Danny Hillis: Inventor, entrepreneur, scientist
Social Media's never by itself the thing that was going to advance humanity nor is it the thing that's going to destroy humanity is actually a tool that we're going to learn to use time like we learned his fire Pie. Hi everyone welcome to behind the tech. I'm your host Kevin Scott Chief Technology Officer for Microsoft in this podcast. We're going to get behind the tech. We'll talk with some of the people who've made our modern tech world royal possible and understand what motivated them to create what they did so join me to maybe learn a little bit about the history of computing and get a few behind the scenes insights into. What's what's happening today? Stick around hello and welcome to behind the tech. I'm Christina Warren. Senior Club advocate advocate at Microsoft's and I'm got today our guest is Danny Hillis and Danny Hillis. I'm so excited about today's guest. He is an incredible pioneer. He is yes So Danny Danny is perhaps most well known although it's like a difficult thing to save you know given how much he's accomplished like what the single best best known thing was but like when he was a student at MIT started. This pioneering company called thinking machines that built the world's fastest supercomputers send Really pioneered a new type of computer architecture that was Was Revolutionary at the time and that has is informed how we build computers even today and he's also been Head of Disney imagineering nearing and. He's got this crazy invention factory Company that he runs now so like Dan he really is like one of the most interesting people I I know and like so creative and like such an amazing entrepreneur. I'm super excited to be able to chat with him today. I'm so excited to. We should get to the interview. Doubtless chat with Danny in today we'll chat with Danny Hillis. Danny's Inventor Engineer Entrepreneur author as a student. Mit He founded the pioneering supercomputing company thinking machines which built the world's world's fastest computers in the eighties and nineties and pave the way for modern large scale computing. After thinking machines Danny ran imagineering at Disney he cofounded applied minds and applied invention an interdisciplinary group of engineers scientists and artists he is visiting professor at the MIT media lab and a great friend Danny Green Beer so you Perhaps more than any other person I know like have a curious and wide set of interest which is awesome and I would really love to understand. Stand like how that got started like where you curious kid. So I was really lucky in that I grew up. All over the world My father studied handed hepatitis so wherever there was hepatitis epidemic. We went there and live so I got to live in countries in Africa. That don't exist in lots of places in Africa and India got to live in Calcutta in Europe and Little towns the southern United States. And so I really there was always something to be curious about right and like beyond the exposure. Not all of these different cultures and people and ideas like You Dad must have been a little bit fearless and adventurous. You know it's interesting thing I think. In retrospect he was just naive. Because when I have kids of my own I was like why did you brought us into war zones and stuff like that. I would never do that with my kids. Like yeah we didn't really understand what we were doing but it seems to have worked out to try every possible kind of education system system or non education system so he was he an epidemiologist by training. That's okay and What did your mom do? Well actually my mom is a great a story because my mom quit school to put my Father Medical School and I always knew. She was super smart but because she wasn't educated people did not treat her like she was smart and she had a southern accent and In those days that question to be ignored. Yeah well Oh I think might still cause you to be ignored. Well when I went to high school she went back to college and Finish College as and and then when I went to college she went to graduate school and got her. PhD biostatistics. Yeah and then all of a sudden everybody started taking taking her seriously as a statistician and well I mean that that is an amazing story. I mean sad that they didn't take her seriously before she got her ph a happy ending. That's great And so when you were a kid it was like this before the personal computing revolution. So like what was your first I contact with computers so partly. I was very fascinated by technology because I was far away from it so I was in places. Where are you know? It wasn't happening And so that made it sort of more enticing for me and when I was living in Calcutta I went down to the the British Council Library English books. You couldn't take him out that you could read them there. And I found bulls laws of thought. Wow and it was too advanced for me but I got the basic idea boolean logic. This is really cool. This is how computers were and so I wanted to build one but of course I couldn't you couldn't buy transistor or a relay or anything so I built my own. MHM switches by using screen from screen. Doors nails stuck into them and I count allies lots of flashlights and I built. Oh my first computer which was basically fixed logic array. That played tic TAC toe so you would move the switches and it would light up one of the nine squares and now. That's pretty incredible. Actually and did you. Have anybody helping you. I mean that's that's certainly not something I would expect like one of my children to go figure out You know certainly lots of adults helped me like you know nail nails and and things like that but I don't think my parents had much audio of what I was doing but I always got encouragement from the people around me and I think that that's one. I mean I did a bunch of crazy stupid things that didn't work and I got encouragement on those without one more. How and so you know? They always they gave me a lot of freedom to make mistakes and so that was a lot of mistaken crazy projects that didn't work. But that one dea and so that kind of got me on a course and actually won the won. The special prize is in the All India Science Fair. So that was that's awesome and like that must have been a really important thing like getting encouragement at the right point when you're young on Sort of like almost starts positive feedback loop absolutely does and people who are interested in what you're doing and and it doesn't really it's not really necessarily have the knowledge and some sense. Maybe I was a little bit lucky that they didn't have the knowledge because I kind of had to figure it it out for myself in a way that but I had resources like the library for example and always had people that were willing to help as much as they couldn and so it's really interesting. It's so different than the world we live in now. Where of course they can find anything on the Internet but in Thursdays it was really very hard to find information about things and so I wonder about this all the time because I like when I was a kid in the seventies it was still still Tourism no Internet right now. Google wikipedia. No Like in you had to like we were relatively poor so like we only had a few books in the house and you know. My parents had bought a world book encyclopedia from one of the sales people and put it on a payment plan. But like you had to go the library really to go get books and I sometimes like romanticized this idea of like. Oh what would