>> Live from Boston, it's theCUBE! Covering IBM Chief Data Officer Summit, brought to you by IBM. >> Welcome back everyone to the IBM CDO Summit and theCUBE's live coverage, I'm your host Rebecca Knight along with my co-host Paul Gillin. We have Joe Selle joining us. He is the Cognitive Solution Lead at IBM. And Thomas Ward, Supply Chain Cloud Strategist at IBM. Thank you so much for coming on the show! >> Thank you! >> Our pleasure. >> Pleasure to be here. >> So, Tom, I want to start with you. You are the author of Risk Insights. Tell our viewers a little bit about Risk Insights. >> So Risk Insights is a AI application. We've been working on it for a couple years. What's really neat about it, it's the coolest project I've ever worked on. And it really gets a massive amount of data from the weather company, so we're one of the biggest consumers of data from the weather company. We take that and we'd visualize who's at risk from things like hurricanes, earthquakes, things like IBM sites and locations or suppliers. And we basically notify them in advance when those events are going to impact them and it ties to both our data center operations activity as well as our supply chain operations. >> So you reduce your risk, your supply chain risk, by being able to proactively detect potential outages. >> Yeah, exactly. So we know in some cases two or three days in advance who's in harm's way and we're already looking up and trying to mitigate those risks if we need to, it's going to be a real serious event. So Hurricane Michael, Hurricane Florence, we were right on top of it and said we got to worry about these suppliers, these data center locations, and we're already working on that in advance. >> That's very cool. So, I mean, how are clients and customers, there's got to be, as you said, it's the coolest project you've ever worked on? >> Yeah. So right now, we use it within IBM right? And we use it to monitor some of IBM's client locations, and in the future we're actually, there was something called the Call for Code that happened recently within IBM, this project was a semifinalist for that. So we're now working with some non-profit groups to see how they could also avail of it, looking at things like hospitals and airports and those types of things as well. >> What other AI projects are you running? >> Go ahead. >> I can answer that one. I just wanted to say one thing about Risk Insights, which didn't come out from Tom's description, which is that one of the other really neat things about it is that it provides alerts, smart alerts out to supply chain planners. And the alert will go to a supply chain planner if there's an intersection of a supplier of IBM and a path of a hurricane. If the hurricane is vectored to go over that supplier, the supply chain planner that is responsible for those parts will get some forewarning to either start to look for another supplier, or make some contingency plans. And the other nice thing about it is that it launches what we call a Resolution Room. And the Resolution Room is a virtual meeting place where people all over the globe who are somehow impacted by this event can collaborate, share documents, and have a persistent place to resolve this issue. And then, after that's all done, we capture all the data from that issue and the resolution and we put that into a body of knowledge, and we mine that knowledge for a playbook the next time a similar event comes along. So it's a full-- >> It becomes machine learning. >> It's a machine learning-- >> Sort of data source. >> It's a full soup to nuts solution that gets smarter over time. >> So you should be able to measure benefits, you should have measurable benefits by now, right? What are you seeing, fewer disruptions? >> Yes, so in Risk Insights, we know that out of a thousand of events that occurred, there were 25 in the last year that were really the ones we needed to identify and mitigate against. And out of those we know there have been circumstances where, in the past IBM's had millions of dollars of losses. By being more proactive, we're really minimizing that amount. >> That's incredible. So you were going to talk about other kinds of AI that you run. >> Right, so Tom gave an overview of Risk Insights, and we tied it to supply chain and to monitoring the uptime of our customer data centers and things like that. But our portfolio of AI is quite broad. It really covers most of the middle and back and front office functions of IBM. So we have things in the sales domain, the finance domain, the HR domain, you name it. One of the ones that's particularly interesting to me of late is in the finance domain, monitoring accounts receivable and DSO, day sales outstanding. So a company like IBM, with multiple billions of dollars of revenue, to make a change of even one day of day sales outstanding, provides gigantic benefit to the bottom line. So we have been integrating disparate databases across the business units and geographies of IBM, pulling that customer and accounts receivable data into one place, where our CFO can look at an integrated approach towards our accounts receivable and we know where the problems are, and we're going to use AI and other advanced analytic techniques to determine what's the best treatment for that AI, for those customers who are at risk because of our predictive models, of not making their payments on time or some sort of financial risk. So we can integrate a lot of external unstructured data with our own structured data around customers, around accounts, and pull together a story around AR that we've never been able to pull before. That's very impactful. >> So speaking of unstructured data, I understand that data lakes are part of your AI platform. How so? >> For example, for Risk Insights, we're monitoring hundreds of trusted news sources at any given time. So we know, not just where the event is, what locations are at risk, but also what's being reported about it. We monitor Twitter reports about it, we monitor trusted news sources like CNN or MSNBC, or on a global basis, so it gives our risk analyst not just a view of where the event is, where it's located, but also what's being said, how severe it is, how big are those tidal waves, how big was the storm surge, how many people were affected. By applying some of the machine learning insights to these, now we can say, well if there are couple hundred thousand people without power then it's very likely there is going to be multimillions of dollars of impact as a result. So we're now able to correlate those news reports with the magnitude of impact and potential financial impact to the businesses that we're supporting. >> So the idea being that IBM is saying, look what we've done for our own business (laughs), imagine what we could do for you. As Inderpal has said, it's really using IBM as its own test case and trying to figure this all out and learning as it goes and he said, we're going to make some mistakes, we've already made some mistakes but we're figuring it out so you don't have to make those mistakes. >> Yeah that's right. I mean, if you think about the long history of this, we've been investing in AI, really, since, depending on how you look at it, since the days of the 90's, when we were doing Deep Blue and we were trying to beat Garry Kasparov at chess. Then we did another big huge push on the Jeopardy program, where we we innovated around natural language understanding and speed and scale of processing and probability correctness of answers. And then we