[4.037][S02] So here we are, the last episode in this series of the DeepMind podcast.[9.576] [9.576][S02]My name is Hannah Fry. I am a mathematician,[12.045] [12.045][S02]and someone who is deeply intrigued by artificial intelligence.[16.049] [16.049][S02]Much like you, I imagine, since you made it this far.[19.219] [19.219][S02]Now we’ve been toying with the big questions in this series.[22.456] [22.456][S02]What is intelligence? How does an algorithm learn?[25.526] [25.526][S02]And what to do with the AI future once we get there?[29.696] [29.696][S02]And I have been asking the team of scientists and engineers[32.432] [32.432][S02]here at DeepMind to give us their take of where things are at[36.403] [36.403][S02]and where they’re going. But now for this final episode,[40.24] [40.24][S02]we have a chance to catch up with Demis Hassabis,[43.31] [43.31][S02]the co-founder and CEO of DeepMind[46.113] [46.113][S02]to hear what he has to say on these questions and more.[50.05] [52.252][S02]Demis Hassabis grew up in North London in the 1970s.[55.822] [55.822][S02]By the age of 13, he was ranked 2nd in the world at Chess in his age group.[61.762] [61.762][S02]At 16 he worked as a games designer-[64.131] [64.131][S02]remember Theme Park? That was him.[66.567] [66.567][S02]Then he went on to study computer science[68.802] [68.802][S02]and then neuroscience before setting up[71.004] [71.004][S02]DeepMind with his two co-founders Shane Legg and Mustafa Suleyman.[75.442] [75.442][S02]His accomplishments are ferociously intimidating.[79.513] [79.513][S02]But as an article in the Times put it,[81.582] [81.582][S02]Demis doesn’t even have the good grace to be socially deficient.[85.886] [85.886][S02]But if all of that makes it sound like Demis is a man with a plan,[89.857] [89.857][S02]then you’d be right.[91.625] [92.226][S01] I had in mind something like creating a company like DeepMind[95.162] [95.162][S01]to research AI from a long time ago,[97.698] [97.698][S01]so I was sort of working back from the end state[100.367] [100.367][S01]which is what would I need, what skills would I need,[102.936] [102.936][S01]what experiences would I need to even stand a chance[105.472] [105.472][S01]of even building something like that.[106.907] [106.907][S02] Because these different aspects of your life -[108.475] [108.475][S02]the chess, the neuroscience, the games design,[110.277] [110.277][S02]they’re not disconnected, I mean they do build to a bigger picture.[113.313] [113.313][S01] They do. And it’s hard to say which way round it is -[115.749] [115.749][S01]so I picked those subjects and those things to study -[118.685] [118.685][S01]say computer science at Cambridge, and then cognitive neuroscience at UCL[121.989] [121.989][S01]because I wanted this component of computer science[125.025] [125.025][S01]and neuroscience to come together[127.16] [127.16][S01]and obviously that’s what we do at DeepMind,[129.563] [129.563][S01]but even the game stuff, that taught me about creative thinking,[133.967] [133.967][S01]also a massive engineering projects,[136.637] [136.637][S01]and then of course it ended up that we used games as our main vehicle[140.941] [140.941][S01]for proving out our AI algorithms. One other thing I’ve learnt from games[145.979] [145.979][S01]is to use every scrap of asset that you have - like in games,[150.017] [150.017][S01]you always have a limited resource pool like you know, if it’s a chess game,[153.52] [153.52][S01]it’s the chess pieces you have left on the board,[155.789] [155.789][S01]and one way to think about games is maximising[158.759] [158.759][S01]the use of the of the assets you have left.[161.361] [161.361][S01]Perhaps that’s why I was biassed towards using games,[163.564] [163.564][S01]but I also felt it was the logical way to go about building AI.[167.634] [167.634][S02] What was your Phd in?[169.736] [169.736][S01] My PhD was in cognitive neuroscience[172.573] [172.573][S01]and I actually decided to study[176.543] [176.543][S01]how memory and imagination works in the brain,[179.847] [179.847][S01]and the reason I chose cognitive neuroscience[181.782] [181.782][S01]is I wanted to better understand[183.25] [183.25][S01]how the brain does certain cognitive functions[186.186] [186.186][S01]so that perhaps we could be inspired on new types of algorithms[189.756] [189.756][S01]based on how the brain works,[191.692] [191.692][S01]and so it’s a good idea to pick functions[194.828] [194.828][S01]that we don’t know how to do in AI[197.097] [197.097][S01]and ah I went to study with Eleanor Maguire at UCL[201.134] [201.134][S01]and she’s one of the world’s leading experts in the hippocampus,[204.471] [204.471][S01]which is critical for memory.[206.173] [206.173][S01]But I told her that what I really wanted to look at was imagination[209.643] [209.643][S01]which is um you can also think of it[211.445] [211.445][S01]as simulating things in the future, in your mind.[215.115] [215.115][S01]Ah for obviously it’s useful for planning but also for creativity.[218.452] [218.452][S01]And the reason I was interested in that is of course[219.953] [219.953][S01]that’s an incredibly important part of human intelligence[223.19] [223.19][S01]and it’s also something I used a lot in my games design career.[227.227] [227.227][S01]So I used a lot of visualisation techniques[229.796] [229.796][S01]and imagining how would a player viscerally like play this game,[233.934] [233.934][S01]like Theme Park and then you try and change something about it -[236.904] [236.904][S01]all in your mind before or in sketches -[239.673] [239.673][S01]before you went to the trouble of programming it all.[242.075] [242.075][S01]And it felt to me that we were using a similar type of process[246.113] [246.113][S01]to the way when we’ve lucidly remember things that have happened to us,[249.917] [249.917][S01]so I thought there maybe there would be a connection[252.352] [252.352][S01]with this kind of you could imagine like a simulation engine of the mind[255.956] [255.956][S01]that was being used both for imagination and memory,[258.759] [258.759][S01]and that’s what I wanted to work on during my PhD.[262.095] [262.095][S01]And we ended up discovering something quite important that that[264.364] [264.364][S01]in fact the hippocampus was at the core of both of those two types of function.[269.903] [269.903][S01]It’s critical for memory, which we already know,[272.372] [272.372][S01]but it’s also critical for imagination.[274.741] [274.741][S01]And you can’t really imagine vividly without your hippocampus[279.079] [279.079][S01]so we ended up discovering this important thing[282.115] [282.115][S01]and then subsequently that’s been at the heart of a lot[284.551] [284.551][S01]of what we try to do in AI[286.854] [286.854][S01]is build memory and imagination abilities into our AI systems,[291.325] [291.325][S01]and we’re still doing that now.