Kai-Fu Lee: AI Superpowers - China and Silicon Valley | Lex Fridman Podcast #27
the following is a conversation of Chi Fuli he's the chairman and CEO of sin evasion ventures that manages a two billion dollar dual currency investment fund with a focus on developing the next generation of Chinese high-tech companies he's the former president of Google China and the founder of what is now called Microsoft Research Asia an institute that trained many of the artificial intelligence leaders in China including CTOs or AI execs at Baidu Tencent Alibaba innova and Huawei he was named one of the 100 most influential people in the world by Time magazine he's the author of seven best-selling books in Chinese and most recently the New York Times bestseller called AI superpowers China Silicon Valley and the New World Order he has unparalleled experience in working across major tech companies and governments and applications of AI and so he has a unique perspective on global innovation in the future of AI that I think is important to listen to and think about this is the artificial intelligence podcast if you enjoy it subscribe on YouTube and iTunes supported enough patreon or simply connect with me on Twitter at lex friedman and now here's my conversation with chi foo lee I emigrated from Russia to US when I was 13 you emigrated to us at about the same age the Russian people the American people the Chinese people each have a certain soul a spirit that permeates throughout the generations so maybe it's a little bit of a poetic question but could you describe your sense of what defines the Chinese soul I think the Chinese soul of people today right we're talking about people who have had centuries of burden because of the poverty that the country has gone through and suddenly shined with hope of prosperity in the past 40 years as China opened up and embraced market economy and undoubtedly there are two sets of pressures on the people that of the tradition that of facing difficult situations and that of Hope of wanting to be the first to become successful and wealthy so that it's a very strong a hunger and strong desire and strong work ethic that drives China forward and is their roots to not just this generation but before that's that's deeper than just the new economic development is there something that's unique to China that you could speak to that's in the people yeah well the Chinese some tradition is about excellence dedication and results and the Chinese exams and study subjects in schools have traditionally started from memorizing ten thousand characters not an easy task to start with and further by memorizing his historic philosophers literature poetry so it really is the probably the strongest rote learning mechanism created to make sure people had good memory and remembered things extremely well that's I think at the same time suppresses the breakthrough innovation and also enhances the speed execution get results and that I think characterizes the historic basis serve on China that's interesting because there's echoes of that and Russian education as well as rote memorization to memorize a lot of poche I mean there's just the emphasis on perfection in all forms mmm that's not conducive to perhaps what you're speaking to which is creativity but you and you think that kind of education holds back the innovative spirit that you might see in the United States well it holds back the breakthrough innovative spirits that we see in the United States but it does not hold back the valuable execution oriented result-oriented value creating engines which we see China being very successful so is there a difference between a Chinese AI engineer today and an American AI engineer perhaps rooted in the culture that we just talked about or the education or the very soul of the people or no and what would your advice be to each if there's a difference well there's a lot that's similar because AI is about mastering Sciences about using known technologies and trying new things but it's also about picking from many parts of possible networks to use and different types of parameters to tune and that part is somewhat rote and it is also as anyone who's built AI products can tell you a lot about cleansing the data because AI runs better with more data and data is generally unstructured error error fall and unclean and the effort to clean the data is is immense so I think the better part of American engineering ai engineering process is to try new things to do things people haven't done before and to use technology to solve most if not all problems so to make the algorithm work despite not so great data find you know error tolerant ways to deal with the data the Chinese way would be - basically enumerate to the fullest extent all the possible ways by a lot of machines try lots of different ways to get it to work and spend a lot of resources and money and time cleaning up data that mean that means the AI engineer may be writing data cleansing algorithms working with thousands of people who label or correct or do things with the data that is the incredible hard work that might lead to better results so the Chinese engineer would rely on and ask for more and more and more data and find ways to cleanse them and make them work in the system and probably less time thinking about new algorithms that can overcome they there are other issues so where's your intuition what do you think the biggest impact the next 10 years lies is it in some breakthrough algorithms or is it in just this at scale rigor a rigorous approach to data cleaning data organizing data onto the same algorithm packed in the applied world is well if you're really in the company and you have to deliver results using known techniques and enhancing data seems like the more expedient approach that's very low risk and likely to generate better and better results and that's why the Chinese approach has done quite well now there are a lot of more challenging startups and problems such as autonomous vehicles medical diagnosis that existing algorithms may probably won't solve and that would put the Chinese approach more challenged and give them more breakthrough innovation approach more more of an edge on those kinds of problems so let me talk to that a little more so you know my intuition personally is that data can take us extremely far so you brought up autonomous vehicles and medical diagnosis so your intuition is that huge amounts of data might not be able to completely help us solve that problem right so breaking that down further in autonomous vehicle I think huge amounts of data probably will solve trucks driving on highways which will deliver a significant value and China will probably lead in that and full l5 autonomous is likely to require new technologies we don't yet know and that might require academia and great industrial research both innovating and working together and in that case us has an advantage so the interesting question in there is I don't know if you're familiar on the autonomous vehicle space and the developments with Tesla and Elon Musk I am where they are in fact full steam ahead into this mysterious complex world of full autonomy l5 l4 l5 and they're trying to solve that purely with data so the same kind of thing that you're saying is just for highway which is what a lot of people share your intuition yeah they're trying to solve with data it's just a linger on that moment forever do you think possible for them to achieve success with simply just a huge amount of this training on edge cases on difficult cases in urban environments not just highway and so on I think they'll be very hard one could characterize Tesla's approach as kind of a Chinese strength approach right gather all the data you can and hope that will overcome the problems but in autonomous driving clearly a lot of the decisions aren't nearly solved by aggregating data and having a feedback loop there are things that are more akin to human thinking and how would those be integrated and built there has not yet been a lot of success integrating human intelligence or you know call it expert systems to be well even though that's a taboo word with the machine learning and the integration the two types of thinking hasn't yet been demonstrated and the question is how much can you push a purely machine learning approach and of course Tesla also has an