kind of carry that right through to the current day where we're now proliferating AI across all of the functions of IBM. And there, then, connecting to your comment, Inderpal's comment this morning was around let's just use all of that for the benefit of other companies. It's not always an exact fit, it's never an exact fit, but there are a lot of pieces that can be replicated and borrowed, either people, process or technology, from our experience, that would help to accelerate other companies down the same path. >> One of the questions around AI though is, can you trust it? The insights that it derives, are they trustworthy? >> I'll give a quick answer to that, and then Tom, it's probably something you want to chime in on. There's a lot of danger in AI, and it needs to be monitored closely. There's bias that can creep into the datasets because the datasets are being enhanced with cognitive techniques. There's bias that can creep into the algorithms and any kind of learning model can start to spin on its own axis and go in its own direction and if you're not watching and monitoring and auditing, then it could be starting to deliver you crazy answers. Then the other part is, you need to build the trust of the users, because who wants to take an answer that's coming out of a black box? We've launched several AI projects where the answer just comes out naked, if you will, just sitting right there and there's no context around it and the users never like that. So we've understood now that you have to put the context, the underlying calculations, and the assessment of our own probability of being correct in there. So those are some of the things you can do to get over that. But Tom, do you have anything to add to that? >> I'll just give an example. When we were early in analyzing Twitter tweets about a major storm, what we've read about was, oh, some celebrity's dog was in danger, like uh. (Rebecca laughs) This isn't very helpful insight. >> I'm going to guess, I probably know the celebrity's dog that was in danger. (laughs) >> (laughs) actually stop saying that. So we learned how to filter those things out and say what are the meaningful keywords that we need to extract from and really then can draw conclusions from. >> So is Kardashian a meaningful word, (all laughing) I guess that's the question. >> Trending! (all laughing) >> Trending now! >> I want to follow up on that because as an AI developer, what responsibility do developers have to show their work, to document how their models have worked? >> Yes, so all of our information that we provided the users all draws back to, here's the original source, here's where the information was taken from so we can draw back on that. And that's an important part of having a cognitive data, cognitive enterprise data platform where all this information is stored 'cause then we can refer to that and go deeper as well and we can analyze it further after the fact, right? You can't always respond in the moment, but once you have those records, that's how you can learn from it for the next time around. >> I understand that building test models in some cases, particularly in deep learning is very difficult to build reliable test models. Is that true, and what progress is being made there? >> In our case, we're into the machine learning dimension yet, we're not all the way into deep learning in the project that I'm involved with right now. But one reason we're not there is 'cause you need to have huge, huge, vast amounts of robust data and that trusted dataset from which to work. So we aspire towards and we're heading towards deep learning. We're not quite there yet, but we've started with machine learning insights and we'll progress from there. >> And one of the interesting things about this AI movement overall is that it's filled with very energetic people that's kind of a hacker mindset to the whole thing. So people are grabbing and running with code, they're using a lot of open source, there's a lot of integration of the black box from here, from there in the other place, which all adds to the risk of the output. So that comes back to the original point which is that you have to monitor, you have to make sure that you're comfortable with it. You can't just let it run on its own course without really testing it to see whether you agree with the output. >> So what other best practices, there's the monitoring, but at the same time you do that hacker culture, that's not all bad. You want people who are energized by it and you are trying new things and experimenting. So how do you make sure you let them have, sort of enough rein but not free rein? >> I would say, what comes to mind is, start with the business problem that's a real problem. Don't make this an experimental data thing. Start with the business problem. Develop a POC, a proof of concept. Small, and here's where the hackers come in. They're going to help you get it up and running in six weeks as opposed to six months. And then once you're at the end of that six-week period, maybe you design one more six-week iteration and then you know enough to start scaling it and you scale it big so you've harnessed the hackers, the energy, the speed, but you're also testing, making sure that it's accurate and then you're scaling it. >> Excellent. Well thank you Tom and Joe, I really appreciate it. It's great to have you on the show. >> Thank you! >> Thank you, Rebecca, for the spot. >> I'm Rebecca Knight for Paul Gillin, we will have more from the IBM CDO summit just after this. (light music)

>> Announcer: Live from the Javits Center in New York City, it's theCUBE. Covering Inforum 2017, brought to you by Infor. >> Welcome back to theCUBE's coverage of Inforum 2017, I am your host, Rebecca Knight, along with my co-host, Dave Vellante. We are joined by Chip Coyle. He is Infor's CMO. Thanks so much for sitting down with theCUBE today. >> Thank you for having me. >> So we just kicked off the show, the general session, Charles Philips, a lot of other Infor executives up there on the main stage talking. Lay it out for us. How many people are here. What are sort of the big themes that you're trying to get across here. >> Yeah, well, first of all it's great for Infor to be having our conference here at the Javits Center. It's about 10 blocks from our home-- >> Rebecca: Your own back yard. >> In New York City, and so this year, we've got nearly 7,000 attendees over the course of the week. Many component programs as we do every year with our partner summit, with our various conferences for the different individual customer constituencies, and executive forum, and of course, a big customer appreciation event happening tomorrow night. >> You've also made some big announcements. I'm talking mostly about Coleman AI, and Burst. I want you, if you can unpack those for our viewers a little bit. >> Yeah, I would say the theme of the conference this year is the age of networked intelligence. And what does that mean? Well, we've had, for the last several years, a layered strategy in our business, starting at the foundation with very deep industry functional applications. Purpose built for the different industries. We've taken all of that technology and moved it to the cloud, so that you get the benefits of the efficiencies and the network capability of taking your applications to the cloud. We recently, a year ago, acquired GT Nexus, which expands our capability, in a broader sense, to a commerce network, and we're able to incorporate that into our traditional applications