back to indexElon Musk: SpaceX, Mars, Tesla Autopilot, Self-Driving, Robotics, and AI | Lex Fridman Podcast #252
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The following is a conversation with Elon Musk,
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his third time on this, The Lex Friedman Podcast.
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Yeah, make yourself comfortable.
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You don't do the headphone thing?
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I mean, how close do I need to get up to the same place?
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The closer you are, the sexier you sound.
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Can't get enough of your love, baby.
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I'm gonna clip that out
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any time somebody messages me about it.
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If you want my body and you think I'm sexy,
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come right out and tell me so.
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Do, do, do, do, do.
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Okay, serious mode activate.
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Come on, you're Russian.
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You can be serious.
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Everyone's serious all the time in Russia.
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Yeah, yeah, we'll get there.
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Allow me to say that the SpaceX launch
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of human beings to orbit on May 30th, 2020
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was seen by many as the first step
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in a new era of human space exploration.
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These human space flight missions were a beacon of hope
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to me and to millions over the past two years
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as our world has been going through
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one of the most difficult periods in recent human history.
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We saw, we see the rise of division, fear, cynicism,
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and the loss of common humanity
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right when it is needed most.
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So first, Elon, let me say thank you
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for giving the world hope and reason
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to be excited about the future.
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Oh, it's kind of easy to say.
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I do want to do that.
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Humanity has obviously a lot of issues
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and people at times do bad things,
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but despite all that, I love humanity
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and I think we should make sure we do everything we can
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to have a good future and an exciting future
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and one where that maximizes the happiness of the people.
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Let me ask about Crew Dragon Demo 2.
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So that first flight with humans on board,
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how did you feel leading up to that launch?
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What was going through your mind?
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So much was at stake.
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Yeah, no, that was extremely stressful, no question.
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We obviously could not let them down in any way.
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So extremely stressful, I'd say, to say the least.
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I was confident that at the time that we launched
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that no one could think of anything at all to do
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that would improve the probability of success.
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And we racked our brains to think of any possible way
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to improve the probability of success.
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We could not think of anything more, nor could NASA.
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And so that's just the best that we could do.
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So then we went ahead and launched.
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Now, I'm not a religious person,
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but I nonetheless got on my knees and prayed for that mission.
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Were you able to sleep?
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How did it feel when it was a success,
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first when the launch was a success,
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and when they returned back home or back to Earth?
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It was a great relief.
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Yeah, for high stress situations,
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I find it's not so much elation as relief.
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And I think once, as we got more comfortable
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and proved out the systems,
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because we really got to make sure everything works,
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it was definitely a lot more enjoyable
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with the subsequent astronaut missions.
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And I thought the Inspiration mission
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was actually a very inspiring Inspiration 4 mission.
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I'd encourage people to watch the Inspiration documentary
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on Netflix, it's actually really good.
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And it really isn't, I was actually inspired by that.
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And so that one I felt I was kind of able
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to enjoy the actual mission
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and not just be super stressed all the time.
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So for people that somehow don't know,
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it's the all civilian, first time all civilian
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out to space, out to orbit.
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Yeah, and it was I think the highest orbit
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that in like, I don't know, 30 or 40 years or something.
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The only one that was higher was the one shuttle,
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sorry, a Hubble servicing mission.
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And then before that, it would have been Apollo in 72.
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So it's cool, it's good.
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I think as a species, we want to be continuing
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to do better and reach higher ground.
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And like, I think it would be tragic, extremely tragic
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if Apollo was the high watermark for humanity,
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and that's as far as we ever got.
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And it's concerning that here we are 49 years
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after the last mission to the moon.
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And so almost half a century, and we've not been back.
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And that's worrying.
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It's like, does that mean we've peaked as a civilization
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So like, I think we got to get back to the moon
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and build a base there, a science base.
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I think we could learn a lot about the nature
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of the universe if we have a proper science base
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on the moon, like we have a science base in Antarctica
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and many other parts of the world.
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And so that's like, I think the next big thing,
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we've got to have like a serious moon base
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and then get people to Mars and get out there
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and be a spacefaring civilization.
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I'll ask you about some of those details,
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but since you're so busy with the hard engineering
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challenges of everything that's involved,
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are you still able to marvel at the magic of it all,
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of space travel, of every time the rocket goes up,
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especially when it's a crewed mission?
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Or are you just so overwhelmed with all the challenges
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that you have to solve?
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And actually, sort of to add to that,
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the reason I wanted to ask this question of May 30th,
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it's been some time, so you can look back
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and think about the impact already.
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It's already, at the time it was an engineering problem
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maybe, now it's becoming a historic moment.
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Like it's a moment that, how many moments
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will be remembered about the 21st century?
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To me, that or something like that,
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maybe Inspiration4, one of those would be remembered
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as the early steps of a new age of space exploration.
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Yeah, I mean, during the launches itself,
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so I mean, I think maybe some people will know,
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but a lot of people don't know,
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is like I'm actually the chief engineer of SpaceX,
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so I've signed off on pretty much all the design decisions.
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And so if there's something that goes wrong
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with that vehicle, it's fundamentally my fault, so.
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So I'm really just thinking about all the things that,
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like, so when I see the rocket,
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I see all the things that could go wrong
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and the things that could be better
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and the same with the Dragon spacecraft.
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It's like, other people will see,
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oh, this is a spacecraft or a rocket
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and this looks really cool.
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I'm like, I've like a readout of like,
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these are the risks, these are the problems,
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that's what I see.
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Like, choo choo choo choo choo choo choo.
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So it's not what other people see
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when they see the product, you know.
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So let me ask you then to analyze Starship
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I know you have, you'll talk about,
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in more detail about Starship in the near future, perhaps.
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Yeah, we can talk about it now if you want.
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But just in that same way, like you said,
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you see, when you see a rocket,
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you see sort of a list of risks.
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In that same way, you said that Starship
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is a really hard problem.
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So there's many ways I can ask this,
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but if you magically could solve one problem perfectly,
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one engineering problem perfectly,
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which one would it be?
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On, sorry, on Starship.
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So is it maybe related to the efficiency,
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the engine, the weight of the different components,
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the complexity of various things,
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maybe the controls of the crazy thing it has to do to land?
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No, it's actually by far the biggest thing
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absorbing my time is engine production.
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Not the design of the engine,
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but I've often said prototypes are easy, production is hard.
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So we have the most advanced rocket engine
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that's ever been designed.
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Cause I'd say currently the best rocket engine ever
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is probably the RD180 or RD170,
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that's the Russian engine basically.
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And still, I think an engine should only count
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if it's gotten something to orbit.
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So our engine has not gotten anything to orbit yet,
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but it is, it's the first engine
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that's actually better than the Russian RD engines,
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which were amazing design.
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So you're talking about Raptor engine.
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What makes it amazing?
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What are the different aspects of it that make it,
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like what are you the most excited about
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if the whole thing works in terms of efficiency,
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all those kinds of things?
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Well, it's, the Raptor is a full flow
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staged combustion engine
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and it's operating at a very high chamber pressure.
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So one of the key figures of merit, perhaps the key figure
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of merit is what is the chamber pressure
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at which the rocket engine can operate?
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That's the combustion chamber pressure.
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So Raptor is designed to operate at 300 bar,
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possibly maybe higher, that's 300 atmospheres.