additional constraint that they don't have all the sensors I know that they think is foolish to use lidar s but that's clearly a one less very valuable and reliable source of inputs that they're forgoing which may also have consequences I think the advantage of course is capturing data no one has ever seen before and in some cases such as computer vision and speech recognition I have seen Chinese companies accumulate data that's not seeing anywhere in the Western world and they have delivered superior results but then speech recognition and object recognition are relatively suitable problems for deep learning and don't have the potentially need for the human intelligence analytical planning elements in the same on the speech recognition side your intuition that speech recognition and the machine learning approaches to speech recognition won't take us to a conversational system that can pass the Turing test which is sort of maybe akin to what driving is so it needs to have something more than just simply simple language understanding simple language generation roughly right I would say that's based on purely machine learning approaches it's hard to imagine it could lead to a full conversational experience across arbitrary domains which is akin to l5 I'm a little hesitant to use the word Turing tests because the original definition was probably too easy we probably do that yeah the spirit of the Turing test that's what I was referring of course so you've had major leadership research positions at Apple Microsoft Google so continuing on the discussion of America Russia Chinese soul and culture and so on what is the culture Silicon Valley in contrast to China and maybe us broadly and what is the unique culture of each of these three major companies in your view I think in aggregates Silicon Valley companies and we could probably include Microsoft in that even though they're not in the valley is really dream big and have visionary goals and believe that technology will conquer all and also the self confidence and the self entitlement that whatever they produce the whole world should use and must use and those are historically important I think you know Steve Jobs famous quote that he doesn't do focus groups he looks in the mirror and asks the first in the mirror what do you want and that really is an inspirational comment that says the great company shouldn't just ask users what they want but develop something that users will know that they want when they see it but they could never come up with themselves I think that is probably the most exhilarating description of what the essence of Silicon Valley is that this brilliant idea could cause you to build something that couldn't come out of focus groups or a be tests and iPhone would be an example of that no one in the age of blackberry would write down they want an iPhone or multi-touch a browser might be another example no one would say they want that in the days of FTP but once they see it they want it so I think that is was Silicon Valley's best at but it also comes with came with a lot of success these products became global platforms and there were basically no competitors anywhere and that has also led to belief that these are the only things that one should do that companies should not tread on other companies territory so that's a you know Groupon and the Yelp and then open table and the GrubHub with each field ok I'm not gonna do the other company's business because that would not be the pride of innovating whatever each of these four companies have innovated but I think the Chinese approach is do whatever it takes to win and it's a winner take all market and in fact in the internet space the market leader will get predominantly all the value extracted out of the system so and the and the and the system isn't just defined as one narrow category but gets broader and broader so it's amazing ambition for success and domination of increasingly larger product categories leading to clear market winner status and the opportunity to extract tremendous value and that develops a practical result oriented ultra ambitious winner-take-all gladiatorial mentality and if what it takes is to build what the competitors built essentially a copycat that can be done without infringing laws if what it takes is to satisfy a foreign country's need by forking the codebase and building something that looks really ugly and different they'll do it so it's contrasted very sharply with the Silicon Valley approach and I think the flexibility and the speed and execution has helped the Chinese approach and I think the Silicon Valley approach is potentially challenged if every Chinese entrepreneurs learning from the whole world US and China and the American entrepreneurs only look internally and right off China as copycat and the second part of your question about the three companies the unique elements of the three companies perhaps yeah I think Apple represents while the user please the user and the essence of design and brand and it's the one company and perhaps the only tech company that draws people with a a strong serious desire for the product and the knee and the willingness to pay a premium because of the halo effect of the brand which came from the attention to detail and great respect for user needs microsoft represents a platform approach that builds giant products that become very strong modes that others can't do because it's well architected at the bottom level and the work is efficiently delegated to individuals and then the the the whole product is build by adding small parts that sum together so it's probably the most um effective high tech assembly line that builds a very difficult product that and the whole process of doing that is kind of a differentiation and something competitors can't easily repeat are there elements of the Chinese approach and the way Microsoft went about assembling those little pieces and dominating them was essentially dominating the market for a long time or do you see this is distinct I think there are elements that are the same I think the three American companies that had or have Chinese characteristics and obviously as well as American characteristics are Microsoft Facebook and Amazon yes that's right Amazon because these are companies that will tenaciously go after adjacent markets build up strong private offering and and find ways to extract greater value from a sphere that's ever-increasing and they understand the value of the platforms so that's the similarity and then with Google I think is a genuinely value oriented company that does have a heart and soul and that wants to do great things for the world by connecting information and that has also very strong technology genes and wants to use technology and has found out-of-the-box ways to use technology to deliver incredible value to the end-user we can look at Google for example you mentioned heart and soul there seems to be an element where Google is after making the world better there's a more positive view I mean I used to have the slogan don't be evil yeah and and Facebook a little bit more as a negative tint to it at least in the perception of privacy and so on do you have a sense of how these different companies can achieve because you've talked about how much we can make the world better in all these kinds of ways with AI what is it about a company that can make give it a heart and soul gain the trust of the public and just actually just not be evil and do good for the world it's really hard and I think Google has struggled with that first that don't do evil mantra is very dangerous because every employees definition of evil is different and that has led to some difficult employee situations for them so I don't necessarily think that's a good value statement but just watching the kinds of things Google or its parent company alphabet does in new areas like health care like you know eradicating mosquitoes things that are really not in the business of a Internet tech company I think that shows that there is the heart and soul and desire to do good and willingness to put in the resources to do something when they see it's good they will pursue it that doesn't necessarily mean it has all the trust of the users I realize while most people would view Facebook as the primary target of their recent and happiness about Silicon Valley companies