#252 – Elon Musk: SpaceX, Mars, Tesla Autopilot, Self-Driving, Robotics, and AI

[0] The following is a conversation with Elon Musk, his third time on this, the Lex Friedman podcast.

[1] And now, a quick few second mention of each sponsor.

[2] Check them out in the description.

[3] It's the best way to support this podcast.

[4] First is Athletic Greens, the all -in -one nutrition drink I drink twice a day.

[5] Second is butcher box, high -quality meat that makes up most of my diet.

[6] Third is Inside Tracker, a service I use to track my biological data.

[7] Fourth is Roka.

[8] My favorite sunglasses and prescription glasses.

[9] And fifth is eight sleep, a self -cooling mattress cover I sleep on.

[10] So the choice is nutrition, food, health, style, or sleep.

[11] Choose wisely, my friends.

[12] And now, onto the full ad reads.

[13] As always, no ads in the middle.

[14] I try to make this interesting, but if you skip them, please still check out the sponsors.

[15] I enjoy their stuff.

[16] Maybe you will too.

[17] This show is brought to you by Athletic Greens, and it's newly named AG1 drink, which is an all -in -one daily drink to support better health and peak performance.

[18] It replaced a multivitamin for me and went far beyond that with 75 vitamins and minerals.

[19] It's the first thing I drink every day.

[20] I drink it twice a day, in fact.

[21] I drink it after a long run.

[22] I recently did a 16 -mile run, and I can't tell you how good it felt to get back and pour myself a refreshing athletic greens and start the day.

[23] day.

[24] I ran fasted and that's probably one of my favorite things to do.

[25] Run for a long period of time on an empty stomach thinking through the problems of the day or the problems of life in general and then get back to sort of ground to normal life by drinking athletic greens, getting in the shower and just hitting the ground running with a little bit of coffee and focus.

[26] Anyway, they'll give you a one month supply of fish oil when you sign up at Athletic Greens .com slash Lex.

[27] That's Athletic Greens .com slash Lex.

[28] This show is brought to you by Butcher Box.

[29] High quality meat that is pretty much the only thing I eat.

[30] They ship a box of meat to your home, eight to 14 pounds of it.

[31] You can pick a pre -made box or customize one, which is what I do.

[32] And that's it.

[33] It's meat of different kinds makes up a large part of my diet.

[34] I just feel good when I consume a large amount of meat.

[35] It's not an allergy thing.

[36] It's not some kind of reducing inflammation thing.

[37] I don't know what it is because I also am pretty happy eating carbs as well.

[38] I just feel better.

[39] I'm happier.

[40] I can perform better both physically and mentally when I consume a large amount of meat.

[41] Whether that's a carnivore or keto diet, I just feel great.

[42] Butcherbox is just high -quality meat that I can rely on.

[43] There's all kinds of cuts there, but ground beef is the basics and the thing I love the most.

[44] For a limited time, Butcherbox is offering new members a great deal for the new year.

[45] Sign up at butcherbox .com slash Lex, and you'll receive the ultimate New Year's bundle in your first box.

[46] This deal includes ground beef, chicken thighs, and more.

[47] That's more than seven pounds of meat added to your first box for free.

[48] Get this New Year's bundle before it's gone by going to Butcher's.

[49] What's Your Box .com slash Lex.

[50] This show is also brought to you by Inside Tracker, a service I use to track biological data.

[51] They have a bunch of plans, most of which include a blood test that gives you a lot of information that you can then make decisions based on.

[52] They have algorithms.

[53] I love the world of the algorithms that analyze your blood data, DNA data, and fitness tracker data to provide you with a clear picture of what's going on inside you and to offer you science -backed, recommendations for positive diet and lifestyle changes.

[54] Andrew Huberman, the great, the powerful Andrew Huberman, talks a lot about it.

[55] David Sinclair, he, by the way, was just on his podcast that you should check out.

[56] Also talks a lot about it in my conversation with him and in his conversation with others.

[57] I love this idea.

[58] It feels like the future.

[59] You should definitely be making lifestyle and health decision based on actual data connected to you, not just the general population.

[60] You are a special, unique, biological fingerprint that requires unique treatment, unique lifestyle decisions.

[61] For a limited time, you can get 25 % off the entire InsideTracker store if you go to insidetrakker .com slash Lex.

[62] That's insidetracker .com slash Lex.

[63] This show is brought to you by Roka, the maker of glasses and sunglasses that I love wearing for their design feel and innovation on materials, optics, and grip.

[64] Roka was started by two All -American Swimmers from Stanford and was born out of an obsession with performance.

[65] Like I said, I love the word obsession and performance.

[66] And I got a chance to meet and hang out a bunch with one of those founders.

[67] Rob, an incredible human being here in Austin.

[68] They have a facility here in Austin.

[69] It's just cool to see people at the top of their game in terms of both design and manufacture and all that kind of stuff.

[70] These glasses, first of all, look badass, look amazing, but they're also designed to be active in.

[71] Extremely lightweight.

[72] The grip is comfortable but strong.

[73] And the style, I said badass, but it's badass in a classy way.

[74] It holds up in all conditions when I'm wearing a suit or wearing running gear, including on long runs in 100 degree Austin weather or in freezing Boston weather, both work.

[75] Check them out for both prescription glasses and sunglasses at roca .com and enter code Lex to save 20 % off your first order.

[76] That's rocca .com and enter code Lex.

[77] This episode is also brought to you by 8Sleep and it's Pod Pro mattress.

[78] It controls temperature with an app.

[79] It's packed with sensors.

[80] It can cool down to as low as 65 degrees on each side of the bed separately.

[81] Given that I just got out of said bed, I could tell you, because it's short -term memory that the thing feels incredible.

[82] There's very few things I enjoy in life.

[83] As much as a power nap or full night's sleep on a cooled bed with a warm blanket, my mind empty of thoughts, having fought the battles of the day, and just resting, escaping it all in a little bit of a dream world.

[84] Alice in Wonderland, but more like Lex in Wonderland.

[85] They have a podpro cover, so you can just add that to your mattress without having to buy theirs.

[86] But their mattress is nice too.

[87] They can track a bunch of metrics like heart rate variability, but cooling alone is worth the money.

[88] Go to Aesleep .com slash Lex to get special savings.

[89] That's Aesleep .com slash Lex, and I will meet you there, my friend, in the dream world.

[90] This is the Lex Friedman podcast, and here is my conversation with Elon Musk.

[91] Yeah, make yourself comfortable.

[92] Oh, wow, okay.

[93] You don't do the headphones thing?

[94] No. Okay.

[95] I mean, how close do I need to get up the same thing?

[96] The closer you are, the sexy you sound.

[97] Hey, babe.

[98] Can't get enough of you all that, baby.

[99] I'm going to clip that out any time somebody messages me about your body.

[100] If you want my body and you think I'm sexy.

[101] Come right out and tell me so.

[102] So, do, do, do, do.

[103] So good.

[104] Okay, serious mode, activate.

[105] All right.

[106] Serious mode.

[107] Come on your Russian, you can be serious.

[108] Everyone's serious all the time in Russia.

[109] Yeah.

[110] We'll get there.

[111] We'll get there.

[112] It's gotten soft.

[113] Allow me to say that the SpaceX launch of human beings to orbit on May 3rd, 30th, 2020, was seen by many as the first step in a new era of human space exploration.

[114] These human spaceflight missions were a beacon of hope, to me and to millions, over the past two years, as our world has been going through one of the most difficult periods in recent human history.

[115] We saw, we see the rise of division, fear, cynicism, and the loss of common humanity, right when it is needed most.

[116] So first, Elon, let me say thank you for giving the world hope and reason to be excited about the future oh it's kind of easy to say i do want to do that humanity has uh obviously a lot of issues and and uh you know people at times do do bad things but you know despite all that um you know i i love humanity and i think we should uh make sure we do everything we can to have a good future and an exciting future and one where that maximizes the happiness of the people let me ask about uh Who Dragon Demo 2?

[117] So that first flight with humans on board, how did you feel leading up to that launch?

[118] Were you scared?

[119] Were you excited?

[120] I was going through your mind.

[121] So much was at stake.

[122] Yeah, no, that was extremely stressful, no question.

[123] We obviously could not let them down in any way.

[124] So extremely stressful, I'd say, to say the least.

[125] I was confident that at the time that we launched, that no one could think of anything at all to do that would improve the probability of success and we racked our brains to think of any possible way to improve the probability of success and we could not think of anything more and nor could NASA and so that that's just the best that we could do so then we went ahead and launched now I'm not a religious person but I nonetheless got on my knees and prayed for that mission.

[126] Were you able to sleep?

[127] No. How did it feel when it was a success?

[128] First, when the launch was a success and when they returned back home or back to Earth?

[129] It was a great relief.

[130] Yeah.

[131] For high -stress situations, I find it's not so much elation as relief.

[132] and you know I think once as we got more comfortable and proved out the systems because you know we really you got to make sure everything works I was it was definitely a lot more enjoyable with the subsequent astronaut missions and I thought the the inspiration mission was was actually very inspiring inspiration for mission I'd encourage people to watch the inspiration documentary on Netflix it's actually really good and it really isn't I was actually inspired by that and I so that one I felt I was kind of able to enjoy the actual mission not just be super stressed all the time so for people that somehow don't know it's the all civilian first time all civilian out to space out to orbit yeah it was I think the highest orbit that in like 30 or 40 years or something.

[133] The only one that was higher was the one shuttle, sorry, a Hubble servicing mission.

[134] And then before that it would have been Apollo in 72.

[135] It's pretty wild.

[136] So it's cool.

[137] It's good.

[138] You know, I think as a species, like we want to be, you know, continuing to do better and reach higher ground.

[139] And like, I think it would be tragic, extremely tragic, if Apollo was the high water mark for humanity, you know, and that's as far as we ever got.

[140] And it's concerning that here we are 49 years after the last mission to the moon.

[141] And so almost half a century, and we've not been back.

[142] And that's worrying.

[143] It's like, does that mean we've peaked as a civilization or what?

[144] So, like, I think we've got to get back to the moon and build a base there, you know, a science base.

[145] I think we could learn a lot about the nature of the universe if we have a proper science base on the moon.

[146] You know, like we have a science base in Antarctica and, you know, many other parts of the world.

[147] And so that's, I think, the next big thing.

[148] We've got to have, like, a serious, like, moon base and then get people to Mars and, you know, get out there and, be a space -faring civilization.

[149] I'll ask you about some of those details, but since you're so busy with the hard engineering challenges of everything that's involved, are you still able to marvel at the magic of it all, of space travel of every time the rocket goes up, especially when it's a crude mission?

[150] Are you just so overwhelmed with all the challenges that you have to solve?

[151] And actually, sort of, to add to that, the reason I wanted to ask this question of May 30th, It's been some time so you can look back and think about the impact already.

[152] At the time, it was an engineering problem maybe.

[153] Now it's becoming a historic moment.

[154] Like, it's a moment that, how many moments would be remembered about the 21st century?

[155] To me, that or something like that, maybe inspiration for one of those would be remembered as the early steps of a new age of space exploration.

[156] Yeah, I mean, during the launches itself, so I mean, I think maybe some people will know but a lot of people don't know.

[157] He's like, I'm actually the chief engineer of SpaceX, so I've signed off on pretty much all the design decisions.

[158] And, you know, so if there's something that goes wrong with that vehicle, it's fundamentally my fault, you know, so.

[159] So I'm really just thinking about all the things that, like, so when I see the rocket, I see all the things that could go wrong and the things that could be better, and the same with the Dragon spacecraft.

[160] It's like other people see, oh, this is a spacecraft or a rocket, and this looks really cool.

[161] I'm like, I've like a readout of like, these are the risks, these are the problems, that's what I see.

[162] Like, so it's not what other people see when they see the product, you know.

[163] So let me ask you then to analyze Starship in that same way.

[164] I know you have, you'll talk about, but in more detail about Starship in the near future, perhaps.

[165] Yeah, we'll talk about it now if you want.

[166] But just in that same way, like you said you see, when you see a rocket, you see a sort of a list of risks.

[167] In that same way, you said that Starship is a really hard problem.

[168] So there's many ways I can ask this, but if you magically could solve one problem perfectly, one engineering problem perfectly, which one would it be?

[169] On Starship?

[170] Sorry, on Starship.

[171] So is it maybe related to the efficiency, the engine, the weight of the different components, the complexity of various things, maybe the controls of the crazy thing as to do to land?

[172] No, actually, by far the biggest thing absorbing my time is engine production.

[173] Not the design of the engine, but I've often said prototypes are easy, production is hard.

[174] So we have the most advanced rocket engine that's ever been designed.

[175] Because I say currently the best rocket engine ever is probably the RD 180 or RD 170, the Dorot Russian engine basically.

[176] And still, I think an engine should only count if it's gotten something to orbit.

[177] So our engine has not gotten anything to orbit yet.

[178] but it is it's the first engine that's actually better than the Russian RD engines which were amazing design so you're talking about Raptor engine what makes it amazing what are the different aspects of it that make it like what are you the most excited about if the whole thing works in terms of efficiency all those kinds of things well it's the Ractor is a full flow staged combustion engine and it's operating at a very high chamber pressure.

[179] One of the key figures of merit perhaps the key figure of merit is what is the chamber pressure at which the rocket engine can operate.

[180] That's the combustion chamber pressure.

[181] So a rafter is designed to operate at 300 bar, possibly maybe higher.

[182] That's 300 atmospheres.

[183] So So the record right now for operational engine is the RD engine that I mentioned, the Russian RD, which is, I believe, around 267 bar.