in different industries. And then, just a couple of months ago, we acquired a business intelligence software company, Burst, which brings some really great technology for business intelligence that we can layer on top of all of our applications in this network environment. And then finally, today, the big announcement was Coleman, as you said, and that was to take our new artificial intelligence platform and really create just profound new ways that the workers in the different industries and their different companies across the networked enterprise, can interact in a business setting, much like people do in a commercial setting today. >> Can you, Chip, talk about the evolution of the brand promise. So when we first met Infor, at AWS Reinvent, it was like who was Infor? Trying to educate people on who Infor is. And so I felt like last year was your sort of stamp of this is how Infor and why Infor is relevant, and now, there seems to be sort of an undertone of innovation. So can you talk about the evolution of the brand and what you see as the brand promise. >> Well, we are very consistent in our branding and positioning of Infor as really the first industry cloud company. We're the ones who have been, at an accelerated pace, bringing the most deep, industry-rich, functional applications to the cloud. And that has created a great layer now, for all of these future innovations that we have talked about today with the benefits of business intelligence enabled applications built right in, so that you can truly have all the information you need at the right time, for the right purpose to make immediate business decisions. And then the potential and capability of artificial intelligence on top of that. >> As the chief marketing officer, can you talk a little bit about how these innovations change how you do your job, and how they make your life easier, in terms of making the right decision at the right time, making the decision better, having the right data? >> Yeah, well some of the other announcements that we're making this week, actually are in my particular line of business, which is marketing, and one of those, for example, is we're broadening our Infor CRM suite, with a link to LinkedIn's Sales Navigator. So that brings a whole set of important data to, about customers, to enable better customer interactions, for our customers. So that's something that we look to be using in our business, along with Marketo, which is a new business partner, as the engine, or the marketing automation platform to fuel our marketing business. So that's how it's impacting me directly in what I do. >> So I wonder if you could help us sort of debunk some of the myths. So Oracle would say enterprise apps aren't moving to the cloud, and we are the company to move them to the cloud, and we're the only company that can move them to the cloud. You know, SAP, it's got it sort of some cloud going on, but most of the stuff remains on prem. We heard today 55% of your revenue comes from cloud. And we know you made a decision years ago to run on AWS. Help us understand, I mean these are core, hard core enterprise apps that are running in the cloud. So help us debunk some of those myths and add some color to that. >> The traditional processes of rolling out major applications and enterprise applications in an enterprise is completely changing. And it's also changing because of the capabilities of the cloud. And the approach that Infor takes, which is very easy to assemble and configure with our Ion technology and collaboration technology, such as Mingle, to put these applications in place in a much faster way for our customers than some of the traditional players in the ERP market have been accustomed to do. And they just don't have the current technology approach or foundation to be able to move quickly to the cloud, as we do at Infor. >> In talking about Infor, you talked a little bit about the brand evolution, how are you getting the word out? Infor is really a sleeping giant in the technology industry. How are you getting your name out there? >> Well one thing that we want to do with our brand is show, well first of all, introduce Infor to the world at large, that hasn't heard of us. And the way that we want to do that is by showing what kind of benefits we can give to customers in different industries. So we just recently launched our first-ever TV commercials. They have run on shows like Meet the Press, and some of the CNBC and MSNBC shows. That has, incidental, all of that was developed entirely, 100% in house, with Hook and Loop, our creative in-house creative agency. So we're very proud of that. We're looking to do more of that with TV. We also have a relationship with the Brooklyn Nets here in New York, where on the business side, we're enabling them with performance and team analytics with a whole slew of applications of that with biometric readings and imagery, when they're moving around on the court. That can then be used to help fine tune and make decisions on which personnel to use, which, what are the best players to be able to, say, shoot a free throw after one day of rest versus two days of rest. That level of analytics. So we are, in that partnership with the Nets, are also in a branding way, going to be on the Nets jersey starting this September with an Infor patch on the jersey. And we're announcing that also, this week. >> Awesome. This is definitely a New York theme here. We're here at the Javits Center, Brooklyn Nets, Hudson Yards, another huge project that you guys are intimately involved in. Not a lot of vendors are explicitly mentioned in that. Maybe talk about that a little bit. >> Well, Hudson Yards as a development is unique in that it is really a completely self-contained city in all respects. Where the concept is to be able to network the data and information of anybody within that city, with respect to where they live in the high-rises, where they shop in the retail stores or grocery stores, where they eat in the restaurants, and where they work with all of the businesses that are locating there, too. So that gives you so much potential to rethink how information can enable, just the way that you move about, even in the city. From keyless entry into facilities, to voice-activated tasks, like, can you please restock in my groceries in my refrigerator in my condo. So there's so many ways that that can be a broad showcase for the true smart city of the future. >> These are high-end clientele. This is very New York. I want to shift gears and talk about the eco system a little bit. There's a few names that I, maybe they were here before, but I hadn't seen them, at least prominently, certainly IBM, you mentioned Marketo, a great interesting partner, hot company, and some of the SIs are sort of coming out of the woodwork. >> Chip: Yes. >> Now when you think about your strategy for sort of micro verticals, the SIs, I always say, they love to eat at the trough. And if there's not a lot of customizations, they're not interested. However, you've attracted them, because you've now got a substantial enough estate. So talk about that evolution of the eco system. >> We're proud to have as our diamond sponsors this year, AVAAP, as well as Marketo. And AVAAP has been a longstanding partner for, implementation partner for us, in expanding areas. Their heritage is with Lawson in health care and they're doing a lot of implementations across our business in all geographies, in all industries. But what's new this year is we also have attracted