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So the record right now for operational engine
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is the RD engine that I mentioned, the Russian RD,
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which is I believe around 267 bar.
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And the difficulty of the chamber pressure
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is increases on a nonlinear basis.
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So 10% more chamber pressure is more like 50% more difficult.
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But that chamber pressure is,
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that is what allows you to get a very high power density
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So enabling a very high thrust to weight ratio
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and a very high specific impulse.
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So specific impulse is like a measure of the efficiency
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of a rocket engine.
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It's really the effect of exhaust velocity
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of the gas coming out of the engine.
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So with a very high chamber pressure,
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you can have a compact engine
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that nonetheless has a high expansion ratio,
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which is the ratio between the exit nozzle and the throat.
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So you see a rocket engine's got sort of like a hourglass
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shape, it's like a chamber and then it necks down
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and there's a nozzle and the ratio of the exit diameter
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to the throat is the expansion ratio.
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So why is it such a hard engine to manufacture at scale?
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It's very complex.
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So a lot of, what is complexity mean here?
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There's a lot of components involved.
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There's a lot of components and a lot of unique materials
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that, so we had to invent several alloys
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that don't exist in order to make this engine work.
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It's a materials problem too.
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It's a materials problem and in a staged combustion,
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a full flow staged combustion,
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there are many feedback loops in the system.
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So basically you've got propellants and hot gas
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flowing simultaneously to so many different places
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on the engine and they all have a recursive effect
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So you change one thing here, it has a recursive effect
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here, it changes something over there
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and it's quite hard to control.
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Like there's a reason no one's made this before.
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And the reason we're doing a staged combustion full flow
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is because it has the highest possible efficiency.
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So in order to make a fully reusable rocket,
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which that's the really the holy grail of orbital rocketry.
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You have to have, everything's gotta be the best.
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It's gotta be the best engine, the best airframe,
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the best heat shield, extremely light avionics,
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very clever control mechanisms.
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You've got to shed mass in any possible way that you can.
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For example, we are, instead of putting landing legs
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on the booster and ship, we are gonna catch them
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with a tower to save the weight of the landing legs.
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So that's like, I mean, we're talking about catching
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the largest flying object ever made with,
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on a giant tower with chopstick arms.
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It's like Karate Kid with the fly, but much bigger.
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I mean, pulling something like that home.
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This probably won't work the first time.
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Anyway, so this is bananas, this is banana stuff.
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So you mentioned that you doubt, well, not you doubt,
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but there's days or moments when you doubt
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that this is even possible.
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It's so difficult.
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The possible part is, well, at this point,
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I think we will get Starship to work.
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There's a question of timing.
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How long will it take us to do this?
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How long will it take us to actually achieve
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full and rapid reusability?
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Cause it will take probably many launches
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before we are able to have full and rapid reusability.
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But I can say that the physics pencils out.
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Like we're not, like at this point,
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I'd say we're confident that, like let's say,
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I'm very confident success is in the set
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of all possible outcomes.
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For a while there, I was not convinced
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that success was in the set of possible outcomes,
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which is very important actually.
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But so we're saying there's a chance.
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I'm saying there's a chance, exactly.
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Just not sure how long it will take.
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We have a very talented team.
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They're working night and day to make it happen.
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And like I said, the critical thing to achieve
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for the revolution in space flight
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and for humanity to be a spacefaring civilization
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is to have a fully and rapidly reusable rocket,
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There's not even been any orbital rocket
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that's been fully reusable ever.
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And this has always been the holy grail of rocketry.
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And many smart people, very smart people,
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have tried to do this before and they've not succeeded.
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So, cause it's such a hard problem.
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What's your source of belief in situations like this?
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When the engineering problem is so difficult,
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there's a lot of experts, many of whom you admire,
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who have failed in the past.
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And a lot of people, a lot of experts,
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maybe journalists, all the kind of,
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the public in general have a lot of doubt
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about whether it's possible.
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And you yourself know that even if it's a non null set,
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non empty set of success, it's still unlikely
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or very difficult.
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Like where do you go to, both personally,
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intellectually as an engineer, as a team,
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like for source of strength needed
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to sort of persevere through this.
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And to keep going with the project, take it to completion.
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A source of strength.
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That's really not how I think about things.
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I mean, for me, it's simply this,
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this is something that is important to get done
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and we should just keep doing it or die trying.
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And I don't need a source of strength.
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So quitting is not even like...
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That's not, it's not in my nature.
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And I don't care about optimism or pessimism.
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Fuck that, we're gonna get it done.
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Gonna get it done.
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Can you then zoom back in to specific problems
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with Starship or any engineering problems you work on?
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Can you try to introspect your particular
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biological neural network, your thinking process
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and describe how you think through problems,
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the different engineering and design problems?
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Is there like a systematic process?
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You've spoken about first principles thinking,
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but is there a kind of process to it?
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Well, yeah, like saying like physics is a law
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and everything else is a recommendation.
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Like I've met a lot of people that can break the law,
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but I haven't met anyone who could break physics.
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So the first, for any kind of technology problem,
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you have to sort of just make sure
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you're not violating physics.
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And first principles analysis, I think,
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is something that can be applied to really any walk of life,
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It's really just saying, let's boil something down
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to the most fundamental principles.
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The things that we are most confident are true
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at a foundational level.
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And that sets your axiomatic base,
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and then you reason up from there,
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and then you cross check your conclusion
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against the axiomatic truths.
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So some basics in physics would be like,
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are you violating conservation of energy or momentum
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or something like that?
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Then it's not gonna work.
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So that's just to establish, is it possible?
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And another good physics tool
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is thinking about things in the limit.
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If you take a particular thing
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and you scale it to a very large number
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or to a very small number, how do things change?
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Both like in number of things you manufacture
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or something like that, and then in time?
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Yeah, like let's say take an example of like manufacturing,
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which I think is just a very underrated problem.
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And like I said, it's much harder to
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take an advanced technology product
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and bring it into volume manufacturing
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than it is to design it in the first place.
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My orders of magnitude.
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So let's say you're trying to figure out
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is like why is this part or product expensive?
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Is it because of something fundamentally foolish
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that we're doing or is it because our volume is too low?
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And so then you say, okay, well, what if our volume
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was a million units a year?
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Is it still expensive?
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That's what I mean by thinking about things in the limit.
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If it's still expensive at a million units a year,
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then volume is not the reason why your thing is expensive.
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There's something fundamental about the design.
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And then you then can focus on reducing the complexity
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or something like that in the design.
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You gotta change the design to change the part
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to be something that is not fundamentally expensive.
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But like that's a common thing in rocketry
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because the unit volume is relatively low.
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And so a common excuse would be,
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well, it's expensive because our unit volume is low.
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And if we were in like automotive or something like that,
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or consumer electronics, then our costs would be lower.
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I'm like, okay, so let's say
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now you're making a million units a year.
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Is it still expensive?
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If the answer is yes, then economies of scale
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are not the issue.
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Do you throw into manufacturing,
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do you throw like supply chain?
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Talked about resources and materials and stuff like that.
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Do you throw that into the calculation
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of trying to reason from first principles,
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like how we're gonna make the supply chain work here?
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And then the cost of materials, things like that.
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Or is that too much?
