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Dave Tang, Western Digital – When IoT Met AI: The Intelligence of Things - #theCUBE


 

>> Presenter: From the Fairmont Hotel, in the heart of Silicon Valley, it's theCUBE. Covering When IoT Met AI The Intelligence of Things. Brought to you by Western Digital. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in downtown San Jose at the Fairmont Hotel, at an event called When IoT Met AI The Intelligence of Things. You've heard about the internet of things, and on the intelligence of things, it's IoT, it's AI, it's AR, all this stuff is really coming to play, it's very interesting space, still a lot of start-up activity, still a lot of big companies making plays in this space. So we're excited to be here, and really joined by our host, big thanks to Western Digital for hosting this event with WDLabs' Dave Tang. Got newly promoted since last we spoke. The SVP of corporate marketing and communications, for Western Digital, Dave great to see you as usual. >> Well, great to be here, thanks. >> So I don't think the need for more storage is going down anytime soon, that's kind of my takeaway. >> No, no, yeah. If this wall of data just keeps growing. >> Yeah, I think the term we had yesterday at the Ag event that we were at, also sponsored by you, is really the flood of data using an agricultural term. But it's pretty fascinating, as more, and more, and more data is not only coming off the sensors, but coming off the people, and used in so many more ways. >> That's right, yeah we see it as a virtual cycle, you create more data, you find more uses for that data to harness the power and unleash the promise of that data, and then you create even more data. So, when that virtual cycle of creating more, and finding more uses of it, and yeah one of the things that we find interesting, that's related to this event with IoT and AI, is this notion that data is falling into two general categories. There's big data, and there's fast data. So, big data I think everyone is quite familiar with by this time, these large aggregated likes of data that you can extract information out of. Look for insights and connections between data, predict the future, and create more prescriptive recommendations, right? >> Right. >> And through all of that you can gain algorithms that help to make predictions, or can help machines run based on that data. So we've gone through this phase where we focused a lot on how we harness big data, but now we're taking these algorithms that we've gleaned from that, and we're able to put them in real time applications, and that's sort of been the birth of fast data, it's been really-- >> Right, the streaming data. We cover Spark Summit, we cover Flink, and New, a new kind of open source project that came out of Berlin. That some people would say the next generation of Spark, and the other thing, you know, good for you guys, is that it used to be, not only was it old data, but it was a sampling of old data. Now on this new data, and the data stream that's all of the data. And I would actually challenge, I wonder if that separation as you describe, will stay, because I got to tell you, the last little drive I bought, just last week, was an SSD drive, you know, one terabyte. I needed some storage, and I had a choice between spinning disc and not, and I went with the flat. I mean, 'cause what's fascinating to me, is the second order benefits that we keep hearing time, and time, and time again, once people become a data-driven enterprise, are way more than just that kind of top-level thing that they thought. >> Exactly, and that's sort of that virtual cycle, you got to taste, and you learn how to use it, and then you want more. >> Jeff: Right, right. >> And that's the great thing about the breadth of technologies and products that Western Digital has, is from the solid state products, the higher performance flash products that we have, to the higher capacity helium-filled drive technologies, as well as devices going on up into systems, we cover this whole spectrum of fast data and big data. >> Right, right. >> I'll give an example. So credit card fraud detection is an interesting area. Billions of dollars potentially being lost there. Well to learn how to predict when transactions are fraudulent, you have to study massive amounts of data. Billions of transactions, so that's the big data side of it, and then as soon as you do that, you can take those algorithms and run them in real time. So as transactions come in for authorization, those algorithms can determine, before they're approved, that one's fraudulent, and that one's not. Save a lot of time and processing for fraud claims. So that's a great example of once you learn something from big data, you apply it to the real-time realm, and it's quite dire right? And then that spawned you to collect even more data, because you want to find new applications and new uses. >> Right, and too kind of this wave of computing back and forth from the shared services computer, then the desktop computer, now it's back to the