[292.826] [292.826][S02] When it comes to bringing those ideas across[294.695] [294.695][S02]and trying to implement them in AI,[296.463] [296.463][S02]where do you find that balance between just directly copying[298.932] [298.932][S02]what the brain’s doing and and and using it for inspiration?[302.269] [302.269][S01] So that’s very important sign post[304.338] [304.338][S01]when you’re um scrabbling around in the dark in the unknown of science,[308.308] [308.308][S01]any signpost is really valuable,[310.344] [310.344][S01]and the brain is the only existence proof[312.312] [312.312][S01]we have in the universe that intelligence is possible.[315.449] [315.449][S01]So it always felt to me that it would be crazy to ignore that[319.119] [319.119][S01]as a source of information of how to build AI.[322.055] [322.055][S01]So we use neuroscience for two things -[324.825] [324.825][S01]one is inspiration for new ideas about algorithms or architectures[329.997] [329.997][S01]to representations that the brain uses.[331.965] [331.965][S01]And then we can get some inspiration for that for new types of algorithms.[335.536] [335.536][S01]The second way we use neuroscience is what I call for validation.[339.406] [339.406][S01]So we may already have some idea from coming from engineering or mathematics[344.344] [344.344][S01]about how to build a learning system that say reinforcement learning -[347.915] [347.915][S01]that came from engineering disciplines and operational research first,[352.152] [352.152][S01]but then in the 90s we discovered that the brain[355.022] [355.022][S01]also implements a form of reinforcement learning[357.224] [357.224][S01]and what that means is that from an AI perspective[360.16] [360.16][S01]you can be sure that reinforcement learning[362.963] [362.963][S01]could plausibly be a component part of an AI system[366.466] [366.466][S01]because it’s in the brain and we know the brain is a general intelligence.[370.003] [370.003][S01]So that means - that’s really important if you’re thinking about[372.806] [372.806][S01]where to put your engineering resources and effort -[375.375] [375.375][S01]you know that if it doesn’t work right now,[376.977] [376.977][S01]and things never work first time in research or engineering,[379.546] [379.546][S01]it’s worthwhile pushing that harder[382.182] [382.182][S01]because you know eventually this must work[385.352] [385.352][S01]because the proof of concept is the brain.[387.554] [387.554][S01]Having said that though, there is another school of thought from[390.557] [390.557][S01]AI practitioners and neuroscientists that we need to slavishly copy the brain[395.596] [395.596][S01]completely from the bottom up like on a neuronal level[399.6] [399.6][S01]and I think that’s also the wrong approach.[401.235] [401.235][S01]What we’re after is what I call a systems neuroscience approach[404.771] [404.771][S01]which is that you’re interested in the algorithms[407.174] [407.174][S01]and the architectures that the brain is using.[410.077] [410.077][S01]Not necessarily the exact implementation details,[413.046] [413.046][S01]because I think that’s likely to be different for in silicon systems -[417.384] [417.384][S01]like in computers compared to carbon based systems like our minds.[421.221] [421.221][S01]There's no reason to think that we would implement[423.757] [423.757][S01]exactly the same implementation details in a silicon[426.86] [426.86][S01]based system that’s going to have different strengths and weaknesses[429.93] [429.93][S01]than a carbon based system like our minds.[432.299] [435.335][S02] Normally tech startups have customers, they have products,[438.772] [438.772][S02]but this is sort of more like a start-up research facility.[442.342] [442.342][S01] Yes.[443.544] [443.544][S02] How do you get something like that off the ground?[445.479] [445.479][S01] It’s pretty hard, I mean -[447.114] [447.114][S01]you’re right in that it’s a very unusual company.[450.717] [450.717][S01]What I try to do is basically take the best from start-up world,[453.654] [453.654][S01]the kind of focus and energy and um pace[457.324] [457.324][S01]that you get in the best start-ups um say in Silicon Valley.[460.794] [460.794][S01]And I wanted to combine that with the best from academia,[463.73] [463.73][S01]which is blue sky thinking, incredibly bright people,[467.634] [467.634][S01]working on you know long-term, big research questions[471.505] [471.505][S01]and stepping into the unknown all the time,[474.141] [474.141][S01]and you know obviously I spend some time in academia myself,[477.644] [477.644][S01]and there’s very great aspects about academia,[480.28] [480.28][S01]but there’s also some things that are frustrating.[482.749] [482.749][S01]Um mostly around um the organisational aspects[486.22] [486.22][S01]and the pace of it can sometimes be slower than you would like.[489.556] [489.556][S01]It’s difficult to get momentum behind things in the way you can a start-up[493.36] [493.36][S01]if it if it’s you know if it things are going well,[496.263] [496.263][S01]but I when I was in academia and I’d already obviously started[499.466] [499.466][S01]and been involved with a few start-ups before going back to do my PhD,[502.436] [502.436][S01]so I’d experience both sides, and I didn’t feel like there[505.506] [505.506][S01]was any reason why these should be mutually exclusive environments.[509.209] [509.209][S01]Although they have generally been treated as very different,[511.812] [511.812][S01]almost opposite environments.[513.547] [513.547][S01]And there’s a lot of things that do seem opposite,[516.116] [516.116][S01]but I felt if you if you were kind of smart about it,[519.052] [519.052][S01]you could extract the best of both those worlds[521.722] [521.722][S01]and combine them into some kind of hybrid organisation,[524.892] [524.892][S01]and I feel that’s what DeepMind is.[526.96] [526.96][S01]And I don’t think many people have ever done that and and so[529.563] [529.563][S01]that’s why it seems quite strange.[531.565] [531.565][S01]Probably as an organisation I think we’ve shown with our scientific output,[536.336] [536.336][S01]even if you measure it by normal measures, Nature, Science papers,[538.972] [538.972][S01]this kind of thing that normal academic labs[540.607] [540.607][S01]would measure themselves by, we’ve been very successful,[543.577] [543.577][S01]and I think you know, we’ve been also on the other side things[545.946] [545.946][S01]we’ve been able to produce really big breakthroughs[549.049] [549.049][S01]that took a lot of engineering effort as well like AlphaGo[552.085] [552.085][S01]which would have been very difficult I think to do in academia,[554.421] [554.421][S01]in a in a normal, you know, small academic lab.[557.324] [557.324][S02] One of the thing that makes DeepMind I guess a bit unusual[560.594] [560.594][S02]is that you publish your work -[563.096] [563.096][S02]I mean other companies don’t really do this - is there some way[565.666] [565.666][S02]that you’re kind of giving away your competitive advantage, really.