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Exactly, so like a good example,
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I think of thinking about things in the limit
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is if you take any machine or whatever,
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like take a rocket or whatever,
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and say, if you look at the raw materials in the rocket,
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so you're gonna have like aluminum, steel, titanium,
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Inconel, specialty alloys, copper,
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and you say, what's the weight of the constituent elements,
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of each of these elements,
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and what is their raw material value?
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And that sets the asymptotic limit
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for how low the cost of the vehicle can be
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unless you change the materials.
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So, and then when you do that,
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I call it like maybe the magic one number
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or something like that.
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So that would be like, if you had the,
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like just a pile of these raw materials,
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again, you could wave the magic wand
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and rearrange the atoms into the final shape.
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That would be the lowest possible cost
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that you could make this thing for
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unless you change the materials.
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So then, and that is almost always a very low number.
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So then what's actually causing things to be expensive
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is how you put the atoms into the desired shape.
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Yeah, actually, if you don't mind me taking a tiny tangent,
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I often talk to Jim Keller,
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who's somebody that worked with you as a friend.
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Jim was, yeah, did great work at Tesla.
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So I suppose he carries the flame
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with the same kind of thinking
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that you're talking about now.
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And I guess I see that same thing
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at Tesla and SpaceX folks who work there,
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they kind of learn this way of thinking
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and it kind of becomes obvious almost.
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But anyway, I had argument, not argument,
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but he educated me about how cheap it might be
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to manufacture a Tesla bot.
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We just, we had an argument.
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How can you reduce the cost of scale of producing a robot?
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Because I've gotten the chance to interact quite a bit,
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obviously, in the academic circles with humanoid robots
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and then Boston Dynamics and stuff like that.
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And they're very expensive to build.
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And then Jim kind of schooled me on saying like,
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okay, like this kind of first principles thinking
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of how can we get the cost of manufacturing down?
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I suppose you do that,
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you have done that kind of thinking for Tesla bot
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and for all kinds of complex systems
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that are traditionally seen as complex.
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And you say, okay, how can we simplify everything down?
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Yeah, I mean, I think if you are really good
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at manufacturing, you can basically make,
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at high volume, you can basically make anything
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for a cost that asymptotically approaches
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the raw material value of the constituents
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plus any intellectual property that you need to do license.
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It's not like that's a very hard thing to do,
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but it is possible for anything.
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Anything in volume can be made, like I said,
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for a cost that asymptotically approaches
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this raw material constituents
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plus intellectual property license rights.
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So what'll often happen in trying to design a product
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is people will start with the tools and parts
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and methods that they are familiar with
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and then try to create the product
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using their existing tools and methods.
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The other way to think about it is actually imagine the,
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try to imagine the platonic ideal of the perfect product
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or technology, whatever it might be.
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And say, what is the perfect arrangement of atoms
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that would be the best possible product?
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And now let us try to figure out
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how to get the atoms in that shape.
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I mean, it sounds,
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it's almost like a Rick and Morty absurd
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until you start to really think about it
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and you really should think about it in this way
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because everything else is kind of,
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if you think, you might fall victim to the momentum
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of the way things were done in the past
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unless you think in this way.
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Well, just as a function of inertia,
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people will want to use the same tools and methods
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that they are familiar with.
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That's what they'll do by default.
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And then that will lead to an outcome of things
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that can be made with those tools and methods
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but is unlikely to be the platonic ideal
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of the perfect product.
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So then, so that's why it's good to think of things
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in both directions.
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So like, what can we build with the tools that we have?
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But then, but also what is the perfect,
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the theoretical perfect product look like?
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And that theoretical perfect part
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is gonna be a moving target
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because as you learn more,
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the definition of that perfect product will change
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because you don't actually know what the perfect product is,
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but you can successfully approximate a more perfect product.
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So think about it like that and then saying,
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okay, now what tools, methods, materials,
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whatever do we need to create
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in order to get the atoms in that shape?
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But people rarely think about it that way.
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But it's a powerful tool.
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I should mention that the brilliant Siobhan Ziles
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is hanging out with us in case you hear a voice
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of wisdom from outside, from up above.
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Okay, so let me ask you about Mars.
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You mentioned it would be great for science
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to put a base on the moon to do some research.
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But the truly big leap, again,
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in this category of seemingly impossible,
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is to put a human being on Mars.
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When do you think SpaceX will land a human being on Mars?
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Hmm, best case is about five years, worst case, 10 years.
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Okay, so I'm gonna ask you about Mars.
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You mentioned it would be great for science
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to put a base on the moon to do some research.
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But the truly big leap, again,
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in this category of seemingly impossible,
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is to put a human being on Mars.
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But the truly big leap, again,
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in this category of seemingly impossible,
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is to put a human being on Mars.
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When do you think SpaceX will land a human being on Mars?
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Hmm, best case is about five years, worst case, 10 years.
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What are the determining factors, would you say,
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from an engineering perspective?
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Or is that not the bottlenecks?
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I don't know, order of magnitude or something like that.
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It's a lot, it's really next level.
link |
So, and the fundamental optimization of Starship
link |
is minimizing cost per ton to orbit,
link |
and ultimately cost per ton to the surface of Mars.
link |
This may seem like a mercantile objective,
link |
but it is actually the thing that needs to be optimized.
link |
Like there is a certain cost per ton to the surface of Mars
link |
where we can afford to establish a self sustaining city,
link |
and then above that, we cannot afford to do it.
link |
So right now, you couldn't fly to Mars for a trillion dollars.
link |
No amount of money could get you a ticket to Mars.
link |
So we need to get that above,
link |
to get that something that is actually possible at all.
link |
But that's, we don't just want to have,
link |
with Mars, flags and footprints,
link |
and then not come back for a half century,
link |
like we did with the Moon.
link |
In order to pass a very important, great filter,
link |
I think we need to be a multi planet species.
link |
This may sound somewhat esoteric to a lot of people,
link |
but eventually, given enough time,
link |
there's something, Earth is likely to experience
link |
some calamity that could be something
link |
that humans do to themselves,
link |
or an external event like happened to the dinosaurs.
link |
But eventually, if none of that happens,
link |
and somehow magically we keep going,
link |
then the Sun is gradually expanding,
link |
and will engulf the Earth,
link |
and probably Earth gets too hot for life
link |
in about 500 million years.
link |
It's a long time, but that's only 10% longer
link |
than Earth has been around.
link |
And so if you think about the current situation,
link |
it's really remarkable, and kind of hard to believe,
link |
but Earth's been around four and a half billion years,
link |
and this is the first time in four and a half billion years
link |
that it's been possible to extend life beyond Earth.
link |
And that window of opportunity may be open
link |
for a long time, and I hope it is,
link |
but it also may be open for a short time.
link |
And I think it is wise for us to act quickly
link |
while the window is open, just in case it closes.
link |
Yeah, the existence of nuclear weapons, pandemics,
link |
all kinds of threats should kind of give us some motivation.
link |
I mean, civilization could die with a bang or a whimper.
link |
If it dies as a demographic collapse,
link |
then it's more of a whimper, obviously.
link |
And if it's World War III, it's more of a bang.
link |
But these are all risks.
link |
I mean, it's important to think of these things
link |
and just think of things like probabilities, not certainties.
link |
There's a certain probability
link |
that something bad will happen on Earth.