some new, some of the big SIs, such as Deloitte and Accenture, Capgemini, Grant Thornton. So they have all come in as sponsors and we're really on the cusp of some big and bigger and better things with them in the different businesses. >> The other thing I wanted to ask you about is Infor has a unique way of attracting interesting speakers. I've done probably five or six thousand interviews in the last five or six years, and some of the most interesting have been at Inforum. Deborah Norville came on in New Orleans, last year Lara Logan, Naomi Tutu, Karina Hollekim, amazing three women interviews. >> Rebecca: This year Susan Rice. >> This year Susan Rice was here, so what's that all about? They're not techies, they're just interesting people. What are you trying to do there? >> Well, we have a program, the Women's Infor Network, WIN, that was created by Pam Murphy, our chief operating officer, and starting a few Inforums ago, we wanted to use Inforum as a platform to showcase innovative women in the world. And it's a little bit of a departure from our product and technology messages. And this year, we've got, as you mentioned, some great inspiring women, like Jill Biden, the former first, vice president-- >> Rebecca: Second lady. >> And also, Susan Rice, as you mentioned. So, it's going to be, it's always a very popular session. >> Yes, and we're looking forward to having those women on theCUBE, too, tomorrow. >> Chip: Absolutely. >> Chip, thanks so much for joining us, it's been a pleasure. >> Thank you for having me. >> I'm Rebecca Knight, for Dave Vellante. We'll have more from Inforum 2017 after this. (techno music)

>> We're here, about to go live, here in a selfie on the pre Silicon Valley Friday Show, about to go live for our show, for some live Friday. We've got a great lineup, it's on my Twitter. Donald Trump and all his viral tweets and now there's an algorithm out there that creates a shorting stock called Trump and Dump, we're going to be talking to the inventor of that new app. Bunch of other great stuff, controversy around Silicon Valley and Intel, controversy on Google, and we'll be watching a great show, well, hopefully you'll be watching. >> Male Announcer: Live, from Cube headquarters in Palo Alto, California it's the Silicon Valley Friday Show, with John Furrier. (serene techno music) >> Hello, everyone, and welcome to the Silicon Valley Friday Show, I'm John Furrier, we are here live in Palo Alto, California for the Silicon Valley Friday Show every Friday morning we broadcast what's going on in Silicon Valley, what's going on in the streets, we call up people and find out what's going on, this show we've got a great lineup. We're going to talk about, I'll say, the news, Twitter, but we've got this fun segment where we have an algorithm, a bot, an AI bot that goes out there and takes all of Donald Trump's tweets and creates a shorting of the stock and creates making money, apparently, Donald Trump's tweets do move the market. We're going to talk about Snapchat, Snap Inc's IPO, and a refiling and some controversy going around that. Also, controversy around Intel Corporation that just announced a fab plant in Arizona and the CEO is in the White House making the announcement, giving the impression that Donald Trump was all behind this, turns out the CEO is a Republican and supports Donald Trump, when apparently this has been in the works for multiple years, so, not sure that's going to be a game changer for Trump but certainly Intel's taking advantage of the schmooze factor and the PR stunt that has people in Silicon Valley up in arms. Obviously, Intel is pro-immigration, bringing people in, obviously, Andy Grove was an immigrant, legend of Intel. And we have also tons of stuff going on, we're going to preview Mobile World Congress the big show in Barcelona at the end of the month. We're doing a two day special here, live in Pal Alto, we're going to do a special, new Silicon Valley version of Mobile World Congress. We'll give you a preview, we're going to talk to some analysts. And also, the fake news, fake accuracy, and all the stuff that's going on, what is fake news? What is inaccurate news? Is there a difference? Does it matter? It certainly does, we have an opinion on that so, great show lineup. First, is actually Twitter earnings are out and they kind of missed and hit their up on the monthly active uniques by two million people. A total of I think 300 million people are using the number here, just on my notes here says, that there are up to 319 million active, monthly active users. And of course, Trump has been taking advantage of Twitter and the Trump bump did not happen for Twitter, although some say Trump kept it alive. But Trump is using Twitter. And he's been actively on Twitter and is causing a lot of people, we've talked about it many times on the show, but the funniest thing that we've seen, and probably the coolest thing that's interesting is that there's an entrepreneur out there, an agency guy named Brian, Ben Gaddis, I'm sorry, president of T3. He's a branding guy, created viral videos on NPR, all over the news, went viral, he created an AI chatbot that essentially takes Donald Trump's tweets, analyzes any company mentioned and then instantly shorts the stock of that company. And apparently it's working, so we're going to take a look at that. We're also going to talk to him and find out what's going on. We're going to have Ben Rosenbaum on, we're going to have someone from Intel on, we have a lot of great guests, so let's take a look at this clip of the Trump and Dump and then we're going to talk to Ben right after. >> Announcer: T3 noticed something interesting about Twitter lately, particularly when this guy gets hold of it. Anytime a company mentions moving to Mexico or overseas or just doing something bad, he's on it, he tweets, the stock tanks. Tweet, tank. Tweet, tank. Tweet, tank. Everyone's talking about how to make sense of all this. T3 thought the unpredictability of it created a real opportunity. Meet the Trump and Dump automated trading platform. Trump and Dump is a bot powered by a complex algorithm that helps us short stocks ahead of the market. Here's how. Every time he tweets, the bot analyzes the tweet to see if a publicly traded company is mentioned. Then, the algorithm runs an instant sentiment analysis of the tweet in less than 20 milliseconds. It figures, positive or negative. A negative tweet triggers the bot to short the stock. Like earlier this month, his Toyota tweet immediately tanked the stock. But the Trump and Dump bot was out ahead of the market. It shorted the second after his tweet. As the stock tanked, we closed our short and we made a profit, huge profit. Oh, and we donated our profits here. So now, when President Trump tweets, we save a puppy. It's the Trump and Dump automated trading platform. Twitter monitoring, sentiment analysis, complex algorithms, real time stock trades. All fully automated, all in milliseconds. And all for a good cause. From your friends at T3. >> Okay, we're back here in Silicon Valley Friday Show, I'm John Furrier and you just saw the Trump and Dump, Trump and Dump video and the creator, that is Ben Gaddis on the phone, president of T3, a privately owned think tank focused on branding. Ben, thanks for joining us today. >> Thanks for having me, John. Excited to talk with you. >> So, big news NPR had on their page, which had the embed on there and it went viral. Great video, but first talk about the motivation, what's going on behind