[568.635] [568.635][S01] Yeah, it’s an interesting issue actually,[570.27] [570.27][S01]so we’ve always published everything we’ve done,[572.639] [572.639][S01]and lots of companies do wonder you know why we’re doing that[576.577] [576.577][S01]because a lot of other companies don’t necessarily do that.[579.947] [579.947][S01]We feel it’s part of the scientific discourse,[582.449] [582.449][S01]like that’s the right way to do science.[584.585] [584.585][S01]We really believe in sort of peer review journals[587.254] [587.254][S01]so that your work is scrutinised at the highest level by your peers,[590.691] [590.691][S01]which is the you know, the gold standard in science.[593.193] [593.193][S01]That’s why we publish in the top journals like Nature and Science.[596.096] [596.096][S01]Also you do get more exposure for your ideas like that,[599.9] [599.9][S01]so some of our top papers had been cited like more[602.669] [602.669][S01]than 5,000 times now in the last 2-3 years,[605.072] [605.072][S01]some of the most cited papers in the world, so that’s great.[608.175] [608.175][S01]You know, and I think that if a community shares ideas like[610.244] [610.244][S01]that the whole field can advance much more quickly[613.28] [613.28][S01]than if everyone was to keep their ideas secret,[615.883] [615.883][S01]but you know, there are some interesting aspects to that -[618.519] [618.519][S01]one is the competitive side,[620.12] [620.12][S01]I mean I feel there that you just need to carry on innovating[623.924] [623.924][S01]than a faster pace than anyone else. That’s the most important thing,[627.094] [627.094][S01]not trying to keep hold of the ideas you already innovated.[630.364] [630.364][S01]You should just be - by the time you’ve you know, you’ve published it,[632.833] [632.833][S01]you should be one or two ideas even further down the line[635.736] [635.736][S01]if you’re continuing to work at the same pace[638.639] [638.639][S01]and the same level of innovation,[640.44] [640.44][S01]so I think that’s really the biggest sort of protection against competitors[644.778] [644.778][S01]- is your pace of innovation.[646.813] [646.813][S02] In the early days, I mean back in sort of you know 2009 -[649.216] [649.216][S02]2010, when AI wasn’t the hot topic that perhaps it is today,[653.187] [653.187][S02]did you find it difficult to get attention from the people,[658.025] [658.025][S02]that I mean, I think I remember reading[659.56] [659.56][S02]that you decided to go straight for billionaires[661.862] [661.862][S02]rather than millionaires when it came to investment.[664.064] [664.064][S01] Yes. Well, that was incredibly tough,[666.433] [666.433][S01]so it’s really hard to remember now, even for me, like 10 years ago,[670.704] [670.704][S01]you know no one was investing in AI.[672.339] [672.339][S01]It was an impossible thing to get money for actually.[675.142] [675.142][S01]You know no one would invest, and it’s still very difficult today[677.711] [677.711][S01]I think on what I would call a deep technology[680.514] [680.514][S01]or a science based start-up, right?[682.983] [682.983][S01]And with no clear product in mind. I mean what we were basically saying[686.32] [686.32][S01]is we were going to build this incredible general purpose technology[690.524] [690.524][S01]that as it got more powerful[692.426] [692.426][S01]there should be a myriad of things you could just apply it to.[695.262] [695.262][S01]But you know, that sounds probably pretty far-fetched[699.366] [699.366][S01]to a normal kind of investor.[701.602] [701.602][S01]It was almost like well that’s what academia is for, isn’t it?[705.038] [705.038][S01]You should be just - if you don’t know - you know it’s blue sky research,[707.975] [707.975][S01]you don’t know when it’s going to work, it’s pure research,[710.844] [710.844][S01]then um go and do that for another 10 years in academia,[713.981] [713.981][S01]and then come and talk to them when it’s working.[716.083] [716.083][S01]But that would have been too slow. And I could see that within academia,[719.753] [719.753][S01]so then that’s why I decided not to go after normal venture capitalists[723.924] [723.924][S01]who certainly in Europe or in the UK they would want to make 10x return,[728.529] [728.529][S01]maybe within 3 - 5 years, right? That’s the kind of time horizon.[732.032] [732.032][S01]Of course that’s no good for a research based company,[735.169] [735.169][S01]you know you haven’t barely got going after 3 years right?[737.804] [737.804][S01]So what you need is a profile investor who is more interested in 1,000x return[742.776] [742.776][S01]but they’re willing to wait 10 years, maybe even 20 years,[746.647] [746.647][S01]and that kind of profile of an investor basically just does not exist in Europe.[751.251] [751.251][S01]Certainly didn’t back in 2010.[753.12] [753.12][S01]Really you’re talking about Silicon Valley, self-made billionaires[757.457] [757.457][S01]I guess, who both have deep enough pockets[759.726] [759.726][S01]to take that kind of bet, and if it doesn’t work, it’s okay.[763.063] [763.063][S01]But they’re also personally interested in these types of topics[766.066] [766.066][S01]and have seen incredibly ambitious things work[769.269] [769.269][S01]because usually that’s how they’ve made their money.[772.339] [772.339][S02] Just going back to the idea of how everything[774.474] [774.474][S02]sort of slots into place - all the different aspects,[776.61] [776.61][S02]all the different passions that you have slots into place.[778.512] [778.512][S02]Didn’t chess play a role in you getting your first funding?[781.281] [781.281][S01] Yes, it did. So um chess has been key you know core part of my personality[785.919] [785.919][S01]I guess because I’ve been playing it for so long,[788.188] [788.188][S01]and I think a lot of my thought processes developed[790.858] [790.858][S01]because of that - so planning,[793.227] [793.227][S01]and thinking about problem-solving, all of these aspects[796.196] [796.196][S01]which I think are useful for for anything that you do in your life.[800.133] [800.133][S01]But it also turned out to be useful directly.[802.202] [802.202][S01]Because one of the first investors we talked[804.605] [804.605][S01]to was a chess player themselves[806.974] [806.974][S01]and a pretty strong junior chess player in the US[809.977] [809.977][S01]and when we were doing sort of our background reading on this,[813.046] [813.046][S01]we spent about a year preparing for this meeting almost[815.849] [815.849][S01]and there was an important meeting[817.084] [817.084][S01]because we knew that not very many people would get what we were doing,[820.22] [820.22][S01]and this was one of the people who felt that we would.