have been like If I were a child now when I had access to the Internet and then like how good that would be and then sometimes I wonder whether or not it would make things too easy when some sense we were all so lucky that we grew up with the technology of computer. Yeah we got to see it in simple enough form. And maybe because I'm older than you. I got to see it in even simpler for him. I remember the first Gal calculator I ever saw in my life. And so in some sense that was an advantage manage because we spent years watching it bill up from the bottom of kind of switching elements in the very simple functions and the machine language programming then all all the layers of software that gradually got put on top of that and now I think it would be very tempting just to kind of skip straight to the real powerful functionality. Yeah and like that's a recurring theme. I mean it's funny like I haven't pro. We've never had this conversation before. But I've I've had this chat on this podcast podcast with a bunch of other people in the same theme emerges over and over again And like there's young one hand all of that complexity and the abstractions that we built up over over the years to sort of package them up in the complexity up in ways where you can very easily Use It to build. Things is great and on the other hand and like not having that deep fundamental understanding of. What's really going on from top to bottom Can Hinder you. Sometimes I ah both kinds of really useful because if you of course if you try to work from that level then you miss a lot of the power of building on what other people have done so on but I mean you said something about like I made some of the first barrel computers and and I say he I wonder if they really the audience is really knows what it meant to make a computer stays so let's let's talk about this. We'll go back to 'em I well. Actually let's let's just go straight there so you you were traveling all over the world You know sort of a precociously curious child And then you you you go to college And it's MIT right. Yeah and actually I went to college really. I mean. The computer thing was cool by. I never thought of it as a career right right. Did they even have a computer. Science program at Mit when you combined with electrical engineer. But when I went there I wanted to be a neurophysiologist silence. Just wanted to say the brain. The brain was obviously the most interesting mystery. And it still actually. I just came from the brain mine conference nice and Yes so this is still basically a mystery US hours we understand a little bit of it but and so when I went to my t- I had read this paper. That was a very excited about that. Stuck probes inside of for all into the adopt nerve and they had worked out the signal. Being sent from the eye to the brain was not just like Pixel it was actually a pattern Detected like a block dot against a moving across a light background so the nerve cells in the eye were encoding information and he's and and it was the paper it was called. What a frog tells? The FROG sprain by Jerry Levin and a couple of CO authors and. I'd read. This is just so excited because this this is probably WANNA do because they're starting to felt like you were just trying to figure out all the neural circuitry and And and my first day of Mit you they have party for the incoming freshmen. And I go to this party and there was this guy sitting there holding forth with the the freshman of pointing out. What are you interested in? Whatever they were interested in he would explain to them by with the crazy thing and so he gets to me and and he says you know what about you? I said I WANNA study neurobiology. And he said Oh that Crock of leap. Yeah Yeah I think I knew who who this was right so he completely tore apart. He told me one good paper that's ever been written and of course you completely tore apart this paper and of course he turned out to be the author of the paper and so So but he did sort of convinced me That that was not the moment to study the brain That it was the tools were too crude. But but he suggested that I go over to meet Marvin Minsk and So I followed that instruction Shen which is another story. That's kind of fun. Yeah Yeah you should tell us the so. I had this instruction to govern and find and the Great Marvin Menzies Ki Moon. Who of course I had heard of? He was legendary totally legendary news. The guy that he and McCarthy had invented the term artificial intelligence yes. Yeah famous Dartmouth Workshop in the summer of fifty five Yeah Yeah and and so. And the I lab in those days often tech wasn't even on campus in the special building the United have special keys to get into so. Of course I went over there and I couldn't even get to US office until without slipping flipping in behind somebody but then I get to his office and he's not there and so I'll hang out and I managed to get a A A job in the undergraduate research job in the building still can't find him Never and I started asking around. They say oh we know. He's down in the basement. This new thing called a microprocessor and he's trying to make it into a personal computer like Alan. Kay was doing often In South Park so I go down to the basement and he only comes in at night to do. This are down the basement night and sure enough you know. There's Marvin surrounded grounded by a bunch of his graduate students and they have big wire wrap boards. And they're working on this thing but I'm so odd by Marvin ski that I don't really feel like I can just open introduced myself. Some sort of hanging out and watch the action and there were some circuit diagrams. So the on the table and start looking at this find mistaken one. I'm like Oh this is my entrees. I go up to Marvin say look you know this mistaken this was it was an inversion of a signal. Okay it was clocking a leading edge instead of a falling jets up version of clocks again. Good mistake for eighteen year old to be able to catch dried. Probably Seventy when I first arrived and so the and he says okay we'll fix it and I'm like vault easily fixed on the machine fixing the diagram and fixing the machine so I did that and then found another mistake and I go w so now just fix them when when you find them you know and so after while Marvin Mesquite just assumed I worked for him and so that was the start of very long relationship so Marvin was European right. He was why I had a couple of advisers. I had. I had a team of Marvin. Men's ski club Shanahan. Dan and Gerry sussman. Yeah it's like the best. PhD Advisors Ever for the dissertation. You were writing incredible. I mean so for the audience like Marvin Muskie is the father of Claude. Shannon is like the father of information theory like basically the foundation of yes the bit and Gerry. Sussman is like one of the most incredible computer scientists who ever lived Like I feel like his His intro tax for computer sciences. Like just the thing of beauty structure and interpretation of computer programs for good. Yeah just an incredible book. Yeah Yeah that was Great Great Group of folks while you your at. MIT studying studying You this is when you founded thinking machines right. Yeah which in those days. That was not a normal normal thing for a student to some company not entirely normal. I mean especially as incompetent. Yeah well it was. It turned it a bigger I was trying to do it at. MIT and couldn't hire people. Because I was a student so so why do this at all well so it was really for artificial