Sebastian Thrun: Flying Cars, Autonomous Vehicles, and Education | Lex Fridman Podcast #59
following is a conversation with Sebastian Thrun he's one of the greatest roboticists computer scientists and educators of our time he led the development of the autonomous vehicles at Stanford that one 2005 DARPA Grand Challenge and placed second in the 2007 DARPA urban challenge he then led the Google self-driving car program which launched the self-driving car revolution he taught at the popular Stanford course on artificial intelligence in 2011 which was one of the first massive open online courses or MOOCs as they're commonly called that experience led him to co-found Udacity an online education platform if you haven't taken courses on it yet I highly recommended their self-driving car program for example is excellent he's also the CEO of Kitty Hawk a company working on building flying cars are more technically Evie tall's which stands for electric vertical takeoff and landing aircraft he has launched several revolutions and inspired millions of people but also as many know he's just a really nice guy it was an honor and a pleasure to talk with him this is the artificial intelligence podcast if you enjoy subscribe I need to give it five stars and Apple podcasts follow it on Spotify supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma M if you leave a review on Apple podcast or YouTube or Twitter consider mentioning ideas people topics you find interesting it helps guide the future of this podcast but in general I just love comments with kindness and thoughtfulness in them this podcast is a side project for me as many people know but I still put a lot of effort into it so the positive words of support from an amazing community from you really helped I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle they can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience I provide time 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and use coal export gas you'll get ten dollars in cash up we'll also donate ten dollars the first which again is an organization that I've personally seen inspired girls and boys the dream of engineering a better world and now here's my conversation or Sebastian Thrun you mentioned that the matrix may be your favorite movie so let's start with the crazy philosophical question do you think we're living in a simulation and in general do you find the thought experiment interesting define simulation I would say maybe we are not but it's completely irrelevant to the way we should act putting aside for a moment the fact that it might not have any impact on how we should act as human beings for people studying theoretical physics these kinds of questions might be kind of interesting looking at the universe's information processing system the universe is an information processing system is a huge physical biological chemical computer there's no question but I live here and now I care about people okay about us what do you think is trying to compute and I think there's an intention I think it just the world evolves the way it devolves and it's it's beautiful is unpredictable and I'm really grateful to be alive spoken like a true human which last time I checked that was oh that in fact this whole conversation is just a touring test to see if if indeed if indeed you are you've also said that one of the first programs of the first few programs you've written was a wait for a TI 57 calculator yep maybe that's early eighties I don't wanna date calculators anything early eight is correct yeah so if you were to place yourself back into that time into the mindset you are in because you have predicted the evolution of computing AI the internet technology in in the decades that followed I was super fascinated by Silicon Valley which I seen on television once and thought my god this is so cool they build like D Rams there and CPUs how cool is that and as a college students a few year later a few days later I decided to be study intelligence and study human beings and found that even back then in the 80s and 90s that artificial intelligence is what fascinated me the most I was missing is that back in the day the computers are really small they're like the brains you could build well not anywhere bigger as a cockroach and cock-horse aren't very smart so we weren't at the scale yet where we are today did you dream at that time to achieve the kind of scale we have today did that seem possible I always wanted to make robots smart I felt it was super cool to build an artificial human and the best way to build not official you want to be a robot because that's kind of the closest if you could do unfortunately we aren't there yet there were words today are still very brittle about as fascinating to study intelligence from a constructive perspective it built something to understand you build what do you think it takes to build an intelligent system and an intelligent robot I think the biggest innovation that we've seen as machine learning and it's the idea that their computers can BC teach themselves let's give an example I'd say everybody pretty much knows what a wok and we learn how to walk in the first year two of our lives but no scientist has ever been able to write on the rules of human gait we don't understand that we can't put we have in our brain somehow we can practice it we understand it that we can articulate that we can't pass it on by language and that to me is kind of a deficiency of today's computer programming even you could program a computer they're so insanely dumb that you have to give them rules for every contingencies very unlike the way people learn but learn from data and experience computers are being instructed and because it's so hard to get this instruction set right we pay software engineers two hundred thousand dollars a year now the most recent innovation which has been to make for like 3040 years is an idea that computers can find their own rules so they can learn from falling down and getting up the same way children can learn from falling down and getting up and that revolution has led to a capability that's completely unmatched today's computers can watch experts do their jobs whether you're a doctor or lawyer pick up the regularities learn those rules and then become as good as the best experts so the dream of in the 80s of expert systems for example had at its core the idea that humans could boil down their expertise on a sheet of paper so sort of reduce sort of be able to explain to machines how to do something explicitly so do you think what's the use of human expertise into this whole picture do you think most of the intelligence will come from machines learning from experience without human expertise input so the question for me is much more how to express expertise um you can express expertise providing a book you can express expertise by showing someone what you're doing you can express expertise by applying it by by many different ways and I think the expert systems was our best attempt in AI to capture expertise in rules there someone sat down and say here the rules of human gait here's when you put your big toe forward and your heel backwards and Yahoo stop stumbling and as we now know the set of rules a set of language that he can command is incredibly limited the human brain doesn't deal with language it is with that subconscious numerical perceptual things that we don't even ever survey off now when a AI system watches an expert do their job and practice their job it can pick up things that people can't even put into writing into books or rules and that's where the real power is we now have AI systems that for example look over the shoulders of highly paid human doctors like dermatologist or radiologists and they can somehow pick up those skills that Noah can express in words so you were a key person in launching three revolutions online education and Thomas vehicles and flying cars or vetoes so high level and I apologize for all the philosophical questions that's no policy necessary how do you choose what problems to try and solve drives you to make those solutions a reality I have two two desires in life I want to literally make the lives of others better or as few of them say maybe joke indeed what make the world a better place if you believe in us it's as funny as it sounds and second I want to learn I want to get in the circus I don't want to be in a dropping with it because if I meant job that I'm good at the chance for me to learn something interesting is actually minimized so I want to be in a job I'm bad at that's really important to me so I'm in a bill for example but people often call flying cars is that electrical vertical takeoff and landing vehicles I'm just no expert in any of this and it's so much fun tool to learn on the job what actually means to build something like this now it's saying that the stuff that I done lately after I finished my professorship at Stanford the video focused on like what has the maximum impact on society like transportation is something has transformed the 21st 20th century more than any other