[822.289] [822.289][S01]So it was important and we couldn’t get a meeting cause[825.192] [825.192][S01]we had no contacts in Silicon Valley,[827.294] [827.294][S01]you know I didn’t know anyone over there in California[829.73] [829.73][S01]-nor did Shane and Mustafa -[831.064] [831.064][S01]you know it’s sort of um how do you break into that world?[834.434] [834.434][S01]And so we finally managed to get asked to a conference[837.938] [837.938][S01]where this billionaire was sponsoring, and then we knew we would meet him[841.508] [841.508][S01]at some kind of after-conference party, but the problem is,[844.311] [844.311][S01]is that there are hundreds of people all trying to pitch him their ideas.[847.781] [847.781][S01]So if you’re just if you’re just another one pitching your another crazy idea,[851.685] [851.685][S01]it’s very unlikely you’re going to get noticed, right?[853.787] [853.787][S01]So I thought instead of that, I’d take this calculated risk[856.723] [856.723][S01]and talk to him about chess instead,[858.592] [858.592][S01]but then you have to have something interesting to say[860.794] [860.794][S01]about chess that may be you hadn’t thought of -[862.796] [862.796][S01]so I used my number one fact on chess that even surprises grand masters,[867.367] [867.367][S01]which is that thinking about it from a game designer point of view,[870.704] [870.704][S01]you know why is chess such a great game?[872.573] [872.573][S01]How did it evolve into such a great game?[874.708] [874.708][S01]And what is it that makes it so great? And my belief is that it’s actually[878.478] [878.478][S01]because of the creative tension of the bishop and knight.[882.182] [882.182][S01]The bishop and knight are basically worth the same -[884.618] [884.618][S01]they are three points each, but they have completely different powers,[889.556] [889.556][S01]and that asymmetry - that sort of creative asymmetry[892.526] [892.526][S01]that happens with the bishop and knights being swapped into various positions[896.163] [896.163][S01]I think is what makes chess a fascinating game.[898.966] [898.966][S01]And so I basically pretty much led out with that line -[901.635] [901.635][S01]I don’t know how I managed to crow bar that into a drinks party -[905.272] [905.272][S01]but I did, but it made him sort of stop and think,[907.908] [907.908][S01]which is exactly what I was hoping. And then he invited us back the next day[911.879] [911.879][S01]to do a proper pitch of our business idea,[914.147] [914.147][S01]so we actually got half an hour with him,[916.183] [916.183][S01]rather than one minute over some drinks,[918.485] [918.485][S01]so ah that actually you know worked out.[920.854] [920.854][S01]So you could say chess worked on two levels then -[922.99] [922.99][S01]the meta level of planning for that[924.925] [924.925][S01]and also actually chess is an intriguing subject in itself.[928.228] [928.228][S02] So actually getting funding from billionaires is really simple -[930.531] [930.531][S02]spend a year studying their interests, come up with a genius idea[934.201] [934.201][S02]that will catch their attention and then and then away you go.[936.537] [936.537][S01] And you have to do a good pitch after that, easy.[939.273] [939.273][S02] Simple! Very straightforward.[941.375] [943.31][S02]One thing that you hear time and time again in this building[946.547] [946.547][S02]and actually throughout this podcast series is how[949.082] [949.082][S02]DeepMind wants to use artificial intelligence to solve everything.[953.82] [953.82][S02]So here is the chance to ask - what do they actually mean by that?[958.091] [958.091][S02]Do they want to be the ones addressing every one of the world’s problems[961.728] [961.728][S02]once intelligence is cracked?[964.231] [965.832][S01] So I’ve you know I have listed -[967.501] [967.501][S01]a working list of a dozen to a couple of dozen scientific problems[971.872] [971.872][S01]that I feel are these kinds of root node problems,[975.976] [975.976][S01]and if we could crack all of those,[978.278] [978.278][S01]then I feel like that would transform society for the better,[981.582] [981.582][S01]and open up all sorts of areas in you know medicine and science[985.385] [985.385][S01]for us to make breakthroughs in.[986.787] [986.787][S02] Go on - give me the list [S01] I can’t -[988.622] [988.622][S02] Some of the list[990.524] [990.524][S01] Well some of the list of things like[992.226] [992.226][S01]I think a key thing we need to crack is cheap, abundant energy[995.596] [995.596][S01]that is renewable and clean.[997.097] [997.097][S01]And so, if that’s fusion, or just way better solar panels[1001.201] [1001.201][S01]with way better batteries with room temperature superconductors,[1004.838] [1004.838][S01]that would also solve that problem.[1006.607] [1006.607][S01]So you know I think there’s a number of solutions to that -[1009.576] [1009.576][S01]some are material science solutions, some are physics solutions,[1012.513] [1012.513][S01]and we should have a go at cracking all of those,[1014.414] [1014.414][S01]but if you crack that, then that would open up all sorts of new issues,[1018.685] [1018.685][S01]so I’ll give you an example - water access - access to clean water.[1022.422] [1022.422][S01]It’s going to become increasingly more important[1024.825] [1024.825][S01]as the population in the world grows, right?[1027.528] [1027.528][S01]And it’s already becoming in some countries more valuable than oil[1030.597] [1030.597][S01]because you know there’s just so little, fresh clean water around, right?[1034.234] [1034.234][S01]for a lot of communities, especially poor communities,[1036.703] [1036.703][S01]it’s an incredible problem.[1038.105] [1038.105][S01]But we have a solution already - it’s desalination, right?[1041.742] [1041.742][S01]70% of the earth is water but it’s salt water,[1045.045] [1045.045][S01]so how do we deal with that? Well desalination technologies exist,[1048.882] [1048.882][S01]the problem is they cost too much energy.[1050.651] [1050.651][S01]They’re too costly. So some rich countries can do it -[1053.287] [1053.287][S01]so I think Israel gets a lot of their water like this[1055.522] [1055.522][S01]and some other countries like that,[1057.09] [1057.09][S01]but of the poor countries it’s too expensive.[1059.593] [1059.593][S01]So if you’ve solved the renewable, cheap, clean energy problem,[1064.798] [1064.798][S01]then you would automatically solve the water access problem.[1069.77] [1069.77][S01]Almost straight away because um that’s actually the issue.[1073.173] [1073.173][S02] So where do you want to be[1074.575] [1074.575][S02]when the water salivation problem is solved?[1077.644] [1077.644][S02]Where do you fit into that story?[1080.08] [1080.08][S01] I hope that we will have been integral[1083.283] [1083.283][S01]in coming up with those solutions[1084.651] [1084.651][S01]by doing something say in fusion or in material science[1089.423] [1089.423][S01]more likely where we’ve come up with using an AlphaZero like system,[1093.794] [1093.794][S01]you know a battery that is 50% more efficient[1097.698] [1097.698][S01]and costs 1/10 of the price of current batteries[1100.567] [1100.567][S01]and lasts you know, 10 times longer.