[184] And the difficulty of the chamber pressure increases on a non -linear basis.

[185] So 10 % more chamber pressure is more like 50%, more difficult.

[186] But that chamber pressure is, that is what allows you to get a very, high power density for the engine, so enabling a very high thrust to weight ratio, and a very high specific impulse.

[187] So specific impulse is like a measure of the efficiency of a rocket engine.

[188] It's really the effect of exhaust velocity of the gas coming out of the engine.

[189] So with a very high chamber pressure, you can have a compact engine that nonetheless has a high expansion ratio, which is the ratio between the exit nozzle and the throat.

[190] So you see a rocket engine, it's got like a sort of like an hourglass shape.

[191] It's like a chamber and then it necks down and there's a nozzle.

[192] and the ratio of the exit diameter to the throat expansion ratio.

[193] So why is it such a hard engine to manufacture at scale?

[194] It's very complex.

[195] So what does complexity mean here?

[196] There's a lot of components involved.

[197] There's a lot of components and a lot of unique materials.

[198] So we had to invent several alloys that don't exist in order to make this engine work.

[199] So it's a materials problem too.

[200] It's a materials problem and in a stage combustion, a full flow stage combustion, there are many feedback loops in the system.

[201] So basically you've got propellants and hot gas flowing simultaneously to so many different places on the engine.

[202] and they all have a recursive effect on each other.

[203] So you change one thing here, it has a recursive effect here, it changes something over there, and it's quite hard to control.

[204] Like there's a reason no one's made this before.

[205] But, and the reason we're doing a stage combustion full flow is because it has the highest, the highest, the vertical possible efficiency.

[206] So in order to make a fully reusable rocket, that's the really the holy grail of orbital rocketry.

[207] You have to have, everything's got to be the best.

[208] It's got to be the best engine, the best airframe, the best heat shield, extremely light avionics, you know very clever control mechanisms you've got to shed mass in any possible way that you can for example we are instead of putting landing legs on the booster and ship we are going to catch them with a tower to save the weight of the landing lens legs so that's like I mean we're talking about catching the largest flying object ever made with on a giant tower with with chaf -stick arms.

[209] It's like karate kid with the fly, but much bigger.

[210] I mean, pulling something like that.

[211] This probably won't work the first time.

[212] Anyway, so this is bananas.

[213] This is banana stuff.

[214] So you mentioned that you doubt, well, not you doubt, but there's days or moments when you doubt that this is even possible.

[215] It's so difficult.

[216] The possible part is, well, at this point, I think we'll get Starship to work.

[217] There's a question of timing.

[218] How long will it take us to do this?

[219] How long will it take us to actually achieve full and rapid reusability?

[220] Because it will take many launches before we're able to have full and rapid reusability.

[221] But I can't say that the physics pencils out.

[222] like we're not like at this point I'd say we're confident that like let's say I'm very confident success is in the set of all possible outcomes right it's not an all set for a while there I was not convinced that success was in the set of possible outcomes which is very important actually but so we're saying there's a chance I'm saying there's a chance exactly just not sure how long it will take but we have a very talented team they're working night and day to make it happen and like the critical thing to achieve for the revolution in space flight and for humanity to be a spacefaring civilization is to have a fully and rapidly reusable rocket, orbital rocket.

[223] There's not even been any orbital rocket that's been fully reusable ever And this has always been the holy grail of rocketry.

[224] And many smart people, very smart people, have tried to do this before and they've not succeeded.

[225] So, because it's such a hard problem.

[226] What's your source of belief in situations like this when the engineering problem is so difficult?

[227] There's a lot of experts, many of whom you admire who have failed in the past.

[228] Yes.

[229] And a lot of people, you know, a lot of experts, maybe journalists, all the kind of, you know, the public in general have a lot of doubt about whether it's possible.

[230] And you yourself know that even if it's a non -nall set, non -empty set of success, it's still unlikely or very difficult.

[231] Like, where do you go to, both personally, intellectually as an engineer as a team, like for source of success?

[232] strength needed to sort of persevere through this and to keep going with the project, take it to completion.

[233] A source of strength.

[234] I just really not how I think about things.

[235] I mean, for me, it's simply this is something that is important to get done, and we should just keep doing it or die trying, and I don't need a source of strength.

[236] So quitting is not even like...

[237] That's not in my nature.

[238] and I don't care about optimism or pessimism.

[239] Fuck that, we're going to get it done.

[240] Going to get it done.

[241] Can you then zoom back in to specific problems with Starship or any engineering problems you work on?

[242] Can you try to introspect your particular biological neural network your thinking process and describe how you think through problems, the different engineering and design problems?

[243] Is there like a systematic process?

[244] You've spoken about first principles thinking, but is there kind of process to it?

[245] Well, I like saying, like physics is law and everything else is a recommendation.

[246] Like I've met a lot of people that can break the law, but I haven't met anyone who could break physics.

[247] So first, for any kind of technology problem, you have to sort of just make sure you're not violating physics.

[248] And, you know, first principles analysis i think is something that can be applied to really any walk of life anything really it's just it's it's really just saying um you know let's let's boil something down to the most fundamental uh principles the things that we are most confident are true at a foundational level and that sets your at your set your axiomatic base and then you reason up from there and then you cross check your conclusion against the the axiomatic truth um So, you know, some basics in physics would be like, oh, you're violating conservation of energy or momentum or something like that.

[249] You know, then you're not going to work.

[250] So that's just to establish, is it possible?

[251] And another good physics tool is thinking about things in the limit.

[252] If you take a particular thing and you scale it to a very large number or to a very small number, how does things change?

[253] Well, it's like temporary, like in number of things you manufacture or something like that, and then in time?

[254] Yeah, like let's say take an example of like manufacturing, which I think is just a very underrated problem.

[255] And like I said, it's much harder to take an advanced technology product and bring it into volume manufacturing than it is to just.

[256] design it in the first place, what is magnitude?

[257] So let's say you're trying to figure out is, like, why is this part or product expensive?

[258] Is it because of something fundamentally foolish that we're doing, or is it because our volume is too low?

[259] And so then you say, okay, well, what if our volume was a million units a year?

[260] Is it still expensive?

[261] That's what I'm thinking about things in the limit.

[262] If it's still expensive at a million units a year, then volume is not the reason why your thing is expensive.

[263] There's something fundamental about the design.

[264] And then you then can focus on reducing the complexity or something like that.

[265] It's got to change the design to change the part to be something that is not fundamentally expensive.

[266] But that's a common thing in rocketry because the unit volume is relatively low.

[267] And so a common excuse would be, well, it's expensive because that unit volume is low.

[268] And if we were in like automotive or something like that or consumer electronics, then our cost would be low.

[269] I'm like, okay, so let's say, now you're making a million units a year.

[270] Is it still expensive?

[271] If the answer is yes, then economies of scale are not the issue.

[272] Do you throw into manufacturing, do you throw like supply chain, you talk about resources and materials and stuff like that, do you throw that into the calculation of trying to reason from first principles, like how we're going to make the supply chain work here?

[273] Yeah, yeah.

[274] And then the cost of materials, things like that, or is that too much?

[275] Exactly.

[276] So, like a good example, I think of thinking about things in the limit is if you take any product, any machine or whatever, like take a rocket or whatever and say if you've got, if you look at the raw materials in the rocket, so you're going to have like an aluminum, steel, titanium, ink canal.

[277] specialty alloys, copper, and you say, what are the, what's the weight of the constituent elements, of each of these elements, and what is their raw material value?

[278] And that sets the asymptotic limit for how low the cost of the vehicle can be unless you change the materials.

[279] So, and then when you do that, I call it like maybe the magic one number or something like that.

[280] So that would be like if you had the, you know, like just a pile of these raw materials here and you could wave the magic wand and rearrange the atoms into the final shape, that would be the lowest possible cost that you could make this thing for unless you change the materials.

[281] So then, and that is always a, almost always a very low number.

[282] So then what's actually causing things to be expensive is how you put the atoms into the desired shape.

[283] Yeah, I actually, if you don't mind me taking a tiny tangent, I often talk to Jim Keller, who's something that worked with you as a film.

[284] Jim was, yeah, did great work at Tesla.

[285] So I suppose he carries the flame of the same kind of thinking that you're talking about now.

[286] And I guess I see that same thing, at Tesla and SpaceX folks who work there, they kind of learn this way of thinking, and it kind of becomes obvious almost.

[287] But anyway, I had argument, not argument, he educated me about how cheap it might be to manufacture a Tesla bot.

[288] We had an argument.

[289] How can you reduce the cost of the scale of producing a robot?

[290] Because I've gotten a chance to interact quite a bit, obviously in the academic circles with humanoid robots and then Boston Dynamics and stuff like that.

[291] And they're very expensive to build.

[292] And then Jim kind of schooled me on saying, like, okay, like this kind of first principles thinking of how can we get the cost of manufacture down.

[293] I suppose you do that.

[294] You have done that kind of thinking for Tesla bot and for all kinds of complex systems that are traditionally seen as complex.

[295] And you say, okay, how can we simplify everything down?

[296] Yeah.

[297] I mean, I think if you are really good at manufacturing, you can basically make at high volume you can basically make anything for a cost that asymptotically approaches the raw material value of the constituents plus any intellectual property that you need to do license.

[298] Anything.

[299] But it's hard.

[300] It's not like, that's a very hard thing to do, but it is possible for anything.

[301] Anything in volume can be made of, like I said, for a cost that asymptotically approaches this raw material constituents plus intellectual property license rights.

[302] So what will often happen in trying to design a product is people will start with the tools and parts and methods that they are familiar with and then and try to create a product using their existing tools and methods.

[303] The other way to think about it is actually try to imagine the platonic ideal of the perfect product or technology, whatever it might be.

[304] and so what is the perfect arrangement of atoms that would be the best possible product and now let us try to figure out how to get the atoms in that shape I mean it sounds it's almost like Rick and Morty absurd until you start to really think about it and you really should think about it in this way because everything else is kind of if you think you might fall victim to the momentum of the way things were done in the past, unless you think in this way.

[305] Well, just as a function of inertia, people want to use the same tools and methods that they are familiar with.

[306] That's what they'll do by default.

[307] And then that will lead to an outcome of things that can be made with those tools and methods, but it is unlikely to be the platonic ideal of the perfect product.

[308] So that's why it's good to think of things in both directions.

[309] and say, like, what can we build with the tools that we have?

[310] But also, what is the perfect, the theoretical perfect product look like?

[311] And that theoretical perfect product is going to be a moving target, because as you learn more, the definition of that perfect product will change because you don't actually know what the perfect product is, but you can successfully approximate a more perfect product.

[312] So the thing about it like that, and then saying, okay, now what tools, methods, materials, whatever, do we need to create in order to get the atoms in that shape.

[313] But people rarely think about it that way.

[314] But it's a powerful tool.

[315] I should mention that the brilliant Chauvin Zillis is hanging out with us in case you hear a voice of wisdom from outside, from up above.

[316] Okay, so let me ask you about Mars.

[317] You mentioned it would be great for science to put a base on the moon to do some research.

[318] But the truly big leap, again in this category of seemingly impossible, is to put a human being on Mars.

[319] When do you think SpaceX will land a human being on Mars?

[320] Best case is about five years, worst case 10 years.

[321] What are the determining factors, would you say, from an engineering perspective, or is that that not the bottlenecks?

[322] You know, it's fundamentally, you know, engineering the vehicle.

[323] I mean, Starship is the most complex and advanced rocket that's ever been made by, I don't know, order of magnitude or something like that.

[324] It's a lot.

[325] It's really next level.

[326] And the fundamental optimization of Starship is minimizing cost per ton to orbit and ultimately cost per ton to the surface of it.

[327] Mars.

[328] This may seem like a mercantile objective, but it is actually the thing that needs to be optimized.

[329] There is a certain cost per ton to the surface of Mars where we can afford to establish a self -sustaining city, and then above that we cannot afford to do it.

[330] So right now, you couldn't fly to Mars for a trillion dollars.

[331] No amount of money could get your ticket to Mars.

[332] So we need to get that above you know to get that like something that is actually possible at all um but but then but that's that we don't we don't just want to have you know with mars flags and footprints and then not come back for a half century like we did with the moon uh in order to pass a very important great filter i think we need to be a multi -planet species um this may sound somewhat esoteric to a lot of people, but eventually given enough time that's something the Earth is likely to experience some calamity that could be something that humans do to themselves or an external event like happens to the dinosaurs and but a bit of eventually and if none of that happens and somehow magically we keep going, then the sun will, the sun is gradually expanding and will engulf the earth.

[333] And probably Earth gets too hot for life in about 500 million years.

[334] It's a long time, but that's only 10 % longer than Earth has been around.

[335] And so if you think about like the current situation, it's really remarkable and kind of hard to believe, but Earth's been around 4 .5 billion years.

[336] this is the first time in four and a half billion years that has been possible to extend life beyond earth and that window of our charity may be open for a long time and i hope it is but it also may be open for a short time and we should uh i think it was wise for us to uh act quickly while the window is open just in case it closes yeah the existence of nuclear weapons pandemics all kinds of threats should kind of give us some motivation I mean civilization could get could die with a bang or a whimper you know if it's a if it dies a demographic collapse then it's more of a whimper obviously and if it's World War III it's more of a bang but these are all risks I mean it's important to think of these things and just you know think of things like probability not certainties.

[337] There's a certain probability that something bad will happen on Earth.

[338] I think most likely the future will be good.

[339] But there's like, let's say, for argument's sake, a 1 % chance per century of a civilization ending event.