invention of my opinion even more than communication and cities are different workers different women's rights are different because of transportation and yet we still have a very suboptimal transportation solution where we kill 1.2 or so million P every year in traffic it's like the leading cause of death for young people in many countries we have here extremely inefficient resource wise just go to your average neighborhood city and look at the number of parked cars that's a travesty in my opinion or where we spend endless hours in traffic jams and very very simple innovations like a self-driving car or what people call a flying car could completely change this and it's there I mean the technology is it's basically there yet close your eyes not to see it so lingering on autonomous vehicles fascinating space some incredible work you done throughout your career there so let's start we'll start with DARPA I think the DARPA challenge there's a desert and then urban to the streets I think that inspired an entire generation of roboticists and obviously sprung this whole excitement about this particular kind of four wheeled robots were called autonomous cars self-driving cars so you led the development of Stanley the autonomous car that one that erased the desert the DARPA challenge in 2005 and junior a car that I finished second in the DARPA Grand Challenge also did incredibly well in 2007 I think what are some painful inspiring or enlightening experiences from that time that stand out to you oh my god painful were all these incredibly complicated stupid bugs that had to be found we had a face where the stanley hour or carded i eventually won the DARPA Grand Challenge but every 30 miles just commit suicide and we didn't know why and it ended up to be that in the sinking of two computer clocks occasionally a clock went backwards and that negative time elapsed screwed up the entire internal logic but it took ages to find this they were like bugs like that I'd say enlightening is the Stanford team immediately focused on machine learning and on software where's everybody else seem to focus on building better hardware our knowledge had been you a human being with an existing rental car can we drive the course I have to might have to build a better rental car I just built it should replace the human being and the human being to me was a conjunction of three steps we had extensors eyes and ears mostly eyes we had brains in the middle and then we had actuators our hands in our feet now the extras I used to build the sensors like she also use it a bit what was missing was the brain so he had to build a human brain and nothing nothing clear them to me that that the human brain is a learning machine so why not just train our robot so it you would build a massive machine learning into our machine and with that were able to not just learn from human drivers we had the entire speed control of the vehicle was copied from human driving but also have the robot learn from experience where it made a mistake and go to recover from it and learn from it you mentioned the pain point of software and clocks synchronization seems to seems to be a problem that continues with robotics it's a tricky one with drones and so on Oh what what does it take to build a thing a system with so many constraints you have a deadline no time you're unsure about anything really it's the first time that people really do even explore yeah it's not even sure that anybody can finish when we were talking about the race of the desert the year before nobody finished what does it take to scramble and finish a product that actually a system that actually works we were very lucky we did a small team that core of the team of four people it was four because five couldn't comfortably sit inside carpet for food and I as a team leader my job was to get pizza for everybody and wash the car and stuff like this and repair the radiator and it broke and debug the system and we were a kind of open mind that we had like no egos involved in this you just wonder to see how far we can get or we did really really well was time management we were done with everything a month before the race and we froze the entire of a month before the race and it turned out looking at other teams every other team complained if they just one more week they would have won and we decided that's gonna fall into a mistake you're gonna be early and we had an entire month to shake that system and we actually found two or three minor bugs in the last month that we had to fix and we were completely prepared in the race occurred okay so first of all that's such an incredibly rare achievement in terms of being able to be done on time or ahead of time what do you how do you do that in your future work what advice do you have in general because it seems to be so rare especially in highly innovative projects like this people work till the last second but the nice thing about the topic one challenge is that the problem was incredibly well-defined we were able for a while to drive the old topic van challenge course which had been used the year before and then at some reason we were kicked out of the region so we had to go to different desert the Sonoran Desert and be able to drive desert trails just at the same time so there was never any debate about like what is actually the problem we didn't sit down and say hey should we build a car or a plane if we had to build a car that made it very very easy then I studied my own life and life of a dozen guys that the typical mistake that people make is that there's this kind of crazy bug left that they haven't found yet and and it's just there regretted and it back would have been trivial to fix it was haven't fixed it yet they didn't want to fall into that trap so I build a testing team we had a testing tena build a testing booklet of 160 pages of tests we had to go through just to make sure we shake all the system appropriately Wow and the testing team was with us all the time and dictated to us today we do railroad crossings tomorrow over do we practice the start of the event and in all of these we thought oh my god has long solved trivial and I mean tested it out oh my god it doesn't were a well for us and why not oh my god it mistakes the and the rails for metal barriers we have to fix this yes so it was easy a continuous focus on improving the weakest part of the system and as long as you you focus on improving the weakest part of the system you eventually build a really great system let me just pause Allah is to me as an engineer is super-exciting that you were thinking like that especially at that stage as brilliant that testing was such a core part of it it may be to linger on the point of leadership I think it's one of the first times you were really a leader and you've led many very successful teams since then what does it take to be a good leader I would say I'm most of all just take credit for the work of others right that's that's very convenient than that because I can't do all the things myself I'm an engineer at heart so I I care about engineering so so I I don't know what the chicken in the egg is but as a kid I love computers because you could tell them to do something and they actually did it it was very cool and you could like in the middle of a night wake up at 1:00 in the morning and switch on your computer and what you told you to yesterday I would still do that was really cool unfortunately that it didn't quite work with people so you go to people and tell them what to do and they don't do it mm-hm and they hate you for it or you do it today and then you go a day later and you stop doing it so you have to so then a question really became how can you put yourself in the brain of the of people as opposed to computers and it has the computers as super dumb then so dumb if if people were as dumb as computers i wouldnt want to walk with them mmm but people are smart and people are emotional and people have pride and people have a spur a shion's so how can i connect to that and that's the thing where most of leadership just fails because many many engineers turn manager believe they can treat their team just the same way I can treat your computer and it just doesn't work this way it's just really bad so how did how can i how are can i connect to people and in turns out as a college professor the wonderful thing you do all the time is to empower other people like your job is to make your students look great that's all you do you're the best coach and it turns out if you do a fantastic job is making a students look great they actually love you and their parents love you and they give you all the credit for stuff you don't deserve since that all my students who are smarter than me all the great stuff invented at Stanford versus their stuff not my stuff and they give me credit and say oh Sebastian but just making them feel good about themselves so the question really is can you take a team of people and what does it take to make them to connect to what they actually want in life and turn this into product affection it turns out every