[1103.203] [1103.203][S01]You know or we would come up with a solar panel -[1105.339] [1105.339][S01]photovoltaic material that is twice as efficient at converting heat energy[1110.377] [1110.377][S01]into electrical energy.[1112.145] [1112.145][S01]So it would be something like that would then unlock the possibility[1116.65] [1116.65][S01]of making desalination within reach of every community.[1120.587] [1120.587][S01]Perhaps that has to be some improvement[1122.055] [1122.055][S01]with the desalination technology itself as well[1125.025] [1125.025][S01]and maybe we can be involved in that.[1126.86] [1126.86][S01]But you know we’re a relatively small company,[1128.896] [1128.896][S01]so and we’re going to stay relatively small,[1130.697] [1130.697][S01]so we have to be efficient with the solutions that we work on.[1134.835] [1135.969][S01]This all just comes, at least from my perspective,[1138.472] [1138.472][S01]from rationally, logically thinking out what’s the best thing you can do[1142.409] [1142.409][S01]and what’s happened so far looking at civilisation in this[1145.479] [1145.479][S01]I mean maybe you could say as a slightly strange way of looking at it[1148.849] [1148.849][S01]but I think it’s the correct way to look at things,[1150.817] [1150.817][S01]and I think most people just don’t think about questions in the right way,[1154.588] [1154.588][S01]and maybe that’s what I’ve done in my whole life[1156.19] [1156.19][S01]is try to ask the right questions[1159.526] [1159.526][S01]and I feel like this is the obvious answer.[1161.995] [1163.063][S02] This is DeepMind, the podcast. An introduction to AI -[1167.267] [1167.267][S02]one of the most fascinating fields in science today.[1170.537] [1172.306][S01] Like I always say to people -[1174.208] [1174.208][S01]whatever your question, the answer is AI.[1176.944] [1176.944][S01]Because it sort of is in the limit, right?[1179.079] [1179.079][S01]I mean that’s a little bit flippantly, but I mean in the limit, it must be,[1182.749] [1182.749][S01]because the answer so far, you know why we’re here,[1186.086] [1186.086][S01]why we’re talking, why we’re using these amazing computers and devices[1189.59] [1189.59][S01]is because of intelligence, human intelligence,[1191.391] [1191.391][S01]and I think it’s miraculous, and the scientific method.[1194.361] [1194.361][S01]Another miraculous thing, I think the greatest discovery of all[1198.098] [1198.098][S01]is that the scientific method works,[1199.766] [1199.766][S01]you know the enlightenment and why should it be?[1202.135] [1202.135][S01]I mean also you must have to question things like that -[1204.071] [1204.071][S01]why should the universe work like that - that the scientific method works,[1207.541] [1207.541][S01]you know it could be a little bit more random,[1208.842] [1208.842][S01]then it would be really confusing, right?[1210.31] [1210.31][S01]If sometimes the sun rose, and sometimes it didn’t -[1212.579] [1212.579][S01]it would be quite hard to do science, then. Right?[1214.715] [1214.715][S01]Sometimes you repeated the experiment with exactly the same conditions,[1217.017] [1217.017][S01]something else, something different happened.[1219.119] [1219.119][S01]But it doesn’t this world doesn't’ seem to work like that,[1221.021] [1221.021][S01]it seems to be repeatable, it seems to be consistent,[1223.991] [1223.991][S01]so therefore knowledge is possible.[1225.926] [1225.926][S01]And incredibly strangely our brains even though they’re evolved for hunting[1230.464] [1230.464][S01]gathering can somehow deal with it - which is kind of miraculous in itself.[1235.002] [1235.002][S01]So how could you not want to a.) work on those questions, and b.)[1238.906] [1238.906][S01]why would there be limits to what that is capable of doing?[1241.909] [1241.909][S02] But the ultimate goal in all of this[1243.977] [1243.977][S02]is to create artificial general intelligence,[1247.247] [1247.247][S02]exactly what is meant by that?[1250.35] [1251.285][S01] Yeah, artificial - I mean there’s not an agreed definition[1254.021] [1254.021][S01]of artificial general intelligence,[1255.989] [1255.989][S01]but the way that Shane and I think about artificial general intelligence[1260.594] [1260.594][S01]is a system that is capable of a wide range of tasks,[1265.299] [1265.299][S01]and if we think about human level artificial general intelligence,[1268.235] [1268.235][S01]then we’re talking about system that can pretty much[1270.47] [1270.47][S01]do the full spectrum of cognitive tasks[1274.374] [1274.374][S01]that humans can at least as good as humans are able to do,[1278.345] [1278.345][S01]that’s you know one reasonable definition[1280.113] [1280.113][S01]of artificial general intelligence.[1281.782] [1281.782][S02] What’s the threshold for AGI then,[1283.517] [1283.517][S02]how will you know when you’re done?[1285.385] [1285.886][S01] That’s a philosophical issue of like[1287.621] [1287.621][S01]how do we know we’re done with building AGI?[1290.624] [1290.624][S01]Certainly for me I’m waiting to see a lot of key moments,[1294.661] [1294.661][S01]for example I think a really big moment will be when an AI system[1299.032] [1299.032][S01]comes up with a new scientific discovery that’s of Nobel prize-winning level,[1305.038] [1305.038][S01]that to me would be a big watershed moment[1308.075] [1308.075][S01]and I think ah an important step in the capabilities of these systems,[1312.346] [1312.346][S01]so you know, capable of some kind of true creativity in some sense.[1316.383] [1316.383][S01]I think other big points will be when it can use language[1320.254] [1320.254][S01]and converse with us in a naturalistic way.[1323.323] [1323.323][S01]It’s capable of learning abstract concepts -[1326.293] [1326.293][S01]these are all things that I think are high-level cognitive abilities[1330.564] [1330.564][S01]that we’re nowhere near yet -[1332.099] [1332.099][S01]and I think will be big signposts on the way.[1334.835] [1334.835][S02] When were you convinced that that all of this was possible?[1338.305] [1338.305][S01] Well I had this in mind since my early teens,[1342.643] [1342.643][S01]I probably read way too much sci-fi I’m guessing.[1345.245] [1345.245][S01]Some of the really formative things on me were Asimov’s Foundation series,[1349.116] [1349.116][S01]so interestingly, not the robotics books,[1351.451] [1351.451][S01]I haven’t really read any of his robot books,[1353.02] [1353.02][S01]but the Foundation series was this really amazing series of sci-fi novels,[1357.691] [1357.691][S01]and then Ian Banks’ Culture Series which is his sort of Space Opera[1362.262] [1362.262][S01]about how the universe would look after humanity[1364.798] [1364.798][S01]has built AI and co-exists with it.