intelligence kind of sidetrack so it was very clear that the brain worked much faster than computers and it was very clear that if computers are going to be fast enough that have an architecture that was more like the bright but in those days as the the doctrine of computer science was that if you use more than one processor problem it gets less and less efficient as you get more of it it was called Amdahl's law right if you remember and so the idea was we'll maybe you can use four or five but you can't use fifty or sixty. We are one hundred and I knew that that sort of had to be wrong for artificial intelligence because our circuits which in milliseconds they were much slower than transistors and yet we could recognize a face and a second so I knew that the brain how to parallel our architecture so oh I didn't know then what was wrong with them. Dole's law But I decided that we needed to build parallel computers very pillow computers computers massively parallel computers. And that was when. LSI Technology was coming out. And you could make these circuits. That were in moss circuits in those days. The later became seem all circuits in so I made. I think probably the first chips that had multiple processors on a single chip chill YEP and so had the basics of multi-core idea and that was considered very radical because how could you use multiple processors on a chip. That was every time we present this. Somebody would raise their hands. Excuse me haven't you ever heard of AMDAHL's law right but like what you were doing was like. Let's forget about the fact that you were graduates you when you're doing it which is like one level of incredible but Like what you were doing was just sort of provocatively different. Like the fastest computers in the world. At the time. We're probably the machines cray was building. That's right and they were deeply pipeline Subaru coincidence Super fast switching. You know they liquid gold because they clocked them as fast as you could possibly clocked the whatever the flavor logic they were using at the time and like they they were and they were all about like making the wire short so that the single processor could operate very quickly and they weren't like I forget exactly exactly what the chronology of things were but like they didn't have I mean they never had many processors maybe four eight processors a- and and so. Yeah that was. That was what a supercomputer was in Iris. Billing this thing which was Actually didn't do flooding point for them. All call me as much more like what actually is now like an invidia chip or something like that except I filled room but was an actually. We built two generations. The first generation was actually literally like a in be chat in terms of his architecture and that was the two was the to see him one and seem to. Yeah that's right and those were very much that she oh single instruction operating a lot of data and so on and then later we made things are more like cloud yet. They came later but when we did the the first one has sixty four thousand processors and that was just like a radical. That'd be people would think you were joking when you said that is incredible and I wrote an article for Scientific American. I said you know it's interesting. There will be lots of processors and it's much better to put them close together then to each other than to people. Because is the talk at higher bandwidth yet. So we're going to put like all the processors. Yeah the whole country will run out awesome big pile of it'll it'll be like utility and this is just too implausible. You can't say that is just too because this is and so these sir. Well we'll let you say a single city and this was when all this was in the early eighties probably. Yeah so they made me target down to whole city will run off this. That's how implausible seemed to people in. It wasn't obvious for a while. How general general purpose it was so of course some of the first people to use it where people like Geoffrey Hinton who use it for connections things as it turns me gave of him a few orders of magnitude as it turned out he needed a few more orders of magnitude than that and and for folks who are listening? Geoffrey Hinton is Like more or less the the creator of modern deep learning certainly one of the creators. That's why he was working on a back in those days and pretty much the same algorithms that are the ones that have come to were and constraints. Like they just vary computational early expensive and like nowhere in the world was there enough compute to train a deep neural network so indeed and it turned out to be true that the hypothesis. That wasn't GonNa make big inroads until had much more computing and did did need parallel computing. I think that's fine. Lay turned out to be true. And of course the Just sixty four thousand processors in those days at the clock speeds. They were out wasn't nearly fast enough right well and I remember so I when I was in graduate school will and this actually. I know I was an undergraduate So I was on a National Science Foundation reached research experiences for undergraduates. So it's assistantship at the University of Illinois at the NCSA and When I got there there they had just installed the biggest five in the world that the biggest public and that was probably the fastest computer in the world? The moment was installed absolutely fast in the world and like I remember seeing this thing for the first time in like not only. Was it to pass computer. It was like this thing of beauty like this giant. You know like sort sort of two thousand one space. Odyssey you know like black a monolithic with these red matrix of L.. Read Read Lincoln. Led fantastically beautiful machine. Will think it's funny. I just got a picture of somebody just sent me a picture. The Museum of Modern Art just opened up at the entrance prince way they they have a connection machine with the lights flashing. That's awesome the museum and then like the funny thing I like it. I mean obviously wasn't a real A A real connection machine but there was one in Jurassic Park. It was fun for you. Do see it in background. They they actually did buy real shell of one and so for like five or six years there. Your company made the fastest computers in the world. We did and Yeah there was a list and yoga quite far down the list before it wasn't one of our machines which which is again like for something that you you started this company when you were you you know when you're a student at MIT and it went on to like have this like lasting mark on the world and like the the thing that you and I have chatted about a bunch of times. We're now building a new flavor of supercomputers to train a Models of these deep neural networks and the architecture texture of the machines that we're building right now is more or less what you built thirty years ago. It's a lot faster a lot faster. But that's fundamentally the same market. You had this idea. That sort of informs like three decades telegram the way that we program does this things like malpractice on our built the hardware actually says so. That's look that's one of the slightly nicer things Now versus then. Dan The frameworks that That you code and are like so much so much more powerful so like you. He ended up like writing a thousand lines Python Code. That's amazing and that's the advantage of sort of starting with the advantage of all all the work that's been done compilers for example and things like that it'd be you know when