this video? This is very cool, explain to the folks out there what this Trump and Dump video is about, why did you create it, and how does it work? >> So, we had just like, I think, almost everyone in the United States, we were having a conversation about what do you do with the fact that President Trump is tweeting and tweeting about these companies, and in many cases negatively. So we saw articles talking about it and actually one day a guy in our New York office came up with this idea that we ought to follow those tweets in real time and if he mentions a publicly traded company negatively, short the stock. And so, we kicked that idea around over slack and in about 30 minutes we had an idea for the platform. And about two days later one of our engineers had actually built it. And so what the platform does is it's really actually simple yet complex. It listens to every tweet that the president puts out and then it does two things: it determines if there's a publicly traded company mentioned and if there is, and it actually does sentiment analysis in real time, so, in about 20 milliseconds, it can tell if the tweet is positive or negative. If it's negative, we've seen the stocks typically go down and we short sell that stock. And so, the profit that we develop from that, then we donate it to the ASPCA and then hopefully we save a puppy or two in the process. >> Yeah, and that's key, I think that's one thing I liked about this was you weren't arbitraging, you weren't like a real time seller like these finance guys on Wall Street, which by the way, have all these complex trading algorithms. Yours is very specific, the variables are basically Donald Trump, public company, and he tends to be kind of a negative Tweeter so, mostly to do with moving to Mexico or some sort of you know, slam or bullying kind of Tweet he does. And which moves the market, and this is interesting though, because you're teasing out something clever and cool on the AI kind of side of life and you know, some sort of semantic bot that essentially looks at some context and looks at the impact. But this is kind of the real world we're living in now, these kinds of statements from a president of the United States, or anyone who's in a position of authority, literally moves the market, so you're not doing it to make money you're doing it to prove a point which is that the responsibility here is all about getting exposed in the sense that you got to be careful of what you say on Twitter when you're the president of the United States. I mean, if it was me saying it, I mean, I'm not going to move the market but certainly, you know, the press who impact large groups of people and certainly the president does that so, did you guys have that in mind when you were thinking about this? >> Well, we did. I mean, I think, you know, our goal was, this is what we do for a living, we help big brands monitor all their digital presences and build digital strategy. So, we're already monitoring sentiment around Twitter and around social platforms so, it's pretty core to what we do. But we're also looking at things that are happening in pop culture and societally, what kind of impact social might have on business. And so, the fact that we're able to take an action and deliver a social action, and deliver a real business outcome is pretty core to what we do. What's different here and what's so unique is the fact that we've never really seen things like, policy, whether it's monetary policy, or just general policy be distributed through one platform like Twitter and have such a big impact. So, we think it's kind of a societal shift that is sort of the new norm. That, I don't know that if everyone has figured out what to do with yet and so our goal is to experiment and decide one, can we consume the information fast enough to take an action? And then how do we build through AI platforms that allow us to be smarter in the world that we're living in today that is very, very unpredictable. >> We have Ben Gaddis, as president of T3 also part of the group that did the Trump and Dump video but he brings out a great point about using data and looking at the collective impact of information in real time. And this interesting, I was looking at some of the impact last night in this and Nordstrom's had a tweet about Ivanka Trump and apparently Nordstrom's stock is up so, is there a flaw in the algorithm here? What's the take on that? Because in a way, that's the reverse of the bullying, he's defensive on that one so, is there a sentiment of him being more offensive or defensive? >> It's pretty standard. So, we're starting to see a pattern. So, what happens is that actually, the Nordstrom stock actually did go down right after the tweet. And so, we saw that that's a pattern that's typical when the president tweets negatively. When he tweets positively, we don't see that much of a bump. When he tweets negatively, typically the stock drops anywhere between one and four percent, sometimes even greater than that. But it rebounds very quickly. So, a big part of what we're trying to do with the bot and the algorithm is understand how long do we hold, and what is that timeframe before people actually come back to more of a rational state and start to buy back a stock that's valuable. Now what's really interesting, you mentioned, you know, the algorithm and whether there's a flaw in it, we learned something very interesting yesterday about Nordstrom's. So, the president tweeted and in that tweet he talked negatively about Nordstrom's, but he also talked very positively about his daughter, Ivanka. And so, the algorithm actually picked up that tweet and registered it as 61.5% positive. So, it didn't trade. So, we actually got kind of lucky on that one. >> You bring up a good point, and this is something that I want to get your thoughts on. You know, we live in an era of fake news, and it's just Snapchat just filed IPO filing to make a change in their filing to show that Amazon is going to be a billion dollar partner as well, which wasn't in the filing. So, there's a line between pure, fake news, which is essentially just made up stuff, and inaccurate news, so what you're kind of pointing out is a new mechanism to take advantage of the collective intelligence of real time information. And so this is kind of a new concept in the media business. And brands, who used to advertise with big media companies, are now involved in this so, as someone who's, you know, an architect for brand and understanding data, how are brands becoming more data driven? >> Well, I think what brands are realizing is that they live in this world that is more real time, that's such a buzzword. But more real time than I think they even thought would ever be possible, the fact that someone like the president can tweet and have literally cut off billions of dollars in market cap value in a moment's time is something that they have to figure out. So, I think the first thing is having the tools in place to actually monitor and understand, and then having a plan in place to react to things that are really quite unpredictable. So, not only, I don't think that you can have a plan for everything but you have to at least have a plan for understanding how you get legal approval on a response. Who would be responsible for that. You know, who do you work with, either through partners or inside of your organization to, you know, to be able to respond to something when you need to get back in promoting, you know, minutes versus hours. The thing that