[1367.134] [1367.134][S01]And then a really big scientific book for me[1369.169] [1369.169][S01]was when I was writing Theme Park,[1372.105] [1372.105][S01]obviously I was working on AI and building AI for the game,[1376.41] [1376.41][S01]but I was also reading books like Gödel, Escher, Bach, by Hofstadter[1380.013] [1380.013][S01]which I suppose is more of a philosophy book,[1382.716] [1382.716][S01]but it’s an incredible piece of work,[1385.085] [1385.085][S01]tying together Gödel’s incompleteness theorem about mathematics,[1389.256] [1389.256][S01]with Escher’s drawings and Bach’s fugues[1392.292] [1392.292][S01]and showing that they’re all related in some way,[1394.661] [1394.661][S01]this repeating cycle of patterns,[1396.53] [1396.53][S01]this infinite patterns that they all exhibit,[1399.333] [1399.333][S01]and then he tied it to consciousness, and intelligence,[1402.536] [1402.536][S01]and it was just really inspiring for me[1405.339] [1405.339][S01]and made me think about these deep questions,[1407.474] [1407.474][S01]and I was discussing this with a lot of my friends[1409.843] [1409.843][S01]who were you know we were writing games together,[1411.979] [1411.979][S01]and we were doing that 24/7[1413.814] [1413.814][S01]and we would discuss these things about what the limits of AI could be[1417.885] [1417.885][S01]if we could not just use it for what we were doing in games,[1420.988] [1420.988][S01]but actually advance it to the level[1422.489] [1422.489][S01]where it would become the same level as human,[1424.992] [1424.992][S01]and they just felt like the sky was the limit.[1428.395] [1428.395][S01]I mean maybe another way I can put it is if you look around us today,[1432.099] [1432.099][S01]you know you look at modern civilisation and its incredible,[1434.968] [1434.968][S01]well what built modern civilisation, intelligence did, right?[1439.106] [1439.106][S01]That’s what built it - human intelligence -[1441.141] [1441.141][S01]and if you were to take us back to our hunter gatherer days -[1445.179] [1445.179][S01]10, 20,000 years ago, 30,000 years ago,[1448.549] [1448.549][S01]and you were to say one day we’re going to build Manhattan,[1452.019] [1452.019][S01]and then fly over from London to Manhattan[1454.221] [1454.221][S01]on a 747 regularly, above the clouds,[1458.125] [1458.125][S01]I mean, what would you have said, that it would be mind boggling right?[1461.895] [1461.895][S01]And yet humanity’s done that incredibly,[1464.598] [1464.598][S01]and I don’t think we stop to think how amazing that is enough[1468.001] [1468.001][S01]because the other thing about the human brain[1469.603] [1469.603][S01]is that it’s incredibly adaptable - right?[1471.238] [1471.238][S01]As soon as something, you know we do something[1473.373] [1473.373][S01]and then it becomes kind of boring and mundane and it’s trivial, right?[1476.743] [1476.743][S01]But I always think about that when I’m taking a transatlantic flight,[1479.913] [1479.913][S01]about how have we with our monkey brains[1483.45] [1483.45][S01]managed to come up with these types of technologies, it’s unbelievable.[1488.856] [1488.856][S01]A 100 tonne of metal flying through the sky above the clouds,[1493.026] [1493.026][S01]so reliably, and so, if you think about that,[1495.562] [1495.562][S01]then, if we now build something like AGI[1498.165] [1498.165][S01]and enhance our own capabilities with this amazing tool,[1502.002] [1502.002][S01]then I feel like almost anything might be possible within the laws of physics[1506.74] [1506.74][S01]and perhaps even beyond the laws of physics[1508.475] [1508.475][S01]because with AI we might discover more about the laws of physics[1513.614] [1513.614][S01]or some holes or flaws in our understanding of the laws of physics,[1516.316] [1516.316][S01]so if you think about that and you extrapolate it a few hundred more years[1520.521] [1520.521][S01]with these kinds of technologies like AGI around,[1523.59] [1523.59][S01]and then what we might be able to build with AGI,[1526.426] [1526.426][S01]I think it could be truly incredible where we’ll be[1528.562] [1528.562][S01]- and I feel it will be something like[1530.163] [1530.163][S01]with the realisation of the true potential of humanity.[1533.901] [1536.904][S02] But however exciting the grand ambition of AGI[1540.073] [1540.073][S02]is, there is also a need to proceed with caution.[1544.545] [1544.545][S01] We’re cognisant of some of the technical questions around AGI -[1548.415] [1548.415][S01]making sure that they do exactly what we want,[1550.684] [1550.684][S01]how do we programme in our values, how do we specify our goals?[1555.856] [1555.856][S01]So these are all the theoretical and technical questions around AGI[1559.126] [1559.126][S01]that people like Nick Bostrom are worried about,[1561.161] [1561.161][S01]and so we and Shane leads our safety team[1565.499] [1565.499][S01]that works on a lot of these questions[1567.901] [1567.901][S01]from a research and technical perspective,[1569.87] [1569.87][S01]and I think there’s a lot more work that needs to be done there.[1572.306] [1572.306][S01]And I think that’s what we’re going to see over the next decade or two.[1575.876] [1578.879][S02] I mean even if you proceed with caution,[1581.615] [1581.615][S02]even if you act as safely as you possibly can based on the information[1585.152] [1585.152][S02]that you have in front of you at that moment,[1587.588] [1587.588][S02]you can’t really mitigate against bad actors,[1592.192] [1592.192][S02]you can’t stop someone else coming in and mucking it up for everyone.[1596.964] [1596.964][S02]Or can you?[1598.232] [1598.232][S01] I think there are ways of minimising that,[1600.667] [1600.667][S01]I think we’ll have to think carefully about that, like at the moment[1603.904] [1603.904][S01]we are at the stage where these systems are still quite nascent.[1607.14] [1607.14][S01]They can do impressive things like play Go,[1609.443] [1609.443][S01]but they are not yet properly general purpose[1612.446] [1612.446][S01]or you know you couldn’t use them for anything very dangerous,[1615.516] [1615.516][S01]or in the real world, so we’ve committed that we won’t do certain applications,[1620.454] [1620.454][S01]you know obviously like things like military and surveillance,[1623.09] [1623.09][S01]so which we think would be bad for society,[1625.392] [1625.392][S01]we don’t think AI should be applied to those things,[1627.361] [1627.361][S01]and we certainly wouldn’t do it ourselves,[1629.129] [1629.129][S01]but if you publish some great algorithms,[1631.698] [1631.698][S01]you have to think about the indirect impact of that if other people -[1635.102] [1635.102][S01]bad actors and so on around the world -[1636.87] [1636.87][S01]potentially use your algorithms for things[1639.64] [1639.64][S01]that you would not have agreed with, we have to use this time[1643.277] [1643.277][S01]now to think about what principles need to be put in place,[1646.713] [1646.713][S01]whether that’s carefully