when we built that machine it was literally take a piece of graph paper and start growing the shape for the transistors on chill. Yeah and then you'd go all the way and then you'd have to write a similar. I'd buy every time making new processor. I'd have to write a new similar ride. And then you have a Herculean effort and you have really really smart people working on this aren't you. That's that's probably the biggest legacy of thinking. Machines is because the architectures I don't that style of massively parallel architectures really didn't become mainstream until all you know really are couple of decades later when you know with the cloud in ought to two things one the cloud is the son of multiple instruction route the single instruction route with with graphics processors. But the real legacy I think was the people and it just because you have the fastest machines in the world it attracted did really bright people who had interesting problems so actually one of my favorite examples was I went out to Caltech pack and asks Richard Feynman the physicist. If he had any students that would be interested in coming to the company Eh. This was when I was very first. Starting to you know spend the summer they are someone turns basically and he said Oh. I've heard about your Kooky architecture. Aw I don't have any people. Caltech students have a lot more sense than that. No nobody I know that would be crazy enough. He says he's actually there is is one guy but he doesn't know anything about computers. Maybe he'd be dumb enough to do it and he's a hard worker and actually I think probably he's your best bet and I said okay. Well I'll I'll hire him his name. He's a Richard Feynman. Dick Firemen was like my summer higher. So you you have to admit you had an unusual start up so you had like Marvin work for you at some Father Turing Award winner Nobel Prize Winter Actually. He wasn't Nobel Prize well while he was a noble prize winner but the males at the Sydney Brenner who later won another prize data. We had people come. Eric Lander who is the you know the famous geneticists and runs the broad institute two and he came. He didn't know anything about biology but he was like you know we're starting to sequence the genome and this is the only computer sort of big enough search for the patterns and someone so he chaim and l. before really he was ever heard of in biology so it was really interesting set of people that came out of that and you know went to went on to do really interesting things across the industry so at some point Like you stopped doing doing thinking machines and like moved onto something else like talk a little bit about like how Like what what happened there so first of all. I didn't anything about making a business. I made a lot of mistakes in high set of the business and at some point we started taking money away from Craig Computer Her which have been the most profitable fortune five hundred company when we started And stop being so profitable as we started selling these parallel machines jeans and so they got some Laws passed that. You couldn't export anything more powerful mccray uh-huh and also the dod had to spend any supercomputer abroad had to be op code compatible with wow L.. So we basically All got totally blindsided by that. And because we had managed to the Company for Growth Growth Growth Growth growth is just an exponential exponential curve. When that didn't happen we ran into a cash crunch so we had to do chapter eleven eleven distress sale from everything looking great and very very quickly? I learned a lot of. I mean if I knew what I know. Now I'd never get business in that position right but I wasn't really thinking about the business and so but it it had the happy ending. which was that the whole hardware side of the company got bought? By this workstation company called Sun Microsystems and and so that team went and I managed to Sunday agreed to give every employee that came a share of Sun microsystems stock for fear of thinking machines. Gene stocks are. They all did very well. That's great and so did sort of help make the web happen. And some people went on to like Harry senior roles microsystems systems and did all sorts of like cool things there. Yeah so and and and others went to another part the part of it went or all and did very. Well they are so this is still a really nice. I'd say Alum Team Yup and you know and also just among the customers to I mean really if you had if you had taken the people that were the customers that were you know the graduate students that were working out there where people like Sergei brand right where you know off programming connection machines. Have you just had a portfolio that was investing in either. The people that were alumni of of of thinking machines are the people that are customers of machines portfolio. It would've been great portfolio. Yeah yeah so you went from thinking machines to Disney also. Yeah so that was a very sad moment for me because that was you know unexpected. Thanks to be going great and then Yep and so I felt I let everybody down. I felt really terrible about it and I just said and my kids were a my my daughter was actually born born on the day that the thinking machines filed chapter eleven. Oh so that was tough. So it's just like you know I just want to do something fun for a while that I can relate to my kids on Yup and I had a friend Brand Farren at Disney he's appoint. Why don't you come on out to Disney? And so I had always wanted to be an engineer. Since I was a kid and I got kind of my second education there. Yes I'll I I thought it was just going to be a Lark. I learned a huge amount there. Yeah I've sort of seen some of the work that you all do now in some of your team in like that time at Disney is is really important What some of the stuff that you do in now right yeah it it it definitely is one of the things I learned is what I mean and before I never had a job so that that was the first thing I learned what looks like being inside a big company right and I remember remember the first time I got a paycheck from Disney had like benefits and and I was like? Oh that's why they're called benefits because always before those are things I had to pay take you sort of saw big companies. Were really good out Ryan. It was so easy for them to do things that we're just impossible for a small camaraderie to do but it was also very hard for them to do certain things that we're easy for small companies so that made me sort of appreciate the there was a need to kind of do interdisciplinary disciplinary things. That companies even incredibly creative companies like Disney where it was founded on creativity didn't mean they were really good. Everything they were really grated Billingham theme park making some of the things that imagineering they did while we were there. So bunch of things for example that my favorite project because I got to see it from clean slate to opening was animal kingdom And that was nice of you know why should play kind of part. Could we have and sitting around blank sheet of paper. Look you know. Here's the plot of land. Could we do with that. And all the crazy ideas about what to do within dizzy has a great brainstorming process. Police Sharat for doing that And then going all the way to the day that opening day where I brought my kids to the park. Wow and the park mark. I don't know if you've ever visited all the Disney parks. One of the design principles is. There's always some something in the