link |
I think most likely the future will be good.
link |
But there's like, let's say for argument's sake,
link |
a 1% chance per century of a civilization ending event.
link |
Like that was Stephen Hawking's estimate.
link |
I think he might be right about that.
link |
So then we should basically think of this
link |
being a multi planet species,
link |
just like taking out a planet from the sky,
link |
multi planet species, just like taking out insurance
link |
Like life insurance for life.
link |
It's turned into an infomercial real quick.
link |
Life insurance for life, yes.
link |
And we can bring the creatures from,
link |
plants and animals from Earth to Mars
link |
and breathe life into the planet
link |
and have a second planet with life.
link |
That would be great.
link |
They can't bring themselves there.
link |
So if we don't bring them to Mars,
link |
then they will just for sure all die
link |
when the sun expands anyway.
link |
And then that'll be it.
link |
What do you think is the most difficult aspect
link |
of building a civilization on Mars?
link |
Terraforming Mars, like from an engineering perspective,
link |
from a financial perspective, human perspective,
link |
to get a large number of folks there
link |
who will never return back to Earth?
link |
No, they could certainly return.
link |
Some will return back to Earth.
link |
They will choose to stay there
link |
for the rest of their lives.
link |
But we need the spaceships back,
link |
like the ones that go to Mars.
link |
We need them back.
link |
So you can hop on if you want.
link |
But we can't just not have the spaceships come back.
link |
Those things are expensive.
link |
We need them back.
link |
I'd like to come back and do another trip.
link |
I mean, do you think about the terraforming aspect,
link |
like actually building?
link |
Are you so focused right now on the spaceships part
link |
that's so critical to get to Mars?
link |
We absolutely, if you can't get there,
link |
nothing else matters.
link |
So, and like I said, we can't get there
link |
at some extraordinarily high cost.
link |
I mean, the current cost of, let's say,
link |
one ton to the surface of Mars
link |
is on the order of a billion dollars.
link |
So, because you don't just need the rocket
link |
and the launch and everything,
link |
you need like heat shield, you need guidance system,
link |
you need deep space communications,
link |
you need some kind of landing system.
link |
So, like rough approximation would be a billion dollars
link |
per ton to the surface of Mars right now.
link |
This is obviously way too expensive
link |
to create a self sustaining civilization.
link |
So we need to improve that by at least a factor of 1,000.
link |
A million per ton?
link |
Yes, ideally much less than a million ton.
link |
But if it's not, like it's gotta be,
link |
so you have to say like, well,
link |
how much can society afford to spend
link |
or just want to spend on a self sustaining city on Mars?
link |
The self sustaining part is important.
link |
Like it's just the key threshold,
link |
the great filter will have been passed
link |
when the city on Mars can survive
link |
even if the spaceships from Earth stop coming
link |
for any reason, doesn't matter what the reason is,
link |
but if they stop coming for any reason,
link |
will it die out or will it not?
link |
And if there's even one critical ingredient missing,
link |
then it still doesn't count.
link |
It's like, you know, if you're on a long sea voyage
link |
and you've got everything except vitamin C,
link |
it's only a matter of time, you know, you're gonna die.
link |
So we're gonna get a Mars city
link |
to the point where it's self sustaining.
link |
I'm not sure this will really happen in my lifetime,
link |
but I hope to see it at least have a lot of momentum.
link |
And then you could say, okay,
link |
what is the minimum tonnage necessary
link |
to have a self sustaining city?
link |
And there's a lot of uncertainty about this.
link |
You could say like, I don't know,
link |
it's probably at least a million tons
link |
cause you have to set up a lot of infrastructure on Mars.
link |
Like I said, you can't be missing anything
link |
that in order to be self sustaining,
link |
you can't be missing, like you need,
link |
you know, semiconductor, fabs, you need iron ore refineries,
link |
like you need lots of things, you know.
link |
So, and Mars is not super hospitable.
link |
It's the least inhospitable planet,
link |
but it's definitely a fixer of a planet.
link |
Earth is pretty good.
link |
Earth is like easy, yeah.
link |
And also I should, we should clarify in the solar system.
link |
Yes, in the solar system.
link |
There might be nice like vacation spots.
link |
There might be some great planets out there,
link |
but it's hopeless.
link |
Too hard to get there?
link |
Yeah, way, way, way, way, way too hard to say the least.
link |
Let me push back on that, not really a push back,
link |
but a quick curve ball of a question.
link |
So you did mention physics as the first starting point.
link |
So, general relativity allows for wormholes.
link |
They technically can exist.
link |
Do you think those can ever be leveraged
link |
by humans to travel fast in the speed of light?
link |
Well, the wormhole thing is debatable.
link |
The, we currently do not know of any means
link |
of going faster than the speed of light.
link |
There is like, there are some ideas about having space.
link |
Like so, you can only move at the speed of light
link |
through space, but if you can make space itself move,
link |
that's like, that's warping space.
link |
Space is capable of moving faster than the speed of light.
link |
Like the universe in the Big Bang,
link |
the universe expanded at much,
link |
much more than the speed of light by a lot.
link |
So, but the, if this is possible,
link |
the amount of energy required to warp space
link |
is so gigantic, it boggles the mind.
link |
So all the work you've done with propulsion,
link |
how much innovation is possible with rocket propulsion?
link |
Is this, I mean, you've seen it all,
link |
and you're constantly innovating in every aspect.
link |
How much is possible?
link |
Like how much, can you get 10x somehow?
link |
Is there something in there in physics
link |
that you can get significant improvement
link |
in terms of efficiency of engines
link |
and all those kinds of things?
link |
Well, as I was saying, really the Holy Grail
link |
is a fully and rapidly reusable orbital system.
link |
So right now, the Falcon 9
link |
is the only reusable rocket out there,
link |
but the booster comes back and lands,
link |
and you've seen the videos,
link |
and we get the nose cone fairing back,
link |
but we do not get the upper stage back.
link |
So that means that we have a minimum cost
link |
of building an upper stage.
link |
And you can think of like a two stage rocket
link |
of sort of like two airplanes,
link |
like a big airplane and a small airplane.
link |
And we get the big airplane back,
link |
but not the small airplane.
link |
And so it still costs a lot.
link |
So that upper stage is at least $10 million.
link |
And then the degree of,
link |
the booster is not as rapidly and completely reusable
link |
as we'd like in order of the fairings.
link |
So our kind of minimum marginal cost
link |
and our counting overhead for per flight
link |
is on the order of 15 to $20 million, maybe.
link |
So that's extremely good for,
link |
it's by far better than any rocket ever in history.
link |
But with full and rapid reusability,
link |
we can reduce the cost per ton to orbit
link |
by a factor of 100.
link |
But just think of it like,
link |
like imagine if you had an aircraft or something or a car.
link |
And if you had to buy a new car
link |
every time you went for a drive,
link |
that would be very expensive.
link |
It'd be silly, frankly.
link |
But in fact, you just refuel the car or recharge the car.
link |
And that makes your trip like,
link |
I don't know, a thousand times cheaper.
link |
So it's the same for rockets.
link |
If you, it's very difficult to make this complex machine
link |
that can go to orbit.
link |
And so if you cannot reuse it
link |
and have to throw even any part of,
link |
any significant part of it away,
link |
that massively increases the cost.