human being that I know has incredibly good intention I've really never really met a person with bad intentions I believe every person wants to contribute I think every person I've met wants to help others it's amazing how much of a urge we have not to just help ourselves but to help others so how can we empower people and give them the right framework that they can accomplish this if in moments when it works it's magical because you'd see the confluence of people being able to make the world a better place and driving enormous confidence and pride out of this and that's when when my environment works the best these are moments where I can disappear for a month and come back and things still work it's very hard to accomplish but in when it works is amazing so I agree very much it's not often heard that most people in the world have good intentions at the core their intentions are good and they're good people that's a beautiful message it's not often heard we make this mistake and this is a friend of mine eggs water token us that we we judge ourselves by our intentions in others by the actions and I think the the biggest skill I mean here in Silicon Valley were full of Engineers I have very little empathy and and I kind of befuddled why it doesn't work for them the biggest skill I think that that people should acquire is to put themselves into the position of the other and listen and listen to what the other has to say and they'd be shocked how similar they are to themselves and they might even be shocked how their own actions don't reflect their intentions I often have conversations with engineers yes they look hey I love you doing a great job and by the way what you just did has the following effect are you aware of that and then people would say oh my god not I wasn't because my intention was that they'd say yeah I trust your intention you're a good human being but just to help you in the future if you keep expressing it that way then people just hate you and I've had many instances we say oh my god thank you for telling me this because it wasn't my intention to look like an idiot wasn't my intention to help other people I just didn't know how to do it simply by the way there's a no-fail carnegie 1936 how to make friends and how to influence others has the entire pipe or just read it and you're done and usually apply it every day and I wish I could I was good enough to apply it every day but it says simple things right like be positive remember previous name smile and eventually have empathy like really think that the person that you hate and you think is an idiot is if you just like yourself it's a person who's struggling who means well and who might need help and guess what you need help I've recently spoken with Stephen Schwarzman I'm not sure if you know who that is but do so and he said I'm a list no but he he said sort of to expand on what you're saying that one of the biggest things you can do is hear people when they tell you what their problem is and then help them with that problem he says it's surprising how few people actually listen to what troubles others and because it's right there in front of you and you can benefit the world the most and in fact yourself and everybody around you by just hearing the problems and solving them I mean that's my my little history of engineering that is while I was engineering with computers I didn't care all what the computers problems for just I just volumize everyone to do it and it doesn't work with me you've become the mean say to do AI do the opposite but let's return to the comfortable world of engineering thinking you can you tell me in broad strokes in how you see it because you're the course starting at the core of driving it the technical evolution of autonomous vehicles from the first DARPA Grand Challenge to the incredible success we see or the program you started with Google self-driving car and way more in the entire industry that sprung up all the different kinds of approaches debates and so on well the idea of self-driving car goes back to the 80s there was a team in Germany on the team at Carnegie Mellon that it's very pioneering work but back in the day I'd say the computers were so efficient that even the best professors and engineers in the world basically stood no chance it then folded into a phase where the US government spent at least half a million dollars that I could count on research projects but the way the procurement works a successful stack of paper describing lots of stuff that no one's ever gonna read was a successful product of a research project so so we trained our researchers to produce lots of paper that all changed for the DARPA Grand Challenge and I really gotta credit the ingenious people at DARPA and the US government in Congress that took a complete new funding model where they said that's not fun effort let's fund outcomes and it sounds way trivial but it there was no tax code that allowed did the use of congressional tax money for a price it was all effort based so if you put in a hundred dollars in you could charge 100 hours you put in a thousand dollars and you could build a thousand hours by shading the focus in city making the price we don't pay you for development we pray for the accomplishment they drew in they automatically drew out all these contractors who are used to the drug of getting money power and they drew in a whole bunch of new people and these people are mostly crazy people there were people who had a car and a computer and they wanted to make a million bucks the million bucks was the official price money was then doubled and they felt if I put my computer in my car and program it I can be rich and it was so awesome like like half the team's there was a team that was surfer dudes and they had like two surfers on the vehicle and brought like these fashion girls super cute girls like twin sisters and and you could tell these guys were not your common I felt very offended who like gets all these big multi-million and billion other countries from the US government and and there was a great we set the universities moved in I was very fortunate at Stanford that I just received tenure so I couldn't be fired whenever I do otherwise I would have done it and I had enough money to finance this thing and I was able to attract a lot of money from from third parties and even car companies moved in they kind of moved in very quietly because they were super scared to be embarrassed that they a car would flip over but Ford was there and Volkswagen was there and a few others and GM was there so it kind of reset the entire landscape of people and if you look at who's a big name in suffering cars today these were mostly people who participated in those challenges ok that's incredible can you just comment quickly on your sense of lessons learned from that kind of funding model and the research that's going on academia in terms of producing papers is there something to be learned and and scaled up bigger these having these kinds of grand challenges that could improve outcomes so I'm a big believer in and focusing on kind of an end-to-end system I'm a really big believer in an insistence building I've always built systems in my academic career even though I love math and an abstract stuff but it's all derived from the idea of let's solve your problem and it's very hard for me to be an academic and say let me solve a component of a problem like if someone this feels like not monitoring logic or AI planning systems where people believe that a certain style of problem-solving is the ultimate end objective and and I would always turn it around and say hey what problem put my grandmother care about that doesn't understand computer technology and doesn't want to understand how could I make her love what I do because only then do I have an impact on the world I can easily impress my colleagues that's that's that that is much easier but impressing my grandmother is very very hard so I've always thought if I can build a self-driving car and and my grandmother can use it even after she loses her driving privileges or Sheldon can use it or we save maybe a million lives a year they would be very impressive and then there's so many problems like these like there's a problem of curing cancer or I'll if twice as long once the problem is defined of course I can solve it in society like it takes sometimes tens of thousands of people to to find a solution there's no way you can fund an army of ten thousand at Stanford so you're going to be the prototype it's bit of meaningful prototype and the DARPA Grand Challenge was beautiful because it told me what this prototype had to do I didn't need to think about what it had to do it is said to read the rules and it was really really beautiful and it's most beautiful you think what academia could aspire to is to build a prototype that's the system's level that solves it gives you an inkling that this problem could be solved with this project that's all I want to emphasize what academia really is and I think people misunderstand it first and foremost academia is a way to educate