[340] Like that was Stephen Hawking's estimate.

[341] I think he might be right about that.

[342] So then, you know, we should basically think of this like being a multi -planet species is like taking out insurance for life itself like life insurance for life so it's turned into an infomercial real quick life insurance for life yes and you know we can bring the creatures from plants and animals from Earth to Mars and breathe life into the planet and have a second planet with life that would be great They can't bring themselves there, you know, so if we don't bring them to Mars, then they will just, for sure, all die when the sun expands anyway, and then that'll be it.

[343] What do you think is the most difficult aspect of building a civilization on Mars, terraforming Mars, like from engineering perspective, from a financial perspective, human perspective, to get a large number of folks there who will never return back to Earth?

[344] No, they could certainly return.

[345] Some will return back to Earth.

[346] They will choose to stay there for the rest of their lives.

[347] Yeah, many will.

[348] But, you know, we need the spaceships back, like the ones that go to Mars.

[349] We need them back.

[350] So you can't hop on if you want, you know.

[351] But we can't just not have the spaceships come back.

[352] Those things are expensive.

[353] We need them back.

[354] I'd like to come back and do another trip.

[355] I mean, do you think about the terraforming aspect, like actually building, how you're so focused right now on the spaceships part that's so critical?

[356] Yeah, we absolutely, if you can't get there, nothing else matters.

[357] So, and like I said, we can't get there with, at some extraordinarily high cost.

[358] I mean, the current cost of, let's say, one ton to the surface of Mars is on the order of a billion dollars.

[359] So, because you don't just need the rocket and the launch and everything.

[360] You need like heat shield.

[361] You need, you know, guidance system.

[362] You need deep space communications.

[363] You need some kind of landing system.

[364] So, like, rough approximation would be a billion dollars per ton to the surface of Mars right now.

[365] This is obviously way too expensive to create a self -sustaining civilization.

[366] So we need to improve that by at least a factor of a thousand.

[367] A million per ton?

[368] Yes, ideally less than a much less than a million a ton.

[369] But if it's not, like, it's got to be.

[370] You have to say, like, well, how much can society afford to spend or want to, just want to spend on a self -sustaining city on Mars?

[371] The self -sustaining part is important.

[372] Like, it's just the key threshold, the grateful to, will have been passed when the city on Mars can survive even if the spaceships from Earth stop coming for any reason.

[373] It doesn't matter what the reason is, but if they stop coming for any reason, will it die out or will it not?

[374] And if there's even one critical ingredient missing, then it still doesn't count.

[375] It's like, you know, if you're on a long sea voyage and you've got everything except vitamin C. And it's only a matter of time, you know, you're going to die.

[376] So we're going to get a Morris City to the point where it's self -sustaining.

[377] I'm not sure this will really happen in my lifetime, but I hope to see it at least have a lot of momentum.

[378] And then you could say, okay, what is the minimum tonnage necessary to have a self -sustaining city?

[379] And there's a lot of uncertainty about this.

[380] You could say, like, I don't know, it's probably at least a million tons because you have to set up a lot of infrastructure on Mars.

[381] Like I said, you can't be missing anything that, in order to be self -sustain, you can't be missed, like you need, you know, semiconductor fabs, you need iron ore refineries, like you need lots of things, you know.

[382] So, and Mars is not super hospitable.

[383] It's the least inhospitable planet, but it's definitely a fixer off of a planet.

[384] Outside of Earth.

[385] Yes.

[386] Earth is pretty good.

[387] Earth is like easy.

[388] And also we should clarify in the solar system.

[389] Yes, in the solar system.

[390] There might be nice vacation spots.

[391] There might be some great planets out there, but it's hopeless.

[392] Too hard to get there?

[393] Yeah, way, way, way, way, way too hard to say the least.

[394] Let me push back on that, not really a pushback, but a quick curveball of a question.

[395] So you did mention physics.

[396] as the first starting point.

[397] So general relativity allows for warm holes.

[398] They technically can exist.

[399] Do you think those can ever be leveraged by humans to travel fast in the speed of light?

[400] Well, are you saying?

[401] The whirlpool thing is debatable.

[402] We currently do not know of any means of going fast than the speed of light.

[403] there is like like there are some ideas about having space like so so you can only move at the speed of light through space but if you can make space itself move that that's like that's warming space space is capable of moving past it than the speed of light right like the universe in the Big Bang the universe the universe expanded it much much more than the speed of light by a lot yeah so but the if this is possible the amount of energy required to wolf space is so gigantic it boggles the mind so all the work you've done with propulsion how much innovation is possible with rocket propulsion is this I mean, you've seen it all, and you're constantly innovating in every aspect.

[404] How much is possible?

[405] Like, how much can you get 10x somehow?

[406] Is there something in there in physics that you can get significant improvement in terms of efficiency of engines and all those kinds of things?

[407] Well, as I was saying, really the Holy Grail is a fully and rapidly reusable orbital system.

[408] so right now the falconine is the only reusable rocket out there but the booster comes back in lens you've seen the videos and we get the nose cone o' fairing back but we do not get the upper stage back so that means that we have a minimum cost of building an upper stage you can think of like a two -stage rocket of sort of like two airplanes like a big airplane and a smaller airplane, and we get big airplane back, but not the small airplane.

[409] And so it still costs a lot, you know, so that upper stage is, you know, at least $10 million.

[410] And then the degree of, the booster is not as reuse, it's not as rapidly and completely reusable as we'd like in order of the farings.

[411] So, you know, our kind of minimum marginal cost, not counting overhead for per flight is on the order of $15 to $20 million, maybe.

[412] So that's extremely good for, it's by far better than any rocket ever in history.

[413] But with full and rapid reusability, we can reduce the cost per ton to orbit by a factor of 100.

[414] Just think of it like Imagine if you had an aircraft or something Or a car And if you had to buy in your car Every time you went for a drive It would be very expensive It would be silly, frankly But In fact you just refuel the car Or recharge the car And that makes your trip Like I don't know A thousand times cheaper So So it's the same for rockets.

[415] It's very difficult to make this complex machine that can go to orbit.

[416] And so if you cannot reuse it and have to have to throw even any part of any significant part of it away, that massively increases the cost.

[417] So, you know, Starship in theory could do a cost per launch of like a million, maybe $2 million or something like that.

[418] and put over 100 tons in orbit.

[419] This is crazy.

[420] Yeah.

[421] That's incredible.

[422] So you're saying like it's by far the biggest bang for the buck is to make it fully reusable versus like some kind of brilliant breakthrough in theoretical physics.

[423] No, no. There's no brilliant break.

[424] No, there's no, just you're going to make the rocket reusable.

[425] This is an extremely difficult engineering problem.

[426] Got it.

[427] But no new physics is required.

[428] Just brilliant engineering, let me ask a slightly philosophical fun question.

[429] Got to ask.

[430] I know you're focused on getting to Mars, but once we're there on Mars, what form of government, economic system, political system do you think would work best for an early civilization of humans?

[431] I mean, the interesting reason to talk about this stuff, it also helps people dream about the future.

[432] I know you're really focused about the short -term engineering dream.

[433] but it's like, I don't know, there's something about imagining an actual civilization on Mars that gives people, really gives people help.

[434] Well, it would be a new frontier and an opportunity to rethink the whole nature of government, just as was done in the creation of the United States.

[435] So, I mean, I would suggest having direct democracy, like people vote directly on things as opposed to representative democracy.

[436] So representative democracy, I think, is too subject to a special interest and, you know, a coercion of the politicians and that kind of thing.

[437] So I'd recommend that there's just direct democracy.

[438] People vote on laws, the population votes on laws themselves.

[439] And then the laws must be short enough that people can understand them.

[440] yeah and then like keeping a well -informed populist like really being transparent about all the information about what they're voting for absolutely transparency yeah and not make it as annoying as those cookies we have to accept the cookies like always like you know there's like always like a slight amount of trepidation when you click accept cookies like i feel as though there's like perhaps like like a very tiny chance that'll open a portal to hell or something like that's exactly how i feel Why do they, why do they keep wanting me to accept that?

[441] What do they want with this cookie?

[442] Like somebody got upset with accepting cookies or something somewhere.

[443] Who cares?

[444] Like, it's so annoying to keep accepting all these cookies.

[445] To me, this is just a great.

[446] Yes, you can have my damn cookie.

[447] I don't care.

[448] He heard her from you on first.

[449] He accepts all your damn cookies.

[450] Yeah.

[451] And stop asking me. It's annoying.

[452] Yeah, it's one example.

[453] of implementation of a good idea done really horribly.

[454] Yeah, it's somebody who was like, there's some good intentions of, like, privacy or whatever, but now everyone just has to accept cookies, and it's not, you know, you have billions of people who have to keep clicking except cookie, it's super annoying.

[455] Then we just accept the damn cookie, it's fine.

[456] There is, like, I think a fundamental problem that we're, because we've not really had a major, like a world war or something like, that in a while and obviously we would like to not have World Wars.

[457] There's not been a cleansing function for rules and regulations.

[458] So wars did have, you know, some sort of lining in that there would be a reset on rules and regulations after a war.

[459] So World Wars 1 and 2, there were huge resets on rules and regulations.

[460] Now, if society does not have a war and there's no cleansing function or garbage collection for rules and regulations, then rules and regulations, then rules regulations will accumulate every year because they're immortal.

[461] There's no actual humans die, but the laws don't.

[462] So we need a garbage collection function for rules and regulations.

[463] They should not just be immortal because some of the rules and regulations that are put in place will be counterproductive, done with good intentions, but counterproductive.

[464] Sometimes not done with good intentions.

[465] So if rules and regulations just accumulate every year and you get more and more of them, then eventually you won't be able to do anything.

[466] You're just like Gulliver with, you know, tied down by thousands of little strings.

[467] And we see that in, you know, U .S. and like basically all economies that have been around for a while.

[468] And regulators and legislators create new rules and regulations every year, but they don't put effort into removing them.

[469] And I think that's very important that we put effort into removing rules and regulations.

[470] But it gets tough because you get special interests that then are dependent on, like they have a vested interest in that, whatever, rule of regulation.

[471] And then they fight to not get it removed.

[472] Yeah, so, I mean, I guess the problem with the Constitution is it's kind of like C versus Java because it doesn't have any garbage collection built in.

[473] I think there should be, when you first said the metaphor of garbage collection, I love it.

[474] It's from a coding standpoint.

[475] From a coding standpoint, yeah, yeah.

[476] It would be interesting if the laws themselves kind of had a built -in thing where they kind of die after a while unless somebody explicitly publicly defends them.

[477] So that's sort of, it's not like somebody has to kill them, they kind of die themselves.

[478] They disappear.

[479] Yeah.

[480] Not to defend Java or anything, but, you know, C++, you know, you could also have great garbage collection in Python and so on.

[481] Yeah.

[482] Yeah, so yeah, something needs to happen, or just the civilization's arteries, arteries just hardened over time, and you can just get less and less done because there's just a rule against everything.

[483] So, so I think, like, I don't know, for Mars or whatever, I'd say, or even for, you know, obviously for Earth as well, like, I think there should be an active process for removing rules and regulations and questioning their existence, just, like, if we've got a function for creating rules and regulations because rules and regulations you can also think of as like they're like software or lines of code for operating civilization.

[484] That's rules and regulations.

[485] So it's not like we shouldn't have rules and regulations, but you have code accumulation, but no code removal.

[486] And so it just gets to become basically archaic bloatware after a while.

[487] And it's just, it makes it hard for things to progress.

[488] So I don't know, maybe Mars, you'd have like, you know, any given law must have a sunset, you know, and, and, and, uh, require active voting to keep, restore, to keep it up there, you know.

[489] Um, and I actually also say, like, and these are just, I don't know, recommendations or thoughts, and ultimately we'll be up to the people on Mars to decide, but I think, um, it should be easier to remove a law than to add one because of the just to overcome the inertia of laws.

[490] So maybe it's like for argument's sake you need like say 60 % vote to have a law take effect, but only a 40 % vote to remove it.

[491] So let me be the guy you posted a meme on Twitter recently where there's like a row of urinals and a guy just walks all the way across and he tells you about crypto.

[492] I mean that's happen to be so many times I think maybe even literally yeah do you think technologically speaking there's any room for ideas of smart contracts or so on because you mentioned laws that's an interesting implement use of things like smart contracts to implement the laws by which governments function like something built on a theorem or maybe a dog coin that enables smart contracts somehow I never I don't quite understand this whole smart contract thing, you know.

[493] I mean, I'm too dumb to understand small contracts.

[494] That's a good line.

[495] I mean, my general approach to any kind of like deal or whatever is just make sure there's clarity of understanding.

[496] That's the most important thing.

[497] And just keep any kind of deal very short and simple, plain language.

[498] And just make sure everyone understands this is the deal.

[499] Is everyone, is it clear?

[500] And what are the consequences if various things don't happen?

[501] But usually deals are, you know, business deals or whatever, are way too long and complex and overly -lawyered and pointlessly.

[502] You mentioned that Doge is the people's coin.

[503] Yeah.

[504] And you said that you were literally going, SpaceX may consider literally putting a Doche coin on the moon.

[505] Is this something you're still considering?

[506] Mars, perhaps.

[507] Do you think there's some chance we've talked about political systems on Mars that Doche coin is the official currency of Mars at some point in the future?

[508] Well, I think Mars itself will need to have a different currency because you can't synchronize due to speed of light.

[509] Or not easily.

[510] So it must be completely stand alone from Earth.

[511] Well, yeah, because Mars is at closest approach, it's four light minutes away roughly, and then at this approach, it's roughly 20 light minutes away, maybe a little more.

