from around the globe it's thecube with digital coverage of exascale day made possible by hewlett packard enterprise welcome everyone to the cube celebration of exascale day ben bennett is here he's an hpc strategist and evangelist at hewlett-packard enterprise ben welcome good to see you good to see you too son hey well let's evangelize exascale a little bit you know what's exciting you uh in regards to the coming of exoskilled computing um well there's a couple of things really uh for me historically i've worked in super computing for many years and i have seen the coming of several milestones from you know actually i'm old enough to remember gigaflops uh coming through and teraflops and petaflops exascale is has been harder than many of us anticipated many years ago the sheer amount of technology that has been required to deliver machines of this performance has been has been us utterly staggering but the exascale era brings with it real solutions it gives us opportunities to do things that we've not been able to do before if you look at some of the the most powerful computers around today they've they've really helped with um the pandemic kovid but we're still you know orders of magnitude away from being able to design drugs in situ test them in memory and release them to the public you know we still have lots and lots of lab work to do and exascale machines are going to help with that we are going to be able to to do more um which ultimately will will aid humanity and they used to be called the grand challenges and i still think of them as that i still think of these challenges for scientists that exascale class machines will be able to help but also i'm a realist is that in 10 20 30 years time you know i should be able to look back at this hopefully touch wood look back at it and look at much faster machines and say do you remember the days when we thought exascale was faster yeah well you mentioned the pandemic and you know the present united states was tweeting this morning that he was upset that you know the the fda in the u.s is not allowing the the vaccine to proceed as fast as you'd like it in fact it the fda is loosening some of its uh restrictions and i wonder if you know high performance computing in part is helping with the simulations and maybe predicting because a lot of this is about probabilities um and concerns is is is that work that is going on today or are you saying that that exascale actually you know would be what we need to accelerate that what's the role of hpc that you see today in regards to sort of solving for that vaccine and any other sort of pandemic related drugs so so first a disclaimer i am not a geneticist i am not a biochemist um my son is he tries to explain it to me and it tends to go in one ear and out the other um um i just merely build the machines he uses so we're sort of even on that front um if you read if you had read the press there was a lot of people offering up systems and computational resources for scientists a lot of the work that has been done understanding the mechanisms of covid19 um have been you know uncovered by the use of very very powerful computers would exascale have helped well clearly the faster the computers the more simulations we can do i think if you look back historically no vaccine has come to fruition as fast ever under modern rules okay admittedly the first vaccine was you know edward jenner sat quietly um you know smearing a few people and hoping it worked um i think we're slightly beyond that the fda has rules and regulations for a reason and we you don't have to go back far in our history to understand the nature of uh drugs that work for 99 of the population you know and i think exascale widely available exoscale and much faster computers are going to assist with that imagine having a genetic map of very large numbers of people on the earth and being able to test your drug against that breadth of person and you know that 99 of the time it works fine under fda rules you could never sell it you could never do that but if you're confident in your testing if you can demonstrate that you can keep the one percent away for whom that drug doesn't work bingo you now have a drug for the majority of the people and so many drugs that have so many benefits are not released and drugs are expensive because they fail at the last few moments you know the more testing you can do the more testing in memory the better it's going to be for everybody uh personally are we at a point where we still need human trials yes do we still need due diligence yes um we're not there yet exascale is you know it's coming it's not there yet yeah well to your point the faster the computer the more simulations and the higher the the chance that we're actually going to going to going to get it right and maybe compress that time to market but talk about some of the problems that you're working on uh and and the challenges for you know for example with the uk government and maybe maybe others that you can you can share with us help us understand kind of what you're hoping to accomplish so um within the united kingdom there was a report published um for the um for the uk research institute i think it's the uk research institute it might be epsrc however it's the body of people responsible for funding um science and there was a case a science case done for exascale i'm not a scientist um a lot of the work that was in this documentation said that a number of things that can be done today aren't good enough that we need to look further out we need to look at machines that will do much more there's been a program funded called asimov and this is a sort of a commercial problem that the uk government is working with rolls royce and they're trying to research how you build a full engine model and by full engine model i mean one that takes into account both the flow of gases through it and how those flow of gases and temperatures change the physical dynamics of the engine and of course as you change the physical dynamics of the engine you change the flow so you need a closely coupled model as air travel becomes more and more under the microscope we need to make sure that the air travel we do is as efficient as possible and currently there aren't supercomputers that have the performance one of the things i'm going to be doing as part of this sequence of conversations is i'm going to be having an in detailed uh sorry an in-depth but it will be very detailed an in-depth conversation with professor mark parsons from the edinburgh parallel computing center he's the director there and the dean of research at edinburgh university and i'm going to be talking to him about the azimoth program and and mark's experience as the person responsible for looking at exascale within the uk to try and determine what are the sort of science problems that we can solve as we move into the exoscale era and what that means for humanity what are the benefits for humans yeah and that's what i wanted to ask you about the the rolls-royce example that you gave it wasn't i if i understood it wasn't so much safety as it was you said efficiency and so that's that's what fuel consumption um it's it's partly fuel consumption it is of course safety there is a um there is a very specific test called an extreme event or the fan blade off what happens is they build an engine and they put it in a cowling and then they run the engine at full speed and then they literally explode uh they fire off a little explosive and they fire a fan belt uh a fan blade off to make sure that it doesn't go through the cowling and the reason they do that is there has been in the past uh a uh a failure of a fan blade and it came through the cowling and came into the aircraft depressurized the aircraft i think somebody was killed as a result of that and the aircraft went down i don't think it was a total loss one death being one too many but as a result you now have to build a jet engine instrument it balance the blades put an explosive in it and then blow the fan blade off now you only really want to do that once it's like car crash testing you want to build a model of the car you want to demonstrate with the dummy that it is safe you don't want to have to build lots of cars and keep going back to the drawing board so you do it in computers memory right we're okay with cars we have computational power to resolve to the level to determine whether or not the accident would hurt a human being still a long way to go to make them more efficient uh new materials how you can get away with lighter structures but we haven't got there with aircraft yet i mean we can build a simulation and we can do that and we can be pretty sure we're right um we still need to build an engine which costs in excess of 10 million dollars and blow the fan blade off it so okay so you're talking about some pretty complex simulations obviously what are some of the the barriers and and the breakthroughs that are kind of required you know to to do some of these things that you're talking about that exascale is going to enable i mean presumably there are obviously technical barriers but maybe you can shed some light on that well some of them are very prosaic so for example power exoscale machines consume a lot of power um so you have to be able to design systems that consume less power and that goes into making sure they're cooled efficiently if you use water can you reuse the water i mean the if you take a laptop and sit it on your lap and you type away for four hours you'll notice it gets quite warm um an exascale computer is going to generate a lot more heat several megawatts actually um and it sounds prosaic but it's actually very important to people you've got to make sure that the systems can be cooled and that we can power them yeah so there's that another issue is the software the software models how do you take a software model and distribute the data over many tens of thousands of nodes how do you do that efficiently if you look at you know gigaflop machines they had hundreds of nodes and each node had effectively a processor a core a thread of application we're looking at many many tens of