young people first and foremost the professor is an educator no matter away what a small suburban college or whether you are a Harvard or Stanford professor that's not the way most people think of themselves in academia because we have this kind of competition going on for citations and and publication that's a measurable thing but that is secondary to the primary purpose of educating people to think now in terms of research most of the great science the great research comes out of universities you can trace almost everything back including Google to universities so there's nothing we do fundamentally broken here it's a it's a good system and I think America has the finest University system on the planet we can talk about reach and how to reach people outside the system it's a different topic but the system would serve as a good system if I had one wish I would say it'd be really great if there was more debate about what the great big problems are on the side and focus on those and most of them are interdisciplinary unfortunately it's very easy to fall into a inner disciplinary viewpoint where your problem is dictators but what your closest colleagues believe the problem is it's very hard to break out and say why there's an entire new field of problems so give an example um prior to me working on self-driving cars I was a roboticist in a machine learning expert and I wrote books on robotics something called probabilistic robotics the survey methods driven kind of viewpoint of the world I build robots that acted in museums as tour guides that bug let children around it's something that it's time was moderately challenging when I started working on cars several colleagues told me Sebastian you're destroying your career because in our field of robotics cars are looked like as a gimmick and they're not expressive enough they can only push the throttle and and in the brakes there's no dexterity there's no complexity it's just too simple and no one came to me and said Wow if you solve that problem you can save a million lives right among all robotic problems that I've seen in my life I would say the self having car transportation Havana has the most hope for society so how come the robotics community was all over the place and of us become because we focused on methods and solutions and not on problems like if you go around today and ask your grandmother what bugs you what really makes you upset I challenge any academic and to do this and then realize how far your research is probably away from that today at the very least that's a good thing for academics they deliberate on the other thing that's really nice in Silicon Valley is Silicon Valley is full of smart people outside academia right so there's the Larry page's and magaz archive books in the world who are anywhere as smart or smarter than the best academics I met in my life and what they do is they they are at a different level they build the systems they build they build the customer-facing system they built things that people can use without technical education and they are inspired by research they're inspired by scientist they hire the best PhDs from the best universities for a reason so I think this kind of vertical integration that between the real product the real impact and the real thought the real ideas there's actually working surprisingly balanced Silicon Valley it did not work as well in other places in this nation so when I worked at Carnegie Mellon we had the world's finest computer science university but there wasn't those people in Pittsburgh that would be able to take these very fine computer science ideas and turn them into massive the impact for products that symbiosis seemed to exist pretty much only in Silicon Valley and maybe a bit in Boston in Austin yeah with Stanford that's it was it's really really interesting so if we look a little bit further on from the the DARPA Grand Challenge and the launch of the Google self-driving car what do you see is the state the challenges of autonomous vehicles as they are now is actually achieving that huge scale and having a huge impact on society I'm extremely proud of what what has been accomplished and again I'm taking a lot of credit for the work for us and I'm actually very optimistic and and people have been kind of worrying is it too fast as to slow I salute there yet and so on it is actually quite an interesting hard problem and in that a self-driving car to build one that manages 90% of the problems encountered in everyday driving is easy we can literally do this over a weekend to do 99% might take a month then there's 1% left so 1% would mean that you still have a fatal accident every week very unacceptable so now you work on this 1% and the 99% of there were any 1% is actually still a relatively easy but now you're down to like a hundredth of one percent and it's still completely unacceptable in terms of safety so the variety of things you encounter are just enormous and that gives me enormous respect for human being available to deal with the couch on the highway right or the DNI headlight or the blown tire that we'd never never been trained for and all of a sudden I have to handle in an emergency situation and often do very very successfully it's amazing from that perspective how safe driving actually is given how many millions of miles we drive every year in this country we are now at a point where I believed it in already is there and I've seen it I've seen it in way more I've seen it in activist engine crews and in a number of companies in unvoyage where vehicles not driving around and basically flawlessly I able to drive people around in limited scenarios in fact you can go to Vegas today and order a Seminole lift and if you got the right setting off your app you'll be picked up by a driverless car now there's still safety drivers in there but that's a fantastic way to kind of learn what the limits of Technology today and there's still some glitches but the gifts have become very very rare I think the next step is gonna be to down cost it to harden it did that entrapment it sends us are not quite an automatic weights than that yet and then you read about the business models to really kind of go somewhere and make the business case and the business case is hard work it's not just oh my god we have this capability people that's gonna buy it you have to make it affordable you have to give people that find the social acceptance of people none of the teams yet has been able to or gutsy enough to drive around without a person inside the car and that's that the next magical hurdle will be able to send these vehicles around completely empty in traffic and I think I'm gonna wait everyday wait for the news that vamo has just done this so you know the interesting you mentioned gutsy I mean let me ask some maybe unanswerable question may be edgy questions but in terms of how much risk is required some guts in terms of leadership style it would be good to contrast approaches and I don't think anyone knows what's right but if we compare Tesla and way mo for example Elon Musk and the way mo team the there's slight differences in approach so on the Elon side there's more I don't know what the right word to use but aggression in terms of innovation and I'm way mo side there's more sort of cautious safety focused approach to the problem what do you think it takes what leadership at which moment is right which approach is right look I'm I don't sit in either of those teams so I'm unable to even verify like somebody says correct right in the end of the day every innovator in in that space will face a fundamental dilemma and I would say you could put aerospace Titans into the same bucket yes which is you have to balance public safety with your drive to innovate and this country in particular in states has a plus your history of doing this very successfully yet travel is what a hundred times are safe per mile than ground travel and then cars and there's a reason for it because people have found ways to be very methodological about ensuring public safety while still being able to make progress on important aspects for example like yell and noise and fuel consumption so I think that those practices are pruned and they actually work we live in a world safer than ever before and yes they will always be the provision that something was wrong there's always the possibility that someone makes a mistake or there's an unexpected failure we can't never guarantee to 100 percent absolute safety other than just not doing it but I think I'm very proud of the history of of United States I mean we've we've dealt with much more dangerous technology like nuclear energy and kept that safe too we have nuclear weapons and we keep those safe so so we have methods and procedures that really balance these two things very very successfully you've mentioned a lot of great autonomous vehicle companies that are taking sort of the level 4 level file they jump in full autonomy or the safety driver and take that kind of approach and also through simulation and so on there's also the approach that Tesla autopilot