thought out regulation,[1649.917] [1649.917][S01]whether that is technical solutions to these problems,[1653.42] [1653.42][S01]mathematical proofs, more engineering solutions,[1657.024] [1657.024][S01]so like one of the projects we have here we call it[1659.793] [1659.793][S01]the virtual brain analytics project[1662.062] [1662.062][S01]and it’s inspired by what we do in neuroscience with FMRI machines[1666.366] [1666.366][S01]to brain scan people[1668.202] [1668.202][S01]while they’re doing tasks to see what parts of the brain light up[1671.205] [1671.205][S01]so we can understand what the brain is doing better,[1673.974] [1673.974][S01]and we should be doing the equivalent of that with our virtual brains,[1676.944] [1676.944][S01]our artificial neural networks,[1679.546] [1679.546][S01]so I think there’s both sort of behavioural,[1681.648] [1681.648][S01]there’s experimental understanding[1683.317] [1683.317][S01]and then there’s mathematical understanding of these systems,[1685.686] [1685.686][S01]and we should do all of those,[1686.954] [1686.954][S01]and what I’m hoping is that we will eventually in the next few years[1689.723] [1689.723][S01]have a much better understanding of these systems than we have today[1693.46] [1693.46][S01]and we may even have some mathematical proofs about[1696.997] [1696.997][S01]if you want to limit a system in a certain way,[1699.233] [1699.233][S01]what do you need to do? What components do you require?[1701.935] [1701.935][S01]Also you know we have to think about publications[1704.238] [1704.238][S01]and other stuff that we talked about earlier -[1706.173] [1706.173][S01]whether um this free exchange of information and knowledge[1710.043] [1710.043][S01]is okay even under situations[1712.145] [1712.145][S01]where there are potentially dangerous applications.[1715.716] [1715.716][S01]And where I would take our lead from this -[1717.15] [1717.15][S01]this is not the first time again this has happened -[1719.286] [1719.286][S01]you know this has happened a lot in biology[1721.255] [1721.255][S01]with designing synthetic biology and viruses, embryology, now with CRISPR[1727.06] [1727.06][S01]so biology actually has a long-standing multi-decade experience[1732.466] [1732.466][S01]of coming together with wider society in the scientists and regulatory bodies[1737.171] [1737.171][S01]and figuring out what are the rules of the road that is safe for everybody,[1741.041] [1741.041][S01]and I think that’s the kind of coordination[1743.41] [1743.41][S01]we’re going to have to have over the next decade.[1746.013] [1746.013][S02] Where do you see DeepMind as sitting in terms[1748.048] [1748.048][S02]of the brand tech industry in terms of ethics and safety,[1752.452] [1752.452][S02]are people following your lead?[1754.254] [1754.254][S01] We’re only one company but we are the biggest[1757.324] [1757.324][S01]probably group anywhere in the world,[1758.825] [1758.825][S01]and we you know are definitely one of the world leaders and acknowledge as so.[1762.796] [1762.796][S01]So that gives a powerful platform to set an example.[1767.467] [1767.467][S01]We can create initiatives, like we helped create the Partnership on AI,[1771.071] [1771.071][S01]which is a cross-industry initiative[1772.539] [1772.539][S01]to talk about some of these issues in products,[1775.576] [1775.576][S01]and we’ve also sponsored a lot of academic groups,[1779.646] [1779.646][S01]we’ve given them money for post-docs[1781.248] [1781.248][S01]and other things at arm’s length to study this,[1783.584] [1783.584][S01]we have close contacts with a lot of the institutes[1786.186] [1786.186][S01]that work on these things, like the Future of Humanity Institute[1788.322] [1788.322][S01]which is just down the road in Oxford,[1789.957] [1789.957][S01]we talk with them all the time, and we ourselves as leaders at DeepMind,[1794.161] [1794.161][S01]we’ve always talked about ethics, and I’ve always had that in mind,[1797.297] [1797.297][S01]and the reason we have from the beginning of DeepMind[1799.066] [1799.066][S01]is that we plan for success,[1801.134] [1801.134][S01]so if we’re planning all these ambitious things for AI to do,[1803.937] [1803.937][S01]then we also need to think carefully about what would that mean,[1807.207] [1807.207][S01]and so we’re doing a lot of things behind the scenes,[1810.077] [1810.077][S01]and I think by sort of being an example,[1812.746] [1812.746][S01]that will influence everybody else I’m hoping,[1815.282] [1815.282][S01]given that we’re in the lead technologically, so, for the moment.[1819.319] [1819.319][S01]That’s why I think also it’s very important we have a technical lead,[1822.222] [1822.222][S01]because why would anyone listen to what you have to say on the ethics front[1826.26] [1826.26][S01]if you’re not one of the leaders technologically right then[1828.695] [1828.695][S01]you could just be any group saying that.[1830.764] [1830.764][S01]So I think to have a seat at the table, whether that’s a country,[1834.201] [1834.201][S01]or a company, or even individuals, you need for credibility purposes,[1838.138] [1838.138][S01]you have to be close to the forefront of the technical side itself.[1841.975] [1841.975][S02] Where does the public fit into all of this,[1843.81] [1843.81][S02]do you need to have the trust in you as a technology company,[1848.282] [1848.282][S02]or do you need to be on board at all - can you kind of do it without them?[1851.118] [1851.118][S01] No, it’s really critical that this is discussed at large with society[1856.557] [1856.557][S01]and everybody and the general public, and I think they need to engage,[1859.96] [1859.96][S01]I mean the problem is that a lot of these technical things are very complex,[1863.13] [1863.13][S01]and you need PhDs to understand them and so on.[1865.732] [1865.732][S01]But some of the fundamentals are quite easy to understand,[1868.368] [1868.368][S01]and what you really need to understand is the consequences of it[1871.839] [1871.839][S01]and then society has to decide as I said before about how these things get used,[1876.91] [1876.91][S01]and how the benefits accrue to different people in society[1880.247] [1880.247][S01]and make sure that is fair,[1881.849] [1881.849][S01]and I think that’s the key thing is to engage with the public now[1885.319] [1885.319][S01]and try and educate them about some of the complexities of the technology,[1889.256] [1889.256][S01]but also the implications,[1890.557] [1890.557][S01]and this is partly what things like this podcast series is about,[1893.126] [1893.126][S01]but also we’ve done a lot of public engagement[1895.395] [1895.395][S01]with the Royal Society, the ‘You and AI’ series that we did last year[1900.534] [1900.534][S01]and I think a lot more of that has to be done.[1903.036] [1903.036][S02] Are you optimistic about the future?