thousands of nodes cores parallel threads running how do you make that efficient so is the software ready i think the majority of people will tell you that it's the software that's the problem not the hardware of course my friends in hardware would tell you ah software is easy it's the hardware that's the problem i think for the universities and the users the challenge is going to be the software i think um it's going to have to evolve you you're just you want to look at your machine and you just want to be able to dump work onto it easily we're not there yet not by a long stretch of the imagination yeah consequently you know we one of the things that we're doing is that we have a lot of centers of excellence is we will provide well i hate say the word provide we we sell super computers and once the machine has gone in we work very closely with the establishments create centers of excellence to get the best out of the machines to improve the software um and if a machine's expensive you want to get the most out of it that you can you don't just want to run a synthetic benchmark and say look i'm the fastest supercomputer on the planet you know your users who want access to it are the people that really decide how useful it is and the work they get out of it yeah the economics is definitely a factor in fact the fastest supercomputer in the planet but you can't if you can't afford to use it what good is it uh you mentioned power uh and then the flip side of that coin is of course cooling you can reduce the power consumption but but how challenging is it to cool these systems um it's an engineering problem yeah we we have you know uh data centers in iceland where it gets um you know it doesn't get too warm we have a big air cooled data center in in the united kingdom where it never gets above 30 degrees centigrade so if you put in water at 40 degrees centigrade and it comes out at 50 degrees centigrade you can cool it by just pumping it round the air you know just putting it outside the building because the building will you know never gets above 30 so it'll easily drop it back to 40 to enable you to put it back into the machine um right other ways to do it um you know is to take the heat and use it commercially there's a there's a lovely story of they take the hot water out of the supercomputer in the nordics um and then they pump it into a brewery to keep the mash tuns warm you know that's that's the sort of engineering i can get behind yeah indeed that's a great application talk a little bit more about your conversation with professor parsons maybe we could double click into that what are some of the things that you're going to you're going to probe there what are you hoping to learn so i think some of the things that that are going to be interesting to uncover is just the breadth of science that can be uh that could take advantage of exascale you know there are there are many things going on that uh that people hear about you know we people are interested in um you know the nobel prize they might have no idea what it means but the nobel prize for physics was awarded um to do with research into black holes you know fascinating and truly insightful physics um could it benefit from exascale i have no idea uh i i really don't um you know one of the most profound pieces of knowledge in in the last few hundred years has been the theory of relativity you know an austrian patent clerk wrote e equals m c squared on the back of an envelope and and voila i i don't believe any form of exascale computing would have helped him get there any faster right that's maybe flippant but i think the point is is that there are areas in terms of weather prediction climate prediction drug discovery um material knowledge engineering uh problems that are going to be unlocked with the use of exascale class systems we are going to be able to provide more tools more insight [Music] and that's the purpose of computing you know it's not that it's not the data that that comes out and it's the insight we get from it yeah i often say data is plentiful insights are not um ben you're a bit of an industry historian so i've got to ask you you mentioned you mentioned mentioned gigaflop gigaflops before which i think goes back to the early 1970s uh but the history actually the 80s is it the 80s okay well the history of computing goes back even before that you know yes i thought i thought seymour cray was you know kind of father of super computing but perhaps you have another point of view as to the origination of high performance computing [Music] oh yes this is um this is this is one for all my colleagues globally um you know arguably he says getting ready to be attacked from all sides arguably you know um computing uh the parallel work and the research done during the war by alan turing is the father of high performance computing i think one of the problems we have is that so much of that work was classified so much of that work was kept away from commercial people that commercial computing evolved without that knowledge i uh i have done in in in a previous life i have done some work for the british science museum and i have had the great pleasure in walking through the the british science museum archives um to look at how computing has evolved from things like the the pascaline from blaise pascal you know napier's bones the babbage's machines uh to to look all the way through the analog machines you know what conrad zeus was doing on a desktop um i think i think what's important is it doesn't matter where you are is that it is the problem that drives the technology and it's having the problems that requires the you know the human race to look at solutions and be these kicks started by you know the terrible problem that the us has with its nuclear stockpile stewardship now you've invented them how do you keep them safe originally done through the ascii program that's driven a lot of computational advances ultimately it's our quest for knowledge that drives these machines and i think as long as we are interested as long as we want to find things out there will always be advances in computing to meet that need yeah and you know it was a great conversation uh you're a brilliant guest i i love this this this talk and uh and of course as the saying goes success has many fathers so there's probably a few polish mathematicians that would stake a claim in the uh the original enigma project as well i think i think they drove the algorithm i think the problem is is that the work of tommy flowers is the person who took the algorithms and the work that um that was being done and actually had to build the poor machine he's the guy that actually had to sit there and go how do i turn this into a machine that does that and and so you know people always remember touring very few people remember tommy flowers who actually had to turn the great work um into a working machine yeah super computer team sport well ben it's great to have you on thanks so much for your perspectives best of luck with your conversation with professor parsons we'll be looking forward to that and uh and thanks so much for coming on thecube a complete pleasure thank you and thank you everybody for watching this is dave vellante we're celebrating exascale day you're watching the cube [Music]

(electronic music) - Welcome to theCube Insights. A podcast that is typically taken from Siliconangle media's theCube interviews, where we share the best of our teams insights from all events we go to and from time to time we want to be able to extract some of our learnings when we're back at the ranch. Joining me for this segment is co-founder, co-CEO, benevolent dictator of a community, my boss, Dave Vellante. - Hey Stu. - Dave. Good to see you dressed down. - Yeah, well. Podcast, right? We got toys, props and no tie. - Yeah, I love seeing this ... we were just talking, John Furrier, who we could really make a claim to say we wouldn't have the state of podcasting today, definitely in tech, if it wasn't for what John had done back in the day with PodTech and it's one of those things, we've talked about podcasts for years but I'd gotten feedback from the community that said, "Wow, you guys have grown and go to so many shows that we want to listen to you guys as to: what was interesting at this show, what did you guys take out of it, what cool people did you interview?" We said, "Well, of course all over youtube, our website thecube.net but it made a lot of sense to put them in podcast form because podcasts have had a great renaissance over the last couple of years. - Yeah, and it's pretty straight forward, as Stu, for us to do this because virtually every show we do, even if it's a sponsor show, we do our own independent analysis upfront and at the tail end, a lot of our people in our community said, "We listen to that, to get the low down on the show and get your unfiltered opinion." And so, why not? - Yeah, Dave. Great point. I love, from when I first came on board, you always said, "Stu, speak your mind. Say what the community; what are the users saying? What does everybody talk about?" As I always say, if there is an elephant in the room we want to put it on the table and take a bite out it. And even, yes, we get sponsored by the companies to be there. We're fully transparent as to who pays us. But from the first Cube event, at the end of the day, where after keynote, we're gonna tell you exactly what we think and we're always welcome for debate. For people to come back, push on what we're saying and help bring us more data because at the end of the day, data and what's actually happening in the world will help shape our opinions and help us move in the direction where we think things should go. - I think the other thing is too, is a lot of folks ask us to come in and talk to them about what we've learned over the past year, the past six months. This is a great way for us to just hit the podcast and just go through, and this is what I do, just go through some of the shows that I wasn't able to attend and see what the other hosts were saying. So, how do you find these things? - Yeah, so first of all, great. theCube insights is