is doing which is kind of incrementally taking a level 2 vehicle and using machine learning and learning from the driving of human beings and trying to creep up trying to incremental improve the system until it's able to achieve level 4 autonomy so perfect autonomy in certain kind of geographical regions what are your thoughts on these contrasting approaches when suppose of all I I'm a very proud Tesla and I literally used the autopilot every day and it literally has kept me safe is a beautiful technology specifically for highway driving when I'm slightly tired because then it turns me into a much safer driver and that I'm a hundred percent confident it's the case and tells us the right approach I think that the biggest change I've seen since I went away one team is is this thing called deep learning deep learning was was not a hot topic when I when I started way more or Google suffering cars it was there in fact we saw the Google brain at the same time in Google X so I invested in deep learning but people didn't talk about it wasn't a hot topic and nowadays there's a shift of emphasis from a more geometric perspective where you use geometric sensors they give you a full 3d view when you do a geometric reasoning about all of this box over here might be a car towards a more human like oh let's just learn about it this looks like the thing I've seen 10,000 times before so maybe it's the same thing machine learning perspective and that has really put I think all these approaches on steroids at Udacity we teach a course in self-driving cars we can in fact I think we'd be if credit is over 20,000 or so people on self-driving car skills so every every self-driving car team in the world now uses our engineers and in this course the very first homework assignment is to do Lane finding on images and lane finding images for layman what this means is you you put a camera into your car or you open your eyes and even know where the lane is right so so you can stay inside the lane with your car humans can do this super easily you just look and you know where the line is just intuitively for machines for long term of a super heart because people would write these kind of crazy rules if there's like vineland marcus and he's for fight really means this is not quite wide enough so let's all it's not right or maybe the Sun is trying so when the Sun shines and this is right and this is a straight line I missed quite a straight line because the ball is curved and and do we know that there's really six feet between lane markings or not or 12 feet whatever it is and now the very students are doing they would take machine learning so instead of like writing these crazy rules for the lane marker is they say let's take an hour driving and label it and tell the vehicle this is actually the lane by hand and then these are examples and have the Machine find its own rules but for lane markings are and within 24 hours now every student there's never done any programming for in this space can write a perfect Lane finder as good as the best commercial line and that's completely amazing to me we've seen progress using machine learning that completely Dwarfs anything that I saw ten years ago yeah and just as a side note the self-driving car nanodegree the fact that you launch that many years ago now maybe four years ago three years ago three years ago is incredible that it that's a great example of system level thinking sort of just taking an entire course I teach each other solve entire problem I definitely recommend people it's been super popular and it's become actually incredibly high quality we build it with Mercedes and and and various other companies in that space and we find that engineers from Tesla and vamo are taking it today the insight was that two things one is existing universities will be very slow to move because the departmental ice and there's no department for self-driving cars so between Mickey and EE and computer science getting these folks together into one room is really really hard and every professor listening he ever know that probably agree to that and secondly even if if all the great universities just did this which none so far has develop a curriculum in this field it is just a few thousand students they can partake because all the great universities are super selective so how about people in India how about people in China or in the Middle East or Indonesia or Africa right should those be excluded from the skill of building self-driving cars are there any dumber than we are any less privileged and the answer is we should just give everybody the skill to build a self-driving car because if we do this then we have like a thousand self-driving car startups and if 10 percent succeed that's like a hundred that means hundred countries now we have self-driving cars and be safer it's kind of interesting to imagine impossible to qualify but the number the you know over a period of several decades the impact that has like a single course like a ripple effect of society if you just recently thought the Android and who was creator of cosmos show it's interesting to think about how many scientists that show launched yes and so it's really in terms of impact I can't imagine a better course than the self-driving car course that's you know the there's other more specific disciplines like deep learning and so on that Udacity is also teaching but self-driving cars it's really really interesting course yeah and it came at the right moment it came at a time when there were a bunch of aqua huggers aqua hire as a acquisition of a company not for its technology or its products or business but for its people so aqua hire means maybe the company of 70 people they have no product yet but they're super smart people and he pays certain amount of money so I took back the highest like GM Cruise and uber and and others and did the math and said hey how many people are there and how much money was paid and as a lower bound is tomato value of an self-driving car engineer in these acquisitions to be at least 10 million dollars right so think about this you you get just have a skill and you team up and build a company and you're worth now is 10 million dollars I mean it's kind of cool I mean but what other thing could you do in life to be worth 10 million dollars within a year yeah amazing but to come back for a moment on to deep learning and its application in autonomous vehicles you know what are your thoughts on Elon Musk's statement provocative statement perhaps that lighter is a crutch so this geometric way of thinking about the world maybe holding us back if what we should instead be doing in this robotics but in this particular space of autonomous vehicles is using camera as a primary sensor and using computer vision or machine learning is the primary way to look up to Commons I think first of all we all know that people can drive cars without light us in their hands because we only have eyes and we most you just use eyes for driving maybe we use some other perception about our bodies accelerations occasionally our years certainly not our noses so that the existence proof is there that eyes must be sufficient in fact we could even drive a car someone put a camera out and then give us the camera image with known agency you would be able to drive a car and that way it the same way so cameras sufficient secondly I really love the idea that in in the Western world we have many many different people trying different hypotheses it's almost like an anthill like if another Idol tries to forage for food but you can sit there as two ands and agree what the perfect path is and then every single ant marches for the most like the location of food is or you can even just spread out and I promise you the spread out solution will be better because if the discussing philosophical intellectual ends get it wrong and they're all moving the wrong direction they're gonna waste a day and then you're gonna discuss again for another week whereas if all these ants go in a random direction someone's gonna succeed and you're gonna come back and claim victory and get the Nobel Prize about everything antipholus and then they'll march in the same direction and that's great about society that's great about the Western society if you're not plant-based you're not central base we don't have a Soviet Union style central government that tells us where to forge we just Forge we start and seek or you get investor money and go out and try it out and who knows is gonna win I like it in your when you look at the long term vision of autonomous vehicles do you see machine learning as fundamentally being able to solve most of the problems so learning from experience I'd say we should be very clear about what machine learning is and is not and I think there's a lot of confusion for this today is a technology that can go through large databases of repetitive patterns and find those patterns so in example we did a study at stand for two years ago where we applied machine learning to detecting skin cancer and images and we harvested or built a data set of 129,000 