center of this kind of dramatic orienting thing like the hassle. Right there's a lot of storytelling reasons for that. But there's something special and in the animal kingdom this amazing tree with animals growing in the bar working things like that and just an incredible thing and I go in there with my five year old kids and we look him walk in look at the tree and they look up. I mean they say Daddy. Did you make that or did God. I was like okay. This is is like the P.. That is pretty good. So and you you were working with computer. Scientists in different kinds of people and what I thought of as an interdisciplinary team before I went to Disney my idea idea of interdisciplinary got broadened out and one thing that Disney is really great about and actually Hollywood is really great about this. They have a kind of a different way of doing big projects As usual attack. Which is the studio model? So let's say Disney makes a movie. Actually there are or some dizzy employees. That make the movie but mostly it is a set of people. The you know Disney knows a great director great actor screenwriter and so they pull those things together And a lot of people who are used to working with each other have roles and so they worked with these other multiple projects in different different combinations. And I realized that was really kind of very efficient way to do innovation. It wasn't I mean and also having seen the downside of but the difficulty making a small company where you get a lot of things exactly right to work some of which have nothing to do with the product roster customer or things like that and so it was sort of Nice to SAR see a different way of doing things and see how efficient and how much energy could get out of people and so on and I. I thought wouldn't it be great to technology projects like that where you had a core of people that kind of knew how to do projects together. There were kind the producer director types. You know they have the concept and then you had a big pool of a network of people that were really good GonNa doing things that you bring on when you needed them and that was a really good way to build technology systems. Yeah and so. That's what I ended up leaving Disney with with Bran Ferren. The guy that I went there with and we started a company basically to do that kind of project where we would quickly build a system on that kind of studio model right and that's that was applied minds that was applied mines and the company. You're running now. Is called applied in bench which serve evolved from applied minds and applied minds. End Up doing two kinds of things. One of which was kind of commercial things turned into commercial products and the other thing was was it started doing things for the government that aerospace companies things like that and those Kinda different rhythm to it and over time I I. I was more interested in the kind of commercial. Things was more interested in the more kind of aerospace projects. Those kinds of those kinds of projects so we ended up so doing two different kinds of things but kind of handicapping each other a little bit because the processes were different for those things so eventually went to brand so look brand. Let's see the Stop the government. I'm at work because it has all these regulations and things like that or let's split the company right and in brands like I don't want more than loving it and so we we split it up and still good friends But took part of the company often just concentrated on commercial work and it's really interesting. Commercial work is so fun. It's all looking for things where somebody has an idea of something. That's going to change the world somehow. Now they don't have all the elements to do it but they have some vision or and so that's a commercial partner and then we go when we team up with them almost like. We're there skunkworks Let's if we worked for them and we work with them to build that new product or line a business or something like that. And and it's your teams still fairly multidisciplinary you have physicists. You have chemists. You have mechanical engineers. You have computer your scientists. You have electrical engineers firmware people. It's people are like what I don't get it hugging and have a team bill satellite and a blood test. Yeah I mean yeah. But then like robots that explode bombs for police forces in the ten thousand year clock. which we're going to talk about a minute and it's incredible edible and and We'll part of what makes it work. Is that network of people out there who have deep knowledge in particular things like you know. We needed a fish psychologist. We don't didn't have a fish psychologist on style. I knew one right which I didn't even know I didn't know such a thing existed before I knew you fish psychologist allergists but there is a kind of expertise that's the systems building at the core. Of course everything is computers too right and so the quarter of everything we do. There's some sort of big data so the payroll processing deem is still kind of their machine. Learning is now tool the use and almost everything so I is still a part of the thread it at all. We usually don't call it. Hey I can use machine learning and things like that is. I'm I'm sort of interested in in that machine. Learning is obviously the more technically Technically accurate label for like what most people doing a are doing doing right now. Like it's a very particular thing it's like you have large volumes of data and like you're building some sort of quasi statistical model to like extract patterns from the data. That let you do classification emf Renson and whatnot. Because it's working really well when it works really powerful machines that we have. Yeah but you also have been doing this long enough where you actually know what an I winter is and so we. We've been through a few the hype cycles like. What's your perspective on that right now? So I think intelligence is Minnie's splendid thing There's lots lots of components to it. There's lots of aspects to it and I think it's happened before that we find some aspect of it it's building block of an important and useful and that becomes a because suddenly make progress so right now it is machine learning pattern recognition incredibly powerful building block. And there's still walks of great things to be done with it and use it in everything so I'm a big fan of it but this still lots of things that a human mind does that don't fit into that paradigm so what happens in the past. Is that when you make explosion everybody starts talking about is taking over the world and and this happened with machine vision was speech recognition that happened. When is planning where you can play is would be humans chows and then what happens? Is People say okay. Well that thing now we understand what that thing is but that's not a lie and so you just start using in that thing as a tool and so I suspect that's what will happen with this. Current thing is people will realize there's more to general artificial intelligence. Dan Dan the multilayer neural networks. And of course there are many people who do realize that and so will you know run into the next ax set of heart problems while people still continue to apply these multi level networks. Two very important problems. I don't want to realize how much you have it. They're going to do but in a certain sense like the the boom bust cycle is just like any other boom bust cycle. Where the both extreme ends of the Saigal