we don't hear people talk near as much about is, our goal was to see how close we can get to the information so we can zoom the data from Twitter's fire hose, so we get it hopefully when everyone else does. And then our goal is to take an action on that quicker than anybody else, and that delta is where we'll make a profit. What's really interesting to me is that the only person closer to that information than the president is Twitter. >> Ben, great to have you on, appreciate it, love to get you back on as a guest. We love to talk about is our model here, it's looking angle, it's extracting the signal from the noise. And certainly the game is changing, you're working with brands and the old model of ad agencies, this is a topic we love to cover here, the old ad agency model's certainly becoming much more platform oriented with data, these real time tools really super valuable, having a listening engine, having some actionable mechanisms to go out there and be part of and influence the conversation with information. Seems to be a good trend that you guys are really riding. Love to have you back on. >> We'd love to be back on, and thanks for the time, we enjoyed it. >> That was Ben Gaddis, who's the president of T3, the firm behind the Trump and Dump, but more importantly highlighting a really big megatrend which is the use of data, understanding its impact, having some analysis, and trying to figure out what that means for people. Be right back with more after this short break. >> [Female Announcer] Why wait for the future? The next evolution in IT infrastructure is happening now. 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Unify your data center with Cisco UCS. >> Male Announcer: You're listening to Cube Fridays, brought to you by Silicon Angle Media. Now, here's John Furrier. >> Okay, welcome back to the Silicon Valley Friday Show, I'm John Furrier, great show today. Our next guest is Dan Rosenbaum, who is the editor of Wearable Tech Insider, Media Probe, been around the industry for years, been a journalist, reporter, editor, variety through his career, knows the tech business certainly on the infrastructure level with the device. Okay, welcome to the show, great to have you, thanks for being available, he's in New York so, Palo Alto, New York connection here. >> Yeah, we got about maybe an hour or so of snow left. But you know, it's February, it does this in New York. >> Great to have you on, we were just talking on our earlier segment before the break about the guy who created the Trump and Dump video which is a chat bot that goes out, looks at Donald Trump's tweets, and then identifies if there's a public company, shorts the stock, and donates to save puppies. So, they're not doing it for profit but they're, you know, they have their intelligence and listening, and we were just riffing on the concept of that there's been fake news and inaccuracy and a new dynamic that's impacting the media business, which is real time information, data, and certainly the world that you're in with Wearables, this new internet of things, which is hard to understand for most common people but it's really the AI new connected network. It's really impacting things, certainly how people get information, how fast they create data, and it's changing the industry landscape certainly from a media standpoint. You get on TV and the mainstream... >> It really is. When the press secretary stood up and said that that the administration sees the media as the adversary, you know, everyone got sort of upset about it but you know, in a lot of ways it's true. That's a fitting way that the media and any administration, any power structure should be facing each other. There's been such a hop in the media to report the truth as best as it can determine and as accurately as it can. Now, there are differing impacts depending on which sphere you're in, and in politics there's always going to be sort of the tension, well, we think, we look at these facts and we think that and we look at those facts and think the other. >> I think ultimately this new formats that are developing really comes back down to I would add to that as trust. This is a collision course of a complete re-transformation of the media landscape and technology's at the heart of it and, you know, you're in the middle of it. With Wearables, you're seeing that at the edge of the network, these are new phenomenons. What's your take on this new trend of, you know, of computing? And I'm not saying singularity, as Ray Kurzweil would say, but you know, ultimately, it is going down to the point now where it's on your body, potentially in your body, but this is a new form of connection. What's your thoughts on this? >> 12 years ago, I was at the party where they launched MSNBC, and I ran into Andrew Lack, who's the CEO of MSNBC at the time, and asked him, why NBC was cutting this collaboration deal with Microsoft, because remember that's how it was started, when there wasn't any means for the news to go upwards. There was no way for citizen news gathering to be represented on this Microsoft-NBC co-venture. And Andrew actually looked down his nose at me, sneered, and goes, "Who in the world would want "people to be contributing to the news?" Well, now we're 10 or 12 years later and as you say, Snapchat and Skype, and all these mobile technologies have just transformed how people get their information, because they're now witnesses, and there are witnesses everywhere. One of the big transformations in, or about wearable technology is that computing infrastructure has moved from islands of stand-alone, massive computers, to networks of massive computers to stand-alone PCs, to networks to PCs, and now the model for computing and communication is the personal area network, the idea of sensor-based technologies is going to change, or already has changed the world of news, it's in the process of changing the world of medicine, it's in the process of changing the way we build houses, the construction business, with the smartphone, the way that we build and relate to cities. >> So, we're here with Dan Rosenbaum, he's the editor of Wearable Tech Insider, but more importantly he's been a tech insider in media going way back, he's seen the cycles of innovation. Love your point about the flowing conversations coming out of the MSNBC kind of executive in the old broadcast models. I mean, I have four kids, my oldest is 21, they don't use, they don't really care about cable TV anymore so, you know, this is now a new narrative so, those executives that are making those comments are either retired or will be dinosaurs. You now have Amazon, you have Netflix, you have, you know, folks, trying to look at this internet TV model where it's fully synchronous so, now you have collective intelligence of vertical markets that have real time ability to surface information up to bigger outlets. So, this collective media intelligence is happening, and it's all being driven by mobile technology. And with that being said, you know, you're in the business, we've got Mobile World Congress coming up, what is that show turning into? Because it's not about the mobile device anymore, the iPhone's 10 years old, that's a game changer. It's growing up. The impact of mobile is now beyond the device. >> Mobile World Congress is all about wireless infrastructure. It goes from everything from a one millimeter square sensor to the national grade wireless network. But what's really cool about Mobile World is that it's the place where communications