skin photo shots that were all had been biopsied for what the actual situation was and those included melanomas and carcinomas also included rashes and other skin conditions lesions and then we had a network find those patterns and it was by and large able to then detect skin cancer with an iPhone as accurately as the best board-certified Stanford level dermatologist we proved that now not this thing was great in this one thing I'm finding skin cancer but it couldn't drive a car so so the difference to human intelligence as we do all these many many things and we can often learn from a very small data set of experiences but as machines still need very large data sets and things should be very repetitive no that's still super impactful because almost everything we do is repetitive so that's gonna we transform human labor but it's not this almighty general intelligence we're really far away from a system that will exhibit general intelligence to that end I actually commiserate the naming a little bit because artificial intelligence if you believe Hollywood is immediately mixed into the idea of human suppression and and machine superiority I don't think that we don't see this in my lifetime I don't think human suppression is a good idea I don't see it coming I don't see the technology being there what I see instead is a very pointed focused pattern recognition technology that's able to extract patterns relation large data sets and in doing so it can be super impactful and super impactful let's take the impact of artificial terrorism on human work we all know that it takes something like 10,000 hours to become an expert if you're gonna be a doctor or lawyer or even a really good driver it takes a certain amount of time to become experts machines now are able and have been shown to observe people become experts in observe experts and then extract those rules from experts in some interesting way they could go from law to sales to driving cars to diagnosing cancer and then giving that capability to people who are completely new in their job we now can and that's that's been done has been done commercially in many many instances that means we can use machine learning to make people an expert on the very first day of their work like think about the impact if if your doctor is still in the first 10,000 hours you have a doctor who's not quite an expert yet who would not want the doctor who is the world's best expert and now we can leverage machines to really eradicate the error and decision making error and lack of expertise for human doctors they could save your life if we can link on that for a little bit in which way do you hope machines in the medical in the medical field could help assist doctors you mentioned this sort of accelerating the learning curve or people if they start a job or in the first 10,000 hours can be assisted by a machine how do you how do you envision that assistance looking so we built this this app for an iPhone that can detect and classify and diagnose skin cancer and we proved two years ago there is as pretty much as good or better than the best human doctor so let me give his story so there's a friend of mine is calling Ben Ben is a very famous venture capitalist he goes to his doctor and the doctor looks at a mall and and says hey that mole is probably harmless and for some very funny reason he pulls out that phone with our app he's a collaborator in our study and the app says no no no this is a melanoma and and for background melanomas are skin cancers the most common cancer in this country melanomas can go from from stage zero to Stage four within less than a year stage zero means you can basically cut it all yourself with better kitchen knife and be safe and Stage four means your chances of leading from five more years in less than 20% so it's a very serious serious serious condition so this doctor who took out the iPhone looked at the iPhone was a little bit puzzled Samina but just to be safe let's cut it out and biopsy it that's that the technical term for let's get an in-depth diagnostics that is more than just looking at it and it came back as cancerous as a melanoma and it was then removed and my friend Ben I was hiking with him and we are talking about a I in and said I turn into this vote on skin cancer he's so funny my doctor just had an iPhone that found my cancer so I was a completely in tree didn't even know about so here's a person I mean this is a real human life right now who doesn't know somebody who's been affected by cancer cancer is cause of death number two cancer is this kind of disease that that is mean in in the following way most cancers can actually be cured relatively easily if we catch them early and and the reason why we don't tend to catch them early is because they have no symptoms like your very first symptom of a gallbladder cancer or a pancreatic cancer might be a headache and when you finally go to your doctor because of these headaches or your back pain and you're being imaged it's usually stage four plus and that's the time when the your curing chances might be dropped to a single-digit percentage so if we could leverage the eye to inspect your body on a regular basis without even a doctor in the room maybe when you take a shower over have you I know this sounds creepy but then we might be able to save millions and millions of lives you've mentioned there's a concern that people have about near-term impacts of AI in terms of job loss so you've mentioned being able to assist doctors being able to assist people in their jobs do you have a worry of people losing their jobs or the economy being affected by the improvements in AI anybody concern about job losses please come to get a sitcom we teach contemporary tech skills and we have a kind of implicit job promise we often when when we measure we spend way over 50% of our graders in new jobs they're very satisfied about it and it costs almost nothing cost like a thousand five hundred max or something like that and so there's a cool new program they agree with the US government guaranteeing that you will help us give scholarships that educate people and in this kind of situation you're working with the US government on the idea of basically building the American dream so Udacity has just dedicated one hundred thousand scholarships for citizens of America for various levels of courses that eventually will get you a job and those courses all somewhat relate with the tech sector because the tech sector is kind of the hottest sector right now and they range from in two level digital marketing to very advanced self driving car engineering and we're doing this with the white house because II think is bipartisan it's an issue that is that if you want to really make America great being able to be a part of the solution and live the American dream requires us to be proactive about our education and our skill set it's just the way it is today and it's always been this way I've always had this American dream to send our kids to college and now the American dream has to be to send ourselves to college into this very vey vey efficiently and very way we can squeeze in and evenings and things to online or at all ages all ages so our our learners go from age 11 to age 80 I just travel Germany and and the guy in train compartment next to me was my students wow that's amazing I don't think about impact we've become the educator of choice for now I believe officially six countries or five countries is most in the Middle East like Saudi Arabia and in Egypt in Egypt we just had a cohort graduate um where we had 1100 high school students that went through programming skills proficient at the level of computer science undergrad and we had a 95% graduation rate even though everything's online it's kind of tough but we kind of trying to figure out how to make this effective the vision is the vision is very very simple the vision is education ought to be a basic human right it cannot be locked up behind ivory tower walls only for the rich people for the parents who might be bright themself into the system and only for young people and only for people from the right demographics literate geography and possibly even the right race it has to be opened up to everybody if we if we are truthful to the human mission via truthful to our values we gonna open up education to everybody in the world so Udacity is pledge of a hundred thousand scholarships I think it's the biggest pleasure of scholarships ever in terms of the numbers and we've working as I said for the White House and with very accomplished CEOs like Tim Cook from Apple and others to really bring education to everywhere in the world not to ask if you pick the favorite of your children but at this podium Jasper no okay good in this particular moment what nanodegree what said of course is are you most excited about Udacity or is that too impossible to pick I've been super excited about something we haven't launched yet in the building which is when we talk to our partner companies we have known a very strong footing in the enterprise world and also to our students