link |
So, you know, Starship in theory
link |
could do a cost per launch of like a million,
link |
maybe $2 million or something like that.
link |
And put over a hundred tons in orbit, which is crazy.
link |
Yeah, that's incredible.
link |
So you're saying like it's by far the biggest bang
link |
for the buck is to make it fully reusable
link |
versus like some kind of brilliant breakthrough
link |
in theoretical physics.
link |
No, no, there's no, there's no brilliant break.
link |
No, there's no, just make the rocket reusable.
link |
This is an extremely difficult engineering problem.
link |
No new physics is required.
link |
Just brilliant engineering.
link |
Let me ask a slightly philosophical fun question.
link |
Gotta ask, I know you're focused on getting to Mars,
link |
but once we're there on Mars, what do you,
link |
what form of government, economic system, political system
link |
do you think would work best
link |
for an early civilization of humans?
link |
Is, I mean, the interesting reason to talk about this stuff,
link |
it also helps people dream about the future.
link |
I know you're really focused
link |
about the short term engineering dream,
link |
but it's like, I don't know,
link |
there's something about imagining an actual civilization
link |
on Mars that gives people, really gives people hope.
link |
Well, it would be a new frontier and an opportunity
link |
to rethink the whole nature of government,
link |
just as was done in the creation of the United States.
link |
So, I mean, I would suggest having a direct democracy,
link |
people vote directly on things
link |
as opposed to representative democracy.
link |
So representative democracy, I think,
link |
is too subject to a special interest
link |
and a coercion of the politicians and that kind of thing.
link |
So I'd recommend that there was just direct democracy,
link |
people vote on laws, the population votes on laws themselves,
link |
and then the laws must be short enough
link |
that people can understand them.
link |
Yeah, and then like keeping a well informed populace,
link |
like really being transparent about all the information,
link |
about what they're voting for.
link |
Yeah, absolute transparency.
link |
Yeah, and not make it as annoying as those cookies
link |
we have to accept. Accept cookies.
link |
I've always, like, you know,
link |
there's like always like a slight amount of trepidation
link |
when you click accept cookies,
link |
like I feel as though there's like perhaps
link |
like a very tiny chance that it'll open a portal to hell
link |
or something like that.
link |
That's exactly how I feel.
link |
Why do they, why do they keep wanting me to accept it?
link |
What do they want with this cookie?
link |
Like somebody got upset with accepting cookies
link |
or something somewhere, who cares?
link |
Like so annoying to keep accepting all these cookies.
link |
To me, this is just a great example.
link |
Yes, you can have my damn cookie.
link |
I don't care, whatever.
link |
Heard it from Ilhan first.
link |
He accepts all your damn cookies.
link |
Yeah, and stop asking me.
link |
Yeah, it's one example of implementation
link |
of a good idea done really horribly.
link |
Yeah, it's somebody who was like,
link |
there's some good intentions of like privacy or whatever,
link |
but now everyone's just has to accept cookies
link |
and it's not, you know, you have billions of people
link |
who have to keep clicking accept cookie.
link |
It's super annoying.
link |
Then we just accept the damn cookie, it's fine.
link |
There is like, I think a fundamental problem that we're,
link |
because we've not really had a major,
link |
like a world war or something like that in a while.
link |
And obviously we would like to not have world wars.
link |
There's not been a cleansing function
link |
for rules and regulations.
link |
So wars did have, you know, some sort of aligning
link |
in that there would be a reset on rules
link |
and regulations after a war.
link |
So World Wars I and II,
link |
there were huge resets on rules and regulations.
link |
Now, if society does not have a war
link |
and there's no cleansing function
link |
or garbage collection for rules and regulations,
link |
then rules and regulations will accumulate every year
link |
because they're immortal.
link |
There's no actual, humans die, but the laws don't.
link |
So we need a garbage collection function
link |
for rules and regulations.
link |
They should not just be immortal
link |
because some of the rules and regulations
link |
that are put in place will be counterproductive,
link |
done with good intentions, but counterproductive.
link |
Sometimes not done with good intentions.
link |
So if rules and regulations just accumulate every year
link |
and you get more and more of them,
link |
then eventually you won't be able to do anything.
link |
You're just like Gulliver with, you know,
link |
tied down by thousands of little structures
link |
by thousands of little strings.
link |
And we see that in, you know, US and like basically
link |
all economies that have been around for a while
link |
and regulators and legislators create new rules
link |
and regulations every year,
link |
but they don't put effort into removing them.
link |
And I think that's very important that we put effort
link |
into removing rules and regulations.
link |
But it gets tough because you get special interests
link |
that then are dependent on, like they have, you know,
link |
a vested interest in that whatever rule and regulation
link |
and then they fight to not get it removed.
link |
Yeah, so I mean, I guess the problem with the constitution
link |
is it's kind of like C versus Java
link |
because it doesn't have any garbage collection built in.
link |
I think there should be, when you first said
link |
the metaphor of garbage collection, I loved it.
link |
Yeah, from a coding standpoint.
link |
From a coding standpoint, yeah, yeah.
link |
It would be interesting if the laws themselves
link |
kind of had a built in thing
link |
where they kind of die after a while
link |
unless somebody explicitly publicly defends them.
link |
So that's sort of, it's not like somebody has to kill them.
link |
They kind of die themselves.
link |
Not to defend Java or anything, but you know, C++,
link |
you know, you could also have a great garbage collection
link |
in Python and so on.
link |
Yeah, so yeah, something needs to happen
link |
or just the civilization's arteries just harden over time
link |
and you can just get less and less done
link |
because there's just a rule against everything.
link |
So I think like, I don't know, for Mars or whatever,
link |
I'd say, or even for, you know, obviously for Earth as well,
link |
like I think there should be an active process
link |
for removing rules and regulations
link |
and questioning their existence.
link |
Just like if we've got a function
link |
for creating rules and regulations,
link |
because rules and regulations can also think of us
link |
like they're like software or lines of code
link |
for operating civilization.
link |
That's the rules and regulations.
link |
So it's not like we shouldn't have rules and regulations,
link |
but you have code accumulation, but no code removal.
link |
And so it just gets to become basically archaic bloatware
link |
And it's just, it makes it hard for things to progress.
link |
So I don't know, maybe Mars, you'd have like,
link |
you know, any given law must have a sunset, you know,
link |
and require active voting to keep it up there, you know.
link |
And I actually also say like, and these are just,
link |
I don't know, recommendations or thoughts,
link |
ultimately will be up to the people on Mars to decide.
link |
But I think it should be easier to remove a law
link |
than to add one because of the,
link |
just to overcome the inertia of laws.
link |
So maybe it's like, for argument's sake,
link |
you need like say 60% vote to have a law take effect,
link |
but only a 40% vote to remove it.
link |
So let me be the guy, you posted a meme on Twitter recently
link |
where there's like a row of urinals,
link |
and a guy just walks all the way across,
link |
and he tells you about crypto.
link |
I mean, that's happened to me so many times.
link |
I think maybe even literally.
link |
Do you think, technologically speaking,
link |
there's any room for ideas of smart contracts or so on?
link |
Because you mentioned laws.
link |
That's an interesting use of things like smart contracts
link |
to implement the laws by which governments function.
