>> Live from San Francisco, it's theCUBE covering Google Cloud Next 2018. Brought to you by Google Cloud and it's ecosystem partners. >> Welcome back everyone. This is theCUBE live coverage of Google Cloud Next '18 in San Francisco. I'm John Furrier with Jeff Frick. We're at day three of three days of wall-to-wall coverage. Go to SiliconANGLE dot com on theCUBE dot net. Check out the on demand videos and the Cloud series special journalism report that we have out there, tons of articles, tons of coverage of Google Next with the news, analysis and opinion, of course, SiliconANGLE. Our next guest is Indranil Chakraborty, Project Manager for IoT Google Cloud. Certainly IoT part of the network part of the Cloud, one of the hottest areas in Cloud is IoT. We've been seeing that. Welcome to theCUBE. >> Thank you. >> Thanks for joining us. IoT is certainly the intersection of a lot of things: Cloud, data center, A.I., soon to be, you know, cryptocurrency and blockchain coming down, not for you guys, but in general those are the big hottest areas. >> IOT is not like, you can't say it's an IoT category, so IoT has to kind of sit in the intersection of a lot of different markets that are kind of pure playing. >> So I first want you to explain to the folks out there watching, what is the Google IoT philosophy? What is the products trying to do? And what are guys announcing here? >> Absolutely. Thanks for having me here, it's really great to be here. And if you think about IoT, and if you think about what we have on Google Cloud, we already have a great set of service for data storage, processing, and machine intelligence. Right, so we have Cloud Machine Learning Engine, we have an on start ML. So most of those data processing and intelligence services are already there. What we announced last year was Cloud IoT Core, which is our fully-managed service for our customers and partners who easily and securely connect their IoT devices to Google Cloud, so they can start transmitting data and then ingest and store in the user downstream services for analysis and machine intelligence. >> I mean, IoT is a great use case of Cloud because one, Cloud shows that you can be incented to collect data. >> Right. >> Cuz now you have the lower cost storage, You've got machine learning, all these things are going on. It's great. >> Exactly. >> But Iot is now the Edge of the network. You've got sensors. You've got cars, like Teslas, people can relate to. So everything's coming online has, not just an IP connection, anything that's a sensor. The IoT's been just evolving. What is the Edge to you guys? What does that mean when I say IoT Edge? What is Google view of the Edge? >> Yeah absolutely, it's a great question. You know, we identified early on the emergent trend of moving compute and intelligence to the edge and close to the device itself. So this week, as you already know, we've announced two products for Edge. One is Cloud IoT Edge, which is a software stack which can run on your gateway device, cameras, or any connected device that has some compute capabilities, which extends that powerful AI and machine learning capabilities of Google Cloud to your Edge device. And we also announced Edge TPU, which is a Google designed high performing chip for to run machine learning inference on the Edge device itself. And so with the combination of Cloud IoT Edge as a software stack and with our Edge TPU, we think we have an integrated machine learning solution for on Google Cloud platform. >> How does that get rolled out? So the chip, I'm assuming, you're doing OEM or deals with manufacturers. Same with the software stack. Is the software stack portable? Explain how you roll those out. >> Yeah, you know we are big into working with our ecosystem and we really want to build a robust part of ecosystem. So we are working with semiconductor companies, such as NXP and Arm, who will build a system-on-module using our Google Edge TPU, which can then be used by gateway device makers. So we have partnership with Harting, Nokia, NEXCOM. We're going to take those SOM, add it to their gateway devices, so to take it to the market. We're also working with a lot of computing companies, such as ADLINK, Acton, and a couple of others, Olya. So they can build an analytic solution using our Cloud IoT Edge software and Edge TPU to combine with the rest of Cloud IoT platform. So we're pretty excited about the partners. >> But every coin has two sides, right? So the kind of knock on the Edge is, now you're attack surface on the security side is growing exponentially. So clearly, security is an important part of what you guys do. And now this is kind of a different challenge when you're now, your point to presence is not like our point to presence, but are going to expand exponentially to all these connected autonomous devices. >> Yep, that's a great point. And you know, we take security very seriously. In fact, last year when we announced Cloud IoT Core, we reject any connection that doesn't use TLS, number one, right? And number two, we individually authenticate each and every device using an asymmetry keypad. In addition to that, we've also announced partnership with Microchip. So Microchip has built this microcontroller crypto, which can have the private key inside the crypto, and we use JWT token that was signed by inside the chip itself. So your private key never leaves the chip at all. So that's one additional reinforcement for security. So we have end to end security. We make sure that the devices are connecting over TLS, but we also have hardware root of trust on the Edge device as well. >> The token model is interesting. Talk about blockchain because you know, David Floy on our analyst team, he and I are constantly riffing on that. IoT actually is interesting use case for blockchain and potentially token economics. How do you guys view that? I know that you just mentioned that this is kind of a thing there. Does it fit in your vision at all? What's your position on how that would work out? >> You know, we are closely looking at the blockchain technology. As of today, we