[1905.606] [1905.606][S01] Yeah I’m very optimistic about the future,[1907.241] [1907.241][S01]but the reason I’m optimistic is[1908.675] [1908.675][S01]because I think AI is coming down the road[1912.112] [1912.112][S01]and I feel like if we build it in the right way[1914.481] [1914.481][S01]and we deploy it in the right way for the benefit of everyone,[1917.451] [1917.451][S01]I think it’s going to be the most amazing transformative technology[1921.388] [1921.388][S01]that humanity’s ever invented.[1923.257] [1923.257][S01]And I would be quite pessimistic[1925.092] [1925.092][S01]about some of the problems we are facing as a society,[1928.562] [1928.562][S01]like climate change and sustainability or inequality.[1932.199] [1932.199][S01]I think these are going to get exacerbated in the next few years.[1935.269] [1935.269][S01]And I’d be pessimistic about our ability to solve[1938.372] [1938.372][S01]that if there wasn’t something like AI on the way,[1941.074] [1941.074][S01]in the near future.[1942.376] [1942.376][S01]I think in order to solve some of these big problems,[1945.112] [1945.112][S01]challenges society has,[1947.214] [1947.214][S01]we either need an exponential improvement in human behaviour,[1950.317] [1950.317][S01]more cooperation, less selfishness, more collaboration,[1954.254] [1954.254][S01]or we need an exponential improvement in technology,[1957.624] [1957.624][S01]and unfortunately the way politics is going right now,[1960.093] [1960.093][S01]I don't really see much evidence of the former[1962.963] [1962.963][S01]and um you know we don’t seem to be able to get our act together[1966.6] [1966.6][S01]globally to do something about climate[1968.635] [1968.635][S01]anywhere near fast enough to deal with the problem[1971.505] [1971.505][S01]and so I think we have to double down on a technical solution.[1975.075] [1975.075][S01]At least um we should try both,[1977.11] [1977.11][S01]but I think we need some technology bets.[1980.18] [1983.417][S02] It’s hard not to be inspired[1984.885] [1984.885][S02]by Demis’s insatiable thirst for knowledge,[1987.855] [1987.855][S02]and find yourself drawn in by his positive view of the future,[1991.592] [1991.592][S02]because if I’m honest, I’m normally quite skeptical.[1995.596] [1995.596][S02]I don’t have a lot of time for overly optimistic marketing talk,[1999.266] [1999.266][S02]and one of my favourite hobbies[2000.934] [2000.934][S02]is to roll my eyes at self-titled futurists at tech conferences,[2006.573] [2006.573][S02]but you know over the last 12 months that I’ve spent hanging around here,[2009.71] [2009.71][S02]I’ve come to the conclusion that there really[2011.645] [2011.645][S02]is something quite special going on at the cutting edge of AI.[2016.817] [2016.817][S02]After 50 years of quite slow progress,[2019.82] [2019.82][S02]it really feels as though the field is finally beginning to deliver.[2024.157] [2024.157][S02]The problems that everyone thought were completely out of reach[2026.894] [2026.894][S02]only a few short years ago are tumbling one by one.[2031.765] [2031.765][S02]And the science is moving forward at a blistering pace,[2036.203] [2036.203][S02]both here and at research labs all around the world.[2040.174] [2040.174][S02]And the questions that people are working on are profound and important.[2045.779] [2045.779][S02]Including some of the potential pitfalls[2048.248] [2048.248][S02]and ethical concerns of this kind of technology.[2052.019] [2052.019][S02]So with all of that in mind,[2053.82] [2053.82][S02]I think I’m going to join Demis in being optimistic about the future,[2058.425] [2058.425][S02]and the potential of AI to be a real positive force for good.[2063.73] [2063.73][S02]But don’t just take my word for it, as we’ve said throughout this podcast,[2067.067] [2067.067][S02]we hope to inspire you on your own AI journey,[2070.304] [2070.304][S02]maybe even by finding the answers[2072.339] [2072.339][S02]to some of the biggest questions there are.[2075.209] [2077.344][S01] I’m an entrepreneur second, I’m a scientist first.[2079.88] [2079.88][S01]It’s just that this was the right vehicle to make this happen,[2082.616] [2082.616][S01]and it seems to have born out,[2084.284] [2084.284][S01]but if I could have made it happen in academia,[2086.987] [2086.987][S01]I would have just done it in academia,[2088.322] [2088.322][S01]it just wasn’t possible under the constraints academia has.[2091.391] [2091.391][S01]And that’s why we also sold the company to Google[2093.46] [2093.46][S01]because it was about what accelerates the mission and the science,[2096.964] [2096.964][S01]and ultimately that’s what I want to do with my life[2099.099] [2099.099][S01]is I want to understand what’s going on here in the universe.[2102.636] [2102.636][S01]Both inside here in the brain[2104.838] [2104.838][S01]and externally out there in the universe.[2107.14] [2107.14][S01]And I guess that’s what’s always driven me[2109.176] [2109.176][S01]is this deep desire to understand what seems to me[2113.08] [2113.08][S01]to be an incredibly interesting and fascinating mysteries[2119.219] [2119.219][S01]that are going all around us and I don’t really understand[2121.889] [2121.889][S01]why more people don’t think about that all the time -[2124.691] [2124.691][S01]I can barely sleep because I’m just fascinated[2127.694] [2127.694][S01]and also troubled by the things around us[2131.999] [2131.999][S01]that we seemingly don’t understand -[2133.534] [2133.534][S01]all the big questions, you know the meaning of life -[2135.802] [2135.802][S01]how did the universe start, what is consciousness,[2137.538] [2137.538][S01]all these questions, which I feel like a blaring klaxon in my mind[2141.408] [2141.408][S01]that I would like to understand and my attempt at doing[2144.578] [2144.578][S01]that is to build AI first.[2147.114] [2150.784][S02] If you would like to find out more about some of the things[2153.52] [2153.52][S02]that we’ve talked about in this episode,[2155.522] [2155.522][S02]or explore the world of AI research beyond DeepMind,[2159.226] [2159.226][S02]you’ll find plenty of useful links in the show notes for each episode,[2162.896] [2162.896][S02]and if there are stories or resources[2164.531] [2164.531][S02]that you think other listeners would find helpful,[2166.9] [2166.9][S02]than let us know -you can message us on Twitter,[2169.436] [2169.436][S02]or email the team at podcasts@deepmind.com.[2173.14] [2173.14][S02]You can also use that address[2174.608] [2174.608][S02]to send us your questions or feedback on the series.[2178.045] [2178.645][S02]DeepMind the podcast has been a Whistledown production,[2181.815] [2181.815][S02]binaural sound recordings were by Lucinda Mason-Brown.[2185.319] [2185.319][S02]The music from this series has been especially composed by Eleni Shaw.[2189.189] [2189.189][S02]Producers were Amy Racs and Dan Hardoon.[2192.125] [2192.125][S02]The Senior Producer was Louisa Field and the series editor was David Prest.[2196.763] [2199.9][S02]I’m Hannah Fry, thank you for listening.[2202.236]