[512] So you can't really have something synchronizing, you know, if you've got a 20 minutes to be a light issue, if it's got a one -minute blockchain.

[513] It's not going to synchronize properly.

[514] So, Mars would, I don't know if Mars would have a cryptocurrency as a thing, but probably, seems likely, but it would be some kind of localized thing on Mars.

[515] And you let the people decide.

[516] Yeah, absolutely.

[517] The future of Mars should be up to the Martians.

[518] Yeah, so, I mean, I think the cryptocurrency thing is an interesting approach to, reducing the error in the database that is called money.

[519] You know, I think I have a pretty deep understanding of what money actually is on a practical day -to -day basis because of PayPal.

[520] You know, we really got in deep there.

[521] And right now the money system, actually, for practical purpose, is really a bunch of heterogeneous mainframes running old cobal.

[522] Okay, you mean literally.

[523] Literally.

[524] That's literally what's happening.

[525] In batch mode.

[526] Okay.

[527] In batch mode.

[528] Yeah.

[529] I pity the poor bastards do you have to maintain that code.

[530] Okay, that's a pain.

[531] Not even Fortran.

[532] It's cobal.

[533] Yep.

[534] It's cobal.

[535] And they still, the banks are still buying mainframes.

[536] in 2021 and running ancient cobal code.

[537] And, you know, the Federal Reserve is like probably even older than what the banks have, and they have an old cobal mainframe.

[538] And so now, and so the government effectively has editing privileges on the money database.

[539] And they use those editing privileges to make more money whenever they want.

[540] And this increases the error in the database.

[541] that is money.

[542] So I think money should really be viewed through the lens of information theory.

[543] And so it's kind of like an internet connection.

[544] Like what's the bandwidth, you know, total bet rate, what is the latency, jitter, packet drop, you know, errors in the network communication.

[545] Just think money like that, basically.

[546] I think that's probably the right way to think of it.

[547] And then say, what system, from an information theory standpoint, allows an economy to function the best.

[548] And, you know, crypto is an attempt to reduce the error in money that is contributed by governments diluting the money supply as basically a pernicious form of taxation.

[549] So both policy in terms of with inflation and actual technological cobalt, like, cryptocurrency takes us into the 21st century in terms of the actual systems that allow you to do the transaction, to store wealth, all those kinds of things.

[550] Like I said, just think of money as information.

[551] People often will think of money as having power in and of itself.

[552] It does not.

[553] Money is information.

[554] And it does not have power in and of itself.

[555] Like, you know, applying the physics tools of thinking about things in the limit is helpful.

[556] If you are stranded on a tropical island and you have a trillion dollars, it's useless because there's no resource allocation.

[557] Money is a database for resource allocation, but there's no resource to allocate except yourself, so money is useless.

[558] if you're stranded around Desert Island with no food all the Bitcoin in the world will not stop you from starving so just think of money as a database for resource allocation across time and space and then what system is what in what form should that that database or data system what would be most effective now there's a there is a fundamental issue with say bitcoin in its current form in that it's the transaction volume is very limited and the latency is very limited and the latency is the latency for a properly confirmed transaction is too long, much longer than you'd like.

[559] So it's actually not great from a transaction -mulling standpoint or a latency standpoint.

[560] So it is perhaps useful to solve an aspect of the money database problem, which is a sort of store of wealth or an accounting of relative obligation.

[561] I suppose, but it is not useful as a currency, as a day -to -day currency.

[562] But people have proposed different technological solutions.

[563] Yeah, Lightning Network and the layer two technologies on top of that.

[564] I mean, it's all, it seems to be all kind of a trade -off, but the point is it's kind of brilliant to say that just think about information, think about what kind of database, what kind of infrastructure enables that exchange of information.

[565] Yeah, so say like you're operating an economy, and you need to have some thing that It allows for the efficient, to have efficient value ratios between products and services.

[566] So you've got this massive number of products and services and you need to, you can't just barter.

[567] It's like, that would be extremely unwieldy.

[568] So you need something that gives you the, the, a ratio of exchange between goods and services.

[569] And then something that allows you to shift obligations across time, like debt, debt and equity, shift obligations across time.

[570] Then what does the best job of that?

[571] Part of the reason why I think there's some merits of Dogecoin, even though it was obviously created as a joke, is that it actually does have a much higher transaction volume capability than Bitcoin.

[572] And the cost of doing a transaction, the Dogecoin fee is very low.

[573] Like right now, if you want to do a Bitcoin transaction, the price of doing that transaction is very high.

[574] So you could not use it effectively for most things.

[575] And nor could it even scale to a high volume.

[576] And when Bitcoin started, I guess around 2008 or something like that, the internet connections were much worse than the RTA.

[577] Like order of bang to, I mean, there's way, way worse, you know, in 2008.

[578] So like having us, you know, a small block size or whatever is, you know, and a long synchronization time is made sense in 2008.

[579] But, you know, 2021 or fast forward 10 years, it's like, it's like, it's like a comically low.

[580] you know it's a so um and i think there's some value to having a linear increase in the amount of currency that is generated um so because some amount of the currency you'd like like if a if a currency is too deflationary or like uh or should say if if if a currency is expected to increase in value over time there's reluctance to spend it because you're like oh if i i'll just hold it and not spend it because it's scarcity is increasing with time so if i spend it now then i will regret spending it so i will just you know total it um but if there's some dilution of the currency occurring over time that's that's more of an incentive to use it as a currency so um those coins somewhat randomly has a, just a fixed number of sort of coins or hash strings that are generated every year.

[581] So there's some inflation, but it's not a percentage base.

[582] It's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a percentage of inflation will necessarily decline over time.

[583] Um, so it just, I don't, I'm not saying that it's like the ideal system for a currency, but I think it actually is just fundamentally better than anything else I've seen, just by accident.

[584] I like how you said around 2008, so you're not, you know, some people suggested, you might be Satoshi Nakamoto, you've previously said you're not, let me ask, you're not for sure.

[585] Would you tell us if you were?

[586] Yes.

[587] Do you think it's a feature or a bug that he's anonymous or she or they?

[588] It's an interesting kind of quirk of human history, that there is a particular technology that is a completely anonymous inventor or creator.

[589] Well, you can look at the evolution of ideas before the launch of Bitcoin and see who wrote, you know, about those ideas.

[590] And then, like, I don't know exactly.

[591] Obviously, I don't know who created Bitcoin for practical purposes, but the evolution of ideas is pretty clear before that.

[592] And, like, it seems as though, like, Nick Zabo is probably more than anyone else responsible for the evolution of those ideas.

[593] So, you know, he claims not to be succors to, not going to be.

[594] But I'm not sure that's neither here or there.

[595] But he seems to be the one more responsible for the ideas behind Bitcoin than anyone else.

[596] So it's not perhaps like singular figures aren't even as important as the figures involved in the evolution of ideas that led to a thing.

[597] Yeah.

[598] Yeah.

[599] It's, you know, perhaps it's sad to think about history, but maybe most names will be forgotten anyway.

[600] What is the name anyway?

[601] It's a name attached to an idea.

[602] What does it even mean, really?

[603] I think Shakespeare had a thing about roses and stuff, whatever he said.

[604] Rose by any other name.

[605] It would smell sweet.

[606] I got Elon to quote Shakespeare.

[607] I feel like I accomplished something today.

[608] Shall I compare you to a summer's day?

[609] I'm going to clip that out.

[610] Not more temperate and more fair.

[611] Autopilot.

[612] Tesla Autopilot has been through an incredible journey over the past six years or perhaps even longer in the minds of, in your mind, in the minds of many involved.

[613] Yeah, I think that's where we first connected, really, was the autopilot stuff, autonomy.

[614] The whole journey was incredible to me to watch.

[615] I was, because I knew, well, part of it was at MIT, and I knew the, the difficulty of computer vision.

[616] And I knew the whole, I had a lot of colleagues and friends about the Darba challenge and knew how difficult it is.

[617] And so there was a natural skepticism.

[618] When I first drove a Tesla with the initial system based on mobile eye, I thought there's no way.

[619] So first when I got in, I thought there's no way this car could maintain, like stay in the lane and create a comfortable experience.

[620] So my intuition initially was that the lane keeping problem is way too difficult to solve.

[621] Oh, they're keeping, yeah, that's relatively easy.

[622] Well, yeah.

[623] But not to solve in the way that we just, we talked about previous is prototype versus a thing that actually creates a pleasant experience over hundreds of thousands of miles or millions.

[624] Yeah, so I was proven wrong.

[625] We had to wrap a lot of code around the mobile eye thing.

[626] It doesn't just work by itself.

[627] I mean, that's part of the story of how you approach things sometimes.

[628] Sometimes you do things from scratch.

[629] Sometimes at first, you kind of see.

[630] see what's out there, and then you decide to do from scratch.

[631] That was one of the boldest decisions I've seen is both on the hardware and the software to decide to eventually go from scratch.

[632] I thought, again, I was skeptical of whether that's going to be able to work out, because it's such a difficult problem.

[633] And so it was an incredible journey.

[634] What I see now with everything, the hardware, the compute, the sensors, the things I maybe care and love about most is the stuff that Andre Carpathie is leading with the dataset selection.

[635] the whole data engine process, the neural network architectures, the way that's in the real world, that network is tested, validated, all the different test sets, you know, versus the image net model of computer vision, like what's in academia, is like real world artificial intelligence.

[636] And Andre is awesome, and obviously plays an important role, but we have a lot of really talented people driving things.

[637] So, and Ashok is actually the, the, head of autopilot engineering.

[638] Andre is the director of AI.

[639] AI stuff, yeah, yeah.

[640] So, yeah, there's, I'm aware that there's an incredible team of just a lot going on.

[641] Yeah, just, you know, obviously people will give, will give me too much credit and they'll give Andre too much credit.

[642] And people should realize how much is going on under the, under the host.

[643] Yeah, it's just a lot of really talented people.

[644] The Tesla autopilot AI team is extremely talented.

[645] It's like some of those smartest people in the world.

[646] So, yeah, we're getting it done.

[647] What are some insights you've gained over those five, six years of autopilot about the problem of autonomous driving?

[648] So you leaped in having some sort of first principles kinds of intuitions, but nobody knows how difficult the problem.

[649] Yeah, I thought the self -driving problem would be hard, but it was harder than I thought.

[650] It's not like I thought it would be easy.

[651] I thought it would be very hard, but it was actually way harder than even that.

[652] So what it comes down to at the end of day is to solve self -driving, you have to solve, you basically need to recreate what humans do to drive, which is humans drive with optical sensors, eyes, and biological neural nets.

[653] And so in order to, that's how the entire road system is designed to work with basically passive optical and neural nets, biologically.

[654] And now that we need to, so actually for full self driving to work, we have to recreate that in digital form.

[655] So we have to, that means cameras with advanced neural nets in silicon form, and then it will obviously solve for full cell driving.

[656] That's the only way.

[657] I don't think there's any other way.

[658] But the question is, what aspects of human nature do you have to encode into the machine, right?

[659] So you have to solve the perception problem, like detect.

[660] And then you first, well, realize what is the perception problem for driving?

[661] Like, all the kinds of things you have to be able to see.

[662] Like, what do we even look at when we drive?

[663] There's a, I just recently heard Andre talked about at MIT about, like, car doors.

[664] I think it was the world's greatest talk of all time about car doors.

[665] Yeah.

[666] the fine details of car doors.

[667] Like, what is even an open car door, man?

[668] So, like, the ontology of that, that's the perception problem.

[669] We humans solve that perception problem, and Tesla has to solve that problem.

[670] And then there's the control and the planning coupled with the perception.

[671] You have to figure out, like, what's involved in driving, like, especially in all the different edge cases.

[672] And then, I mean, maybe you can comment on this, how much game theoretic kind of stuff needs to be involved at a four -way stop sign as humans when we drive our actions affect the world like it changes how others behave most of the time was driving you're usually just responding to the scene as opposed to like really asserting yourself in the scene do you think I think these I think these sort of control logic conundrums are not the hot part.

[673] The, you know, let's see.

[674] What do you think is the hard part in this whole beautiful, complex problem?

[675] So it's a lot of friggin software, man, a lot of smart lines of code.

[676] For sure, in order to have, create an accurate vector space.

[677] So, like, you're coming from image space, which is like this flow of photons, you're going to the camera, cameras, and then you have this massive bitstream in image space, and then you have to effectively compress the massive bitstream.

[678] corresponding to photons that knocked off an electron in a camera sensor and turn that but stream into vector space.

[679] By vector space, I mean like, you know, you've got cars and humans and lane lines and curves and traffic lights and that kind of thing.

[680] once you have an accurate vector space the control problem is similar to that of a video game like a grand theft order of cyberpunk if you have accurate accurate vector space it's the control problem is it's I wouldn't say it's it's it's trivial it's not trivial but it's um it's it's it's not like some insurmountable thing it's but having an accurate vector space is very difficult Yeah, I think we're humans don't give enough respect to how incredible the human perception system is, mapping the raw photons to the vector space representation in our heads.

[681] Your brain is doing an incredible amount of processing and giving you an image that is a very cleaned up image.

[682] Like when we look around here, you see color in the corners of your eyes, but actually your eyes have very few cones, like cone receptors in the peripheral vision.

[683] Your eyes are painting color in the peripheral vision.

[684] You don't realize it, but their eyes are actually painting color.

[685] And your eyes also have like there's blood vessels and all sorts of gnarly things.

[686] And there's a blind spot, but do you see your blind spot?

[687] No. Your brain is painting in the missing, the blind spot.