we've kind of always focused on these hard skills like the programming skills or math skills or building skills or design skills and a very common task is soft skills like how do you behave in your work how you develop empathy how do you work in a team what are the very basics of management how do you do time management how do you advance your career in the context of a broader community and that's something that we haven't done very valid audacity and I would say most universities doing very poorly as well because we're so obsessed with individual test scores and and so little pace a little attention to teamwork in education so that's something I see us moving into as a company because I'm excited about this and I think look we can teach people tech skills and they're going to be great but if you teach people empathy that's gonna have the same impact may be harder than self-driving cars but I don't think so I think the rules are really simple you just have to you have to you have to want to engage it's it's via we literally went in in school and in k-12 we teach kids like get the highest math score and if you are a rational human being you might evolved from this education say having the best math score and the best English scores make me the best leader and it turns out not to be the case it's actually really wrong because making first of all in terms of math scores I think is perfectly fine to hire somebody with great math skills you'd have to do yourself you can't hire some of the good empathy for you that's much harder but it can always hire some with great math skills but we live in in affluent world where we constantly deal with other people and it's a beauty it's not a nuisance it's a beauty so if we somehow develop that muscle that we can do that well and empower others in the workplace I think you're gonna be super successful and I know many fellow roboticists and computer scientists that I will assist take this course not to be named many many years ago 1903 the Wright brothers flew in Kitty Hawk for the first time and you've watched a company of the same name Kitty Hawk with the dream of building flying cars evey tall's so at the big picture what are the big challenges of making this thing that actually inspired generations of people about what the future looks like what does it take one of the biggest challenges so so flying cars has always been a dream of boy every girl wants to fly let's be honest yes and let's go back in on history of you're dreaming of flying I think my answer my single most remembered childhood dream has been a dream where I was sitting on a pillow and I could fly I was like five years old I remember like maybe three dreams are much higher but that's the one that we remember most vividly and then Peter Thiel famously said they promise us flying cars and they give us 140 characters pointing as Twitter at the time limiting message size 240 characters so if you're coming back now to really go for this super impactful stuff like flying cars and to be precise they're not really cars they don't have wheels they actually much closer to a helicopter than anything else they take off vertically in the fly horizontally but they have important differences one difference is that they are much quieter if you just released a vehicle called project heavy side they can fly over you as low as a helicopter and you basically can't hear it's like 38 decibels it's like like that if you were inside a library you might be able to hear it but anywhere outdoors your ambient noise is higher secondly they're they're much more affordable they're much more affordable than helicopters and the reason is helicopters are expensive for many reasons there's lots of single point of figures in a helicopter there's a bolt between the blades that's cause Jesus fault and the reason why it's called Jesus board is it that if this boat breaks you will die there is no second solution in helicopter flight whereas we have these distributed mechanism when you go from gasoline to electric you can now have many many many small motors as opposed to one big motor and that means if you lose one of those motors not a big deal heavy side if it loses a motor has eight of those you lose one of those eight motors so it's seven left you can take off just like before and land just like before we are now also moving into a technology it doesn't require a commercial pilot because in some level flight is actually easier than than ground transportation like in self-driving cars oh the world is full of like children and bicycles and other cars and mailboxes and curbs and shrubs and what-have-you all these things you have to avoid when you go above buildings and tree lines there's nothing there I mean you can do the test right now look outside and count the number of things you see flying I'd be shocked if you could see more than two things it's probably just zero in the Bay Area the most I've ever seen was six and maybe it's 15 or 20 but not ten thousand so the sky is very ample and very empty and very free so the vision is can be built a socially acceptable mass transit transit solution for daily transportation that is affordable and we have an existence proof Heaviside can fly a hundred miles in range with still 30% electric reserves it can fly up to like a hundred and eighty miles an hour we know that that solution that scale would make your ground transportation 10 times as fast as a car based on use census data which means we would take your 300 hours of day of yearly commute down to 30 hours and giving 270 hours back who wouldn't want I mean who doesn't hate traffic like I hate give me the person that doesn't hate traffic I hate traffic every day every time I want traffic I hate it and and if we could free the world from traffic we have technology we can free the world from traffic yeah we have the technology it's there we have an existence proof test it's not a technological problem anymore do you think there is a future where tens of thousands maybe hundreds of thousands of both delivery drones and flying cars of this kind a VTOL fill the sky i absolutely believe this and there's obviously the societal acceptance is a major question and of course safety as I believe in and safety of you exceed ground transportation safety as has happened for aviation already commercial aviation and in terms of acceptance I think one of the key things is noise that's why we are focusing relentlessly on noise and we bid perhaps the crisis electric VTOL vehicle ever built the nice thing about the sky is three-dimensional so so any mathematician will immediately recognize the difference between 1d of a lack of regular highway to three of a sky but to make it clear for the layman say you want to make a hundred vertical lanes of highway 101 in San Francisco because you believe building a health and vertical lanes is the right solution imagine how much it would cost to stack a hundred vertical lanes physically onto 101 there would be prohibitive that would be consuming the world's GDP for an entire year just for one highway it's amazing expensive again in the sky it would just be a recompilation of a piece of software because all these lanes are virtual that means any vehicle that is in conflict with another vehicle would just go to different altitudes and then the conflict is gone and if you don't believe this that's exactly how how commercial aviation works when you fly from New York to San Francisco another plane flies from Sanford to New York there are different altitudes so they don't hit each other it's a soft problem for the jet space and it will be a soft problem for the urban space there's companies like Google Bing and Amazon working on very innovative solutions how do a space management use exactly the same principles as we use today throughout today's dance there's nothing hard about this do you envision autonomy being a key part of it so that that the flying vehicles are either semi autonomous or fully autonomous a hundred percent autonomous you don't want idiots like me flying in the sky I promise you and if you have ten thousand what's the movie The Fifth Element to get a thief over to happen if it's not autonomous in a centralized that's a really interesting idea of a centralized sort of management system for lanes and so on so actually just being able to have similar as we have in the current commercial aviation but scale it up to which much more vehicles a really interesting optimization problem it is vey mathematically very very straightforward like the gap we leave between jets is Gargantuas and part of the reason is there isn't that many gents so this feels like a good solution today when you get vectored by a traffic control someone talks to you right so any ATC controller might have up to maybe 20 planes on the same frequency and then talk to you have to talk back and it feels right because there isn't more than 20 pins around any hours so you can talk to everybody but if there's 20,000 things around he can't talk to everybody anymore so we have to do something that's called digital like text messaging like we