many would put Google in that category and some have named Google's business practices as predatory also so it's kind of difficult to have the two parts of a body the brain wants to do what it's supposed to do for shareholder maximize profit and then the heart and soul wants to do good things that may run against at what that brain wants to do so in this complex balancing that these companies have to do you've mentioned that you're concerned about a future were too few companies like Google Facebook Amazon are controlling our data are controlling too much of our digital lives can you elaborate on this concern and perhaps do you have a better way forward I think I'm hardly the most vocal a complainer of this course there are a lot louder complaints out there I do observe that's having a lot of data thus perpetuates their strengths and limit competition in many spaces but I also believe a AI is much broader than the internet space so the entrepreneurial opportunity still exists in using AI to empower financial retail manufacturing education applications so I don't think it's quite a case of um full monopolistic dominance that makes that totally stifles innovation but I do believe in their areas of strength is hard to to dislodge them I don't know if I have a good solution probably the best solution is let the entrepreneurial VC ecosystem work well and find all the places that can create the next Google the next Facebook so there will always be increasing number of challengers in some sense that has happened a little bit you see uber Airbnb having emerged despite the strength of the that the big three and and I think China as an environment may be more interesting for the emergence because if you look at companies between let's say 50 to 300 billion dollars China has emerged more of such companies than the you in the in the last three to four years because of the larger marketplace because of the more fearless nature of the entrepreneurs that and and the Chinese Giants are just as powerful as American ones Tenzin Alibaba very strong but by tense has emerged worth 75 billion and financial well it's Alibaba affiliated it's nevertheless independent and worth 150 billion and so III do think if we start to extend to traditional businesses we will see value very valuable companies so it's probably not the case that in five or ten years we'll still see the whole world with these five companies having such dominance so you've mentioned a couple times this fascinating world of entrepreneurship in China of the fearless nature of the entrepreneur so can you maybe talk a little bit about what it takes to be an entrepreneur in China what are the strategies that are undertaken what are the ways to achieve success what is the dynamic of vfc funding of the way the government helps companies isn't one what are the interesting aspects here that are distinct from they're different from the Silicon Valley world of entrepreneurship home many of the listeners probably still would brand Chinese entrepreneur as copycats and no doubt ten years ago that would not be an inaccurate description back ten years ago an entrepreneur probably could not get funding if he or she could not describe what product he or she is copying from the US the first question is who has proven this business model which is a nice way of asking Corey copying and and that reason is understandable because China had a much lower internet penetration and and didn't have enough indigenous experience to build innovative products and secondly the internet was emerging link startup was the way to do things building a first minimally viable products and then expanding was the right way to go and the American successes have given the shortcuts that if you took your if you build your minimally Viable Product based on an American product it's guaranteed to be a decent starting point then you tweak it afterwards so as long as there's no IP infringement which as far as no there hasn't been in the mobile and AI spaces that's a much better shortcut and I think Silicon Valley would view that as still not very honorable because that's not your own idea to start with but you can't really at the same time believe every idea must be your own and believe in the Lean Startup methodology because Lean Startup is intended to try many many things and then converge one that works and it's meant to be iterating changed so finding a decent starting point without legal violations there should be nothing morally dishonorable about that so just a quick pause on that it's fascinating that that's is why is that not honorable right he's exactly as you formulated is it seems like a perfect start for business yeah is to to take you know look at Amazon and say okay well we'll do exactly what Amazon is doing let's start there yeah in this particular market and then let's I'll innovate them from that starting point yes I'm up with new ways I mean is it wrong to be accept the word copy catchy sounds bad but is it wrong to be a copycat it just seems like a smart strategy but yes doesn't have a heroic nature to it yeah that like I said like a Steve Jobs Elon Musk sort of in something completely coming up with something completely new yeah I like the way you describe it it's a non heroic acceptable way to start the company and maybe more expedient so that's the that's I think a baggage for silicon vally that if it doesn't let go then it made limits the ultimate ceiling of the company take snapchat as an example I think you know Evans brilliance he build great products but he's very proud that he wants to build his own features not copy others while Facebook was more willing to copy his features and you see what happens in the competition so I think putting that handcuff on a company would limit its ability to reach the maximum potential so back to the Chinese environment copying was merely a way to learn from the American masters just like we if you would we learned to play piano or painting you start by copying you don't start by innovating when you don't have the basic skill sets so very amazingly the Chinese entrepreneurs about six years ago started to branch off with these lean startups built on American ideas to build better products than American products but they did start from the American idea and today we we Chad is better than whatsapp Weibo is better than Twitter and Yahoo is better than Korra and so on so that I think is some Chinese entrepreneurs going to step two and in step three is once these entrepreneurs have done one or two of these companies they they now look at the Chinese market and the opportunities and come up with ideas that didn't exist elsewhere so products like and financial under which includes Ali pay which is mobile payments and also the financial products for loans built on that and also in education VIP kid and in social video social network tick-tock and in social ecommerce pin dodo and then in ride-sharing mo bike these are all Chinese innovative products that now are being copied elsewhere so and and the additional interesting herbs raishin is some of these products are built on unique Chinese demographics which may not work in the US but may work very well in Southeast Asia Africa and other developing worlds that are a few years behind China and a few of these products may be armed Universal and are getting traction even in the United States such as tick tock so this whole ecosystem is supported by VCS as a virtuous cycle because a large market with with innovative entrepreneurs will draw a lot of money and then invest in these companies so as the market gets larger and larger u.s. mark china market is easily three four times larger than the u.s. they will create greater value and greater returns for the VCS thereby raising even more money so at San ovations ventures our first fund was fifteen million our last fund was five hundred million so it reflects the valuation of the companies and our us going multistage and things like that it also has government support but not in the way most Americans would think of it the government actually leaves the entrepreneurial space as a private enterprise so they're self-regulating and the government would build infrastructures that would around it to make it work better for example the mass entrepreneur mass innovation plan builds eight thousand incubators so the pipeline is very strong