or not helpful like the over hype Like where you get reckless with investments and you you like have a whole bunch of people who like really miss understand what's going on and are sort of making these leaps leaps of faith basically about what is coming next both positive and negative combat both positive and negative which is really important. Like oh you know like is going to be this apocalyptic bad thing. It's going to be this like you know. Sort of unrestrained Utopia like both of those extremes are like bad things to mirror from from where we're at but the bus cycle that heats up. And then you know the bubble pops and everyone is everyone's in sort of the the doldrums of the aftermath of this whole thing and that's also not helpful because it gets underfund head and it's very hard hard to you good ideas to get any attraction and so on so yeah. I sort of feel like we'd be maybe five or ten years ahead of where we are right now. We had just been able to mediate eight. Some of the boom and bust over the past four decades. Yeah I think that's probably right. That's probably true with technologies. In general part of it happens to with Kalana of what determines the usefulness of technology as people and people's ability to tap to it and and so on so I think part of what causes that cycle is technology goes very quickly and then gets ahead of people's ability to use it and society's ability to adapt to it and then it sort of feels like it's not working and it feels like it's bad and and then you sort of have a reaction to it like we're going through with social media right now and social media's was never by itself thing that was going to advance humanity nor is it the thing that's going to destroy humanity as actually a tool that we're going to learn to use with time like you learn to use fire and so it's it takes us a while to work those things out and sometimes it takes longer to work out the societal response to something than it does actually developed. I mean the thing that I tell. Technology analogy folks about all the time is they. I is not a product. It is Like a feature. It's a technique like machine learning. Is I mean just exactly what you said. It is It's such a useful technique right now that every maker like whether your computer scientists are another flavor of engineer. Scientists are like someone who's trying to create something with technology like ought to be a thing. That's in your bag of tricks. You can use to help you solve your problem any and it's a very very very powerful tool but it's not magic that's right anymore. The Hash table is magic. That's right. Paul has several ashes kind of magic. He passed away and I think you know you can say so. So we've seen waves about this at the one we're going through now and but yeah everybody they should learn about it. Everybody should learn how to use it and I'm not against worrying about the implications of things. Yeah I mean look at things like you know what happens when you have the ability to recognize everybody's spaces. How does that affect you know? Government's ability to control US citizens house. Those are things we really should be working about those things. We'll take longer than the the developing the face recognition. Yeah I mean the thing that I think we need to be doing more of is we need to be having more robust public. The debate about the pros and cons of these things like I. I'm personally uncomfortable in a world where the technologists make policy by virtue of the things that we're building sort of policy is better. Made by policymakers with the input of the public in a democracy. And like you. You have to have everybody sort of playing their part in contributing. It's also a very hard to do. It's hard to guess what the issues are going to be. Yeah it's certainly the first time I saw twitter. I didn't think oh well. Let's think about the fact this is going to have on the political system right. I mean it just never occurred. You're in either and and you know and now I can look back and say Oh actually sounded very big effect and I think we really need to think about that. Yeah we need But it's it's hard to see so even if there had been if somebody had asked that question which I didn't but if somebody had is not clear to me that they would they've been able to think through all the implications on the kinds of emergent behavior and ultimately I do believe that these technologies allergies are going to create a kind of emergent behavior in society. That's good yes because I think that's a trend in evolution cooperate parade and they do better things as they and like the overwhelming trend with human use of technology for the past. Few hundred thousand years has been positive like a certain sense. Like you get assert like. I think fairly trivial that like human like we couldn't even support the population relations human beings that we have right now without just the technology that we've developed over the past fifty years. It's clear things are getting better. Yeah and I never said not just getting physically better but also morally better. Yeah I mean you know the world's a nicer place than it was when I was a kid and the another a lot of things that were just accepted opted that we would no longer accept right now right how women were treated about racial segregation was the norm in the south. When I lived in the south left and my parents I remember my parents while this is wrong? There's nothing you can do about it. Well it turns out there was things to do about it right and in some of the tools like these social media tools that are causing problems right now like actually in em- places had been helpful for remedying some of these he's Like issues of injustice. Yeah and they've helped they've also created injustices. Sometimes you know we've had people literally been killed because of you know runaway runaway memes. That have happened on social media and things like that so we'll we'll learn how to use them but I think you're right. The general trend for technology is not that it makes everything better every time. But it's certainly more steps forward than it has steps backwards and that has been the trend really probably since fire. Alright that is exactly what I was thinking when I said three hundred thousand years probably fire longer than that but you know it's fire it's it's agriculture. It's unsure ensure a few people got burned on that one right early on indeed And it's not that it is monotone positive like not every step is is positive but like what's positive because we willfully and thoughtfully make it into the policy that you're talking about is you can't and just say well we'll make the technology and it will automatically be positive. It's positive because we discuss it. We think about it we think about how to use it and fortunately urgently. Now there's more people that are trying to make the world better than trying to make the world wars. Yeah so one of the more interesting multidisciplinary things that you'd I like that I'm just sort of personally fascinated by this Ten thousand year clock. Can you tell us a little bit about that project project. So is that actually has genesis back. When I was making the fastest machines in the world and all my customers were coming to me and say can you make it faster faster faster instead of nanoseconds can you go to them? Two seconds and and I'm so tired of making everything faster. Faster faster her. I really want to make something slower. I mean it was sort of in