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State University of New York at Potsdam ​from the Fairmont Hotel in the heart of Silicon Valley get the cube covering when IOT met AI the intelligence of things brought to you by Western Digital hey welcome back everybody Jeff Rick here with the Hugh we're in downtown San Jose at the Fairmont Hotel at a little event it's when IOT met AIB in intelligence of things as we're about the internet of things all the time this is really about the data elements behind AI and machine learning and IOT and we're going to get into with some of the special guests here and we're excited to get the guys it's going to kick off this whole program shortly there's Tom stßrmer he is the and it's a new title the global managing director ecosystem and partnership from Accenture Tom welcome thank you Jeff and congrats on the on the promotion thank you so I owe t AI buzzwords a lot of stuff going on but really starting to see stuff begin to happen I mean there's lots of little subtle ways that we're seeing AI work its way into our lives and machine learning work our way into its life but obviously there's a much bigger wave that's about to crest here shortly so you kind of look at the landscape from your point of view get is work a lot of customers you get to see the stuff implemented in industry it's kind of your take on where we are well I would say that we're actually very early you know there are certain spaces with very well-defined parameters where AI has been implemented successfully you know industrial controls and a micro level where there's a lot of well known parameters that the systems need to operate in and it's been very easy to be able to set those parameters up it's been a lot of historical heuristic systems to kind of define how those work and they're really replacing them with AI so in the industrial space there's a lot of take-up and you know we'll even talk a little bit later about Siemens who's really created a sort of a self managed Factory who's been able to take that out from a tool level to a system level to a factory level to enable that to happen and of those weren't those broader capabilities and I think that's one of the inflection points we're going to see in other areas where there's a lot more predictability in a lot of other IT systems right right to be able to take that kind of system level and larger scale factors of AI and enable predicting around that like supply chains for example right we're really not seeing a lot of that yet but we're seeing some of the micro but pieces being injected in where the danger of it going wrong is lower because the training for those systems is very difficult it's interesting there's so much talk about the sensors and the edge and it's computing and that's that's interesting but as you said it's really much more of a system approach is what you need and it's really kind of economic boundaries of the logical system by which you're trying to make a decision and we talk all the time you optimizing for you know one wind turbine are you optimizing for one field that contains so many wind turbines are you optimizing for the entire plant or you optimizing for a much bigger larger system that may or may not impact what you did on that original single turbine so systems approach is a really critical port it really is and what we've seen is that IOT investments have been have trailed a lot of expectations to when they were going to really jump in the enterprise and what we're finding is that we talk to our customers a lot of them are saying look I've already got data I've got some data let's say I'm a mining company and I've got equipment done in mind I've got sensors or oxygen levels I just don't get that much value from it in part of the challenges that they're looking at it from a historical data perspective and saying well I can see the trajectory over time of what's happening inside of my mind but I haven't really been able to put in prediction I haven't been able to sort of assess when equipment might fail so we're seeing that when we're able to show them the ability to affect an eventual failure that might shut down revenue right right for a day or two when you some significant equipment sales we're able to get them to start making those investments and they're starting to see the value in those micro those micro pockets and so I think we're going to see it start to propagate itself through at a smaller scale right and prove itself because there's a lot of uncertainty there's a lot of work that's got to be done to stitch them together and IOT infrastructure itself is already pretty big right as it is short that mine company assets because we had caterpillar on a couple weeks ago and you know they're driving fleets of autonomous vehicles we're talking about some of those giant mining trucks who you know any unscheduled downtime the economic impact is you know immense well beyond and they're worrying about a driver being sick or had a fight with his wife or you know whatever reason is bring them the productivity of those vehicles so it's actually amazing there's little pockets where people are doing it I'm curious to get your point of view on kind of you know