or telecom ministers get together with infrastructure carriers, get together with the hardware manufacturers, and they hash out the problems that won't resolve five, 10, 15 years down the road in new products and new services. This is the place where everyone comes together. The back rooms at Mobile World Congress are the hottest place, and the back rooms are the places that you can't get into. >> We're here with Dan Rosenbaum, who's an industry veteran, also in the media frontlines in wireless technology, I mean, wearable technology and among other things, good view of the landscape. Final point, I want to just get a quick comment from ya, I was watching on Facebook, you had a great post around Facebook is feeding you an ad for a $19 million staid-in, let's feel Connecticut. And then you said, "One of us as the wrong idea, so you must be really loaded." This retargeting bullshit on Facebook is just ridiculous, I mean, come on, this bad, big data, isn't it? >> (laughing) Yeah, I mean, the boast of Google is that they want to make, you know, ads so relevant that they look like content. Well, in the process to getting there, there's going to be misses. You know, if this real estate agent decides that they want to hit everyone in my zip code, or everyone in my county, or whatever, and they wanted pay the five dollars so that I'd see that video, god bless 'em, let 'em do it, it's not going to make me, it's not going to overcome any kind of sales resistance. I don't know that I wanted to move up to Litchfield, Connecticut anyway, but if I did, sure, a $19 million house would be really nice. >> You could take a chopper into Manhattan, you know, just drop into Manhattan with a helicopter. >> They would want to take it. >> Alright, we can always take the helicopter in from Litchfield, you know, right at the top of your building. Dan, thanks so much for spending the time, really appreciate it, and we'll have to bring, circle back with you on our two day Mobile World Congress special in Palo Alto we'll be doing, so appreciate the time. Thanks a lot. >> Love to do it, thanks for having me. >> Okay, that was Dan Rosenbaum, really talking about, going down in the weeds a little bit but really more importantly, this Mobile World Congress, what's going on with this new trend, digital transformation really is about the impact to the consumer. And what's going on Silicon Valley right now is there's some hardcore tech that is changing the game from what we used to know as a device. The iPhone's only 10 years old, yet 10 years old, before the iPhone, essentially it was a phone, you made phone calls, maybe surf the Web through some bad browser and do text messages. That's now completely transforming, not just the device, it's the platform, so what we're going to see is new things that are happening and the tell signs are there. Self driving cars, autonomous vehicles, drones delivering packages from Amazon, a completely new, digitized world is coming. This is the real trend and we're going to have an executive from Intel on next to tell us kind of what's going on because Intel is at the ground zero of the innovation with Moore's Law and the integrated circuit. But they're bringing their entire Intel inside as a global platform, and this is really going to be driven through a ton of 5G, a new technology so, we're going to dig in on that, and we're going to have a call-in from her, she's going to be coming in from Oregon and again, we're going to get down to the engineers, the people making the chips under the hood and bringing that to you here on the Silicon Valley Friday Show, I'm John Furrier, we'll be right back after this short break. >> My name is Dave Vellante, and I'm a long-time industry analyst. So, when you're as old as I am you've seen a lot of transitions. Everybody talks about industry cycles and waves, I've seen many, many waves. I've seen a lot of industry executives and I'm a little bit of an industry historian. When you interview many thousands of people, probably five or six thousand people as I have over the last half of the decade, you get to interact with a lot of people's knowledge. And you begin to develop patterns so, that's sort of what I bring is an ability to catalyze a conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody is an expert at something, everybody's passionate about something and has real deep knowledge about that something. Well, we want to focus in on that area and extract that knowledge and share with our communities. This is Dave Vellante, and thanks for watching the Cube. (serene techno music) >> Male Announcer: You're listening to the Silicon Valley Friday Show with John Furrier. >> Okay, welcome back to the Silicon Valley Friday Show, I'm John Furrier, we're here in Palo Alto for this Friday Show, we're going to go under the hood and get into some technology impact around what's going on in the industry, specifically kind of as a teaser for Mobile World Congress at the end of the month, it's a big show in Barcelona, Spain where the whole mobile and infrastructure industry comes together, it's kind of like CES, Consumer Electronics Show, in the mobile world but it's evolved in a big way and it's certainly impacting everyone in the industry and all consumers and businesses. This is Intel's Lynn Comp and this is Intel who, we know about Moore's Law, we know all about the chips that make everything happen, Intel has been the engine of innovation of the PC revolutions, it's been the engine of innovation now in the Cloud and as Intel looks at the next generation, they are the key player in this transformation that we are seeing with AI, wearable computers, internet of things, self driving cars, AI, this is all happening, new stuff's going on. Lynn, welcome to the program. >> Thank you so much, it's great to be here. >> So, you're up in Oregon, thanks for taking the time to allow us to talk via phone, appreciate it. Obviously, Intel, we've been following you guys, and I've been a big fan since 1987, when I almost worked there right out of college. Went to Hewlett Packard instead, but that's a different story but, great, great innovation over the years, Intel has been the bell weather in the tech industry, been a big part of the massive change. But now, as you look at the next generation, I mean, I have four kids and they don't watch cable TV, they don't like, they don't do the things that we used to do, they're on the mobile phone all the time. And the iPhone is now 10 years old as of this year, this early winter part of this, Steve Jobs announced it 10 years ago. And what a change has it been, it's moved from telephone calls to a computer that happens to have software that makes telephone calls. This is a game changer. But now it seems that Mobile World Congress has changed from being a telephone centric, voice centric, phone device centric show to a software show, it seems to be that software is eating the world just like CES is turning into an automotive show. What is Mobile World Congress turning into? What's the preview from Intel's perspective? >> You know, it's a really fascinating question because many years ago, you would only see a bunch of very, very intense base station design, you know, it was very, very oriented around wireless, wireless technology, and radios, and those are really important because they're an engine of fabric that you can build capabilities onto. But last year, just as a reference point for how much it's changed, we have Facebook giving one of the main keynotes. And