the branding we have on it. We're on iTunes, We're on Spotify, We're on Google Play, Buzzsprout's what we use to be able to get it out there. It's an RSS on wikibon.com. I will embed them every once in a while or link to them. We plan to put them out, on average, it's once a week. We wanna have that regular cadence Typically on Thursday from a show that we've been out the spring season is really busy, so we've often been doing two a week at this point, but regular cadence, just podcasts are often a little tough to Google for so if you go into your favorite player and look at thecube insights and if you can't find it just hit you, me, somebody on the team up. - So you just searched thecube insights in one of those players? - Yeah absolutely, I've been sitting with a lot of people and right now it's been word of mouth, this is the first time we're actually really explaining what we're doing but thecube one word, insights is the second word I found it real quick in iTunes I find it in Google Play, Spotify is great for that and or your favorite podcast player Let us know if we're not there. - So maybe talk about some of the things we're seeing. - Yeah absolutely - The last few months. - So, right when we're here, what are our key learning? So for the last year or two Dave, I've really been helping look at the companies that are in this space, How are they dealing with multi cloud? And the refinement I've had in 2018 right now is that multi cloud or hybrid cloud seems to be, where everyone's Landing up and part of it is that everything in IT is heterogeneous but when I talk about a software company, really, where is their strength? are they an infrastructure company that really is trying to modernize what's happening in the data center are they born with cloud are they helping there? or are they really a software that can live in SAAS, in private cloud and public cloud? I kinda picture a company and where's their center of gravity? Do they lean very heavily towards private cloud, and they say public cloud it's too expensive and it's hard and You're gonna lose your job over it or are they somebody that's in the public cloud saying: there's nothing that should live in the data center and you should be a 100% public cloud, go adopt severless and it's great and the reality is that customers use a lot of these tools, lots of SAAS, multiple public Cloud for what they're doing and absolutely their stuff that's living in the data center And will continue for a long time. what do you see in it Dave? - My sort of takeaway in the last several months, half a year, a year is we used to talk about cloud big data, mobile and social as the forward drivers. I feel like it's kinda been there done that, That's getting a little bit long in the tooth and I think there's like the 3DS now, it's digital transformation, it's data first, is sort of the second D and disruption is the 3rd D And I think if you check on one of the podcast we did on scene digital, with David Michella. I think he did a really of laying out how the industry is changing there's a whole new set of words coming in, we're moving beyond that cloud big data, social mobile era into an era that's really defined by this matrix that he talks about. So check that out I won't go into it in detail here but at the top of that matrix is machine intelligence or what people call AI. And it's powering virtually everything and it's been embedded in all types of different applications and you clearly see that to the extent that organizations are able to Leverage the services, those digital services in that matrix, which are all about data, they're driving change. So it's digital transformation actually is real, data first really means You gotta put data at the core of your enterprise and if you look at the top five companies in terms of market cap the Googles, the Facebooks, the Amazons, the Microsofts Etc. Those top five companies are really data first. But People sometimes call data-driven, and then disruption everywhere, one of my favorite disruptions scenarios is of course crypto and blockchain And of course I have my book "The Enigma war" which is all about crypto, cryptography and we're seeing just massive Innovation going on as a result of both blockchain and crypto economics, so we've been really excited to cover, I think we've done eight or nine shows this year on crypto and blockchain. - Yeah it's an interesting one Dave because absolutely when you mention cryptocurrency and Bitcoin, there's still a lot of people in the room that look at you, Come on, there's crazy folks and it's money, it's speculation and it's ridiculous. What does that have to do with technology? But we've been covering for a couple of years now, the hyper ledger and some of these underlying pieces. You and I both watch Silicon Valley and I thought they actually did a really good job this year talking about the new distributed internet and how we're gonna build these things and that's really underneath one of the things that these technologies are building towards. - Well the internet was originally conceived as this decentralized network and well it physically is a decentralized network, it's owned essentially controlled by an oligopoly of behemoths and so what I've learned about cryptocurrency is that internet was built on protocols that were funded by the government and university collaboration so for instance SMTP Gmail's built on SMTP (mumbles) TCPIP, DNS Etc. Are all protocols that were funded essentially by the government, Linux itself came out of universities early developers didn't get paid for developing the technologies there and what happened after the big giants co-opted those protocols and basically now run the internet, development in those protocol stopped. Well Bitcoin and Ethereum and all these other protocols that are been developed around tokens, are driving innovation and building out really a new decentralized internet. So there's tons of innovation and funding going on, that I think people overlook the mainstream media talks all about fraud and these ICO's that are BS Etc. And there's certainly a lot of that it's the Wild West right now. But there's really a lot of high quality innovation going on, hard to tell what's gonna last and what's gonna fizzle but I guarantee there's some tech that's being developed that will stay the course. - Yeah I love....I believe you've read the Nick Carr book "The Shallows", Dave. He really talked about when we built the internet, there's two things one is like a push information, And that easy but building community and being able to share is really tough. I actually saw at an innovation conference I went to, the guy that created the pop-up ad like comes and he apologizes greatly, he said "I did a horrible horrible thing to the internet". - Yeah he did - Because I helped make it easier to have ads be how we monetize things, and the idea around the internet originally was how do I do micropayments? how do I really incent people to share? and that's one of the things we're looking at. - Ad base business models have an inherent incentive for large organizations that are centralized to basically co-opt our data and do onerous things with them And that's clearly what's happened. users wanna take back control of their data and so you're seeing this, they call it a Matrix. Silicon Valley I think you're right did a good job of laying that out, the show was actually sometimes half amazingly accurate and so a lot of development going on there. Anywhere you see a centralized, so called trusted third-party where they're a gatekeeper and they're adjudicating essentially. That's where crypto and token economics is really attacking, it's the confluence of software engineering, Cryptography and game theory. This is the other beautiful thing about crypto is that there is alignment of incentives between the investor, the entrepreneur, the customer and the product community. and so right now everybody is winning, maybe it's a bubble but usually when these bubbles burst something lives on, i got some beautiful tulips in my front yard. - Yeah so I love getting Insight into the things that you've been thinking of, John Furrier, the team, Peter Borus, our whole analyst team. Let's bring it back to thecube for a second Dave, we've done a ton of interviews I'm almost up to 200 views this year we did 1600 as a team last year. I'll mention two because one, I was absolutely giddy and you helped me get this interview, Walter isaacson at The Dell Show, One of my favorite authors I'm working through his DaVinci book right now which is amazing he talks about how a humanities and technology, the Marrying of that. Of course a lot of people read the Steve Jobs interview, I love the Einstein book that he did, the innovators. But if you listen to the Michael Dell interview that I did and then the Walter isaacson I think he might be working on a biography of Michael Dell, which i've talk to a lot of people, and they're like i'd love to read that. He's brilliant, amazing guy I can't tell you how many people have stopped me and said I listened to that Michael Dell interview. The other one, Customers. Love talking about customers especially people that they're chewing glass, they're breaking down new barriers. Key Toms and I interviewed It was Vijay Luthra from Northern trust. Kissed a chicago guy And he's like "this is one of the oldest and most conservative financial institutions out there". And they're actually gonna be on the stage at DockerCon talking about containers they're playing with severless technology, how the financial institutions get involved in the data economy, Leverage this kind of environment while still maintaining security so it was one that I really enjoyed. How about...... what's jumped out of you in all your years? - (Mumbles) reminds me of the quote (mumbles) software is eating the world, well data is eating software so every company is.... it reminds me of the NASDAQ interview that I did Recently and all we talked about, we didn't talk about their IT, we talked about how they're pointing their technology to help other exchanges get launched around the world and so it's a classic case of