to the VCS for autonomous vehicles the Chinese government is building smart highways with sensors smart cities that separate pedestrians from cars that may allow initially an inferior autonomous vehicle company to launch a car without increasing with lower casualty because the roads or the city is smart and the Chinese government at local levels would have these guiding funds acting as LPS passive LPS to funds and when the fund makes money part of the money made is given back to the GPS and potentially other LPS to reach increase everybody's return at the expense of the government's return so that's interesting incentive that and trusts that task of choosing entrepreneurs to VCS who are better added in the government by letting some of the profits I'll move that way so this is really fascinating right so I look at the Russian government as a case study where let me put it this way there is no such government driven large-scale support of entrepreneurship and probably the same is true in the United States but the entrepreneurs themselves kind of find a way yeah so maybe in a form of advice or explanation how did the Chinese government arrive to be this way so supportive entrepreneurship to be in this particular way so forward-thinking at such a large scale and also perhaps how can we copy it in other countries yeah that how can we encourage other governments given the United States government to support infrastructure for autonomous vehicles in that same kind of way perhaps yes so these some techniques are the result of several key things some of which may be learn the both some of which may be very hard one is just trial and error and watching what everyone else is doing I think it's important to be humble and not feel like you know all the answers the guiding funds idea came from Singapore which came from Israel and China made a few tweaks and turned it into a because the Chinese cities and government officials kind of compete with each other because they all want to make their city more successful so they can get the next level in their crew in their political career and it's somewhat competitive so the central government made it a bit of a competition everybody has a budget they can put it on AI or they can put it on bio or they can put it on energy and then whoever gets the results the city shines the people are better off the mayor gets a promotion so the tools kind of almost like an entrepreneurial environment for local governments to see who can do a better job and also many of them try different experiments some have given award to very smart researchers just give them money and hope they'll start the company some have given money to academic research labs maybe government research labs to see if they can spin-off some companies from the science lab or something like that some have tried to recruit overseas Chinese to come back and start companies and they've had mixed results the one that worked the best was the guiding funds so it's almost like a Lean Startup idea where people try different things and what works sticks and everybody copies so now every city has a guiding fund so that's how that came about the autonomous vehicle and the massive spending in highways in smart cities that's a Chinese way it's about building infrastructure to facilitate it's a clear division of the government's responsibility from the market the markets should do everything in a private freeway but there are things the market can't afford to do like infrastructure so the government always appropriate large amounts of money for infrastructure building this happened happens with not only autonomous vehicle in the eye but happened with the 3G and 4G you'll find that the Chinese a wireless reception is better than the u.s. because massive spending that tries to cover the whole country whereas in the US it may be a little spotty it's a government driven because I think they view the coverage of of cell access and 3G 4G access to be a governmental infrastructure spending as opposed to as opposed to capitalistic so that's of course the state-owned enterprises also public traded but they also carry a government responsibility to deliver infrastructure to all so it's a different way of thinking that may be very hard to inject into Western countries to say starting tomorrow bandwidth infrastructure and highways are going to be governmental spending with some characteristics what's your sense and sorry to interrupt but because it's such a fascinating point do you think on the autonomous vehicle space it's possible to solve the problem of full autonomy without significant investment in infrastructure well that's really hard to speculate I think it's not a yes/no question but how long does it take question you know 15 years 30 years 45 years clearly with infrastructure augmentation where there's ro the city or whole city planning building a new city I'm sure that will accelerate the day of the l5 I I'm not knowledgeable enough and it's hard to predict even one we're knowledgeable because a lot of it is speculative but in the US I don't think people would consider building a new city the size of Chicago to make it a I slash autonomous city they're smaller ones being built I'm aware of that but is infrastructure spent really impossible for us or Western countries I don't think so the u.s. highway system was built was that during President Eisenhower or Kennedy as Eisenhower yeah so so so maybe historians can study how the President Eisenhower get the resources to build this massive infrastructure that surely gave us tremendous amount of prosperity over the next decade if not century if I may comment on that then it takes us to artificial intelligence a little bit because in order to build infrastructure it it creates a lot of jobs so I'll be actually interested if you would say that you talk in your book about all kinds of jobs that could could not be automated I wonder if building infrastructures one of the jobs that would not be easily automated something you could think about because they think you mentioned somewhere in the talk or that there there might be as jobs are being automated a role for government to create jobs that can't be automated yes I think that's a possibility back in the last financial crisis China puts a lot of money to basically give this economy a boost and a lot of it a lot of the one into infrastructure building and and I think that's a legitimate way and the government level to to deal with the employment issues as well as build out the infrastructure as long as the infrastructures are truly needed and as long as there isn't an employment problem which no we don't know so maybe taking a little step back if you've been a leader and a researcher in AI for several decades at least 30 years so how is AI changed in the west and the east as you've observed as you've been deep in it over the past 30 years well a I began as the pursuits of understanding human intelligence and the term itself represents that but it kind of drifted into the one sub area that worked extremely well which is machine intelligence and that's actually more using pattern recognition techniques to basically do incredibly well on the limited or domain large amount of data but relatively simple kinds of farm planning tasks and not very creative so so we didn't end up building human intelligence we built a different machine that was a lot better than us some problems but nowhere close to us other problems so today I think a lot of people still misunderstand when we say artificial intelligence and what various products can do people still think it's about replicating human intelligence but the products out there really are closer to having invented the internet or the spreadsheet or the database and getting broader adoption and peeking further to the fears near-term fears that people have about AI so you're commenting on the sort of the general intelligence that people in the popular culture from sci-fi movies have a sense about AI but there's practical fears about AI the kind the narrow AI that you're talking about of automating particular kinds of jobs and you talk about them in the book so what are the kinds of jobs in your view that you see in the next 5-10 years beginning to be automated by AI systems algorithms yes this is a also maybe a little bit counterintuitive because it's the routine jobs