[688] You're going to do these like, see these things online where you look here and look at this point and then look at this point.

[689] And if it's in your blind spot, your brain will just fill in the, the missing bits.

[690] So cool.

[691] The peripheral vision is so cool.

[692] Yeah.

[693] Makes you realize all the illusions for vision science.

[694] It makes you realize just how incredible the brain is.

[695] The brain is doing a crazy amount of post -processing on the vision signals from your eyes.

[696] It's insane.

[697] So, and then even once you get all those vision signals, your brain is constantly trying to forget as much as possible.

[698] So human memory is, perhaps the weakest thing about the brain is memory.

[699] So because memory is so expensive to a brain and so limited, your brain is trying to forget as much as possible and distill the things that you see into the smallest amounts of information possible.

[700] So your brain is trying to not just get to a vector space, but get to a vector space that is the smallest possible vector space of only relevant objects.

[701] And I think you can sort of look inside your brain, or at least I can.

[702] Like when you drive down the road and try to think about what your brain is actually doing consciously.

[703] And it's consciously, it's, it's like you'll see a car that's, because you're, you're, you don't have cameras, you don't have eyes in the back of your head or the side, you know, so you say like, you're, you're, you're, you basically your, your, your head is like a, you know, you basically have like two cameras on a slow gimbal.

[704] And, and what's your, and I say it's not that.

[705] Great.

[706] Okay, you and eyes are, you know, like, and people are constantly distracted and thinking about things and texting and doing all sorts of things they shouldn't do in a car, changing the radio station.

[707] So having arguments, you know, is like, so, so then, like, say like, like, when's the last time you looked right and left, you know, or rearward, or even diagonally, you know, forward, to actually refresh your vector space.

[708] So you're glancing around, and what your mind is doing is trying to distill the relevant vectors, basically objects with a position and motion, and then editing that down to the least amount that's necessary for you to drive.

[709] It does seem to be able to edit it down or compress it even further into things like concepts.

[710] So it's like it goes beyond, the human mind seems to go sometimes beyond vector space to sort of space of concepts to where you'll see a thing it's no longer represented spatially somehow it's almost like a concept that you should be aware of like if this is a school zone you'll remember that as a concept which is a weird thing to represent but perhaps for driving you don't need to fully represent those things or maybe you get those kind of indirectly you need to establish vector space and then actually have predictions for those vector spaces.

[711] So like you know like if you know like you drive past say a bus and you see that there's people before you drove past the bus you saw people crossing or some just imagine there's like a large truck or something blocking site but before you came up to the truck you saw that there were some kids about to cross the road road in front of the truck.

[712] Now you can no longer see the kids, but you need to be able, but you would now know, okay, those kids are probably gonna pass by the truck and cross the road, even though you cannot see them.

[713] So you have to have memory, you have to need to remember that there were kids there and you need to have some forward prediction of what their position will be.

[714] It's a really hard problem.

[715] At the time of relevance.

[716] So with occlusions and computer vision, when you can't see an object, anymore even when just walks behind a tree and reappears that's a really really i mean at least in academic literature it's tracking through occlusions it's very difficult yeah we're doing it um i understand this yeah so some of it's object permanence like same thing happens with the humans with neuralness like when like a toddler grows up like there's a there's a point in time where uh they develop they have a sense of object permanence so before a certain age if you have a ball and you put it behind your back and you pop it out before they have object permanence it's like a new thing every time it's like whoa this toy went boof despaired and now it's back again and they can't believe it and that you can play peekaboo all day long because the peekaboo is fresh every time but then we figure out object permanence then they realize oh no the object is not gone it's just behind your back sometimes I wish we never did figure out object permanence yeah so that's that's an important problem to solve.

[717] Yes.

[718] So, like an important evolution of the neural nets in the car is memory across both time and space.

[719] So now you can't remember, like you have to say, like, how long do you want to remember things for?

[720] And it, there's a cost to remembering things for a long time.

[721] So you can, you know, like run out of memory to try to remember too much for too long.

[722] And then you also have things that are stale if they remember them for too long and then you also need things that are remembered over time so even if you like say have like for i going to say five seconds of memory on a time basis but like let's say you you're parked at a light and you and you saw use a pedestrian example that people were waiting to cross the across the road and you can't you can't quite see them because of an occlusion uh but they might wait for for a minute before the light changes for them to cross the road, you still need to remember that that's where they were and that they're probably going to cross the road type of thing.

[723] So even if that exceeds your time -based memory, it should not exceed your space memory.

[724] And I just think the data engine side of that, so getting the data to learn all the concepts that you're saying now is an incredible process.

[725] It's this iterative process of just, it's this hydranet, many hyphenate.

[726] We're changing the name to something else.

[727] Okay.

[728] I'm sure it would be equally as Rick and Morty like.

[729] There's a lot of We've re -architected the neural nets in the cars so many times it's crazy.

[730] Oh, so every time there's a new major version, you'll rename it to something more ridiculous or memorable and beautiful, sorry?

[731] Not ridiculous, of course.

[732] If you see the full the full array of neural nets that are operating in the car it kind of boggles the mind there's so many layers it's crazy so yeah but and we started off with simple neural nets that were basically image recognition on a single frame from a single camera and then trying to knit those together with C. I should say we're really primarily running C here because C++ is too much overhead.

[733] And we have our own C compiler.

[734] So to get maximum performance, we actually wrote our own C compiler and are continuing to optimize our C compiler for maximum efficiency.

[735] In fact, we've just recently done a new rev on a C compiler that will compile directly to our autopilot hardware.

[736] So you want to compile the whole thing down with your own compiler.

[737] Yeah, so efficiency here, because there's all kinds of compute.

[738] There's CPU, GPU, there's like basic types of thing, and you have to somehow figure out the scheduling across all of those things.

[739] And so you're compiling the code down.

[740] Yeah.

[741] That does all, okay.

[742] So that's why there's a lot of people involved.

[743] There's a lot of hardcore software engineering at a very sort of bare metal level.

[744] because we're trying to do a lot of compute that's constrained to the, you know, our full -self -driving computer.

[745] So, and we want to try to have the highest frames per second possible, with a sort of very finite amount of compute and power.

[746] So we really put a lot of effort into the efficiency of our compute.

[747] And so there's actually a lot of work done by some very talented software engineers at Tesla that at a very foundational level to improve the efficiency of compute and how we use the trip accelerators, which are basically, you know, doing matrix math, dot products, like a bazillion dot products.

[748] And it's like, what are neuralettes?

[749] It's like, compute -wise, like 99 % dot products.

[750] So, you know.

[751] And you want to achieve as many high frame rates like a video game.

[752] You want full resolution, high frame rate?

[753] High frame rate, low latency, low jitter.

[754] So I think one of the things we're moving towards now is no post -processing of the, image through the image signal processor.

[755] So what happens for cameras is that almost all cameras is they, there's a lot of post -processing done in order to make pictures look pretty.

[756] And so we don't care about pictures looking pretty.

[757] We just want the data.

[758] So we're moving just raw photon counts.

[759] So the system will Like the Image that the computer sees is actually much more Than what you see if you're represented on a camera It's got much more data And even in very low light conditions You can see that there's a small photon count difference Between you know This spot here and that spot there Which means that so it can see in the dark incredibly well Because it can detect these tiny differences in photon counts Like much better than you could partially imagine.

[760] And then we also save 13 milliseconds on a latency.

[761] So.

[762] From removing the post processing on the image?

[763] Yes.

[764] It's like because we've got eight cameras and then there's roughly, I don't know, one and a half milliseconds or so, maybe 1 .6 milliseconds of latency for each camera.

[765] And so, like, going to just, basically bypassing the image processor gets us back 13 milliseconds of latency, which is important.

[766] And we track latency all the way from, you know, photon hits the camera to, you know, all the steps that it's got to go through to get, you know, go through the various neural nets and the C code and there's a little bit of C++ there as well.

[767] Well, maybe a lot, but the core stuff is, the heavy -duty computer is old -in -see.

[768] And so we track that latency all the way to an output command to the drive unit to accelerate the brakes to slow down, steering, you know, turn left or right.

[769] So, because you go to output a command, that's going to go to a controller, and like some of these controllers have an update frequency.

[770] That's maybe 10 hertz or something like.

[771] like that, which is slow.

[772] That's like, now you lose 100 milliseconds potentially.

[773] So then we want to update the drivers on the, like say, steering and braking control to have more like 100 hoots instead of 10 hoots, then you've got 10 milliseconds latency instead of 100 milliseconds, worst case latency.

[774] And actually, jitter is more of a challenge than latency.

[775] Because latency is like you can anticipate and predict, but if you've got a stack up of things going from the camera to the computer through then a series of other computers and finally to an actuator on the car, if you have a stack up of tolerances, of timing tolerances, then you can have quite a variable latency, which is called jitter.

[776] And that makes it hard to anticipate exactly how you should turn the car or accelerate because if you've got maybe 150, 200 milliseconds of jitter, then you could be off by, you know, up to 0 .2 seconds.

[777] And this could make a big difference.

[778] So you have to interpolate somehow to deal with the effects of jitter, so that you can make robust control decisions.

[779] So the jitters and the sensor information.

[780] Or the jitter can occur at any stage in the pipeline.

[781] You can, if you have fixed latency, you can anticipate.

[782] And like say, okay, we know that our information is, for argument's sake, 150 milliseconds stale.

[783] So, for argument, for a 150 milliseconds from photon's taking camera to where you can measure a change in the acceleration of the vehicle.

[784] So then you can say, okay, well, we're going to, we know it's 150 milliseconds, so we're going to take that into account and compensate for that latency.

[785] However, if you've got then 150 milliseconds of latency plus 100 milliseconds of jitter, which could be anywhere from zero to 100 milliseconds on top.

[786] So then your latency could be from 150 to 15 milliseconds.

[787] Now you've got 100 milliseconds that you don't know what to do with.

[788] And that's basically random.

[789] So getting rid of jitter is extremely important.

[790] And that affects your control decisions and all those kinds of things.

[791] Okay.

[792] Yeah, the car is just going to fundamentally maneuver better with lower jitter.

[793] got it the cars will maneuver with superhuman ability and reaction time much faster than a human I mean I think over time the autopilot full self driving will be capable of maneuvers that you know are far more than what like James Bond could do in the best movie type of thing that's exactly where I was imagining in my mind as you said it it's like impossible maneuvers that a human couldn't do well let me ask sort of looking back the six years looking out into the future based on your current understanding how hard do you think this this full self -driving problem when do you think Tesla will solve level four fSD i mean it's looking quite likely that it will be next year and what does the solution look like is it the current pool of fsd beta candidates they start getting greater and greater as they have been degrees of autonomy and then there's a certain level beyond which they can do their own, they can read a book.

[794] Yeah, so, I mean, you can see that anybody who's been following the full -stop driving beta closely will see that the rate of disengagement has been dropping rapidly.

[795] So like a disengagement be where the driver intervenes to prevent the car from doing something.

[796] dangerous potentially.

[797] So the interventions per million miles has been dropping dramatically.

[798] At some point, and that trend looks like it happens next year, is that the probability of an accident on FSD is less than that of the average human and then significantly less than that of the average human.

[799] So it certainly appears like we will get there next year.

[800] Then, of course, then there's going to be a case of, okay, well, we now have to prove this to regulators and prove it to, you know, and we want a standard that is not just equivalent to a human, but much better than the average human.

[801] I think it's got to be at least two or three times higher safety than a human.

[802] So two or three times lower probability of injury than a human.

[803] before we would actually say like okay it's okay to go it's not going to be equivalent it's going to be much better so if you look at 10 point FSD 10 .6 just came out recently 10 .7 is on the way maybe 11 is on the way somewhere in the future yeah we were hoping to get 11 out this year but it's 11 actually has a whole bunch of fundamental rewrites on the neural net architecture and some fundamental improvements in creating vector space.

[804] there is some fundamental leap that really deserves the 11.

[805] I mean, that's a pretty cool number.

[806] 11 would be a single stack for all, you know, one stack to rule them all.

[807] And but there are just some really fundamental neural net architecture changes that are that will allow for much more capability but but you know at first they're going to have issues so like we have this working on like sort of alpha software and it's good but it's uh it's it's it's basically taking a whole bunch of cc plus plus code and and deleting a massive amount of c plus code and replacing it with the neural net and you know andre makes this point a lot which is like neural nets, like kind of eating software.

[808] You know, over time, there's like less and less conventional software, more and more neural net.

[809] Which is still software, but it's, you know, still comes out to lines of software.

[810] But it's more neural net stuff and less, you know, heuristics, basically.

[811] If you're more, more matrix -based stuff and less heuristics, based stuff.

[812] And, you know, like, one of the big changes will be, like right now the neural nets will deliver a giant bag of points to the C++ or CNC plus code.

[813] Yeah.

[814] We call it the giant bag of points.

[815] Yeah.

[816] And it's like, so you go to pixel and, and something associated with that pixel.

[817] Like this pixel is probably car.

[818] This pixel is probably lane line.

[819] Then you've got to assemble this giant bag of points in the C code and turn it into vectors.

[820] And it does a pretty good job of it, but it's a, it's, we want to just, we need another layer of neural nets on top of that to take the giant bag of points and distill that down, to vector space in the neural net part of the software as opposed to the heuristics part of the software.

[821] This is a big improvement.

[822] Neuron nets all the way down is what you want.

[823] It's not even old neural net, but it's, it's, this will be just a this is a game changer to not have the bag of points, the giant bag of points that has to be assembled with many lines of CFC plus plus and have the and have a neural net just assemble those into a vector.