procurer of technology now becoming a seller of technology, and we've seen that everywhere. I think what's gonna be interesting Stu is AI, I think that more AI is gonna be bought, than built by these companies and that's how they will close the gap, I don't think the average everyday global 2000 company is gonna be an AI innovator in terms of what they develop, I think how they apply it is where the Innovation is gonna be. - Yeah Dave we had this discussion when it was (mumbles) It was the practitioners that will Leverage this will make a whole lot more money than the people that made it. - We're certainly seeing that. - Yeah I saw.....I said like Linux became pervasive, it took RedHat a long time to become a billion dollar company, because the open stack go along way there. Any final thoughts you wanna go on Dave? - Well so yeah, check out thecube.net, check out thecube insights, find that on whatever your favorite podcast player is, we're gonna be all over the place thecube.net will tell you where we're gonna be obviously, siliconangle.com, wikibon.com for all the research. - Alright and be sure to hit us up on Twitter if you have questions. He's D Villante on twitter, Angus stu S-T-U, Furrier is @Furrier, Peter Borus is PL Borus on twitter, Our whole team. wikibon.com for the research, siliconangle.com for the news and of course thecube.net for all the video. - And @ TheCube - And @TheCube of course on Twitter for our main feed And we're also up on Instagram now, so check out thecube signal on one word, give you a little bit of behind the scenes fun our phenomenal production team help to bring the buzz and the energy for all the things we do so for Dave Vellante, I'm Stu Miniman, thanks so much for listening to this special episode of thecube insights. 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>> Narrator: Live from Las Vegas, it's the Cube. Covering Interconnect 2017. Brought to you by IBM. >> OK, welcome back everyone. We're here live in Las Vegas. I'm wearing the Blockchain Revolution hat right here. Of course, I'm John Furrier with the Cube, and my co host Dave Vellante, we're excited to have celebrity author, thought leader, futurist and fill in the blank on the title Don Tapscott, who's the author of the Blockchain Revolution. Legend in the industry, thought leader, you and your son a compelling new book, but you've been on the fringe of all the game changing technologies going back with social media, we've been following your work, it's been great. Now we're at the front range of Blockchain, OK? Now it's becoming pretty clear to some of the innovators like IBM and others that it's not about Bitcoin alone, it's about the Blockchain Revolution, the Blockchain itself. Welcome to the Cube and what's going on? What is Blockchain? (laughing) >> Well, it's great to hear, be here. The one thing you didn't mention is I play keyboards in a rock band. So. >> The most interesting man on the Cube right now. >> We used to do a concert every year whether our public demanded it or not, but no, we're a charity event. We've raised a few million dollars for good causes. Anyway. I think, along with my son Alex, we figured this out a couple of years ago that this is the second era of the internet. For the first few decades, we've had the internet of information. And if I send you some information, PDF, PowerPoint, E-mail, even with the website, I keep the original. I'm sending you a copy. That doesn't work so great for assets. Like money, stocks, bonds. Identities, votes. Music, art. Loyalty points. If I send you $100, it's really important I don't still have the money, and I can't send it to you. So this has been called the double spend problem by cryptographers for a long time. And Blockchain solves this problem. We've had the internet of information, now we're getting the internet of value. Where anything of value, from money to votes to music can be exchanged peer to peer. And where we can transact, keep records, and trust each other without powerful intermediaries. Now that doesn't mean intermediaries are going to go away, but they're going to have to embrace this technology or they will be toast. >> I mean, this is clear, you see the distributive computing paradigm, I mean, we're all network guys and by training, you can follow this revolution. But now when you start thinking about trust and value and you talk about digitizing the world. So, if you go to digital transformation, that's the thesis, that we're in this digital transformation, you're digitizing money, you're digitizing transactions. Explain more on the value piece because now if everything's going digital, there now needs to be a new model around how to handle the transactions at scale, and with security problems, hackers. >> Yeah, OK. Well that gets to a couple of really good points. First of all, what is digital? You know, you think, "Well, I tap my card at Starbucks "and bits go through all these networks and different "companies with different computer systems and three "days later a settlement occurs." But that's actually a bunch of messages. It's not money. Money, cash, is a bare instrument. If you have cash in your pocket, you are the bearer of that instrument, which means that you own it. And what we're talking about is something very different here, of creating digital cash. That's stored on a global ledger. So, rather than there being a three day settlement period, there's no settlement period because you're just making a change in the database. And this is a very revolutionary concept. And as for security, I mean, think about, I don't know, you're right, it's not about Bitcoin. But if we took the case of the Bitcoin Blockchain. If I wanted to hack that, I'd have to hack that 10 minute block that has all those transactions, which is linked to the previous block and the previous block, I'd have to hack the entire history of commerce on that Blockchain, not just on one computer, but simultaneously across millions of computers, all using the highest level of cryptography, while the most powerful computing resource in the world, the minors are watching me to make sure I don't mess around. Now, I won't say it's impossible, just like I suppose it's not impossible to take a Chicken McNugget and turn it back into a chicken, but it's really hard to do. A lot, and so these systems are way more secure than our current systems. >> Yes, it fundamentally impossible, and you don't have a third party verification system that's also an exposure area, it's globally distributed, right, so let's go back to what is Blockchain? What's the Blockchain 101? >> Well, Blockchain is a distributed ledger where anything of value, from money to votes, and music can be stored, transacted, managed, in a secure and confidential way, and where trust between parties is established, not by a big intermediary, but by cryptography, by collaboration, and some clever code. >> So, talk about the premise of the book. Sort of why you wrote it and what the fundamental premise is. >> Well, three years ago, three years and five weeks ago, at a father son ski trip, over a large piece of beef, and a very nice bottle of wine, Alex and I started thinking about what all this means. And we decided to work together. And he wrote a very cogent paper about how this new ecosystem could govern itself and my publisher got wind of it and said, "That sounds like a book." So we launched a dozen projects, couple of years ago, on how this technology changes, not just financial services, how it changes the corporation and the deep structure and architecture of the firm. How it changes every industry. How it changes government. Democracy, there's an opportunity to end the crisis of legitimacy of our democratic institutions. But what it means for culture and so on. And then we wrote the book. And it was published in May 10th last year, it's been a big best seller, it's the best selling book on Blockchain. It's actually the only real book on Blockchain. In some countries it was ridiculous. For a while, in Canada, it was competing with Harry Potter and an adult coloring book, as the best selling book in the country. >> That's the state of our culture right there. (laughing) >> What is an adult coloring book, anyway? (laughing) >> That's the million dollar question right there. >> There are a lot of geeky books on Blockchain, but this-- >> Well, actually, there aren't, there are books on crypto currency, on Bitcoin. >> Yeah, absolutely. >> And but the only real book on Blockchain is Blockchain Revolution. >> So, but you're really focusing on the business impact, organizational impact, even societal impact, so explain the premise. >> Well, where do we start? Let's start with the firm. Corporation, foundation of capitalism, based on double entry accounting. That's what enabled capitalism. Well, with Blockchain, you get a third entry onto the ledger, so you have triple entry accounting, so you don't need, say, audits. Every year, because there's an annual audit. That's just the beginning. Because the reason that we have firms, according to the Nobel Prize winning economist Ronald Coase, is that the transaction costs in an open market, like the cost of search, finding all the right people and information, the cost of contracting, for every little activity we're contract prohibitive. The cost of coordination, getting all these people to work together, didn't know each other. The cost of establishing trust, all of that in an open market is prohibitive, so we bring that inside the boundaries of a firm. Well, Blockchain will devastate those transaction costs. So we're talking about a fundamental change in how we orchestrate capability, in our economy, to innovate, to create goods and services. And for that matter, to create public value. So this is not some interesting little technology. This is the second era of the internet. I think it's going to be bigger than the first era was. >> So the internet, I mean, the value creation side. So let's take that additional asset side. So assume everything's digitized, got IOTs out there, industrial IOT, wearables, smart cars, smart cities, smart everything, but now you've got to create value