don't have anything specific to announce in terms of a product perspective, but we do have, we do use JSON web token, which is standard on the web, use to sign those using our private keys. So that works beautifully, but we're closely monitoring and looking at it. We don't have anything to announce today. >> Not yet, but they're going to share that. Their research is working on it, interesting scenario. So in general, benefits to customers who're working with IoT, your team, cuz you have the core, you have the chip, you have the software stack. There's always an architectural discussion depending upon the environment. Do you move the compute to the data? Do you move the data to the Cloud? What's the role of data in all this cuz certainly you got the processing power. What's the architectural framework and benefits to the customers who are working with Google. >> Yeah, so let's make a specific example, LG CNS. They want to improve their productivity in the factory, and what they've done is they've built a machine learning model to detect defects on their assembly line using Cloud machine learning engine. And they've used this one engineer a couple of weeks and they would train the model on Cloud. Now with Cloud IoT Edge and the Edge TPU, they can run that train model locally on the camera itself, so they can do realtime defect analysis at a pretty fast moving assembly line. So that's the model which we are working on where you use Cloud for high compute for training, but you use the Edge TPU and the Cloud IoT Edge for local inference for real time detection as well. >> How do you guys look at the IoT market because depending on how you're looking at it, you can look at smart cities, you can look at self-driving cars? There's a huge aperture of different use cases. It could be humans with devices, also you guys have Android, so it's kind of a broad scope. You guys got to kind of have that core tech, which it sounds like you're putting in the center of all this. How do you guys look at that? How do you guys organize around that? I think Ann Green mentioned verticals, for instance, is there different verticals? I mean, how do you guys go at that mark with the product? >> IoT is a nation market. And what we offer as Google Cloud, is a horizontal platform, what we call it is Cloud IoT platform, which has got Cloud IoT core on the Cloud side, Cloud IoT Edge, the Edge TPU. And we really want to work with our partners our solution integrators and ISVs, to help build those vertical applications. And so we're working with partners on the healthcare side, manufacturing. We have Odin Technology as one of the partner to really build this vertical up. >> You guys are not going to be dogmatic, this is how our IoT sleeve. You're going to let a thousand flowers bloom kind of philosophy. Put it out there, connect, and let the innovation happen with the ecosystem. >> Yeah, we really believe in driving, moving the, having robust ecosystem. So we want to provide a horizontal platform, which really makes it easy for partners and customers to build vertical solutions. >> Another kind of unique IoT challenge, which you didn't have in the past, we've all seen great pictures of the inside of Google Data Centers. They're beautiful and tight and lots of pretty pictures, very different than out in a minefield or a lot of these challenging IT environments where power could be a challenge. The weather could be a challenge. Connectivity to the internet could be a challenge. Obviously, and then you need to power them. When you talk about how much store do you have locally, how much compute do you have locally. So as you look at that landscape, how has that shaped your guys' views? What are some of the unique challenges that you guys have faced? And how are you overcoming some of those? >> Yeah, that's a great question and this is one of the primary reasons why we announced Cloud IoT Edge, which is software stack, and Edge TPU. So that for use cases where you have limited connectivity, oil wells or farm field, windmills. Connectivity is limited, and you cannot rely on connectivity for reliable operations. But you can use Cloud IoT Edge with our partner device ecosystem to run some of the compute locally. You can store data locally. You can analyze locally, and then push some of the incremental data to the Cloud to further update your model in the Cloud. So that's how we were thinking about this. We have to have some compute locally for those reasons. >> Release the hard coupling, if you will. So it's really got to be a dynamic coupling based on the situation, based on the timing, maybe. >> Exactly. >> Schedule updates, and these type of things. So it's not just connected. >> Exactly. It doesn't need to be continuously connected, right? As long as there's enough connectivity to download some of the updated model, to download the latest firmware and the software. You can run local compute and local machine learning inference on the Edge itself. That's the model we're looking at. So you can train in Cloud, push down the updates to the Edge device, and you can run local compute and intelligence on the device itself. >> A lot of conscious we've been having lately has been about, how do you manage the Edge, has been an area of discussion. Why I want to have a multi-threaded computer, basically, on a device that could be attacked with malware, putting bounds around certain things. You need the IP there. You want to have as much compute, obviously, we'd agree. But there's going to be policies you're starting to think about. This is where I think it gets interesting when you look at what's going on at the abstractions up the stack that you guys are doing. How does that kind of thinking impact some rollouts of IoT because I'm looking to imagine that you won't have policies. Some might trickle data back. It might not be data intensive. Some might want more security. Containers, all this kind of tying in. Is that right? Am I getting that right? How do you see that happening? >> So when you think about Edge, there are different layers. There are different tiers. There