[824] So the neural net is outputting much, much less data.

[825] It's outputting this is a lane line, this is a curb, this is drivable space, this is a card, this is a pedestrian or a cyclist or something like that.

[826] It's outputting, it's really outputting propof vectors to the CEC plus plus control code.

[827] as opposed to the sort of constructing the vectors in C. We've done, I think, quite a good job of, but we're kind of hitting a local maximum on how well the C can do this.

[828] So this is really a big deal.

[829] And just all of the networks in the car need to move to surround video.

[830] There's still some legacy networks that are not surround video and all of the training needs to move to surround video and the efficiency of the training it needs to get better and it is and then we need to move everything to raw photon counts as opposed to processed images.

[831] It's just quite a big reset on the training because the system's trained on post -processed images so we need to redo all the training to train again.

[832] To train a against the raw photon counts instead of the post -processed image.

[833] So ultimately, it's kind of reducing the complexity of the whole thing.

[834] So reducing the - Lines of code will actually go lower.

[835] Yeah, that's fascinating.

[836] So you're doing fusion of all the sensors, reducing the complexity of having to deal with these sensors.

[837] Fusion of cameras, is the other cameras, really.

[838] Right, yes.

[839] Same with humans.

[840] Yeah.

[841] Well, I guess we got years too.

[842] Okay.

[843] Yeah, well, we'll actually need to incorporate sound as well because you know you need to like listen for ambulance sirens or you know fire tracks you know somebody like you know yelling at you or something I don't know just there's a little bit of audio that needs to be incorporated as well do you know go back to break yeah let's sure let's take a break honestly frankly like the ideas are the easy thing and the implementation is the hard thing like the idea of going to the moon is the easy part not going to the moon is the hard part.

[844] It's the hard part.

[845] And there's a lot of hardcore engineering that's got to get done at the hardware and software level, like, said, optimizing the C compiler and just, you know, cutting out latency everywhere.

[846] Like, this is, if we don't do this, the system will not work properly.

[847] So the work of the engineers doing this, they are like the unsung heroes, but they are critical to the success of the situation.

[848] I think you made it clear.

[849] I mean, at least to me, it's super exciting, everything that's going on outside of what Andre is doing.

[850] Just the whole infrastructure of the software.

[851] I mean, everything is going on with Data Engine, whatever it's called.

[852] The whole process is just a work of art to me. The sheer scale of it is boggles of mine.

[853] Like the training, the amount of work done with the, like we written all this custom software for training and labeling.

[854] And to do auto labeling.

[855] Auto labeling is essential.

[856] because especially when you've got like surround video it's very difficult to like label surround video from scratch is extremely difficult like take a human's such a long time to even label one video clip like several hours or the order label it basically we just apply like heavy duty like a lot of compute to the video clips to pre -assign and guess what all the things are that are going on in this round video.

[857] And then there's like correcting it.

[858] And then all the human has to do is like tweet, like say, you know, adjust what is incorrect.

[859] This is like increases productivity by effect 100 or more.

[860] Yeah.

[861] So you've presented Tesla bot as primarily useful in the factory.

[862] First of all, I think human robots are incredible.

[863] From a fan of robotics, I think the elegance of movement that humanoid robots, the bipedal robots show are just so cool.

[864] So it's really interesting that you're working on this and also talking about applying the same kind of all the ideas of some of which we've talked about with Data Engine, all the things that we're talking about with Tesla Autopilot, just transferring that over to just yet another robotics problem.

[865] I have to ask, since I care about human -robot interaction, so the human side of that, so you've talked about mostly in the factory, do you see it, it also, do you see part of this problem that Tesla bot has to solve as interacting with humans and potentially having a place like in the home?

[866] So interacting, not just, not replacing labor, but also like, I don't know, being a friend or an assistant.

[867] Yeah, yeah, I think the, the possibilities are, you know, endless.

[868] Yeah, I mean, it's obviously like a, it's not quite in Tesla's primary mission direction of accelerating sustainable energy, but it is a, an extremely useful thing that we can do for the world, which is to make a useful humanoid robot that is capable of interacting with the world and helping in many different ways.

[869] So certainly in fact, reason, and really just, I mean, I think if you say like, extrapolate to, you know, many years in the future, it's like, I think work will become optional.

[870] so like there's a lot of jobs that if people weren't paid to do it they wouldn't do it like it's not it's not fun you know necessarily like if you're washing dishes all day it's like you know even if you really like washing dishes you really want to do it for eight hours a day every day probably not so um and then there's like dangerous work and basically if it's dangerous boring uh it has like potential for repetitive stress injury that kind of thing then that's really where humanoid robots would add the most value initially.

[871] So that's what we're aiming for is to, for the humanoid robots to do a job that people don't voluntarily want to do.

[872] And then we'll have to pair that, obviously, with some kind of universal basic income in the future.

[873] So I think.

[874] Do you see a world when there's like hundreds of millions?

[875] of Tesla bots, doing different, performing different tasks throughout the world?

[876] Yeah, I haven't really thought about it that far into the future, but I guess there may be something like that.

[877] So, I can ask a wild question.

[878] So the number of Tesla cars has been accelerating, has been close to 2 million produced.

[879] Many of them have autopilot.

[880] I think we're over 2 million now, yeah.

[881] Do you think there will ever be a time where there will be more Tesla bots than Tesla cars?

[882] yeah actually it's funny you asked this question because normally I do try to think pretty far into the future but I haven't really thought that far into the future with the Tesla bot or it's code named Optimus I call it Optimus subprime because it's not like a giant transformer robot but it's meant to be a general purpose helpful bot and basically like the things that we're basically like Tesla I think is the has the most advanced real world AI for interacting with the real world which it develops as a function of to make self -driving work and so along with custom hardware and like a lot of you know hardcore low -level software to have it run efficiently and be you know power efficient because you know it's one thing to do neural nets if you've got a gigantic sober room with 10 ,000 computers, but now let's say you just, you have to now distill that down into one computer that's running at low power in a humanoid robot or a car.

[883] That's actually very difficult.

[884] A lot of hardcore software work is required for that.

[885] So since we're kind of like solving the navigate the real world with neural nets problem for cars, which are kind of like robots with four wheels, then it's like kind of a natural extension of that is to put it in a robot with arms and legs and actuators.

[886] So, like, the two hard things are, like, you basically need to make the, how the robot be intelligent enough to interact in a sensible way with the environment.

[887] So you need real, real world AI, and you need to be very good at manufacturing, which is a very hard problem.

[888] Tesla is very good of manufacturing and also has the real world AI.

[889] So making the humanoid robot work is basically it means developing custom motors and sensors that are different from what a car would use.

[890] But we've also, I think we have the best expertise in developing advanced electric motors and power electronics.

[891] So it just has to be for a humanoid robot application of a car.

[892] Still, you do talk about love sometimes.

[893] So let me ask, this isn't like for like sex robots or something like that.

[894] I love it's the answer.

[895] Yes.

[896] There is something compelling to us, not compelling, but we connect with humanoid robots or even like with a dog in shape of dogs.

[897] it just it seems like you know there's a huge amount of loneliness in this world all of us seek companionship and with other humans friendship and all those kinds of things we have a lot of here in austin a lot of people have dogs sure there seems to be a huge opportunity to also have robots that decrease the uh the amount of loneliness in the world or help us humans connect with each with each other so in the way that dogs can um Do you think about that, would testify about it all, or is it really focused on the problem of performing specific tasks, not connecting with humans?

[898] I mean, to be honest, I have not actually thought about it from the companionship standpoint, but I think it actually would end up being, it could be actually a very good companion.

[899] And it could, you develop like a personality over time that is, is unique.

[900] Like, you know, it's not like they're just all the robots are the same.

[901] And that personality could evolve to be, you know, match the, the owner or the, you know, I guess the owner.

[902] Well, whatever you want to call it.

[903] The other half, right?

[904] In the same way that friends do.

[905] See, I think that's a huge opportunity.

[906] I think.

[907] Yeah, no, that's interesting.

[908] thing like um the because you know like there's a japanese phrase are like the wabi sabi you know the subtle imperfections are what makes something special yeah and the subtle imperfections of the personality of the robot mapped to the subtle imperfections of the robot's human friend i don't know owner sounds like maybe the wrong word but um could actually make an incredible buddy basically In that way, the imperfections.

[909] Like R2D2 or like a C3PO sort of thing, you know.

[910] So from a machine learning perspective, I think the flaws being a feature is really nice.

[911] You could be quite terrible at being a robot for quite a while in the general home environment or all the in general world.

[912] And that's kind of adorable.

[913] And that's like those are your flaws.

[914] And you fall in love with those flaws.

[915] So it's very different than autonomous driving where it's a very high stakes environment.

[916] you cannot mess up.

[917] And so it's more fun to be a robot in the home.

[918] Yeah, in fact, if you think of like C3PO and R2D2, like they actually had a lot of like flaws and imperfections and silly things and they would argue with each other.

[919] Were they actually good at doing anything?

[920] I'm not exactly sure.

[921] They definitely added a lot to the story.

[922] But there's sort of quirky elements and, you know, that they would like make mistakes and do things.

[923] Like it was like, it made them relatable, I don't know, endearing.

[924] So, so yeah, I think that that could be something that probably would happen.

[925] But our initial focus is just to make it useful.

[926] So I'm confident we'll get it done.

[927] I'm not sure what the exact time frame is, but like we'll probably have, I don't know, a decent prototype towards the end of next year or something like that.

[928] And it's cool that it's connected to Tesla, the car.

[929] Yeah, it's using a lot of, you know, it would use the autopilot inference computer and a lot of the trading that we've done for the four cars in terms of recognizing real -world things could be applied directly to the robot.

[930] But there's a lot of custom actuators and sensors that need to be developed.

[931] And an extra module on top of the vector space for love.

[932] Yeah.

[933] That's me saying.

[934] Okay.

[935] We could add that to the car too.

[936] That's true.

[937] That could be useful in all environments.

[938] Like you said, a lot of people argue in the car, so maybe we can help them out.

[939] You're a student of history, fan of Dan Carlin's Hardcore History Podcast.

[940] Yeah, that's great.

[941] Greatest podcast ever?

[942] Yeah, I think it is, actually.

[943] it almost doesn't really count as a podcast it's so good it's more like a audiobook yeah so you were on the podcast with dan i just had a chat with him about it he said you guys went military and all that kind of stuff uh yeah it's literally uh it was basically um uh it should be titled engineer wars uh essentially like like when there's a rapid change in the rate of technology then engineering plays a pivotal role in victory in battle.

[944] How far back in history did you go?

[945] Did you go World War II?

[946] It was supposed to be a deep dive on fighters and bomber technology in World War II, but that ended up being more wide -ranging than that.

[947] Because I just went down the total rat hole of studying all of the fighters and bombers of World War II and like the constant rock paper says this game that one country would make this plane and then it makes a plane to beat that and that rock try to make a plane to beat that and really what matters is like the pace of innovation and also access to high quality fuel and raw materials.

[948] So like Germany had like some amazing designs but they couldn't make them because they couldn't get the raw materials and they had a real problem with the oil and fuel, basically.

[949] The fuel quality was extremely variable.

[950] So the design wasn't the bar neck?

[951] Yeah, like the U .S. had kick -ass fuel that was like very consistent.

[952] Like the problem is if you make a very high performance aircraft engine, in order to make high performance, you have to, the fuel, the aviation gas has to be a consistent mixture.

[953] and it has to have a high octane.

[954] Like high octane is the most important thing, but also can't have like impurities and stuff because you'll foul up the engine.

[955] And Germany just never had good access to oil.

[956] Like they tried to get it by invading the Caucasus.

[957] But that didn't work too well.

[958] Never works well.

[959] They don't work out for them.

[960] See you.

[961] Nice for you.

[962] So Germany was always struggling with shit with basically shitty oil.

[963] And so then they couldn't count on high quality fuel for their aircraft.

[964] So then they had to have all these additives and stuff.

[965] So whereas the U .S. had awesome fuel.

[966] And that provided that to Britain as well.

[967] So that allowed the British and the Americans to design aircraft engines that were super high performance better than anything else in the world.

[968] Germany could design the engines.

[969] They just didn't have the fuel.

[970] And then also the quality of the aluminum allies that they were getting was also not that great.

[971] And so, you know, is this like, do you talked about all this with Dan?

[972] Yep.

[973] Broadly looking at history, when you look at Jenghis Khan, when you look at Stalin, Hitler, the darkest moments of human history, what do you take away from those moments?

[974] Does it help you gain insight about human nature, about human behavior today?

[975] whether it's the wars or the individuals or just the behavior of people, any aspects of history.

[976] Yeah, I find history fascinating.

[977] There's just a lot of incredible things that have been done, good and bad, that they just help you understand the nature of civilization and individuals.

[978] Does it make you sad that humans do these kinds of things to each other?

[979] other you look at the 20th century world war two the cruelty the abuse of power talk about communism marxism and Stalin um i mean some of these things do i mean if you like there's a lot of human history um but most of it is uh actually people just getting on with their lives uh you know and and it's not like human history is just uh what non -stop war and disaster is it those are actually just those are intermittent and rare and if they weren't then you know humans would soon cease to exist um but it's just that wars tend to be written about a lot and whereas like uh something being like well a normal year where nothing major happened was just get written about much but that's you know most people just like farming and kind of like living their life you know um being a villager somewhere and every now and again there's a war and I think so um and yeah but I have to say like that there aren't very many books that I where I just had to stop reading because it was just too too dark but the book about Stalin the court of the red czar I had to stop reading it was just too too dark rough yeah the 30s there's a lot of lessons there to me in particular that it feels like humans like all of us have that it's the old Soljean it's in line that the line between good and evil runs to the heart to every man that all of us are capable of evil all of us are capable of good it's almost like this kind of responsibility that all of us have to to tend towards the good.

