own it. Yeah, my son is doing a GNAI project, he's in the middle school, and then he said, hey, daddy, can I get some budget from you? I said, sure. He's doing great. And I'm asking him, I said, how much? You know, he said, five dollars. Five dollars would give him a long way to do it. He's gonna be a great entrepreneur, you see funding. You often say this industry has solved complexity with complexity, because you think about the cloud, we talked about two pizza teams, right? Two pizza, and then that turned into what you just described as a 20 pizza team. Will the same thing happen here? Because we're saying, okay, you can start these companies for a lot less, right? Do you think that the complexity that we tend to add on to this business is gonna be similar in that we tend to modularize things, we tend to open source, you know, new projects, and it increases complexity? Do you think that will? But then at that point, you're talking about a very different problem, because you know, like any technology, right? Once that one technology becomes the mainstream, right? So I grew up at VMware, right, you know? Just a very small number of people get a first hypervisor out, right? But by the time, you know, I left VMware 10 years later, it was 15,000 people working on that hypervisor. Success. The reason is because then you have a partnership, integration this, you know, sales and the storyline. You're growing your market, yeah. But that's a very different problem. I think, you know, what we are talking about here is, you know, the superpower that Genevieve I brings to the table can do things that otherwise takes five people. Yeah, and I think that's the, my point about complexity, Dave, is that AI can reduce that. I think that's the key. My question on what you were saying earlier about models. Brad and Satya, also, and I talked about at Amazon, and your guests talked about as well, it's not just the models that are important. It's the end-to-end, and you say last mile, so I'm assuming that there's the beginning, middle, and end of the story. So you could have a great model, but if you're too focused on one model and Arun and Intel just said, why build a model that already exists, it means to an end. So my guest panelists actually all talk about this one thing, right? One is technology, the other one is how you look at it, the technology, right? VJ actually mentioned to me, you know, early today during my lunch, he said, hey, and everyone's talking about hallucination being a problem. Sure, it can be a problem sometimes, but look at a hallucination as a feature, right? You know, it's kind of a creativity. So this is, at that point, it's like how you work with the generative AI. You need to rethink about, you know, that it takes a different culture, a different mindset, a different way of thinking. So I was asking my panelists today about, hey, what is the, you know, it will take time. What sort of things will it take time, right? What is the technology built out? But the other thing is actually the way we think about how we are working with this technology will take time. It's not like everyone still thinks of the traditional way, right? Enterprise software. So I think that would take some time. You don't want hallucination, just keep it sober. Feed it data that you know is good, and keep your model clean. Howie, final word, what's your takeaway from SuperCloud 4 this year? If you look back at the conversations you had, how much is we're having here? What's your big takeaway? So this is the fourth episode of this, you know, SuperCloud, I remember a year ago, right? This is about cloud, not AI. And then in SuperCloud 2, you know, I was among one of the smaller people talking about AI, generative AI, right? Last episode, you know, I was more talking about security, but a lot more generative AI. I think at this time, right, you know, SuperCloud is about, you know, the generative AI. Can we just call it Super AI day and just kind of get over with it? Super power. Yes, so my takeaway is, you know, this thing is, you know, it's going to be real, and it's going to take time. And unlike the previous generation of the technology wave, it will still take time, but at a compressed timeframe. You're a wonderful contributor. Thank you so much for all the prep work that you did. Organizing the panel was fantastic. And if you need analyst's job, we got some openings for you. I know you got a nice gig over in Palo Alto. We have stock options too. Coins. Cube coins. Cube coins. Howey, great panel, you hosted again. Again, this is what we're going to do more of. Thank you for your contribution, folks watching. People bring their guests to the table, amazing guests, great content. All of SuperCloud's have been about data, and the data is changing now in generative AI. This is the next big thing. It's just early days. It's not even inning one. It's pre-gaining. There's a generational shift happening. It's all about data. It's all about scale and software. The superpowers will be there. We'll be back with the short break after the short break for closing segments. Stay with us.