my mind. It was kind of a joke but then I heard this story about new college Oxford which rich it's called new college because there's only five hundred years but they were replacing the old beams and new in the new college common room? And you couldn't just go down to the lumber yard and by fifty foot beam in the beyond by the time they did in the nineteen fifties because they weren't trees big enough anymore thus right but Oxford had some forests so they went to the Oxford Forrester said. Do you have any oak trees that we could harvest and the poster said. Yeah we have the ones that were planted to replace the beams in new college when I heard that story. Wow that's planning well it's also I realize how small my life had become that started thinking about it and this was like in the nineteen ninety s while I was thinking and I realized when I was a kid growing coming up in the seventies we were thinking about the year two thousand and here it was the one thousand nine hundred and the future was still like the year two thousand and so it was as if the future has been shrinking by one year per year for my whole life And I wanted to do something that you know stretched out my imagination. More always loved up reading science fiction things like that and I wanted. I wanted to be involved in project. Let me put my mind forward into the future more and so I started taking because I'm an engineer about building something and so I started thinking bill air clock because I wanted to be built out of technology that I knew would last and people could maintain over a long period of time and so on and when I started talking to friends about it I found that it was kind of almost like a Roszak test chest former. I talked to a musician friend like Brian. You know he would like Whoa wait. Kinds of sounds. Is it going to make talk to a lawyer for like well. How do you write the contract for the lander and so everybody would start thinking about whatever it was they thought about but on a different timescale? That's super interesting. Yeah and so I was getting excited about that and then Stewart Brown who is totally remarkable hero liberal mine said you know this making everybody think about things differently. We should start a foundation to think about things like that and and so that was the origin of the long now foundation which actually Bryant he gave the name to And so I've been working on building that clock ever since then and we've built built several versions of it. We started the first versions and the London Science Museum. The next next version you can see actually in San for Cisco or re thing the long now headquarter and then now. We're building the the real one that that will last for ten thousand years in a mountain in Texas instead. Strive to sing a little bit. So you have a mountain in Texas drilled. A shaft hat was the diameter editor of the shadow. It's A. It's a twelve foot diameter shafts. About five hundred feet deep. The reason for all of this is you can't build a building the last ten thousand year so you have to put it in the middle of a mountain and like like not just any mountain like you had to select the mountain to be like geographic geologically stable vessel years of exploring around searching for a mountain and fortunately I found one that was on property that was on by. Jeff Bezos was a big supporter of the foundation. And so it was like okay. Well we're we've got to do this. Yes and so. He's the primary funder of constructing o'clock in the mountain But even make five hundred foot shaft is not as easy as you think but so you have to do. Is You actually have to dig to the bottom of the shaft with dynamite and then you drill a hole a little small hall with an oil well kind of all and then you put this giant Ramiro. pull it up through the mountain. Yeah and none of this like virtually none of this is off. The shelf composed well Yeah so some of that is author was not off. The shelf is is if you want to spiral staircase cut into the rock around Michelle. Then you have to build a custom robot to do that Washington Yeah. Fortunately I did conveniently have this company around. That was good and stuff like that. So we built that we built a robot that climbed up the shaft with a diamond saw cutting a spiral staircase into it. And I mean if you if you look on the long. Now Foundation's foundation's website. You can see movies of this So it's been a couple of years building spiral staircase and then we put into gears and including like giant bells els and the Times that will Bring a different sequence of bells every day for ten thousand years just the mechanical engineering on. This thing is absolutely incredible audible because I mean you had to cycle tests all of these things to make sure that they were going to be able to do their job over ten thousand years. That's a funny thing. What what we learned was that actually most of the things that we tested worked fine the first time but we had to repair the machines tested them about ten times? Sometimes it's actually very hard to make a machine. Tell US ten thousand years worth of cycles without the machine breaking right so yeah pretty much everything that we've had that you know moves or we've tested pretend thousand years worth of motion and they're sort of incredible things in there like you have one of the yet. We have a mechanism in there that is like involves a a gigantic courts. Lund's yes that's the photo. So how do you make. Okay how do you make a mechanical photo cell and the answer is but you first of all you you bill. Like a meter wide hordes lands uh shines light onto a box which when it heats up it expands and that expansion is what triggers in the reason. You need that just because you need something to adjust the clock to keep it on time if nobody visit for a thousand years or something The way that adjusts itself is during in the summer the summer solstice the light shines down. The shaft focuses with that where it's land causes the thing to expand and then that adjust the clock. Yeah and and like this this all I mean to me. It sounds almost like something from like Indiana Jones our tomb raider movie that you know like some future civilization is it's going to discover this and Like it's going to be Like a archaeology project to figure out why this thing is. They're doing what it's doing but is Also a lot of what I was thinking about when designing is what would be like define this after a thousand years of it being lost or discovered Robert and and actually the fun thing was that I realized that you'd really like to know how long it had been undiscovered. So one of the the interesting things about it. Is that when you go up to the clock. It initially reads the time the last person was there And then you wind it so it knows what time it is but it doesn't tell you until you wind up. Oh then when you wind it it moves the dates forward and it moves the astronomical display of the Sun loons and the SARS forward until it gets current time the current date. Then everything stops and now you've reset it says when the next person comes Kelsey when you wound so you even thinking about the game if occasion of like how you get the clock wound. Well it's the story of vacation or you know. This is one of the things I really really learned at at Disney is how important well first of all the hardest part of the building. A ten thousand year clock is that people have to care about it because if they don't care about it then they'll just sell the metal