[980] And so, like, to me, looking at history is almost like an example of, look, you have some charismatic leader that convinces you of things.

[981] It's too easy, based on that story, to do evil onto each other, onto your family, onto others.

[982] And so it's like our responsibility to do good.

[983] It's not like now is somehow different from history.

[984] That can happen again.

[985] All of it can happen again.

[986] And yes, most of the time, you're right I mean the optimistic view here is mostly people are just living life and as you've often memed about the quality of life was way worse back in the day and it keeps improving over time through innovation to technology but still it's somehow notable that these blimps of atrocities happen sure yeah I mean life was really tough for most of history I mean well if most of human history a good year would be one where not that many people in your village died of the plague, starvation, freezing to death, or being killed by a neighboring village.

[987] It's like, well, it wasn't that bad.

[988] You know, it was only like, you know, we lost 5 % this year.

[989] That was good year.

[990] You know, that would be part of the course.

[991] Like, just not starving to death would have been like the primary goal of most people in through its right history is making sure we'll have not foods last through the winter or not get, not freeze or whatever.

[992] So, um, now food is plentiful.

[993] I have an obesity problem.

[994] you know, so.

[995] Well, the lesson there is to be grateful for the way things are now for, for some of us.

[996] We've spoken about this offline.

[997] I'd love to get your thought about it here.

[998] If I sat down for a long form in -person conversation, with the president of Russia, Vladimir Putin.

[999] Would you potentially want to call in for a few minutes to join in on a conversation with him, moderated and translated by me?

[1000] Sure, yeah, sure, I'd be happy to do that.

[1001] You've shown interest in the Russian language.

[1002] Is this grounded in your interest in history of linguistics, culture, general curiosity?

[1003] I think it sounds cool.

[1004] Sounds cool, and that looks cool.

[1005] Well, it's, you know, it's a, It takes a moment to read Cyrillic.

[1006] Once you know what the Sorrelic characters stand for, actually, then reading Russian becomes a lot easier because there are a lot of words that are actually the same, like Bank is Bank.

[1007] So find the words that are exactly the same, and now you start to understand Cyrillic, yeah.

[1008] If you can sound it out, then it's much, there's at least some.

[1009] commonality of words.

[1010] What about the culture?

[1011] You love great engineering, physics.

[1012] There's a tradition of the science is there.

[1013] Sure.

[1014] You look at the 20th century from rocketry, so, you know, some of the greatest rockets of the space exploration has been done in the Soviet Union.

[1015] Yeah.

[1016] So do you draw inspiration from that history, just how this culture that in many ways, I mean, one of the sad things is because of the language, a lot of it is lost to history because it's not translated, all those kinds of, because it is in some ways an isolated culture.

[1017] It flourishes within its borders.

[1018] Yeah.

[1019] So do you draw inspiration from those folks from the history of science engineering there?

[1020] I mean, the Soviet Union, Russia and Ukraine as well and have a really strong history in spaceflight.

[1021] Some of the most advanced impressive things in history were done by the Soviet Union.

[1022] So one cannot help but admire the impressive rocket technology that was developed.

[1023] After the full of the Soviet Union, there's much less that that happened.

[1024] But still things are happening, but it's not quite at the frenetic pace that it was happening before the Soviet Union kind of dissolved into separate republics.

[1025] Yeah, I mean, there's Roscosmos, the Russian agency.

[1026] I look forward to a time when those countries with China are working together.

[1027] The United States are all working together.

[1028] Maybe a little bit of friendly competition, but...

[1029] I think friendly competition is good.

[1030] You know, governments are slow, and the only thing is slower than one government is a collection of governments.

[1031] So, yeah.

[1032] The Olympics would be boring if everyone just crossed the finishing line at the same time.

[1033] Yeah.

[1034] Nobody would watch.

[1035] Yeah.

[1036] And people wouldn't try hard to run fast and stuff.

[1037] So I think friendly competition is a good thing.

[1038] This is also a good place to give a shout -out to a video title, the entire Soviet rocket engine family tree by Tim Dodd, a .k .a. everyday astronaut.

[1039] It's like an hour and a half.

[1040] It gives the full history of Soviet rockets.

[1041] And people should definitely go check out and support Tim in general.

[1042] That guy is super excited about the future, super excited about spaceflight.

[1043] Every time I see anything by him, I just have a stupid smile on my face because he's so excited about stuff.

[1044] I love people like that.

[1045] Tim Dodd is really great.

[1046] If you're interested anything to do with space, he's in terms of explaining rocket technology to your average person he's awesome the best i'd say um and um i should say like the probably reason like uh i switched us from like rafter at one point was going to be a hydrogen engine um but hydrogen has a lot of challenges it's very low density it's a deep cryogen so it's only liquid at a very you know very close to absolute zero requires a lot of insulation.

[1047] So there's a lot of challenges there.

[1048] And I was actually reading a bit about Russian rocket engine development.

[1049] And at least the impression I had was that Soviet Union, Russia and Ukraine primarily, were actually in the process of switching to methylox.

[1050] and there were some interesting test stand data for ISP, like they were able to get up to like a 380 second ISP with a methylox engine.

[1051] And I was like, well, okay, that's actually really impressive.

[1052] So I think you could actually get a much lower cost, like in optimizing cost per time to orbit cost per time to Mars.

[1053] it's uh i think um methane oxygen is the way to go um and i was partly inspired by the russian work on the test stands uh with methylox engines and now for something completely different do you mind doing a bit of a meme review in the spirit of the great the powerful beauty pie let's say one to eleven just go over a few documents printed out we can try Let's try this.

[1054] I present to you document number uno.

[1055] I don't know.

[1056] Vlad the impaler discovers marshmallows.

[1057] That's not bad.

[1058] So you get it because he likes impaling things?

[1059] I don't know, three, whatever.

[1060] Oh, that's not very good.

[1061] This is ground in some engineering, some history.

[1062] Street.

[1063] Yeah, give us an 8 out of 10.

[1064] What do you think about nuclear power?

[1065] I'm in favor of nuclear power.

[1066] I think it's in a place that is not subject to extreme natural disasters, I think it's nuclear power is a great way to generate electricity.

[1067] I don't think we should be shutting down nuclear power stations.

[1068] Yeah, but what about Chernobyl?

[1069] Exactly.

[1070] So, I think people, there's like a lot of fear of radiation and stuff.

[1071] And it's, I guess, the problem is like a lot of people just don't understand.

[1072] They didn't study engineering or physics.

[1073] So they don't, it's just the word radiation just sounds scary, you know.

[1074] So they don't, they can't calibrate what radiation means.

[1075] But radiation is much less dangerous than, than you think.

[1076] So, like, for example, Fukushima, you know, when the Fukushima problem happened to the tsunami, the, I got people in California asking me if they should worry about radiation from Fukushima.

[1077] And I'm like, definitely not, not even slightly, not at all.

[1078] that is crazy and just to show like this is how like the dangers is so much overplayed compared to what what it really is that I actually flew to Fukushima and I actually I donated a solar power system for water treatment plant and and I made a point of eating locally grown vegetables um on TV in Fukushima like I'm still alive okay so it's not even that the risk of these events is low but the impact of them is impact is greatly exaggerated it's just human nature it's people don't know what radiation is like I've had people ask me like what about radiation from cell phones quoting causing brain cancer I'm like when you say radiation do you mean photons or particles then like that I don't know what what do you mean protons particles.

[1079] Do you mean let's say photons?

[1080] What frequency or wavelength?

[1081] And they're like no, I have no idea.

[1082] Like, do you know that everything's radiating all the time?

[1083] Like, what do you mean?

[1084] Like, yeah, everything's radiating all the time.

[1085] Photons are being emitted by all objects all the time, basically.

[1086] So, and if you want to know what it's what it means to stand in front of nuclear fire, go outside.

[1087] The sun is a gigantic, you know, thermonuclear reactor that you're staring right at it.

[1088] Are you still alive?

[1089] Yes.

[1090] Okay.

[1091] Yeah, I guess radiation is one of the words that could be used as a tool to fearmonger by certain people.

[1092] That's it.

[1093] I think people just don't understand.

[1094] I mean, that's the way to fight that fear, I suppose, is to understand, is to learn.

[1095] Yeah, just say like, okay, how many people have actually died from nuclear accidents?

[1096] It's like practically nothing.

[1097] And say how many people have died from, you know, coal plants, and it's a very big number.

[1098] So, like, obviously we should not be starting up coal plants and shutting down nuclear plants.

[1099] It just doesn't make any sense at all.

[1100] Coal plants, like, I don't know, 100 to a thousand times worse for health than nuclear power plants.

[1101] You want to go to the next one?

[1102] It's really bad.

[1103] It's 90, 180, and 360 degrees Everybody loves the math Nobody gives a shit about 270 It's not super funny I don't know like 203 Yeah This is not You know LOL situation Yeah That's pretty good The United States Oscillating between establishing And destroying dictatorships it's like a metric is that a metric yeah metronome yeah yeah it's uh 7 out of 10 it's kind of true oh yeah this is uh this is kind of personal for me next one oh man this is likea yeah well no this is or it's like referring to like or something as like as like a husband yeah yeah hello yes this is dog your wife was launched to space and then the last one is him with his eyes closed in a bottle of vodka yeah like it didn't come back No. They don't tell you the full story of, you know, what the love, the impact they had on the loved ones.

[1104] True.

[1105] That one gets an 11 for me. Just have the Soviet shadow.

[1106] Yeah, this keeps going on the Russian theme.

[1107] First man in space, nobody cares, first man in the moon.

[1108] Well, I think people do care.

[1109] No, I know, but there is.

[1110] Your Gargaran's names will be forever in history, I think.

[1111] there is something special about placing like stepping foot onto another totally foreign land it's not the journey like people that explore the oceans it's not as important to explore the oceans as to land on a whole new continent yeah this is about you oh yeah i'd love to get your comment on this yon musk after sending six point six billion dollars to the u .n to end world hunger you have three hours um you know i mean obviously six billion dollars is not going to end world to hunger so um so i mean the reality is at this point the world is producing uh far more food than it can really consume it like we don't have a caloric uh constraint at this point so where there is hunger it is almost always due to um it's like like civil war strife or some like um it's um it's It's not a thing that is extremely rare for it to be just a matter of like lack of money.

[1112] It's like, you know, it's like some, the Civil War and some country and like one part of the country is literally trying to starve the other part of the country.

[1113] So it's much more complex than something that money could solve.

[1114] It's geopolitics.

[1115] It's a lot of things.

[1116] It's human nature.

[1117] It's governments.

[1118] It's money, monetary systems, all that kind of stuff.

[1119] Yeah, food is extremely cheap these days.

[1120] It's like, I mean, the U .S. at this point, you know, among low -income families, obesity is actually another problem.

[1121] It's not, like, obesity is it's not hunger.

[1122] It's like too many calories.

[1123] So it's not that nobody's hungry anywhere.

[1124] It's just, it's just this is not a simple matter of adding money and solving it.

[1125] What do you think that one gets?

[1126] It's getting...

[1127] I'm not two.

[1128] Just going after Empire's World.

[1129] Where did you get those artifacts?

[1130] The British Museum.

[1131] Shout out to Monty Python.

[1132] We found them.

[1133] Yeah, the British Museum is pretty great.

[1134] I mean, admittedly, Britain did take these historical artifacts from all around the world and put them in London.

[1135] But, you know, it's not like people can't go see them.

[1136] So it is a convenient place to see these ancient artifacts is London for, you know, for a large segment of the world.

[1137] So I think, you know, on balance, the British Museum is a net good.

[1138] Although I'm sure a lot of countries are arguing about that.

[1139] Yeah.

[1140] It's like you want to make these historical artifacts accessible to as many people as possible.

[1141] And the British Museum, I think does a good job with that.

[1142] Even if there's a darker aspect to like the history of empire in general, whatever the empire.

[1143] however things were done it is the history that happened you can't sort of erase that history unfortunately you could just become better in the future that's the point yeah I mean it's like well how are we going to pass moral judgment on these things like it's like if you know if one is going to judge say the British Empire you're going to judge you know what everyone was doing at the time and how were the British relative to everyone and I think the brochure would actually get like a relatively good grade relatively good grade not in absolute terms but compared to whatever else was doing they were not the worst like said you got to look at these things in the context of the history at the time and say what were the alternatives and what are you comparing it against and I do not think it would be the case that Britain would get a a bad grade when looking at history at the time.

[1144] Now, if you judge history from, you know, from what is morally acceptable today, you're basically going to give everyone a failing grade.

[1145] I'm not clear.

[1146] I don't think anyone would get a passing grade in their morality of, like, you go back 300 years ago, like, who is getting a passing grade?

[1147] Basically, no one.