do have solutions like we have about four or five billion smartphones in the world now all right and they all connected and some of you solved the scale problem for smart phones we know where they all are they can talk to somebody and they're very reliable they amazingly reliable we could use the same system the same scale for air traffic control so instead of me as a pilot talking to a human being and in the middle of the conversation receiving a new frequency like how ancient is that we could digitize the stuff and and digitally transmitted the right flight coordinates and that solution will automatic a laugh to 10,000 vehicles we talked about empathy a little bit do you think we'll one day build an air a eye system that a human being can love and that loves that human back like in the movie her look I'm I'm a pragmatist for me a is a is a tool it's like a shovel and the ethics of using the shovel I always with us the people and and there has to be this way in terms of emotions I would hate to come into my kitchen and see that my refrigerator spoiled all my food then have it explained to me that it fell in love with a dishwasher and I wasn't as nice the dishwasher so as a result it neglected me there would just be a bad experience and it would be a bad product I would probably not recommend this for frigerator to my friends and that's where I draw the line I think to me technology has to be reliable it has to be predictable I want my car to work I don't want to fall in love with my car I just wanted to work I wanted to compliment me not to replace me I have very unique human properties and I want the machines to make me turn me into a superhuman like I'm already a superhuman today thanks to the machines that surround me and give you examples I can run across the Atlantic at near the speed of sound at 36,000 feet today that's kind of amazing I can my voice now carries me all the way to Australia using a smartphone today and it's not not the speed of sound which would take hours it's the speed of light my voice travels at the speed of light how cool is that that makes me superhuman I would even argue my my flushing toilet makes me superhuman just think of the time before flushing toilets and and maybe you have a veiled person in your family that you can ask about this or take a trip to rural India until experience it it's it's it makes me superhuman so to me what technology does it complements me it makes me stronger therefore words like love and compassion have very little a very little interest in this for machines I have interested men people you don't think first of all beautifully put beautifully argued but do you think love has use in our tools compassion I think laughs is a beautiful human concept and if you think what love really is love is a means to convey safety to convey trust I think Trust has a huge need in technology as well much as people we want to trust our technology the same way we - or in similar way we trust people in in human interaction standards have emerged and and feelings emotions have emerged may be genetically may be very largely that I able to convey sense of trust sense of safety sense of passion of love of dedication that that makes the human fabric and I'm a big slacker for love I want to be laughter I want to be trusted ever me admired all these wonderful things and because all of us who we have this beautiful system I wouldn't just blindly copy this to the machines here's why when you look at say transportation you could have observed that up to the end of the 19th century so transportation used any number of legs from one leg to two legs to a thousand legs and you could have concluded that is the right way to move about the environment we've been made exceptional birds who is flapping wings in fact there are many people in aviation that flap wings to the arms and jump from Cliffs most of them didn't survive then then the interesting thing is that the technology solutions are very different like in technologies really easily by the wheel in biology is super hard ability there's very few perpetually rotating things in in in biology and everyone sells things in in engineering we can build wheels and those wheels gave rise to cars similar wheels gave rides to to aviation like there's no thing there flies there wouldn't have something rotates like a jet engine or helicopter blades so the solutions have used very different physical laws in nature and that's great so for me to be too much focused on oh this is how nature does it this is replicated if we really believed that the solution to the irish revolution was a humanoid robot it would still be waiting today again beautifully put you said that you don't take yourself too seriously you just say that i mean you want you to say that maybe you don't take me seriously I'm not yeah you're right I don't wanna I just made that up but you know you have a humor and a lightness about life that I think is it is beautiful and inspiring to a lot of people where does that come from the smile the humor the lightness amidst all the chaos of the hard work that you and where does that come from I just love my life I love I love the people around me I love I'm just so glad to be alive like I'm about 52 how to believe people say 5251 so now feel better but in in in in in looking around the world looking just go back 200 300 years like Humanity is what 300 thousand years old but for the first 300,000 years - the last 100 our life expectancy would have been plus or minus 30 years roughly give or take so I would be long dead now like that makes me just enjoy every single day of my life because I don't deserve this like why am i porn today when so many of my interest has died of horrible deaths like famines massive wars that ravaged Europe for the last 1000 years mostly disappeared after World War 2 when the Americans and the Allies did something amazing to my country that didn't deserve it my country of Germany it was so amazing and then when you when you're live and feel this every day then it is so amazing what what we can accomplish what we can do we live in the world that is so incredibly vastly changing every day almost everything that we cherish from your smartphone to your flushing toilet to all these basic inventions your new clothes you're wearing your watch your plain penicillin and no anesthesia for surgery penicillin have been invented in the last 150 years so in the last 150 years something magical happened and I would trace it back to Gutenberg and the printing press that has been able to disseminate information more efficiently than before that all of a sudden they're able to invent agriculture and nitrogen fertilization that made agriculture so much more potent that we didn't if you focus of hams anymore and you could start reading and writing and we could become all these wonderful things we are today for me LM pilot - massage therapist - software engineer this is amazing like living in that time is such a blessing we should sometimes really think about this Steven Pinker who as a very famous author and philosopher whom I really adore wrote a great book called enlightenment now and that's maybe the one book I would recommend and he asked the question if there was only a single article written in the 20th century don't leave an article but would it be what's the most important innovation the most important thing that and he would say this article would credit a guy named Carl Bosch and I challenge anybody have you ever heard of the name Carl Bosch I hadn't okay there's a there's a Bosch corporation in Germany but it's not associated with Carl Bosch so I looked it up kibosh invented nitrogen fertilization and in doing so together with an older invention of irrigation was able to increase the yield Ferrari cultural land by a factor of twenty six so a two thousand five hundred percent increase in infertility of land and that so Steve Pinker argues saved over two billion lives today two billion people who would be dead if this man hadn't done what he had done okay think about that impact and what that means to society that's that's the way I look at the world I mean it's so amazing to be a life and be part of this and I'm so glad I lived after Cobb abortion not before I don't think there's a better way to end it Sebastian it's an honor to talk to you to have had the chance to learn from you thank you so much for talking so commingling so your pleasure thank you for listening to this conversation with Sebastian Thrun and thank you to our presenting sponsor cash app download it use coal xpod cast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on YouTube get five stars in a podcast supported on patreon or connect with me on Twitter and now let me leave you with some words of wisdom from Sebastian Thrun it's important to celebrate your failures as much as your successes if you celebrate your failures really well if you say wow I failed I tried I was wrong but I learned something then you realize you have no fear when your fear goes away you can move the world thank you for listening and hope to see you next time you