as a firm, so let's roll that forward, we have the now somewhat frictionless transactional environment in an open market, how do firms create value out of those digital assets? >> Well, they'll create value in some ways that are radically different than today. So let me give you an example. Who are the big digital value disrupters today? Well, you can start with the so called sharing economy. You know, Uber, Airbnb, Lyft. >> The Cube. >> Sorry? >> The Cube. (laughing) We're disrupting the world right now. >> Well, you're actually not a sharing economy company in the sense that I think. >> In the traditional sense. >> Actually, I don't think they are, either. I mean, the reason that Uber's successful is precisely because it doesn't share. It's a service aggregator. So, why do you need a $70,000,000,000 corporation to do what Uber does? It could be done by a distributed ledger with some smart contracts and autonomous agents. Everything that the corporation does could be done by software. Airbnb. You know, how about, we'll call it B Airbnb, Blockchain Airbnb. So, you go onto your mobile device, and you're looking for a place, and you're going to be in Vegas, and all the hotels are booked because of IBM, and then you find a place, you book it, and then you show up, you turn your key that starts a smart contract payment to the owner of the apartment or the room, and you check out, you turn your key, it's closed. The software has a payment system built into it. So the renter of the room gets paid. You enter a five star on your device. And that's immutable, and it's a five star rating on a Blockchain. Everything that Airbnb as a company does could actually be done by this software. So, Bob Dylan, there's something going on here and you don't know what it is, I mean, people are all locked in an old paradigm about what's disruption. Get ready for this. >> So what's the impact, I mean, not the impact, what's the inhibitor, so, obviously, any new technology you see all the naysayers, so obviously this is a great vision, what's going to be the impediment? >> Well, they are all kinds of impediments and inhibitors, and there are all kinds of ways that this can get messed up. A big one is that we're overcoming now is that people think, well this is about Bitcoin, well, it's not. The real pony here is the underlying technology of Blockchain, and that's the biggest innovation in computer science in a generation, I think. But also, you know, I wrote this 1992 in Paradigm Shift, I said, when you get a new paradigm, it's a new mental model, and these things cause dislocation and disruption and uncertainty, and they're nearly always received with coolness. I mean, you guys know what it's like to be received with coolness as you introduce a new idea as do I, going back to the '70s. But, and vested interests fight against change. And leaders of old paradigms have great difficulties embracing the new. So you think about a company like Western Union that can charge 10% for remittances that take four to seven days. Well, with new tools, they don't take four to seven days, they take minutes, and they charge, based on Blockchain, they charge a point and a half. So, it's the old-- >> The inhibitors, they got to get their solutions out there so that they could go after and eat some of the lunch of the older guys. >> Well, they have to eat their own lunch, that's-- >> Western Union could be disrupted by a new entrant, right? So you got a new entrant coming in, they got to cannibalize themselves-- >> And at that point, it tips, there are enough disruptive entrants, right? >> So, it's all those inhibitors to change and for the IT people that are at this event, this is an exciting opportunity, but you do need to learn a new kind of knowledge base to function in this distributed ledger environment. You need to learn about hyper ledger, for starters, because that's the real enterprise platform. >> All right, so folks watching, like my son who helps us out sometimes as well, you have a father son relationship, which is super inspirational. He's, say he wants to get involved in Blockchain. He wants to jump right in, he's kind of a hacker type, what does he do? How does he get involved? Obviously read the book, Blockchain Revolution, get the big picture. Is there other things you'd advise? >> Well, buying the book in massive volume is always a good first step, no. Seriously. Well, one thing I always say to people is personal use is a precondition for any kind of comprehension. So just go get yourself a wallet for some crypto currency and download it and you'll learn all about public key encryption and so on. But I think in a company there are a number of things that managers need to do. Need to start doing pilots, sandboxes, developing and understanding use cases, and our new Blockchain research institute is going to be a big help in that. But also, for an IT person, is your son an IT guy or he's more an entrepreneur? >> No, he's 21 years old. >> He's 21. >> He doesn't know anything about IT. >> He's a computer science guy. >> He's born in the cloud. IT, can't spell IT. >> Well. (laughing) >> IT's for old guys like us. (laughing) >> We're telling him what he should do, he should be here telling us what we should do. >> John: That's why we hired him, he's a little guinea pig. >> Digital natives, you know, we're digital immigrants, we had to learn the language. But, for the IT people, it's all about not just experimenting, but about moving towards operational systems and about architecture. Because our architectures are based on traditional computing environments and this is something from Paradigm Shift, you remember, I interviewed Max Hopper who invented the Sabre Reservation System for American Airlines, and he says, "The big problem, Don, "is that if I don't have a target architecture, "every time I spend a dollar, I'm building up my legacy "and making it worse by investing in IT." And so that's where I came up with this formulation, yeah, God may have created the world in six days, but he didn't have an installed base to start with. (laughing) So, what we need to do is to start to think about architectures that embrace Blockchain. And this is an historic new opportunity for anybody who cares about IT. >> Is the disruptive enabler for Blockchain the fact that we're now fully connected as a society, or is it something else that we don't see? What's your view on, what's the real wealth creating disruptive enabler? >> Well, you can sense that the rate of change is a lot faster for the second generation than the first. 1993, '94, when I wrote the Digital Economy, it was dial-up. Ebay. >> 14 four. >> Amazon didn't exist. >> Actually 98 I think it was. >> When I wrote that book. Google was five years away. Facebook was 10 years away, so but now we've got wireless, we've got IP everywhere. We've got mobility. We've got the cloud, we've got all the preconditions for this new innovation to happen a lot faster. And that's why, I mean, a year ago, there wasn't a lot of talk at this event about Blockchain. Today it's the big buzz. >> I wonder if you could talk about other applications. You talk about hyper ledger, it's a great place for a starting point, especially for IBM, but one of the areas I'm excited about is security. You know, like the MIT Enigma Project, and there are others, you know, security is such a problem. Every year we look back, John and I, we say, do we feel more secure? And no, we feel less secure. What about the application of Blockchain in security use cases? >> Well, Blockchains are more secure in a number of ways. One is they're harder to hack than traditional servers. And people say, "No, our company, we're bulletproof." Right, tell that to JP Morgan and Home Depot-- >> Target fidelity-- >> The Democratic National Convention, but also tell it to the CIA. I mean, if the CIA can be hacked, then any of these traditional server technologies can be hacked. So that, alone, is a huge case to move towards hyper ledger and these other type platforms. But you said, "I feel less secure these days." And that's a really interesting statement. Because I think that, in many ways, the security of the person has been undermined by the internet of information, as well. That, first of all, we don't own the data that we create. That's a crazy situation. We all create this massive new asset. It's a new asset class. Probably more important than industrial plant, in the industrial age. Maybe more important than land in the agrarian age. We create it, but these data frackers, you know, like-- >> Facebook. >> --Facebook. Own it and that's a big problem. The virtual you is not owned by you. So we need to get our identity back and to manage it responsibly, and people who say to me, "Well, Don, privacy's dead, get over it." This is foolishness. Privacy is the foundation of freedom. And all these things are happening in our world today that undermine our basic security. Our identity's being taken away from us. Or the fact that things happen in this digital world that we don't know, what are the underlying algorithms? If I take this, and I drop it, that's called gravity. I know what's going to happen. But if I go onto Facebook and I do certain things, I have no idea what are the algorithms that's determining what's happening with that and how the data is used. So-- >> Hello fake news. That's how fake news came about. >> Well, yeah, totally. >> People don't know what to trust and it's like, wait a minute. >> Exactly, and well, this has led, also, to a total fragmentation of public discourse, where we've all ended up in these little self reinforcing echo chambers where the purpose of information is not to inform us, it's to, I don't know, give us comfort. >> Divide people. >> Yeah. So, I'm not saying that Blockchains can fix everything, in fact, they can't fix anything, it's humans that fix things. But the key point that Alex and I make in the book is that once again the technology genie has escaped from the bottle, and it was summoned by this person that we don't even know who they are. At a very uncertain time in history. But it's giving us another kick at the can. To sort of fix these