[1148] And we might not get a passing grade from generations that, that come after us uh what does that one get uh sure uh six seven seven for the monte python maybe i always love monte python they're great uh life of brian and the quest of holy grail are incredible yeah yeah yeah those serious eyebrows is brazinev how important you think is facial hair to great leadership well you got a new haircut is that is that is that is how does that affect your leadership i don't know hopefully not it doesn't um yeah the second is no one there's no one competing with bresden there's no one too those are like epic eyebrows so sure that's ridiculous give it a six or seven i don't know uh i like this like shakespeare an analysis of memes uh brezny he had a he had a flare for drama as well like you know showmanship yeah yeah it must come from the eyebrows all right invention great engineering look what I invented that's the best thing since ripped up bread yeah because they invented sliced bread am I just explaining memes at this point this is what my life has become um he's a meme or you're a meme what it like a you know like a scribe that like runs around with the kings and just like writes down memes I mean when was a cheeseburger invention that's like an epic invention yeah like like wow you know that was versus just like a burger or burger I guess a burger in general it's like you know um then there's like what is a burger what's a sandwich and then you start getting it's a pizza sandwich and what is the original it's it's it gets into an ontology argument yeah but everybody knows like if you order like a burger or cheeseburger or whatever and you like you get like you know tomato and some lettuce and onions and whatever and you know, mayor and ketchup and mustard.

[1149] It's like epic.

[1150] Yeah, but I'm sure they've had bread and meat separately for a long time and it was kind of a burger on the same plate but somebody who actually combined them into the same thing and they buy it and hold it makes it convenient.

[1151] It's a materials problem.

[1152] Like your hands don't get dirty and whatever.

[1153] Yeah, it's brilliant.

[1154] That is not what I would have guessed.

[1155] But everyone knows like if you order a cheeseburger, you know where you're getting you know it's not like some obtuse like i wonder what i'll get you know um you know uh fries are i mean great i mean they're the devil but fries are awesome um and uh yeah pizza is incredible food innovation doesn't get enough love yeah i guess is what we're getting at it's great um uh what about the uh matthew mcanahey austinite here uh president kennedy do you know how to put men on the moon yet and ask them no President Kennedy be a lot cooler if you did pretty much sure six six or seven I suppose and this is the last one that's funny someone drew a bunch of dicks all over the walls 16 chapel boys bathroom sure I'll give it nine it's it's really true this is our highest ranking meme for today I mean it's true like how do they get away with that.

[1156] Lots of nakedness.

[1157] I mean, dickpicks are, I mean, just something throughout history.

[1158] As long as people can draw things, there's been a dick pick.

[1159] It's a staple of human history.

[1160] It's a staple.

[1161] Consistence throughout human history.

[1162] You tweeted that you aspire to comedy, you're friends with Joe Rogan.

[1163] Might you do a short stand -up comedy set at some point in the future?

[1164] Maybe open for Joe, something like that.

[1165] Really, stand -up?

[1166] Actually, just full -on stand -up?

[1167] Full -on stand -stand -up?

[1168] that in there or is that I've never thought about that it's extremely difficult if at least that's what like Joe says and the comedian say huh I wonder if I could um I mean I want to find out you know I have done stand up for friends just uh impromptu you know I'll get get on like a roof and they they do laugh but they are friends too so I don't know if you got to caught, you know, like a room of strangers, are they going to actually also find it funny?

[1169] But I could try, see what happens.

[1170] I think you'd learn something either way.

[1171] Yeah.

[1172] I kind of love both when you bomb and when you do great, just watching people, how they deal with it.

[1173] It's so difficult.

[1174] It's so, you're so fragile up there.

[1175] It's just you.

[1176] And you think you're going to be funny.

[1177] And when it completely falls flat, it's just, it's beautiful to see people.

[1178] deal with like that I might have enough material to do standard I've never thought about it but I might have enough material I don't know like 15 minutes or something oh yeah yeah do a Netflix special I Netflix special sure what's your favorite Rick and Morty concept just to bring that on you is there there's a lot of scientific engineering ideas explored there there's the there's the butter robot It's a great show.

[1179] You like it?

[1180] Yeah, Rigger and Mordy's awesome.

[1181] Somebody that's exactly like you from an alternate dimension showed up there, Elon Tusk.

[1182] Yeah, that's right.

[1183] That you voiced.

[1184] Yeah.

[1185] Rigan Mordy certainly explores a lot of interesting concepts.

[1186] I'm sure like what's the favorite one.

[1187] I don't know.

[1188] The butter robot certainly is, you know, it's like, it's certainly possible to have too much sentience in a device.

[1189] Like you don't want to have your toast to be like a super genius toaster.

[1190] it's going to hate life because all it could just make is toast but it's like you don't want to have like superintel just stuck in a very limited device Do you think it's too easy if we're talking about from the engineering perspective of super intelligence like with Marvin the robot like is it it seems like it might be very easy to engineer just a depressed robot like it's not obvious to engineer a robot that's going to find a fulfilling existence same as humans I suppose those.

[1191] But I wonder if that's like the default.

[1192] If you don't do a good job on building a robot, it's going to be sad a lot.

[1193] Well, we can reprogram robots easier than we can reprogram humans.

[1194] So I guess if you let it evolve without tinkering, then it might get sad.

[1195] But you can change the optimization function and have it be a cheery robot.

[1196] You, like I mentioned, with SpaceX, you give a lot of people hope, and a lot of people look up to you, millions of people look up to you.

[1197] If we think about young people in high school, maybe in college, what advice would you give to them about if they want to try to do something big in this world, they want to really have a big positive impact?

[1198] What advice would you give them about their career, maybe about life in general?

[1199] try to be useful do things that are useful to your fellow human beings to the world it's very hard to be useful very hard you know are you contributing more than you consume you know like can you try to have a positive net contribution to society I think that's the thing to aim for You know, not to try to be sort of a leader for the sake of being a leader or whatever.

[1200] A lot of the time people who, a lot of times the people you want as leaders are the people who don't want to be leaders.

[1201] So if you can live a useful life, that is a good life, a life worth having lived.

[1202] you know and like I said I would encourage people to use the mental tools of physics and apply them broadly in life there are the best tools when you think about education and self -education what do you recommend so there's the university there is self -study there is a hands -on sort of finding a company or a place or a set of people that do the thing you're passionate about and joining them as early as possible.

[1203] There's taking a road trip across Europe for a few years and writing some poetry, which trajectory do you suggest in terms of learning about how you can become useful, as you mentioned, how you can have the most positive impact.

[1204] I encourage people to read a lot of books.

[1205] Just basically try to ingest as much information as you can.

[1206] And try to also just develop a good general knowledge.

[1207] So you at least have like a rough lay of the land of the knowledge landscape.

[1208] Like try to learn a little about a lot of things.

[1209] Because you might not know what you're really interested.

[1210] How would you know what you're really interested in if you at least aren't like doing it.

[1211] Peripheral exploration or broadly of the knowledge landscape?

[1212] and you talk to people from different walks of life and different industries and professions and skills and occupations like just try learn as much as possible man's search for a meeting isn't the whole thing a search for meaning is yeah what's the meeting of life and all you know but just generally like I said I would encourage people to read broadly in many different subject areas.

[1213] And then try to find something where there's an overlap of your talents and what you're interested in.

[1214] So people may be good at something, or they may have skill at a particular thing, but they don't like doing it.

[1215] So you want to try to find a thing where you're, that's a good combination of the things that you're inherently good at, but you also like.

[1216] doing um and um and reading is a super fast shortcut to to figure out which where are you you both good at it you like doing it and it will actually have positive impact well you got to learn about things somehow so reading a broad range it just really read read it you know more important was that kid i I read through the encyclopedia.

[1217] So that was pretty helpful.

[1218] And also things I didn't even know existed, a lot, so obviously.

[1219] It's like as broad as it gets.

[1220] Encyclopedias were digestible, I think, you know, whatever, 40 years ago.

[1221] So, you know, maybe read through the condensed version of the Encyclopedia Britannica.

[1222] I'd recommend that.

[1223] You can always skip subjects.

[1224] You read a few paragraphs and, no, you're not interested.

[1225] Just jump to the next one.

[1226] So read the encyclopedia or skim through it.

[1227] And, but, you know, I put a lot of stock and certainly have a lot of respect for someone who puts in an honest day's work to do useful things.

[1228] And just generally to have, like, not a zero -sum mindset or, like, have more of a, grow the pie mindset like the if you sort of say like when when we see people like some including some very smart people kind of taking an attitude of like like like like doing things that seem like morally questionable it's often because they have at a base sort of axiomatic level a zero -sum mindset and and they without realizing it they don't realize they have a zero -sum mindset or or at least they don't realize it consciously.

[1229] And so if you have zero -sum mindset, then the only way to get ahead is by taking things from others.

[1230] If it's like, if the, if the, if the pie is fixed, then the only way to have more pie is to take someone else's pie.

[1231] But this is false.

[1232] Like obviously the pie has grown dramatically over time, the economic pie.

[1233] So in reality, you can have, overuse this analogy.

[1234] you have a lot of, there's a lot of pie.

[1235] Pie, pie is not fixed.

[1236] So you really want to make sure you don't, you're not operating without realizing it from a zero -sum mindset, where the only way to get ahead is to take things from others, then that's going to result in you try to take things from others, which is not good.

[1237] It's much better to work on adding to the economic pie.

[1238] So, you know, creating, creating, like I said, creating more than you consume, doing more than you.

[1239] Yeah.

[1240] So that's a big deal.

[1241] I think there's like a fair number of people in finance that do have a bit of a zero -sum mindset.

[1242] I mean, it's all walks of life.

[1243] I've seen that.

[1244] One of the reasons Rogan inspires me is he celebrates all there's a lot.

[1245] There's not creating a constant competition.

[1246] Like, there's a scarcity of resources.

[1247] What happens when you celebrate others and you promote others, the ideas of others, it actually grows that pie.

[1248] I mean, every, like, the resources become less scarce.

[1249] And that applies in a lot of kinds of domains.

[1250] It applies in academia where a lot of people are very, see some funding for academic research, is zero sum.

[1251] It is not.

[1252] If you celebrate each other, if you make, if you get everybody to be excited about AI, about physics above, mathematics, I think there'd be more and more funding, and I think everybody wins.

[1253] Yeah, that applies, I think, broadly.

[1254] Yeah, yeah, exactly.

[1255] So last question about love and meaning.

[1256] What is the role of love in the human condition broadly and more specific to you?

[1257] How has love, romantic love, or otherwise made you a better person, a better human being?

[1258] Better engineer?

[1259] Now you're asking really perplexing questions.

[1260] it's hard to give up i mean there are many books poems and songs written about what is love and what is what exactly you know um you know what is love baby don't hurt me um that that's one of the great ones yes yeah you've you've earlier quoted shakespeare but that that's really up there yeah i mean love is a many splendid thing I mean there's because we've talked about so many inspiring things like be useful in the world sort of like solve problems alleviate suffering but it seems like connection between humans is a source you know it's a source of joy is the source of meaning and that's what love is friendship love I just wonder if you think about that kind of thing when you talk about preserving the light of human consciousness and us becoming a multi -planetary species.

[1261] I mean, to me at least, that means, like, if we're just alone and conscious and intelligent, it doesn't mean nearly as much as if we're with others, right?

[1262] And there's some magic created when we're together.

[1263] The friendship of it, and I think the highest form of it is love, which I think broadly is much bigger than just sort of romantic, but also, yeah, romantic love and family and those kinds of things.

[1264] Well, I mean, the reason I guess I care about us becoming a multi -planet species and a space -franc civilization is, foundationally, I love humanity.

[1265] And so I wish to see it prosper and do great things and be happy.

[1266] And if I did not love humanity, I would not care about these things.

[1267] So when you look at the whole of it, the human history, all the people was ever lived, all the people alive now.

[1268] It's pretty, we're okay.

[1269] On the whole, we're pretty interesting a bunch.

[1270] Yeah.

[1271] All things considered.

[1272] And I've read a lot of history, including the darkest, worst parts of it.

[1273] And despite all that, I think on balance, I still love humanity.

[1274] You joked about it with a 42.

[1275] What do you think is the meaning of this whole?

[1276] thing?

[1277] Is there a non -umerical representation?

[1278] Yeah, well, really, I think what Douglas Adams was saying in the Hitchhack's Guide of the Galaxy is that the universe is the answer.

[1279] And what we really need to figure out are what questions to ask about the answer that is the universe.

[1280] Yeah.

[1281] And that the question is the really the hard part.

[1282] And if you can properly frame the question, then the answer, relatively speaking, is easy.

[1283] So therefore, if you want to understand what questions to ask about the universe, you want to understand the meaning of life, we need to expand the scope and scale of consciousness so that we're better able to understand the nature of the universe and understand the meaning of life.

[1284] And ultimately, the most important part would be to ask the right question.

[1285] Yes.

[1286] Thereby elevating the role of the interviewer.

[1287] Yes, exactly.

[1288] as the most important human in the room.

[1289] Good questions are, you know, it's hard to come up with good questions.

[1290] Absolutely.

[1291] But yeah, like, it's like that is the foundation of my philosophy is that I am curious about the nature of the universe, and, you know, and obviously I will die, I don't know when I'll die, but I won't live forever.

[1292] But I would like to know that we're on a path to understanding the nature of the universe and the meaning of life and what questions to ask about the answer to that is the universe.

[1293] And so if we expand the scope and scale of humanity and consciousness in general, which includes silicon consciousness, then, you know, that seems like a fundamentally good thing.

[1294] Elon, like I said, I'm deeply grateful that you would spend your extremely valuable time with me today and also that you are given millions of people hope in this difficult time, this divisive time in this cynical time.

[1295] So I hope you do continue doing what you're doing.

[1296] Thank you so much for talking today.

[1297] Oh, you're welcome.

[1298] Thanks for excellent questions.

[1299] Thanks for listening to this conversation with Elon Musk.

[1300] To support this podcast, please check out our sponsors in the description.

[1301] And now, let me leave you with some words from Elon Musk himself.

[1302] When something is important enough, You do it even if the odds are not in your favor.

[1303] Thank you for listening and hope to see you next time.