that will be displaced the soonest and they may not be displaced entirely maybe 50% 80% of a job but when the workload drops by that much employment will come down and also another part of misunderstanding as most people think of AI replacing routine jobs then they think of the assembly line the workers well that will have some effect but it's actually the routine white-collar workers that's easier to replace because to replace the white-collar worker you just need software to replace a blue-collar worker you need robotics mechanical excellence and the ability to deal with dexterity and maybe even unknown environments very very difficult so if we were to categorize the most dangerous white-collar jobs there would be things like back-office people who copy and paste and deal with simple computer programs and data and maybe paper and OCR and they don't make strategic decisions they basically facilitate the process the software and papers don't work so you have people dealing with new employee orientation searching for past lawsuits and financial documents and doing reference check for basic searching and management of data data that's the most in danger of being lost in addition to the white-collar repetitive work a lot of simple interaction work can also be taken care of such as telesales telemarketing customer service as well as many physical jobs that are in the same location and don't require a high degree of dexterity so fruit picking dishwashing assembly line inspection our jobs in that category so all together back office is a big part and the other the the the blue-collar may be smaller initially but over time they I will get better and when we start to get to over the next 15 20 years the ability to actually have the dexterity of doing assembly line that's a huge chunk of jobs and and when autonomous vehicles start to work initially starting with truck drivers but eventually to all drivers that's another huge group of workers so I see modest numbers in the next five years but increasing rapidly after that I'm worried of the jobs that are in danger and the gradual loss of jobs I'm not sure if you're familiar with Andrew yang yes I am so there's a candidate for president of the United States whose platform Andrew yang is based around in part around job loss due to automation and also in addition the need perhaps of universal basic income to support jobs that are folks who lose their job due to automation and so on and in general support people under complex unstable job market so what are your thoughts about his concerns him as a candidate his ideas in general I think his thinking is generally in the right direction [Music] but his approach as a presidential candidate maybe a little bit head at a time I think the displacements will happen but will they happen soon enough for people to agree to vote for him the unemployment numbers are not very high yet and I think you know he and I have the same challenge if I want to theoretically convince people this is an issue and he wants to become the president people have to see how can this be the case when an employment numbers are low so that is the challenge and I think I think we do I do agree with him on the displacement issue on universal basic income at a very vanilla level I don't agree with it because I think the main issue is retraining so people need to be incented not by just giving a monthly $2,000 check or $1,000 check and do whatever they want because they don't have to know how to know what to retrain to go into what type of a job and guidance is needed and Retraining is needed because historically when technology revolutions when routine jobs were displaced new routine jobs came up so they there was always room for that but with a eye on automation the whole point is replacing all routine jobs eventually so there will be fewer and fewer routine jobs and an AI will create jobs but it won't create routine jobs because if it creates routine jobs why wouldn't a I just do it so therefore the people who are losing the jobs aren't losing routine jobs the jobs that are becoming available are non routine jobs so the social stipend needs to be put in place is for the routine workers who lost their jobs to be retrained maybe in six months maybe in three years takes a while to retrain on a non routine job and then take out a job that will last for that person's lifetime now having said that if you look deeply into Andrews document he does cater for that so I'm not disagreeing with what he's trying to do but for simplification sometimes he just says ubi but simple ubi wouldn't work and I think you've mentioned elsewhere that I mean the goal isn't necessarily to give people enough money to survive or live or even to prosper the point is to give them a job that gives a meaning that meaning is extremely important that our employment at least in the United States and perhaps it cares across the world provides something that's forgive me for saying greater than money it provides meaning so now what kind of jobs do you think can't be automated you talk a little bit about creativity and compassion in your book what aspects do you think it's difficult to automate for an AI system because an AI system is currently merely optimizing it's not able to reason plan or think creatively or strategically it's not able to deal with complex problems it can't come up with a new problem and solve it a human needs to find the problem and pose it as an optimization problem then have the AI work habits so in AI would have a very hard time discovering a new drug or discovering a new style of painting or dealing with complex tasks that such as managing a company that isn't just about optimizing the bottom line but also about employee satisfaction corporate brand and many many other things so that is one category of things and because these things are challenging creative complex doing them creates a higher high degree of satisfaction and therefore appealing to our desire for working which isn't just to make the money make the ends meet but also that we've accomplished something that others maybe can't do or can do as well another type of job that is much numerous would be compassionate jobs jobs that require calm empathy human touch human trusts hey I can't do that because AI is cold calculating and even if it can fake that to some extent it will make errors and that will make it look very silly and also I think even if they added okay people would want to interact with the people another person whether it's for some kind of a service or a teacher or a doctor or concierge or a masseuse or a bartender there are so many jobs where people just don't want to interact with a cold robot or software I've had an entrepreneur who built an elderly care robot and they found that the elderly really only used it for customer service and huh but not to service the product but they click on the customer service and the video of a person comes up and then the person says how come my daughter didn't call me let me show you the grandkids so people learn for that people people interaction so even the robots improved people just don't want it and those jobs are going to be increasing because AI will create a lot of value 16 trillion dollars to the world in next 11 years according to PwC and that will give people money to enjoy services whether it's eating a gourmet meal or tourism and traveling or having concierge services the the service is revolving around you know every dollar of that 16 trillion dollars will be tremendous it will create more opportunities that are to service the people who did well through AI with with with things but even at the same time the entire society is very much short in need of many service oriented compassionate oriented jobs the best example is probably in healthcare services there's going to be 2 million new jobs not coming replacement just in brand-new incremental jobs in the next six years in health care services that includes nurses orderly in the hospital elderly care and and also at home care it's particularly lacking and those jobs are not likely to be filled so there's likely to be a shortage and the reason they're not filled is simply because they don't pay very well and that the social status of these jobs are not very good so they pay about half as much as a heavy equipment operator which will be replaced a lot sooner