you've managed to comment the guys like I'm not sure the value is because the other kind of big topic that we see is when will the data in the intelligence around the data actually start to impact a balance sheet because then it used to be kind of a pain right you had to store it and keep it and it cost money and you know the provision servers and storage really now in the future the the data that you have the algorithms you apply to it will probably be an increasing percentage of your asset value if not the primary part of your asset value things I think we'll start to figure that out well they are so if you look if you step back away from IOT for a minute and you look at how AI is being applied more broadly we're finding some transformational value propositions that are that are delivering a lot of impacts to the bottom line and it's anywhere from you know where people inside of a company interact with their customers being able to anticipate their next move being able to predict you know given these parameters with this customer you know what kind of even what kind of customer care agent should I put on the phone with them right for you even pick up the phone to anticipate some of those expectations and we're seeing a lot of value and things like that and so excuse me so when you when you zoom it back into IOT you know some of the challenges are that the infrastructure to implement IOT is very fragmented there's 360 some IOT platform providers on in the world and the places where we're seeing a lot of traction in using predictive analytics and AI for for IOT is really coming in to verticals like like industrial equipment manufacturers where they've kind of owned the stack or I can write to find everything from the bottom up and what they're actually being able to do is to start to sell product heavy equipment by the hour where I'll use because they're able to get telemetry off of that product see what's happening be able to see when a failure is about to come and actually sell it as a service back to a customer and be able to predictably and analyze when something sells and get spares there in time and so those are some of the pockets where it's really far ahead because they've got a lot of vertical integration of what's happening and I think the challenge on adoption a broader scale for companies that don't sell very expensive assets into the market is how do i as a company start to stitch my own assets that are from all kinds of different providers and all kinds of different companies into a single platform and what the focus has really been in IOT lately for the past couple years is what what infrastructure should I place to get the data how do i provision equipment how do I track it how do I manage it and look at the data back right and I think that's necessary but completely insufficient to really get a lot of value IOT because really all you're able to do then is get data we do it right all the values really in the data itself right and so the the alternative approach a lot of companies are taking is starting to attack some of these smaller problems and each one of them tends to have a lot of value on its own and so they're really deploying that way and some of them are looking for ways to let those battles of the platforms you know at least get from 360 10 to 200 so that I can make some bets and it's actually proving to be a value but I think that is one of the obstacles we have to adoption so the other thing you mentioned interesting before we turn on the cameras is really thinking about you know AI as a way to adjust the way that we interact with machines right and there's those two views of you know the machines taken over the world is that the beautiful view or it frees us up to do other things or suddenly nobody has a job right the answer is probably somewhere in the middle but but clearly AI is going to change the way and we're starting to see just barely the beginnings of Alexa and Syrian and Google home voice interfacing and the way that we faculties machines which is going to change dramatically with the power of as you said prescriptive analytics presumptive activity right and just change that interaction from what's been a very rote fixed hard to change to pudding as you said some of these lighter weight faster to move more agile layers on the top stack which you can still integrate some of those core si P systems and systems of record in a completely different way exactly as you know I actually use I often use the metaphor of autonomous driving and people seem to think that that's kind of way far out there but if you look at how driving an autonomous vehicles so much different from driving a regular car right you have to worry about it the minutia of executing the driving process and you have to worry about throttle brake you have to worry about taking a right turn on red you have to worry about speeding what you have to worry about is the more abstract concepts of you know source destination route that I might want to take you maybe can offload that as well and so it changes what the person interacting with the AI system is actually able to do and the level of cognitive capability of the variable to exercise right we're seeing similar things in you know in medical treatment we're using AI to do predictive analytics around integration coming off of medically forming it's not only starting to improve diagnosis in certain scenarios but it's also enabling the texts and the the doctors involved in the scans to think on a more abstract level about what's what the broader medical issues are right and so it's really changing sort of the dialogue that's happening around what's going on and I think this is a good metaphor for us to look at when we talk about societal impacts right well right because there are some people who embrace moving forward to those higher cognitive functions and someone's existing but I think if you look at it from a customer standpoint as well no matter what business you manage your services business and product business the way you interact with your employees and the way you interact with your