link |
Like something built on Ethereum,
link |
or maybe a dog coin that enables smart contracts somehow.
link |
I don't quite understand this whole smart contract thing.
link |
I mean, I'm too dumb to understand smart contracts.
link |
That's a good line.
link |
I mean, my general approach to any kind of deal or whatever
link |
is just make sure there's clarity of understanding.
link |
That's the most important thing.
link |
And just keep any kind of deal very short and simple,
link |
plain language, and just make sure everyone understands
link |
this is the deal, is it clear?
link |
And what are the consequences if various things
link |
But usually deals are, business deals or whatever,
link |
are way too long and complex and overly lawyered
link |
You mentioned that Doge is the people's coin.
link |
And you said that you were literally going,
link |
SpaceX may consider literally putting a Doge coin
link |
on the moon, is this something you're still considering?
link |
Mars, perhaps, do you think there's some chance,
link |
we've talked about political systems on Mars,
link |
that Doge coin is the official currency of Mars
link |
at some point in the future?
link |
Well, I think Mars itself will need to have
link |
a different currency because you can't synchronize
link |
due to speed of light, or not easily.
link |
So it must be completely stand alone from Earth.
link |
Well, yeah, because Mars is, at closest approach,
link |
it's four light minutes away, roughly,
link |
and then at furthest approach, it's roughly
link |
20 light minutes away, maybe a little more.
link |
So you can't really have something synchronizing
link |
if you've got a 20 minute speed of light issue,
link |
if it's got a one minute blockchain.
link |
It's not gonna synchronize properly.
link |
So Mars, I don't know if Mars would have
link |
a cryptocurrency as a thing, but probably, seems likely.
link |
But it would be some kind of localized thing on Mars.
link |
And you let the people decide.
link |
The future of Mars should be up to the Martians.
link |
Yeah, so, I think the cryptocurrency thing
link |
is an interesting approach to reducing
link |
the error in the database that is called money.
link |
I think I have a pretty deep understanding
link |
of what money actually is on a practical day to day basis
link |
because of PayPal.
link |
We really got in deep there.
link |
And right now, the money system, actually,
link |
for practical purposes, is really a bunch
link |
of heterogeneous mainframes running old COBOL.
link |
Okay, you mean literally.
link |
That's literally what's happening.
link |
Yeah, pretty the poor bastards who have
link |
to maintain that code.
link |
Okay, that's a pain.
link |
Not even Fortran, it's COBOL.
link |
And the banks are still buying mainframes in 2021
link |
and running ancient COBOL code.
link |
And the Federal Reserve is probably even older
link |
than what the banks have, and they have
link |
an old COBOL mainframe.
link |
And so, the government effectively has editing privileges
link |
on the money database.
link |
And they use those editing privileges to make more money,
link |
whatever they want.
link |
And this increases the error in the database that is money.
link |
So, I think money should really be viewed
link |
through the lens of information theory.
link |
And so, it's kind of like an internet connection.
link |
Like what's the bandwidth, total bit rate,
link |
what is the latency, jitter, packet drop,
link |
you know, errors in network communication.
link |
Just think of money like that, basically.
link |
I think that's probably the right way to think of it.
link |
And then say what system from an information theory
link |
standpoint allows an economy to function the best.
link |
And, you know, crypto is an attempt to reduce
link |
the error in money that is contributed
link |
by governments diluting the money supply
link |
as basically a pernicious form of taxation.
link |
So, both policy in terms of with inflation
link |
and actual like technological COBOL,
link |
like cryptocurrency takes us into the 21st century
link |
in terms of the actual systems
link |
that allow you to do the transaction,
link |
to store wealth, all those kinds of things.
link |
Like I said, just think of money as information.
link |
People often will think of money
link |
as having power in and of itself.
link |
Money is information and it does not have power
link |
Like, you know, applying the physics tools
link |
of thinking about things in the limit is helpful.
link |
If you are stranded on a tropical island
link |
and you have a trillion dollars, it's useless
link |
because there's no resource allocation.
link |
Money is a database for resource allocation,
link |
but there's no resource to allocate except yourself.
link |
So, money is useless.
link |
If you're stranded on a desert island with no food,
link |
all the Bitcoin in the world will not stop you
link |
So, just think of money as a database
link |
for resource allocation across time and space.
link |
And then what system, in what form
link |
should that database or data system,
link |
what would be most effective?
link |
Now, there is a fundamental issue
link |
with say Bitcoin in its current form
link |
in that the transaction volume is very limited
link |
and the latency for a properly confirmed transaction
link |
is too long, much longer than you'd like.
link |
So, it's actually not great from a transaction volume
link |
standpoint or a latency standpoint.
link |
So, it is perhaps useful to solve an aspect
link |
of the money database problem, which is the sort of store
link |
of wealth or an accounting of relative obligations,
link |
I suppose, but it is not useful as a currency,
link |
as a day to day currency.
link |
But people have proposed different technological solutions.
link |
Yeah, Lightning Network and the layer two technologies
link |
I mean, it seems to be all kind of a trade off,
link |
but the point is, it's kind of brilliant to say
link |
that just think about information,
link |
think about what kind of database,
link |
what kind of infrastructure enables
link |
that exchange of information.
link |
Yeah, just say like you're operating an economy
link |
and you need to have some thing that allows
link |
for the efficient, to have efficient value ratios
link |
between products and services.
link |
So, you've got this massive number of products
link |
and services and you need to, you can't just barter.
link |
It's just like, that would be extremely unwieldy.
link |
So, you need something that gives you the ratio
link |
of exchange between goods and services.
link |
And then something that allows you
link |
to shift obligations across time, like debt.
link |
Debt and equity shift obligations across time.
link |
Then what does the best job of that?
link |
Part of the reason why I think there's some
link |
Merit Doge coin, even though it was obviously created
link |
as a joke, is that it actually does have
link |
a much higher transaction volume capability than Bitcoin.
link |
And the costs of doing a transaction,
link |
the Doge coin fee is very low.
link |
Like right now, if you want to do a Bitcoin transaction,
link |
the price of doing that transaction is very high.
link |
So, you could not use it effectively for most things.
link |
And nor could it even scale to a high volume.
link |
And when Bitcoin started, I guess around 2008
link |
or something like that, the internet connections
link |
were much worse than they are today.
link |
Like Order of magnitude, I mean,
link |
just way, way worse in 2008.
link |
So, like having a small block size or whatever
link |
is, and a long synchronization time made sense in 2008.
link |
But 2021, or fast forward 10 years,
link |
it's like comically low.
link |
And I think there's some value to having a linear increase
link |
in the amount of currency that is generated.
link |
So, because some amount of the currency,
link |
like if a currency is too deflationary,
link |
or I should say, if a currency is expected
link |
to increase in value over time,
link |
there's reluctance to spend it.
link |
Because you're like, oh, I'll just hold it and not spend it
link |
because it's scarcity is increasing with time.
link |
So, if I spend it now, then I will regret spending it.
link |
So, I will just, you know, hodl it.
link |
But if there's some dilution of the currency occurring
link |
over time, that's more of an incentive
link |
to use it as a currency.
link |
So, those coins, somewhat randomly has just a fixed,
link |
a number of sort of coins or hash strings
link |
that are generated every year.
link |
So, there's some inflation, but it's not a percentage base.