and they pay probably comparably to someone on the assembly line and if so if we ignoring all the other issues and just think about satisfaction from one's job someone repetitively doing the same manual action and assembly line that can't create a lot of job satisfaction but someone taking care of a sick person and and getting a hug and thank you from that person in the and the family I think is is quite satisfying so if only we could fix the pay for service jobs there are plenty of jobs that require some training or a lot of training for the people coming off the routine jobs to take we can easily imagine someone who was maybe a cashier at the grocery store s stores become automated learned to become a nurse or a at home care also to one the point now the blue-collar jobs are going to stay around a bit longer some of them quite a bit longer you know a I cannot be told go clean an arbitrary home that's incredibly hard arguably is an l5 level of difficulty right and then AI cannot be a good plumber because plumber is almost like a mini detective that has to figure out where the leak came from so yet AI probably can be an assembly line and auto mechanic and so on so one has to study which blue-collar jobs are going away and facilitate retraining for the people to go into the ones that won't go away or maybe even will increase I mean it is fascinating that it's easier to build a world champion chess player than it is to build a mediocre plumber yes right very true iji and that goes counterintuitive to a lot of people's understanding of what artificial intelligence is so it sounds I mean you're painting a pretty optimistic picture about retraining about the number of jobs and actually the meaningful nature of those jobs once we automate repetitive tasks so overall are you optimistic about the future where much of the repetitive tasks are automated that there is a lot of room for humans for the compassionate for the creative input that only humans can provide I am optimistic if we start to take action if we have no action in the next five years I think it's going to be hard to deal with the devastating losses that will emerge so if we start thinking about retraining maybe with the low-hanging fruits explaining to vocational schools why they should train more plumbers that other mechanics may be starting with some government subsidy for corporations to have more training positions we start to explain to people why retraining is important we start to think about what the future of education how that needs to be tweaked for the era of AI if we start to make incremental progress and the greater number of people understand then there's no reason to think we can't deal with this because this technological revolution is arguably similar to what electricity industrial revolutions and internet brought about do you think there's a role for policy for governments to step in to help with policy to create a better world absolutely and I and the government's don't have to believe an employment will go up and they don't have to believe automation will be this fast to do something revamping vocational school would be one example another is if there is a big gap in health care service employment and we know that a country's population is is growing Oh more longevity living older because people over 80 require five times as much care as those under 80 then it is a good time to incent training programs for elderly care to find ways to improve the pay maybe one way would be to offer as part of Medicare or the equivalent program for people over 80 to be entitled to a few hours of elderly here at home and then that might be reimbursable and that will stimulate the service industry around the policy do you have concerns about large entities whether it's governments or companies controlling the future of AI development in general so we talked about companies do you have a better sense that governments can better represent the interest of the people then companies or do you believe companies are better representing the interests of the people or is there no easy answer I don't think there's an easy answer because there's a double-edged sword the companies and governments can provide better services with more access to data and more access to AI but that also leads to greater power which can lead to uncontrollable problems whether it's monopolies or corruption in the government so I think one has to be careful to look at how much data that companies and governments have and and some kind of checks and balances would be helpful so again I come from Russia there's something called the Cold War so let me ask a difficult question here looking at conflict the Steven Pinker written a great book that conflict all over the world is decreasing in general but do you have a sense that having written the book AI superpowers do you see a major international conflict potentially arising between major nations whatever they are with its roster China European nations United States or others in the next 10 20 50 years around AI around the digital space cyberspace do you worry about that that is there something is that something we need to think about and try to alleviate or prevent I believe in greater engagement a lot of the worries about more powerful AI are based on a arms race metaphor and the when you extrapolate into military kinds of scenarios AI can automate and and and you know animus weapons that needs to be controlled somehow and autonomous decision-making can lead to not enough time to fix international crises so I actually believe a Cold War mentality would be very dangerous because should two countries rely on AI to make certain decisions and they don't in talk to each other they do their own scenario planning then something could easily go wrong I think engagement interaction some protocols to avoid inadvertent disasters is actually needed so it's natural for each country to want to be the best whether it's in nuclear technologies or AI or bio but I think is important to realize if each country has a black box AI and that don't talk to each other that probably presents greater challenges to humanity then if they interacted I think there can still be competition but with some degree of protocol for interaction just like when there was a nuclear competition there were some protocol for deterrence among US Russia and China and I think that engagement is needed so of course we're still far from AI presenting that kind of danger but what I worry the most about is the level of engagement seems to be coming down the level of distrust seems to be going up especially from the US towards other large countries such as China and of course Russia and Russia yes is there a way to make that better so that's beautifully put level engagement and even just basic trust and communication as opposed to sort of you know making artificial enemies out of particular particular countries did you ever you have a sense how we can make it better mentionable items that as a society we can take on I'm not an expert at geopolitics but I would say that we look pretty foolish as humankind when we are faced with the opportunity to create sixteen trillion dollars for for Humanity and we we're in yet we're not solving fundamental problems with parts of the world still in poverty and for the first time we have the resources to overcome poverty and hunger we're not using it on that but we're fueling competition among superpowers and that's a very unfortunate thing if we become utopian for a moment imagine a a benevolent world government that has this 16 trillion dollars and maybe some AI to figure out how to use it to deal with diseases and problems and hate and things like that world would be a lot better off so what is wrong with the current world I think the people with more skill than then I should just think about this and then at your politics issue with superpower competition is one side of the issue there's another side which I worry maybe even even even more which is as the 16 trillion dollars all gets made by US and China and a few of the developed other developed countries the poorer country will get nothing because they don't have technology and the the wealth disparity and the end of inequality will increase so a poor a country with a large population will not only benefit from the AI pool or other technology booms but