customers can fundamentally be changed with AI because AI can enable the technology to bend it to your intentions right similar to the call sign that we talked right right right those are subtle subtle activities it's not just AI for voice recognition but it's also using AI and a holter what options are given to you and what scenarios are going to be most beneficial and more often than not you get it right right well the other great thing about autonomous vehicles I mean it's such a fun topic because it's something that people can understand and they can see and they they can touch in terms of a concept to talk about some of these higher-level concepts but the second-order impact which most people don't begin to think they're like I want to drive my cars you know you don't need parking lots anymore because the cars cannot park off site just like they do at airport today at the rental car agency you know you don't need to build a crash cage anymore because the things are not going to crash that often compared to human drove so housing interior experience of a car change when you don't have to build basically a crash cage I mean there's so many second-order impacts that people don't even really begin to think about we see this time and time again we saw it with kind of cloud innovation where it's not just is it cheaper to rent a server from Amazon than to buy one from somebody else it does the opportunity for innovation enable more of your people to make more contributions than they could before because they were too impatient to wait to order the server from the IT guy so that's where I think two people so underestimate kind of the big you know Mars law my favorite you know we we overestimate the short term and completely underestimate the long term the impact of these things as a doubling function exactly yeah absolutely it's I mean it's our time for people for human kind is geared towards when you're thinking right right so when something like Moore's Law because they need to double every 18 months price performance continues to increase storage compute visualization display networking finally the sensors and mountains all of these things have gotten so much cheaper it's hard for human of any intelligence to really comprehend with what happens when that doubling occurs for the next 20 years which we're now getting on the tail end of fact and so those manifests themselves in ways that are a little bit unpredictable and I think that's going to be one of our most exciting challenges over the next five years is what does an Enterprise look like right what does a product look like one of the lessons that I spent a lot of time in racecar engineering and in my younger days and actually did quants and analytics and what what we learned from that point is as you learned about the data you started to fundamentally change about architecture of the product and I think that's going to be a whole new series of activities that happen at the marketplace right rethinking fundamentally product Weaver is a great example of a company that's completely disrupted an industry in on the surface of it it's been it's been disrupted because of the fact that they essentially disassociated the consumption from the provision of the product and just have to phone those asset so they could grow wrapped right right but what they fundamentally did was to to use AI to be able to to broker when should I get more cars where should the cars go and because they're you know they're also we're on the forefront of being able to drive this whole notion of context on cars and getting people's conceptual mindset shifted to having now in a car - or I know a new breeze going to be there it becomes like a power right or I could just rely on it and now people are actually starting to double you know double think about should I even on the car right right a whole different a whole different impact of the autonomous vehicles and if I do in the car why should it be sitting in the driveway when I'm not driving it all right send it out to go it's not to go work for me make it a performing asset well a great conversation you guys essentially than the great spot and always at the cutting edge 8 - teeth a guy used to work within a century you know we had you know you guys squeeze out all the fat in the supply chain in the CRP days and again a lot of these things are people changing the lens and seeing fadna deficiency and then attacking in a different way whether to wear air BnB with empty rooms in people's houses it Paul Doherty on it that G industrial internet launched a few years back you guys are in a great position because you get to sit right at the forefront and help these people make those transformations and I'll tell you how many supply chains is another one of those high level systems opportunities for AI we're being able to optimize you know think about a completely automated distribution chain from factory all the way to the drone landing at your front doorstep I'm a consumer and that's a whole nother level of efficiency that we can't even contemplate or bet against Bezos that's what I always say all right Tom Sturmer thanks for spending a few minutes in and good luck with the keynote appreciation all right i'm jeff break you're watching the Q we're at the intelligence of things where I would seem that AI you're watching the cube thanks for watching New York University Polytechnic School of Engineering.