link |
It's a percentage of the total amount of money
link |
it's a fixed number.
link |
So, the percentage of inflation
link |
will necessarily decline over time.
link |
So, I'm not saying that it's like the ideal system
link |
for a currency, but I think it actually is
link |
just fundamentally better than anything else I've seen
link |
just by accident, so.
link |
I like how you said around 2008.
link |
So, you're not, you know, some people suggested
link |
you might be Satoshi Nakamoto.
link |
You've previously said you're not.
link |
You're not for sure.
link |
Would you tell us if you were?
link |
Do you think it's a feature or a bug
link |
that he's anonymous or she or they?
link |
It's an interesting kind of quirk of human history
link |
that there is a particular technology
link |
that is a completely anonymous inventor
link |
Well, I mean, you can look at the evolution of ideas
link |
before the launch of Bitcoin
link |
and see who wrote, you know, about those ideas.
link |
And then, like, I don't know exactly,
link |
obviously I don't know who created Bitcoin
link |
for practical purposes,
link |
but the evolution of ideas is pretty clear for that.
link |
And like, it seems as though like Nick Szabo
link |
is probably more than anyone else responsible
link |
for the evolution of those ideas.
link |
So, he claims not to be Satoshi Nakamoto,
link |
but I'm not sure that's neither here nor there,
link |
but he seems to be the one more responsible
link |
for the ideas behind Bitcoin than anyone else.
link |
So, it's not perhaps like singular figures
link |
aren't even as important as the figures involved
link |
in the evolution of ideas, the Leto thing, so.
link |
Yeah, it's, you know, perhaps it's sad
link |
to think about history,
link |
but maybe most names will be forgotten anyway.
link |
What is a name anyway?
link |
It's a name attached to an idea.
link |
What does it even mean, really?
link |
I think Shakespeare had a thing about roses and stuff,
link |
A rose by any other name, it smells sweet.
link |
I got Elon to quote Shakespeare.
link |
I feel like I accomplished something today.
link |
Shall I compare thee to a summer's day?
link |
I'm gonna clip that out.
link |
I said it to people.
link |
Not more temperate and more fair.
link |
Tesla autopilot has been through an incredible journey
link |
over the past six years,
link |
or perhaps even longer in the minds of,
link |
in your mind and the minds of many involved.
link |
Yeah, I think that's where we first like connected really
link |
was the autopilot stuff, autonomy and.
link |
The whole journey was incredible to me to watch.
link |
I was, because I knew, well, part of it is I was at MIT
link |
and I knew the difficulty of computer vision.
link |
And I knew the whole, I had a lot of colleagues and friends
link |
about the DARPA challenge and knew how difficult it is.
link |
And so there was a natural skepticism
link |
when I first drove a Tesla with the initial system
link |
based on Mobileye.
link |
I thought there's no way, so first when I got in,
link |
I thought there's no way this car could maintain,
link |
like stay in the lane and create a comfortable experience.
link |
So my intuition initially was that the lane keeping problem
link |
is way too difficult to solve.
link |
Oh, lane keeping, yeah, that's relatively easy.
link |
Well, like, but not this, but solve in the way
link |
that we just, we talked about previous is prototype
link |
versus a thing that actually creates a pleasant experience
link |
over hundreds of thousands of miles or millions.
link |
Yeah, so we had to wrap a lot of code
link |
around the Mobileye thing.
link |
It doesn't just work by itself.
link |
I mean, that's part of the story
link |
of how you approach things sometimes.
link |
Sometimes you do things from scratch.
link |
Sometimes at first you kind of see what's out there
link |
and then you decide to do from scratch.
link |
That was one of the boldest decisions I've seen
link |
is both in the hardware and the software
link |
to decide to eventually go from scratch.
link |
I thought, again, I was skeptical
link |
of whether that's going to be able to work out
link |
because it's such a difficult problem.
link |
And so it was an incredible journey
link |
what I see now with everything,
link |
the hardware, the compute, the sensors,
link |
the things I maybe care and love about most
link |
is the stuff that Andre Karpathy is leading
link |
with the data set selection,
link |
the whole data engine process,
link |
the neural network architectures,
link |
the way that's in the real world,
link |
that network is tested, validated,
link |
all the different test sets,
link |
versus the ImageNet model of computer vision,
link |
like what's in academia is like real world
link |
artificial intelligence.
link |
And Andre's awesome and obviously plays an important role,
link |
but we have a lot of really talented people driving things.
link |
And Ashok is actually the head of autopilot engineering.
link |
Andre's the director of AI.
link |
AI stuff, yeah, yeah.
link |
So yeah, I'm aware that there's an incredible team
link |
of just a lot going on.
link |
Yeah, obviously people will give me too much credit
link |
and they'll give Andre too much credit, so.
link |
And people should realize how much is going on
link |
Yeah, it's just a lot of really talented people.
link |
The Tesla Autopilot AI team is extremely talented.
link |
It's like some of the smartest people in the world.
link |
So yeah, we're getting it done.
link |
What are some insights you've gained
link |
over those five, six years of autopilot
link |
about the problem of autonomous driving?
link |
So you leaped in having some sort of
link |
first principles kinds of intuitions,
link |
but nobody knows how difficult the problem, like the problem.
link |
I thought the self driving problem would be hard,
link |
but it was harder than I thought.
link |
It's not like I thought it would be easy.
link |
I thought it would be very hard,
link |
but it was actually way harder than even that.
link |
So, I mean, what it comes down to at the end of the day
link |
is to solve self driving,
link |
you basically need to recreate what humans do to drive,
link |
which is humans drive with optical sensors,
link |
eyes and biological neural nets.
link |
And so in order to,
link |
that's how the entire road system is designed to work
link |
with basically passive optical and neural nets,
link |
And now that we need to,
link |
so for actually for full self driving to work,
link |
we have to recreate that in digital form.
link |
So we have to, that means cameras with advanced neural nets
link |
in silicon form, and then it will obviously solve
link |
for full self driving.
link |
That's the only way.
link |
I don't think there's any other way.
link |
But the question is what aspects of human nature
link |
do you have to encode into the machine, right?
link |
Do you have to solve the perception problem, like detect?
link |
And then you first realize
link |
what is the perception problem for driving,
link |
like all the kinds of things you have to be able to see,
link |
like what do we even look at when we drive?
link |
There's, I just recently heard Andre talked about MIT
link |
I think it was the world's greatest talk of all time
link |
about car doors, the fine details of car doors.
link |
Like what is even an open car door, man?
link |
So like the ontology of that,
link |
that's a perception problem.
link |
We humans solve that perception problem,
link |
and Tesla has to solve that problem.
link |
And then there's the control and the planning
link |
coupled with the perception.
link |
You have to figure out like what's involved in driving,
link |
like especially in all the different edge cases.
link |
And then, I mean, maybe you can comment on this,
link |
how much game theoretic kind of stuff needs to be involved
link |
at a four way stop sign.
link |
As humans, when we drive, our actions affect the world.
link |
Like it changes how others behave.
link |
Most autonomous driving, if you,
link |
you're usually just responding to the scene
link |
as opposed to like really asserting yourself in the scene.
link |
I think these sort of control logic conundrums
link |
are not the hard part.
link |
The, you know, let's see.