they will have their workers who previously had hoped they could do the china model and do outsourced manufacturing or the india model so they could do the house or some process or call center all those jobs are going to be gone in 10 or 15 years so the the individual citizen may be a net liability I mean financially speaking to a poorer country and not an asset to claw itself out of poverty so in that kind of situation these large countries with was not much tech are going to be facing a downward spiral and it's unclear what could be done and and then when we look back and say there's 16 trillion dollars being created and it's all being kept by us China and other developed countries it just doesn't feel right so I hope people who know about geopolitics can find solutions that's beyond my expertise so different countries that we've talked about have different value systems if you look at the United States to an almost extreme degree there is a an absolute desire for freedom of speech if you look at a country where I was raised that desire just amongst the people is not that not as elevated as it is basically fundamental level to the essence of what it means to be America right and the same is true with China there's different value systems and there is some censorship of Internet content that China and Russia and many other countries undertake do you see that having effects on innovation other aspects of some of the text of AI development we talked about and maybe from another angle do you see that changing different ways over the next 10 years 20 years 50 years as China continues to grow as it does now in its tech innovation there's a common belief that full freedom of speech and expression is correlated with creativity which is correlated with entrepreneurial success I think empirically we have seen that is not true and China has been successful that's not to say the fundamental values are not right or not the best but it's just that that that perfect correlation isn't isn't there it's hard to read the tea leaves on an opening up or not in any country and I've not been very good at that in my past predictions but I do believe every country shares some fundamental value a lot of fundamental values for the long-term so you know China is drafting its privacy policy for individual citizens and they don't look that different from the American or European ones so people do want to protect their privacy and have the opportunity to express and I think the fundamental values are there the question is in the execution and timing how soon or when will that start to open up so so as long as each government knows ultimately people want that kind of protection there should be a plan to move towards that as to when or how and I'm not an expert on the point of privacy to me it's really interesting so AI needs data to create a personalized awesome experience yeah all right I'm just speaking general in terms of products and then we have currently depending on the age and depending on the demographics of who we were talking about some people are more or less concerned about the amount of data they handover so in your view how do we get this balance right that we provide an amazing experience to people that use products you look at Facebook you know the more Facebook knows about you yes it's scary to say the better you can probably yeah but experience it could probably create so any of you how do we get that balance right yes I think a lot of people have a misunderstanding that it's okay and possible to just rip all the data out from a provider and give it back to you so you can deny them access to further data and still enjoy the services we have if we take back all the data all the services will give us nonsense will no longer be able to use products that function well in terms of you know right ranking right products right user experience so so yet I do understand we don't want to permit misuse of the data from legal policy and point I think there can be severe punishment for those who have egregious misuse of the data that's I think a good first step actually China in this side on this aspect has very strong laws about people who sell or give data to other companies and and that over the past few years since the that loud locking came into effect pretty much eradicated the illegal distribution sharing of data additionally I think giving I think in technology is often a very good way to solve technology misuse so can we come up with new technologies that will let us have our cake and eat it too people are looking into homomorphic encryption which is letting you keep the data have it encrypted and train on encrypted data of course we haven't solved that one yet but that kind of direction may be worth pursuing also federated learning which would allow one hospital to train on its hospital's patient data fully because they have a license for that and then hospitals would then share their models not data with models to create a super AI and that also maybe has some promise so I would want to encourage us to be open-minded and think this think of this as not just the policy binary yes/no but letting the technologists try to find solutions to let us have our cake in either two or have most of our cake and eat most of it too finally I think giving each end user a choice is important and having transparency is important also I think that's universal but the choice you give to the user should not be at a granular level that the user cannot understand gdpr today causes all these pop ups of yes/no will you give this site this right to use this part of your data I don't think any user understands what they're saying yes or no to and I suspect most are just saying yes because they don't understand so while GDP are in its current implementation has lived up to its promise of transparency and user choice it implemented it in such a way that really didn't deliver the the spirit of GDP our it fit the letter but not the spirit so again I think we need to think about is there a way to fit the spirit of GDP our by using some kind of technology can we have a slider that's an AI trying to figure out how much you want to slide between perfect protection secure security of your personal data versus high degree of convenience with some risks of not having full privacy each user's should have some preference and that gives you the user choice but maybe we should turn the problem on its head and ask can there be an AI algorithm that can customize this because we can understand the slider but we sure cannot understand every pop up question and I think getting that right requires getting the balance between what we talked about earlier which is heart and soul versus profit driven decisions and strategy I think from my perspective the best way to make a lot of money in the long term is to keep your heart and soul intact I think getting that slider right in the short term may feel like you'll be sacrificing profit but in the long term you were beginning user trusts and providing a great experience do you share that kind of view in general yes absolutely I would I sure would hope there is a way we can do long term projects that's really do the right thing I think a lot of people who embrace GDP are their hearts in the right place I think they just need to figure out how to build a solution I've heard utopians talk about solutions that get me excited but not sure how in the current funding environment they can get started right people talk about imagine this crowd-sourced data collection that we all trust and then we have these agents that we ask them to ask the trusted agent to we that agent only that platform said trusted joined platform that that we all believe is trustworthy that can give us all the closed-loop personal suggestions by the new social network new search engine new e-commerce engine that has access to even more of our data but not directly but indirectly so I think that general concepts of licenses into some trusted engine and finding a way to trust that engine seems like a great idea but if you think how long it's gonna take to implement and tweak and develop it right as well as to collect all the Trust's and the data from the people it's beyond the current cycle of venture capital right so how do you do that it's a big question you've recently had a fight with cancer Stage four lymphoma and