are the gateway class devices, which has high compute, and all the way to sensors. Our focus really is on the Edge devices, which has some decent compute capabilities and you can scale up to high-end devices as well. And when you think about policies, on the Cloud side, we have IM policies, so you can define roles, and you can define policies, based on which you can decide which devices should get what software or which user should get access to particular data types as well. So we have the infrastructure already, and we're leveraging that for the IoT platform. >> Yeah, and automate a lot of those kind of activities as well. >> Exactly. >> Alright, so I got to ask you about the show. What's some of the cool things you're seeing, for the folks that couldn't make it that are watching this video live and on demand. What's happening here at Google? What's the phenomenon Google Cloud? What are some of the hot stories? What's the vibe? What are the cool things that you are seeing? >> Absolutely. So I'm biased, so I'm going to start with IoT. You know, we have an IoT showcase where we have a pedestal where we're showing the Edge TPU and the Edge TPU board as well. And there is a lot of work which is happening there. There's a maintenance team there as well, so I would highly encourage attendees to go check it out. >> What are people saying about that? The demos and the sessions, what are some of the feedback? Share some color commentary around reactions. >> Yeah, we've been getting a lot of positive reactions. In fact, we just had a couple of breakout sessions, and a lot of interest from partners across the board to engage with us. So we are pretty excited with our announcement on the Edge side. The whole orchestration of training model in the Cloud and then pushing it down and then sending updates, that's where it really makes it easy for a lot of the partners. So they're excited about it as well. >> They're going to make some good money with it too. You guys are making the mark, and not trying to go too far. Laying the foundational work, the horizontal scale. >> Yes, exactly. And we really focused, for the Edge TPU, we really focused on performance per dollar and performance per watt. And so that has been what we are striving to really have high performance for lower cost. So that's what we're targeting. And a couple of other things, the whole server-less capabilities, and the fact that Cloud functions have become GA, is pretty exciting. And Cloud IoT Core is also a fully managed server-less architecture in a machine. The AI and auto ML which we announced with NLP and text and speech is pretty exciting as well. And that works very well with some of our IoT use cases as well. So I think those are a couple of announcements, which I'm pretty excited about. >> Yeah, I think the automation theme too, really resonated well on all that. Cuz what comes out of that is, humans still got to be more proficient in doing the new stuff, but also they got to run this. And you've got developers enough to build apps that drives value, so you got the value development with the applications, and then also the operational side, which is, I don't want to say becoming generic, but it's not specialized as used to be. Network operator, this guys does this, this gal does that. I mean, it used to be very stove piped. Now it's much more of a how do you run the environment? >> Exactly, and to your point, even on the IoT space, it's also very relevant. I mean there are a lot of overlaps between what used to be just devops and OTE and IT. There are a lot of overlaps there. And so we're looking at it closely as well to make sure that we can really simplify the overall requirement and the tooling which is needed for building an IoT solution. >> For the people that are not following Google as closely as say we are, for instance, they're not inside the ropes, inside the baseball, if you will, in the industry. See Google Cloud, they know Google as Gmail, search, et cetera. They look a couple years ago, Google Cloud had app engine, the OG of Google Cloud, as it's called. What would you say to the folks now that are watching? What's different about Google Cloud now, and what should they know about Google Cloud that they may not know about. What would you say to that person? >> Absolutely, and the first thing is we are very serious about enterprise. You can see here the number of attendees who have come here and how we have multiple buildings where we organized the conference. We're very serious over enterprise. Second, back in the days, two years back, we were really focused on building products, which works for specific use cases. We didn't think about end to end solution, but now the focus has changed. And we're really thinking about, we always had the technology with packaging the products, and now we're thinking about providing end to end solutions, the framework where for a business user, enterprise user, they can just take the solution, and they know it will work. Alright, so there's been a lot of focus on that. And our key differentiator is about machine intelligence and AI, right? That's where Google thrives. We've been spending a lot of time on it, and now we're focused on democratizing AI. Not just on the Cloud, but also on the Edge with the announcement of HTPU. >> And I really think you guys have done a good job with the mindset of making it consumable. In an end to end framework with the option. We've got Kubernetes, and Container's been around for a while, but it's working with multiple environments. I think that is a real mindset shift. >> Exactly. >> So congratulations. >> Thank you. >> Thanks for coming on, appreciate it. >> Absolutely, was great having you guys. >> Google IoT, just plug into the Google Cloud. It'll suck all your data in. Give you some compute at the Edge. Open it up to partners, really focusing on the ecosystem and enabling new types of functionality. It's theCUBE, bringing you the data here on day three at Google Cloud Next '18. We'll be right back with more coverage. Stay with us after this short break. (modern music)