problems. To make a world where trust is embedded in everything and where things are trustworthy, and where people are trustworthy, and maybe we can rewrite the whole economic power grid and the old order of things for the better. And that's really important. >> My final question for you, and this is kind of a thought provoking question. Every major revolution, you see, big one, you've seen a counter culture, '60s, computer revolution, PC revolution, are we on the edge now of a new counter culture developing? Because the things you're kind of teasing out is this new generation, is it the '60s version of tech hippies or is there going to be a, because you're getting at radical reconfiguration, radical value creation, this is good evolution, and fast. So you can almost see the young generation, like my son, you're talking about, teaching us how to do it, that's a counter culture. Do you see that happening? >> Well, first of all, I see this change in culture profoundly, so artists can get fairly compensated for the work they create. Imogen Heap puts her song on a Blockchain platform, and the song's inside a smart contract that specifies the IP rights. And you want to listen to it, maybe it's free, you want to put it in your movie, it costs more. The way she describes it is the song acts as a business, and it has a bank account. So, we can profoundly change many aspects of culture, bringing more justice to our culture. But I'm not sure there'll be a counter culture in the traditional sense because you've got people embracing Blockchain that want to fix a bunch of problems, but also people who want to make large organizations more competitive and more effective. The smart banks are embracing this because they know they can cut their transaction costs in half, probably. And they know that if they don't do it, somebody else will. >> And IBM's embracing it because they write software and they service all those firms with technology. >> Well, IBM, the case of IBM is really interesting, and I'll end on that one. That if you think about it, and I go back, I mean, there were only main frames when I started, and IBM was the leader of the bunch, right? And then all the bunch died, but IBM somehow reinvented itself and it got into mini computers and then we saw the rise of the PC and IBM invented the IBM PC, and then we got into the internet, and once again, all these companies died off but somehow IBM was able to find within itself the leadership to transform itself. And I'm, I won't say I'm shocked, but I have to tell you, I'm really delighted that IBM has figured this one out and is driving hard to be a leader of this next generation of the internet. >> And they're driving open source, too, to give IBM a plug, Don Tapscott, great to have you on the Cube. Good luck with your speech today. A legend in the industry, great thinker, futurist. Amazing work. Blockchain is the next revolution, it will impact, it's an opportunity for entrepreneurs, this is a disruptive enabler, you can literally take down incumbent businesses. Changing the nature of the firm, radical economical change. Thanks so much for sharing the insight. >> Nice hat, too. >> I got a nice hat. I got a free bowl of soup with this hat, as they say-- >> Don: It's all about the Blockchain, baby. >> It's all about the Blockchain. >> It's all about the Blockchain. >> More Blockchain Cube analysis as we disrupt you with more coverage, I'm John Furrier, Dave Velante, stay with us. (musical sting)

[Music] live from cambridge massachusetts extracting the signal from the noise it's the cube covering the MIT chief data officer and information quality symposium now your host dave Volante and paul Gillett hi buddy welcome back to Cambridge Massachusetts we're at MIT Paul Gillan and myself are here for two days and we're really pleased to have sandy Pentland on he's the director of MIT Media labs entrepreneurship program just coming off a keynote mr. Alex sandy Pentland Spellman thanks for coming with you how'd you get that name sandy was that the color you know my dad was named Alex too so I had to get the diminutive so Alexander turns into Zander or Sasha or sandy ah excellent so man it's stuck so we learned from your keynote today that like your mom said hey if every other kid jumps off the bridge do you and the answer should be yes why is that well if your other friends or presumably as rational as you and have same sort of values as you and if they're doing something that looks crazy they must have a piece of information you don't like maybe Godzilla is coming bridges come and it really is time to get off but and so so while it's used as a metaphor for doing the irrational things it's actually shows that using your social context can be most rational because it's a way of getting information that you don't otherwise have so you broke down your talk to chief data officers and new types of analysis smarter organizations smarter networks and then really interesting new new architecture if we could sort of break those down sure you talked about sort of networks not individual nodes as really should be the focus to understand behavior can you unpack that a little well it's a little bit like the bridge or metaphor you know a lot of what we learn a lot of our behavior comes from watching other people we're not even conscious of it but you know if everybody else starts you know wearing a certain sort of shoe or or you know acting in a certain or using a phrase in business like all these new sort of buzz phrases like oh you have to - because it's to fit in it means something it's it's part of being hyper formants and being part of your group but that's not in data analytics today today what they look at is just your personal properties not what you're exposed to and the group that you're part of so they would look at the guy on the bridge and they say he's not going to jump because he doesn't have that information but on the other hand if all of other people who like him are making a different decision he probably is going to jump and your research has been you dig into organizations and you've found the relationship between productivity and this type of analysis has been pretty substantial very substantive offenses a ssin and outside of the organization dealing with customers so people focus on things like personality history various sort of training things like that what we find is compared to the pattern of interaction with other people so who do you talk to when and what situations those other factors are tiny they're often a whole order of magnitude less important than just do you talk to all the people in your group do you talk outside of your group do if you violate the org chart and talk to other people if you do you're almost certainly one of the high productivity high innovation people so what what impact does this have or were the implications of this on organizations which historically have been have been highly Madonn hierarchies reporting structures all of these institutions that we evolved in the post-world War two ERA is this working against their productivity well what they did is is they set some simple rules in that they could deal with and wrap their head around but what we find is that those simple rules are exactly the opposite of what you need for innovation and because really what they're doing is they're enforcing silos they're enforcing atomization of the work and everybody talks about we need to be more fluid we need to be more innovative we need to be able to move faster and what that requires is better communication habits and so what we find when we measure the communication habits is that that's exactly right better communication habits lead to more innovative organizations what's really amazing is almost no organization does it so people don't know does everybody talk to everybody in this group do they talk outside of the group there's no graphic there's no visualization and when you give a group a visualization of their pattern of organization of communication they change it and they become more innovative they become more productive I'm sure you're familiar with holacracy this idea that of doing away with with organizational boundaries and sort of do titles and sure everybody talks to everyone is that in your view a better way to structure an organization think that's too extreme but it's headed in the right direction I mean so what we're talking first of all people try to do this without any data so you know everybody's the same well everybody really isn't the same and how would you know if you're behaving as well as the same as other people or I mean there's no data so so what I'm suggesting is something that's sort of halfway between the two yeah you can have leaders you can have organization in there but you also have to have good flow of ideas and what that means is you have to make talking outside your org chart a value it's something you're rewarded for it means that including everybody in the loop in your organization is something you ought to be rewarded for and of course that requires data so the sorts of things we do with peoples we make displays could just be piece of paper that shows the patterns of communication and we give it to everybody and you know what people actually know what to do with it when you give it to them they say well gee you know this group of people is all talking to each other but they're not talking to that group maybe they ought to talk to each other it's that simple but in the lack of data you can't feel so you instrumented people essentially with let's badges and you could measure conversations at the watercooler yeah they're their frequency their duration not the content not the content just that's the activity just is it happening right and is it happening between groups just just people from this group go to that other groups water cooler stuff like that and that actually is enough to really make a substantial difference in the corporation and you gave an example of you were able to predict trending stories on Twitter better than the internal mechanism and Twitter did I understand that Kerina so what we've done by studying