a in a sort of deep personal level what did it feel like in the darker moments to face your own mortality well I've been the workaholic my whole life and I've basically worked nine ninety six 9:00 a.m. to 9:00 p.m. six days a week roughly and I didn't really pay a lot of attention to my family friends and people who loved me and my life revolved around optimizing for work while my work was not routine my optimization really what made my life basically a very mechanical process but I got a lot of highs out of it because of accomplishments that I thought were really important and dear and the highest priority to me but when I faced mortality and the possible death in a matter of months I suddenly realized that this really meant nothing to me that I didn't feel like working for another minute that if I had six months left in my life I would spend it all with my loved ones and you know thanking them giving them love back and apologizing to them that I lived my life the wrong way so so that moment of reckoning caused me to really rethink that's why we exist in this world is is something that we might be too much shaped by the society to think that success and accomplishments is why we live but while that can get you periodic successes and satisfaction it's really in the facing death you see what's truly important to you so as a result of going through them the challenges with cancer I've resolved to live a more balanced lifestyle I'm now in remission knock on wood and I'm spending more time with my family my wife travels with me when my kids need me I spend more time with them and before I used to prioritize everything around work when I had a little bit of time I would dole it out to my family now when my family needs something really need something I drop everything at work and go to them and then in the time remaining I allocate to work but once family is very understanding it's not like they will take me 50 weeks so 50 hours a week from me so I'm actually able to still work pretty hard maybe ten hours less per week so I realized the most important thing in my life is really love and the people I love and that give that the highest priority it isn't the only thing I do but when that is needed I put that at the top priority and I feel much better and I feel much more balanced and I think this also gives a hint as to a life of routine work a life of pursuit of numbers while my job was not routine it wasn't pursuit of numbers pursuit of can I make more money can i fund more great companies can I raise more money can I make sure our VC is ranked higher and higher every year this competitive nature of driving for bigger numbers and better numbers became a endless pursuit of that's mechanical and bigger numbers doesn't really didn't make me happier and faced with death I realized the bigger numbers really meant nothing and what was important is that people who have given their heart and their love to me deserve for me to do the same there's deep profound truth in that that everyone should hear and internalize and that's really powerful for you to say that I have to ask sort of a difficult question here so I've competed and sports my whole life looking historically I'd like to challenge some aspect of that a little bit on the point of hard work that it feels that there are certain aspects that is the greatest the most beautiful aspects of human nature is the ability to become obsessed of becoming extremely passionate to the point where yes flaws are revealed and just giving yourself fully to a task that is in another sense you mentioned love being important but in another sense this kind of obsession this pure exhibition of passion and hard work is truly what it means to be human what lessons should we take this deeper because Eve accomplished incredible things you say it chasing numbers but really there's some incredible work there so how do you think about that when you look back in your 20s 30s what was what would you do differently would you really take back some of the incredible hard work I would but it's it's in percentages right we're both computer scientists so I think when one balances one's life when when one is younger you you might give a smaller percentage to family but you will still give him high priority and when you get older you would give a larger percentage to them and still the high priority and and when you're near retirement you give most of it to them and the highest priority so I think the key point is not that we would work 20 hours less for the whole life and just spend it aimlessly with the family but that when the family has a need when your wife is having a baby when your daughter has a birthday or when they're depressed or when they're celebrating something or when they have a get-together or we have family time that it's important for us to put down our phone and PC and be a hundred percent with them and that priority on the things that really matter isn't going to be so taxing that it would eliminate or even dramatically reduce our accomplishments it might have some impact but it might also have other impact because if you have a happier family maybe you fight less you fight less you don't spend time taking care of all the aftermath of a fight so it's unclear that it would take more time and if it did I'd be willing to to take that reduction and it's not a dramatic number but it's a number that I think would give me a greater degree of happiness and knowing that I've done the right thing and still have plenty of hours to it to get the success that I want to get so given the many successful companies that you've launched and much success throughout your career what advice would you give to young people today King or doesn't have to be young but people today looking to launch and to create the next one billion-dollar tech startup or even AI base startup I would suggest that people understand technology waves move quickly what worked two years ago may not work today and that is very much case in point for AI I think two years ago or maybe three years ago you certainly could say I have a couple of super-smart PhDs and we're not sure what we're gonna do but here's what how we're gonna start and get funding for a very high valuation those days are over because AI is going from rocket science towards mainstream not yet commodity but more mainstream so first the creation of any company to eventual capitalists has to be creation of business value and monetary value and when you have a very scarce commodity VCS may be willing to accept greater uncertainty but now the number of people who have the equivalent of PhD three years ago because that can be learned more quickly platforms are emerging the costs to become a AI engineer is much lower and there are many more AI engineers so the market is different so I would suggest someone who wants to build an AI company be thinking about the normal business questions what customer cases are you trying to address what kind of pain are you trying to address how does that translate to value how will you extract value and get paid through what channel and how much business value will get created that's today needs to be thought about much earlier upfront then it did three years ago the scarcity question of AI talent has changed the number of AI talent has changed so now you need not just AI but also understanding of business customer and and the marketplace so I also think you should have a more reasonable valuation expectation and growth expectation there's going to be more competition but the good news though is that AI technologies are now more available in open source tensorflow pi torch and such tools are much easier to use so you should be able to experiment and get results iteratively faster than before so take more of a business mindset to this think less of this as a laboratory taken into a company because we've gone beyond that stage the only exception is if you truly have a breakthrough in some technology that really no one has then then the old way still works but I think that's harder and harder now so I know you believe as many do that we're far from creating an artificial general intelligence system but say once we do and you get to ask her one question what would that question be what is it that differentiates you and me beautifully put careful thank you so much for your time today thank you you