or something right so that's the hardest design problem and I think I learned things at Disney. That helped me with that design problem in the same way. I kind of learned stuff. It might. He helped me with the material science problems and things like fight that yeah but it I'm I I am just fascinated by the the breadth of your curiosity and expertise not is because for many people like you go get like a PhD anything and like that would be your area of expertise and like what you and like you. You know the way that you achieve impact in the world is getting deeper and more focused on this thing and like you just. It's like we have these crazy broad conversations about things Like I was incredibly fortunate in the mentors that I had. I mean if you just think of people like Marvin Linski Claude and Richard Feinman. Those were all people like that. They were people that had curiosity. And so because I was just lucky to have had them as an example of a sub at different way of approaching the world. And so it's just I you know I are a lot of fun every day I have to say so So we're we're both really lucky to be alive at this time. Yes us Because probably they would have burned us of the steak or something during a lot of times in history. So yeah we yes They they they probably would Like we it is one of the things that I am I'm very grateful. For by modern societies societies. Not just tolerant of curious is people but like actually encourages and I hope we never lose that done. And that's not a normal thing in history. Actually it is not unlike you can go read plenty about how curious people were persecuted in the past So hopefully not something. We lose anytime soon. So we're almost out of time and like I always ask people What they do outside of work for five I may be a peculiar Russian? Ask She because I think. You've structured your life brilliantly where you have fun in like all of the work that you do. What do you do Outside of well. Let's see I mean in really. I have to say that there is kind of a blend of of farming work for me but I do some things that I have no excuse for doing at all at work like like I make perfume Know that and I do that really just because it uses a different part of my brain than everything else I do because I tend to be an over thinker over very logical and my thing. You can't be logical about perfume you can't even really give names to the right. So Oh it's a set of a meditative thing for me because it turns off what a neurophysiologist we call my default mode network right right and So so my default mode is very analytical but in that you really just have to be experiential so I look for excuses to do that out in nature that sorts of things to compliment. Yeah let's Super Goal while this was great everytime I talked to learn something new Thank you so much for being on the podcast today. Well it's as pleasure being interviewed by a alike mind awesome. So that was Kevin Scott chatting with Danny Hillis Kevin. That conversation was incredible. I would love to just like I would love to watch Netflix. Show about Danny. NFL Danny's frame for four sure And like I I always have have a great time chatting with Danny. I've known him for a couple years now And I think the thing that always strikes me about Danny is this Just this mindset that he has That I think is a big part of what's allowed him to do the things that he's done so like part part of that mindset is he. I think just sort of assumes that a problem is solvable until like he's got some pretty serious proof that it isn't which leads Tim just dive into things and persist like you can sort of see it. Even the TIC TAC toe machine that he created when he you know I love that story ready so much. That was so funny. Because listen to that you totally can see how a kid who's in India who is taking books off the shelf and figuring out how to build this machine gene. How that person goes on to be adult? WHO's working at Disney and running the imagineering stuff and is is building all these these machines and making all these inventions like it completely makes sense? Yeah I mean art totally makes sense but like you really do have to appreciate what an unusual set of circumstances that was so this is Calcutta. GotTa look I I think in the nineteen sixties so before the personal computing revolution had even begun to start And you in a he. He's just sort of figuring this out on his own Without mentors but like you know I. I think in the conversation when we pressed him like he You know he has this sort of humility about what he did and so granted. He's an incredibly smart person. But like the thing that's really important. I think thing for all of us to understand is that he had a whole bunch of failed attempts at building this thing before he got the successful thing And like take that mindset and ability to like not only jump into a problem in the first place but then to persist through even when you fail a bunch of times that trying to get to the solution like that is an incredibly important part about being a really effective creator even entrepreneur without a doubt because realistically we you know you're going to fail they're going to be things that don't work out and I think it's really inspiring to see someone who has been so successful and has done all these amazing things and is so smart. Admit I've had to you know. Try a bunch of times. I've had to figure things out. It hasn't just been super easy because sometimes the myth is just. Oh you you know I. It was just that my fingers and it was done and to know that it it took persistence and creativity and think about how to solve problems differently into to try and try and try again is really inspiring. Yeah and I think this is one of the things that people who aren't in the day to day grind of creating technology engineering new things like doing science sometimes. Don't don't get to see so like what you see is like the in thing that POPs south after we've been successful and the reality is even for like incredibly brilliant people. You have more failures than you do successes on your way to you that success. There's a there's a great episode of the Simpsons where Homer is obsessed with Thomas Edison. And he's trying to come up with his own inventions. And when he goes to the Thomas Edison Museum. He finds a list of Thomas Edison comparing himself to Leonardo Da Vinci and he suddenly feels better about himself that he didn't you achieve. What Edison had? I think that's a good thing to kind of put into perspective that that there's a lot of failures and there's a lot of attempts that as you said we don't always see When we see the final product but but is part of the process of creating things yes indeed And so like for everyone listening to the podcast like that's just more encouragement for you all to like go out and try and try and try again because ultimately that's the only way that anyone ever gets to like something being new and interesting and successful absolutely all right. Well we are about out of time as always we would love to hear from you at behind the tech at Microsoft Dot Dot Com. So tell us what's on your mind. Maybe tell us about some of the various tech innovations that you're excited about retail spot. Some of the ways that you've tried to do something maybe you failed maybe succeeded. He did tell us about your tech euros and maybe we will invite them on the show and of course be sure to tell your friends and colleagues about the show. Thanks for Listening Act.