cloud, and then now it's-- >> Dave: Out with the edge. >> IoT, it's all about the edge. >> Yeah, right. >> And at the end of the day, it's going to be application-specific. What needs to be processed locally, what needs to be processed back at the computer, and then all the different platforms. We were again at a navigation for autonomous vehicles show, who knew there was such a thing that small? And even the attributes of the storage required in the ecosystem of a car, right? And the environmental conditions-- >> That's right. >> Is the word I'm looking for. Completely different, new opportunity, kind of new class of hardware required to operate in that environment, and again that still combines cloud and Edge, sensors and maps. So just the, I don't think that the man's going down David. >> Yeah, absolutely >> I think you're in a good spot. (Jeff laughing) >> You're absolutely right, and even though we try to simplify into fast data, and big data, and Core and Edge, what we're finding is that applications are increasingly specialized, and have specialized needs in terms of the type of data. Is it large amounts of data, is it streaming? You know, what are the performance characteristics, and how is it being transformed, what's the compute aspect of it? And what we're finding, is that the days of general-purpose compute and storage, and memory platforms, are fading, and we're getting into environments with increasingly specialized architectures, across all those elements. Compute, memory and storage. So that's what's really exciting to be in our spot in the industry, is that we're looking at creating the future by developing new technologies that continue to fuel that growth even further, and fuel the uses of data even further. >> And fascinating just the ongoing case of Moore's law, which I know is not, you know you're not making microprocessors, but I think it's so powerful. Moore's law really is a philosophy, as opposed to an architectural spec. Just this relentless pace of innovation, and you guys just continue to push the envelope. So what are your kind of priorities? I can't believe we're halfway through 2017 already, but for kind of the balance of the year kind of, what are some of your top-of-mind things? I know it's exciting times, you're going through the merger, you know, the company is in a great space. What are your kind of top priorities for the next several months? >> Well, so, I think as a company that has gone through serial acquisitions and integrations, of course we're continuing to drive the transformation of the overall business. >> But the fun stuff right? It's not to increase your staff (Jeff laughing). >> Right, yeah, that is the hardware. >> Stitching together the European systems. >> But yeah, the fun stuff includes pushing the limits even further with solid state technologies, with our 3D NAND technologies. You know, we're leading the industry in 64 layer 3D NAND, and just yesterday we announced a 96 layer 3D NAND. So pushing those limits even further, so that we can provide higher capacities in smaller footprints, lower power, in mobile devices and out on the Edge, to drive all these exciting opportunities in IoT an AI. >> It's crazy, it's crazy. >> Yeah it is, yeah. >> You know, terabyte SD cards, terabyte Micro SD cards, I mean the amount of power that you guys pack into these smaller and smaller packages, it's magical. I mean it's absolutely magic. >> Yeah, and the same goes on the other end of the spectrum, with high-capacity devices. Our helium-filled drives are getting higher and higher capacity, 10, 12, 14 terabyte high-capacity devices for that big data core, that all the data has to end up with at some point. So we're trying to keep a balance of pushing the limits on both ends. >> Alright, well Dave, thanks for taking a few minutes out of your busy day, and congratulations on all your success. >> Great, good to be here. >> Alright, he's Dave Tang from Western Digital, he's changing your world, my world, and everyone else's. We're here in San Jose, you're watching theCUBE, thanks for watching.

Published Date : Jul 3 2017

SUMMARY :

in the heart of Silicon Valley, it's theCUBE. and on the intelligence of things, is going down anytime soon, that's kind of my takeaway. If this wall of data just keeps growing. is not only coming off the sensors, and then you create even more data. and that's sort of been the birth of fast data, and the other thing, you know, good for you guys, and then you want more. And that's the great thing about the breadth and then as soon as you do that, And at the end of the day, and again that still combines cloud and Edge, I think you're in a good spot. is that the days of general-purpose compute and storage, but for kind of the balance of the year kind of, of the overall business. But the fun stuff right? in mobile devices and out on the Edge, I mean the amount of power that you guys pack that all the data has to end up with at some point. and congratulations on all your success. and everyone else's.

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