they're known for their software, they're known for social media, and so you'll see Facebook and Google with an exhibitor there last year as well, so you're not just seeing suppliers into the traditional wireless industry for equipment and the operators who are the purchaser, you're seeing many, many different players show up very much like how you said CES has a lot of automotives there now. >> Yeah, we've seen a lot of revolutions in the computer industry, Intel created a revolution called the Computer Revolution, the PC Revolution, and then it became kind of an evolution, that seems to be the big trends you see, that cycle. But it seems now that we are, kind of been doing the evolution of mobile computing, and my phone gets better, 10 years down to the iPhone, 3G, 4G, LT, okay, I want more bandwidth, of course, but is there a revolution? Where can you point to? Where is the revolution, versus just standard evolutionary kind of trends? Is there something coming out of this that we're going to see? >> That is such a great question because when you look at the first digital wireless technologies that came out and then you had 2G, and 3G, and 4G, those really were evolutionary. And what we're finding with 5G that I believe is going to be a huge theme at Mobile World Congress this year is it is a completely different ballgame, I would say it's more of an inflection point or very revolutionary. And there's a couple reasons for that, both tie up in how ITU is specifying the use cases, it's licensed and unlicensed spectrum which is kind of unusual for how it's been done if you will get 2, 3, and 4G. The other thing that's really interesting about 5G, that it's an inflection point is there's a lot more intelligence assumed in the network and it helps address some of the challenges I think that the industry is seeing a different industry with some of the IoT promise we'll roll out where some of the macro design networks that we'd seen in the past, the ability to have the right latency, the right bandwidth, and the right cost matched to the needs of a specific IoT use case was much more limited in the past and I think we'll see a lot more opportunities moving forward. >> Great, great stuff, we're with Lynn Comp with the Network Platforms Group at Intel. You know, you bring up some, I like the way you're going with this, there's so much like, impact to society going on with these big, big trends. But also I was just having a conversation with some young folks here in Palo Alto, high school kids and some college kids and they're all jazzed up about AI, you can almost see the... I don't want to say addiction but fascination and intoxication with technology. And there's some real hardcore good tech going on here, could you just share your thoughts on, you know, what are some of those things that are going to, 'cause I mean, 5G to wireless, I get that, but I mean, you know, these kids that we talked to and folks that are in the next generation, they love the autonomous vehicles. But sometimes I can't get a phone signal, how are cars going to talk to each other? I mean, how does this, I mean, you've got to pull this together. And these kids are like, and it's into these new careers. What's your thoughts on what are some of the game changing tech challenges that are coming out of this? >> Let's just start with something that was a great example this year 'cause I think I have kids a similar age. And I had been skeptical of things like even just virtual reality, a augmented or virtual reality. And then we had this phenomena last summer that really was just a hint, it wasn't really augmented reality, but it was a hint of the demand that could be met by it and it's Pokemon Go. And so, an example with that, I mean, it really wasn't asking a significantly higher amount of data off the network, but it did change the use profile for many of the coms service providers and many of the networks where they realized I actually have to change the architecture, not just of what's at the edge but in my core network, to be more responsive and flexible, you are going to see something even more so with autonomous driving, even if it's just driver assist. And similar to how the auto pilot evolution happened, you're still going to have these usage patterns where people have too many demands, too much information coming at them, they do want that assistance, or they do want that augmented experience to interact with a brand, and it's going to really stress the network and there's going to have to be a lot of innovation about where some of these capabilities are placed and how much intelligence is close to the user as opposed to just a radio, probably going to need a lot more analytics and a lot more machine learning capabilities there as well. >> We had a segment earlier in the show, it was the entrepreneur who created the Trump and Dump chat bot that would go out and read Donald Trump's tweets and then short all public companies that were mentioned because the trend is, they would do that, but this is an example of some of these chat bots and some of this automation that's going on and it kind of brings the question up to some of the technology challenges that we're looking out at the landscape that we're discussing is the role of data really is a big deal and software and data now have an interaction play where you got to move data around the networks, networks are now ubiquitous, networks are now on people, networks are now in cars, networks are now part of all this, I won't say unstructured networks, but omni-connected fabric. So, data can really change what looks like an optimal architecture to a failed one, if you don't think about it properly. So, how do you guys at Intel think about the role of data? I mean, how do you build the new chips and how do you look at the landscape? And it must be a big consideration, what's your thoughts about the role of data? Because it can happen at any time, a tsunami of data could hit anything. >> Right, the tsunami of data. So for us, it's any challenge, and this is just in Intel's DNA, historically, we'll get challenges as opportunities because we love to solve these really big problems. And so, when you're talking about data moving around a network you're talking about transformation of the network. We've been having a lot of discussions with operators where they see the data tsunami, they're already seeing it, and they realized, I have got to reconfigure the architecture of my network to leverage these technologies and these capabilities in a way that's relevant for the regulatory environment I'm in. But I still have to be flexible, I have to be agile, I have to be leveraging programmability instead of having to rewrite software every generation or every time a new app comes out. >> Lynn, thanks so much for coming on. Like we always say, you know, engine room more power, you can never have enough compute power available in network bandwidth, as far as I'm concerned. You know, we'd love to increase the power, Moore's Law's been just a great thing, keeps on chugging along. Thanks for your time and joining us on the Silicon Valley Friday Show, appreciate it. Thanks so much. >> Thank you. >> Alright, take care. Okay, this is Silicon Valley Friday Show, I'm John Furrier, thanks so much for listening. I had Ben Gaddis on, Dan Rosenbaum, and Lynn Comp from Intel really breaking it down and bringing you all the best stories of the week here on the Silicon Valley, thanks for watching. (techno music) (bright instrumental music)