 We've lost Vegas, Nevada, again always in Vegas for all the great cube action, Silicon Angle and Wikibon's theCUBE. Our flagship program. We go out to the events that strike the silver from the noise. I'm John Furrier. The founder of Silicon Angle. I'm Jordan, my co-host. Hi, everybody. I'm Dave Vellante of wikibon.org. Dylan Larson is here. He's the director of Xeon Platform Marketing for Intel. Welcome. Thanks. It's good to be here. Good to see you, Dylan. We've had a big discussion today about metadata and Flash and, you know, it's just starting to morph this whole thing together. What are you guys seeing in that regard? It's exactly that. I think what we're seeing is more and more the storage platforms are going to do more computation. Whether it's no longer just sort of placing data on disks. It's all about analytics. It's about doing much more deeper, more efficient provisioning of the capability. I think we're just seeing, putting the CPU to work in ways that we hadn't seen before. Analytics coming to storage platforms is good news for you because we're going to need more juice, right? Absolutely. Analytics is a big deal. I was saying that you couldn't do a presentation anywhere in the industry without talking about cloud about six months ago. Now you can't do one without talking about analytics or Hadoop or different technologies that are basically putting the data to work. Intel marches to the cadence of Moore's law. Those who say Moore's law is dead. Is Moore's law dead? No. Not by law. So why do they say that? Why do people say Moore's law is dead? I mean processors still doubling in performance every 18 months, right? Because the problems are hard. I mean, I think if you're going to continue to drive this relentless cadence to drive the geometries of the transistors down smaller and smaller, you get these things where you do run into the limits of physics, but we're not there. We are on that cadence and we march to a cadence across pretty much everything we do. This sort of very regular predictable beat rate and it helps make the products better. It helps us get to the product to the market on time, put Moore's law to work. The ending of that journey. Now you're at zillions of cores soon. What has changed in the business from your perspective, looking at all aspects, whether it's cryptography on the fly to say something as trivial as doing a real-time analytical query that would have taken a pre-processing, query run, send it out to the data warehouse, get it back in six weeks later. You're exactly right. I mean, a couple of things. The Moore's law we talked about has been kind of that fundamental enabler. We can put more and more transistors in the same dye area by just following Moore's law. So we can pack more and more capability in smaller spaces. And then you add, so what are you going to do with that space? You can do specialized acceleration to do cryptography, like you said, crypto on the fly. You can add more cores to the product. But it has absolutely done what you said. It's given us ability to get to very real-time analytic type of processing. It's given us ability to take a whole new class of performance to everybody. And as we watch our products, customers are choosing to buy high-core counts. They're choosing to buy high-performance because it matters, especially for these new Atlanta handlers. What have you seen? I just want to, on a personal level, you put Intel aside for me. You've seen, you're close to a lot of action and you're on road maps with the processors that are out a couple of years. What are you seeing right now in today's business that just blows your mind? I mean, just in that question we just had crypto on the fly. This is stuff that was unheard of a decade ago. So you've got a new generation of people coming into the enterprise, coding, computer science, doubly, all this great stuff. You guys are still building more friends. What are you seeing right now that blows your mind in terms of the tech and the science? A couple of things that kind of blow my mind is putting, then this is going to be back to the analytics thing. It sounds like party line, but it's not. I mean, putting that much information to work is just amazing to me. I mean, when you talk about basically indexing the entire Internet, Google style, you talk about taking all this data and finding out some of these esoteric trends that people are doing online with your services and being able to basically build correlations between what's happening. I think the whole machine learning idea of kind of classifying behavior and then putting it to work is really, really interesting. It does blow me away. We love that too. Machine learning is so early in this development, and back to the AI theory days was the learning machine. Watson's a great example for it with IBM. That should morph. It should morph pretty well. I think so. I think that there's an appetite for that. When you talk to end customers, CIOs, and big data architecture guys, you do get this view of saying, how do I put this data to work in new ways? They want to be able to do it with some level of autonomy because you can't manage all that stuff. All the things that are also going on, that's interesting, is obviously augmented reality has brought a whole other kind of first person gamer perspective to things like Google Glass. Obviously that's good for the headlines, but still it's early, it's unbaked. Unlike the iPhone, we had a conversation last night at a party at Palo Alto, and it was like talking about the iPhone. I was in the debate and said, hey, the iPhone was pretty well formed. People knew how to make phone calls and do text messages, and you had an app economy in iTunes and the App Store. Even Gen 1 was still good up. You can get that paradigm. Google Glass is still early. What the hell was that? But still, for Gen 1, it's pretty good. So you've got augmented reality and the Internet of Things, or the Industrial Internet, whatever you want to call it, intelligent edge-based data, or devices that need to be addressable. Those things are happening very, very fast. What's your take on those two phenomenons? I think that the part that blows my mind is just the scale involved. You talk about billions of billions of people, billions of billions of devices all interacting with these large clouds, these large data sources, creating data with every move they make. So that's the part that blows me away. It's just how do you keep up with that many concurrent sessions? How do you keep up with that much data access? How do you keep up with the level of scale that's demanded? And I think that's the part that has been talking about what's been great about the business, what's been great about multi-core. It's been that's one of those technologies that feeds that ability to scale to these very, very massive, massive footprints. What do you make of the whole hyperscale trends that's going on? I mean, it seems like the enterprise is starting to learn a lot from the hyperscale. But then there's this other meme going on that the hyperscale guys themselves are saying, you know, maybe we're taking this too far. Yeah. And I think for the same reasons, probably, which is, how do I manage all of these different devices? I mean, if I always used to say the cheapest server you can make is a virtual machine, right? The fastest one you can deploy is probably a virtual machine as well. So, you know, I think that there's going to needs to be an economic and a conversation on this as well. I think the TCO models for these will probably emerge over the next, you know, a couple of years. Yeah, just share nothing as it gets big, it's hard. Yeah, exactly. All right, Dylan, well, listen, thanks very much for stopping by the Cube. It's really a pleasure seeing you. Thank you, my pleasure. Intel, Xeon cores, multiple cores, 8, 10, 12, 20, 40. I mean, it's just going to keep doubling and doubling and doubling Moore's law. Enabling a lot of great stuff, new technology, and it's exciting for science, data, computer science, social science, engineering, a lot of great stuff, new era. And we're going to have Kim Stevenson coming on for 30 CIO, give great talk here on the modern enterprise. It's a great view. Love what she's doing over there with Intel. Congratulations. We'll be right back to Silicon Angle and the Cube. We'll be right back after this short break. Thank you.