organizations like this and coming up with these sort of rules of how people behave so the notion that people learn from each other and that it's the patterns of communication that matter you can encode that along with machine learning and suddenly you get something that looks like machine learning but in many ways it's more powerful and more reliable and so we have a spin-out called Endor and what that does is it lets your average guy who can use a spreadsheet do something that's really competitive with the best machine learning groups in the world and that's pretty exciting because everybody has these reams of data but what they don't have is a whole bunch of PhDs who can study it for six months and and come up with a machine learning algorithm to do it they have a bunch of guys that are smart know the business but they don't know the machine learning so it endured doesn't supply something like a spreadsheet to be able to allow the normal guy to do as good as the machine learning guys there's a lot of focus right now on anticipating predicting customer behavior better a lot of us been focused on on individuals understanding individuals better is that wrongheaded I mean should marketers be looking more at this group theory and treating customers more as buckets of similar behaviors it's not it's not buckets but treating people as individuals is is a mistake because while people do have individual preferences most of those preferences are learned from other people it's keeping up with the Jones it's fitting in its it's learning what the best practice is so you can predict people better from the company they keep than you can from their demographics always virtually every single time you can do better from the company they keep than from the standard sort of data so what that means is when you do analysis you need to look at the relationships between people and at one level it's sort of obvious you analyze somebody personally without knowing something about their relationships right about you know the type of things they do the places they go those are important but they're usually not in the data and what I find is I do this with a lot of big organizations and what I find is you look at their data analytics it's all based on individuals and it's not based on the context to those individuals absolutely I want to ask you further about that because when I think of the surveys that I fill out they're always about my personal preference Yahoo I want to do I can't remember ever filling out a survey that asked me about what my peer group does are you saying that those are the questions we should be asking yeah exactly right and of course you want to get data about that you want to know if if you go to these locations all the time to go to that restaurant you go to this sort of entertainment who else goes there what are they by what's trending in your group because it's not the general population and these not necessary people I know but they're people I identify with Yammer haps that's why I go to certain restaurants not because my friends go there but because people who I aspire to be like yeah there yeah and and the other way around you go there and you say well gosh these other people are like me because they go here too and I see that they're you know wearing different sort of clothes or they're by or the simplest thing you go to restaurants you see other people all buying the mushi yes maybe I should try the mushi I usually don't like it but seems to work well and this is I like this restaurant and everybody else who comes here likes it so I'll try it right it's that simple so it's important to point out we're talking about the predictive analytics Capas they're probably people watching might say this Sandi's crazy we mean we don't want it personalized we want to personalize the customer experience still I'm presuming sure but when we're talking about predictive analytics you're saying the the community the peer group is a much better predictor than the individual that's right yeah okay so I want to come back to the the org chart these are you saying that org charts shouldn't necessarily change but the incentives should or your previous thing to do is you have an org chart but the incentives that are across the entire organization is good communication within the box you're in and good communication outside of the box and to put those incentives in place you need to have data you need to be able to have some way of estimating does everybody talk to each other do they talk to the rest of the organization and there's a variety of ways you can do that we do it with little badges we do it by analyzing phone call data email is not so good because email is not really a social relationship it's just this this little formal thing you do often but by using things like the badges like the phone calls surveys for that matter right you can give people feedback about are they communicating in the right way are they communicating with other parts of the organization and by visualizing that to people they'll begin to do the right thing you had this notion of network tuning oh you don't want an insufficiently diverse network but you don't want a network that's too dense you might find the sweet spot in the middle desert how do you actually implement that that tuning well the first thing is is you have to measure okay you have to know how dense is the social interaction the communication pattern because if you don't know that there's nothing to - right and then what you want to ask is you want to ask the signal property of something being two dances the same ideas go around then around and around so you look at the graph that you get from this data and you ask you know this Joe talked to Bob talk to Mary talk to Joe talk to you know is it full of cycles like that and if it's too full of cycles then that's a problem right because it's the same people talking to each other same ideas going around and there's some nice mathematical formulas for major in it they're sort of hard to put into English but it has to do with if you look at the flow of ideas are you getting a sufficiently diverse set of ideas coming to you or is it just the same people all talking to each other so are you sort of cut off from the rest of the world in your book social physics you talk about rewards and incentives isms and one of the things that struck me as you say that that rewards that people are actually more motivated by rewards for others than for themselves correct me if I'm wrong if paraphrasing you wrong there but but there's but but rewarding the group or or doing something good for somebody else is actually a powerful incentive is it is that the true the case well you said it almost right so so if you want to change behavior these social incentives are more powerful than financial incentives so if you have everybody in a group let's say and people are rewarded by the behavior of the other people in the group what will they do well they'll talk to the other people about doing the right thing because their reward my reward depends on your behavior so I'm gonna talk to you about it okay and your reward depends on it you'll talk and I don't know so what we're doing is we're creating much more communication around this problem and social pressure because you know if you don't do it you're screwing me and and you know I may not be a big thing but you're gonna think twice about that whereas some small financial award usually it's not such a big thing for people so if you think people talk a lot about you know persona persona marketing when I first met John Fourier he had this idea of affinity rank which was his version of you know peer group PageRank hmm do you do you hear a lot about you know get a lot of questions about persona persona marketing and and what does your research show in terms of how we should be appealing to that persona so sorry good questions about that some time and I don't know what he really originally intended but the way people often imply it is very static you have a particular persona that's fixed for all parts of your life well that's not true I mean you could be a baseball coach for your kid and a banker during the day and a member of a church and those are three different personas and what defines those personas it's the group that you're interacting with it's it's the the people you learn with and try and fit in so your persona is a variable thing and the thing that's the key to it is what are the groups that you're you're interacting with so if I analyzed your groups of interactions I'd see three different clusters I'd see the baseball one I'd say the banking one I'd see the church group one and then I would know that you have three personas and I could tell which one you're in typically by seeing who you're spending time with right now is the risk of applying this idea of behaviors influenced by groups is there the risk of falling over into profiling and essentially treating people anticipating behaviors based upon characteristics that may not be indicative of how any individual might act back credit alcoholics as you example right I don't get a job because people like people who are similar to me tend to be alcoholics let's say this is different though so this is not people who are similar to you if you hang out with alcoholics all the time then they're really eyes are good on that you're an alcoholic it may not be yes and there is a risk of over identifying or or extrapolating but it's different than people like me I mean if you go to the you know the dingy bars were beers or a buck and everybody gets wasted and you do that repeatedly you're talking about behaviors rather than characteristics behaviors rather than characteristics right I mean you know if you drink a lot maybe you drink a lot so we have a question from the crowd so it says real time makes persona very difficult yeah so it was come back to furriers premise was I was Twitter data you know such is changing very rapidly so are there social platforms that you see that can inform in real time to help us sort of get a better understanding of persona and affinity group affinity well there are data sources that do that right so first as if I look at telephone data or credit card data even for that matter sure this geo-located I can ask but what sort of people buy here or what sort of people are in this bar or restaurant and I can look at their demographics and where they go to I showed an example of that in San Francisco using data from San Francisco so there is this data which means that any app that's interested in it that has sufficient breadth and although sufficient adoption can do these sorts of analyses can you give an example of how you're working with the many organizations now I'm sure you can't name them but can you give an example of how you're applying these principles practically now whether it's in law enforcement or in consumer marketing how are you putting these to work well there's a bunch of different things that that go together with this view of you know it's the flow of ideas that's the important thing not the demographics so talk about behavior change and we're working with a small country to change their traffic safety by enrolling people in small groups where you know the benefit I get for driving right depends on your safety and we're good buddies we know that that's how you sign up sign up with your buddies and what that means is I'm going to talk to you about your driving if you're driving in a dangerous way and that we've seen in small experiments is a lot more effective than giving you points on your driver's license or discount on your insurance the social relationships so so that's an example another example is we're beginning a project to look at unemployment and what we see is is that people have a hard time getting re-employed don't have diverse enough social networks and it sounds kind of common sense but they don't physically get out enough compared to the people that do get jobs so what's the obvious thing well you encouraged them to get out more you make it easier for them to get out more so those are some examples when you talk about health care what you can do is you can say well look you know I don't know particular things you're doing but based on the behavior that you show right and the behavior of the people you hang with you may be at much higher risk of diabetes and it's not any particular behavior this is the way medical stuff is always pitched is you know it's this behavior that beer every combination of things all right and so you're not really aware that you're doing anything bad but if all your buds are at risk of it then you probably are too because you're probably doing a lot of the same sort of behaviors and medicine is a place where people are willing to give up some of the privacy because the consequences are so important so we're looking at people who are interested in personalized medicine and are willing to you know share their data about where they go and what they spend time doing in order to get statistics back from the people they spend time with about what are the risk factors they pick up from the people around them and the behaviors they engage in um your message this to the cdos today was you know you were sort of joking you're measuring that right and a lot of times they weren't a lot of the non-intuitive things your research has found so I wanna talk about the data and access to the data and how the CBO can you know affect change in their organization a lot of the data lives in silos I mean if they certainly think of social data Facebook LinkedIn yeah Twitter you mentioned credit card data is that a problem or is data becoming more accessible through api's or is it still just sort of a battle to get that data architecture running well it's a it's a battle and in fact actually it's a political and very passionate battle and it revolves around who controls the data and privacy is a big part of that so one of the messages is that to be able to get really ditch data sources you have to engage with the customer a lot so people are more than willing our research we've set up you know entire cities where we've changed the rules and we've found that people are more than willing to volunteer very detailed personal data under two conditions one is they have to know that it's safe so you're not reselling it you're handling it in a secure way it's not going to get out in some way and the other is that they get value for it and they can see the value so it's not spreading out and they're part of the discussion so you know you want more personalized medicine people are willing to share right because it's important to them or for their family you know if you want to share we're willing to share very personal stuff about their kids they would never do that but if it results in the kid getting a better education more opportunity yeah they're absolutely willing so that leads to a great segue into enigma yeah you talked about enigma as a potential security layer for the internet but also potential privacy yeah solution so talk about enigma where it's at yeah what it is where it's at and how it potentially could permeate yeah so we've been building architectures and working with this sort of problem this conundrum basically datas and silos people feel paranoid and probably correctly about their data leaky now companies don't have access to data don't know what to do with it and a lot of it has to do with safe sharing another aspect of this problem is cybersecurity you're getting increasing the amount of attacks done stuff bad for companies bad for people it's just going to get worse and we actually know what the answers to these things are the answers our data is encrypted all the time everywhere you do the computation on encrypted data you never transmit it you never unencrypted it to be able to do things we also know that in terms of control of the data is possible to build fairly simple permission mechanisms so that you know the computer just won't share it in the wrong places and if it does you know skyrockets go up and the cop scum you can build systems like that today but the part that's never been able never allowed that to happen is you need to keep track of a lot of things in a way that's not hackable you need to know that somebody doesn't just short-circuit it or take it out the back and what's interesting is the mechanisms that are in Bitcoin give you exactly that power so you whatever you feel about Bitcoin you know it's speculative bubble or whatever the blockchain which is part of it is this open ledger that is unhackable and and has the following characteristics that's amazing it's called trustless what that means is you can work with a bunch of crooks and still know that the ledger that you're keeping is correct because it doesn't require trusting people to work with them it's something where everybody has to agree to be able to get things and it works it works in Bitcoin at scale over the whole world and so what we've done is adapted that technology to be able to build a system called enigma which takes data in an encrypted form computes on it in an encrypted form transmits it according to the person's permissions and only that way in an encrypted form and you know it provides this layer of security and privacy that we've never had before there have been some projects that come close to this but know we're pretty excited about this and and what I think you're going to see is you're going to see some of the big financial institutions trying to use it among themselves some of the big logistics some of the big medical things trying to use it in in hotspots where they have real problems but the hope is is that it gets spread among the general population so it becomes quite literally the privacy and security level that doesn't have Warren Buffett might be right that it might fail as a currency but the technology has really inspired some new innovations that's right so so it's essentially a distributed it's not a walled garden it's a distributed black box that's what you're describing you never exposed the data that's right you don't need a trusted third party that's getting attacked that's right nobody has to stamp that this is correct because the moment you do that first of all other people are controlling you and the second thing is is there a point of attack so it gets rid of that trusted third party centralization makes it distributed you can have again a bunch of bad actors in the system it doesn't hurt it's peer-to-peer where you have to have 51% of the people being bad before things really go bad how do you solve the problem of performing calculations on encrypted data because they're classic techniques actually it's been known for over 20 years how to do that but there are two pieces missing one piece is it wasn't efficient it scaled really poorly and what we did is came up with a way of solving that by making it essentially multi scale so it's it's a distributed solution for this that brings the cost down to something that's linear in the number of elements which is a real change and the second is keeping track of all of the stuff in a way that's secure it's fine to have an addition that's secure you know but if that isn't better than a whole system that secure it doesn't do you any good and so that's where the blockchain comes in it gives you this accounting mechanism for knowing which computations are being done who has access to them what the keys are things like that so Google glass was sort of incubated in MIT Media labs and well before yeah my group you go right in your group and yeah it didn't take off me because it's just not cool it looks kind of goofy but now enigma has a lot of potential solving a huge problem are you can open-source it what do you yeah it's an open-source system we hope to get more people involved in it and right now we're looking for some test beds to show how well it works and make sure that all the things are dotted and crossed and so forth and where can people learn more about it oh go to a nygma dot media dot mit.edu all right sandy we're way over our time so obviously you were interesting so thanks keep right there buddy Paul and I we right back with our next guest we're live from see this is the cube right back [Music]