link |
What do you think is the hard part
link |
in this whole beautiful, complex problem?
link |
So it's a lot of freaking software, man.
link |
A lot of smart lines of code.
link |
For sure, in order to have,
link |
create an accurate vector space.
link |
So like you're coming from image space,
link |
which is like this flow of photons,
link |
you're going to the camera, cameras,
link |
and then you have this massive bitstream
link |
in image space, and then you have to effectively compress
link |
a massive bitstream corresponding to photons
link |
that knocked off an electron in a camera sensor
link |
and turn that bitstream into a vector space.
link |
By vector space, I mean like, you know,
link |
you've got cars and humans and lane lines and curves
link |
and traffic lights and that kind of thing.
link |
Once you've got all of that in your head,
link |
once you have an accurate vector space,
link |
the control problem is similar to that of a video game,
link |
like a Grand Theft Auto of Cyberpunk,
link |
if you have accurate vector space.
link |
It's the control problem is,
link |
I wouldn't say it's trivial, it's not trivial,
link |
but it's not like some insurmountable thing.
link |
Having an accurate vector space is very difficult.
link |
Yeah, I think we humans don't give enough respect
link |
to how incredible the human perception system is
link |
to mapping the raw photons to the vector space
link |
representation in our heads.
link |
Your brain is doing an incredible amount of processing
link |
and giving you an image that is a very cleaned up image.
link |
Like when we look around here, we see,
link |
like you see color in the corners of your eyes,
link |
but actually your eyes have very few cones,
link |
like cone receptors in the peripheral vision.
link |
Your eyes are painting color in the peripheral vision.
link |
You don't realize it,
link |
but their eyes are actually painting color
link |
and your eyes also have like this blood vessels
link |
and all sorts of gnarly things and there's a blind spot,
link |
but do you see your blind spot?
link |
No, your brain is painting in the missing, the blind spot.
link |
You're gonna do these things online where you look here
link |
and look at this point and then look at this point
link |
and if it's in your blind spot,
link |
your brain will just fill in the missing bits.
link |
The peripheral vision is so cool.
link |
It makes you realize all the illusions for vision sciences,
link |
so it makes you realize just how incredible the brain is.
link |
The brain is doing crazy amount of post processing
link |
on the vision signals for your eyes.
link |
And then even once you get all those vision signals,
link |
your brain is constantly trying to forget
link |
as much as possible.
link |
So human memory is,
link |
perhaps the weakest thing about the brain is memory.
link |
So because memory is so expensive to our brain
link |
your brain is trying to forget as much as possible
link |
and distill the things that you see
link |
into the smallest amounts of information possible.
link |
So your brain is trying to not just get to a vector space,
link |
but get to a vector space that is the smallest possible
link |
vector space of only relevant objects.
link |
And I think you can sort of look inside your brain
link |
or at least I can,
link |
when you drive down the road and try to think about
link |
what your brain is actually doing consciously.
link |
And it's like you'll see a car,
link |
because you don't have cameras,
link |
I don't have eyes in the back of your head or a side.
link |
So you basically have like two cameras on a slow gimbal.
link |
And eyesight is not that great.
link |
Okay, human eyes are like,
link |
and people are constantly distracted
link |
and thinking about things and texting
link |
and doing all sorts of things they shouldn't do in a car,
link |
changing the radio station.
link |
So having arguments is like,
link |
so when's the last time you looked right and left
link |
and rearward, or even diagonally forward
link |
to actually refresh your vector space?
link |
So you're glancing around and what your mind is doing
link |
is trying to distill the relevant vectors,
link |
basically objects with a position and motion.
link |
And then editing that down to the least amount
link |
that's necessary for you to drive.
link |
It does seem to be able to edit it down
link |
or compress it even further into things like concepts.
link |
So it's not, it's like it goes beyond,
link |
the human mind seems to go sometimes beyond vector space
link |
to sort of space of concepts to where you'll see a thing.
link |
It's no longer represented spatially somehow.
link |
It's almost like a concept that you should be aware of.
link |
Like if this is a school zone,
link |
you'll remember that as a concept,
link |
which is a weird thing to represent,
link |
but perhaps for driving,
link |
you don't need to fully represent those things.
link |
Or maybe you get those kind of indirectly.
link |
You need to establish vector space
link |
and then actually have predictions for those vector spaces.
link |
So if you drive past, say a bus and you see that there's people,
link |
before you drove past the bus,
link |
you saw people crossing or some,
link |
just imagine there's like a large truck
link |
or something blocking site.
link |
But before you came up to the truck,
link |
you saw that there were some kids about to cross the road
link |
in front of the truck.
link |
Now you can no longer see the kids,
link |
but you would now know, okay,
link |
those kids are probably gonna pass by the truck
link |
and cross the road, even though you cannot see them.
link |
So you have to have memory,
link |
you have to need to remember that there were kids there
link |
and you need to have some forward prediction
link |
of what their position will be at the time of relevance.
link |
So with occlusions and computer vision,
link |
when you can't see an object anymore,
link |
even when it just walks behind a tree and reappears,
link |
that's a really, really,
link |
I mean, at least in academic literature,
link |
it's tracking through occlusions, it's very difficult.
link |
Yeah, we're doing it.
link |
I understand this.
link |
It's like object permanence,
link |
like same thing happens with humans with neural nets.
link |
Like when like a toddler grows up,
link |
like there's a point in time where they develop,
link |
they have a sense of object permanence.
link |
So before a certain age, if you have a ball or a toy
link |
or whatever, and you put it behind your back
link |
and you pop it out, if they don't,
link |
before they have object permanence,
link |
it's like a new thing every time.
link |
It's like, whoa, this toy went poof, just fared
link |
and now it's back again and they can't believe it.
link |
And that they can play peekaboo all day long
link |
because peekaboo is fresh every time.
link |
But then we figured out object permanence,
link |
then they realize, oh no, the object is not gone,
link |
it's just behind your back.
link |
Sometimes I wish we never did figure out object permanence.
link |
Yeah, so that's a...
link |
So that's an important problem to solve.
link |
Yes, so like an important evolution
link |
of the neural nets in the car is
link |
memory across both time and space.
link |
So now you can't remember, like you have to say,
link |
like how long do you want to remember things for?
link |
And there's a cost to remembering things for a long time.
link |
So you can like run out of memory
link |
to try to remember too much for too long.
link |
And then you also have things that are stale
link |
if you remember them for too long.
link |
And then you also need things that are remembered over time.
link |
So even if you like say have like,
link |
for our good sake, five seconds of memory on a time basis,
link |
but like let's say you're parked at a light
link |
and you saw, use a pedestrian example,
link |
that people were waiting to cross the road
link |
and you can't quite see them because of an occlusion,
link |
but they might wait for a minute before the light changes
link |
for them to cross the road.
link |
You still need to remember that that's where they were
link |
and that they're probably going
link |
to cross the road type of thing.
link |
So even if that exceeds your time based memory,
link |
it should not exceed your space memory.
link |
And I just think the data engine side of that,
link |
so getting the data to learn all of the concepts
link |
that you're saying now is an incredible process.
link |
It's this iterative process of just,
link |
it's this hydranet of many.
link |
We're changing the name to something else.
link |
Okay, I'm sure it'll be equally as Rick and Morty like.
link |
There's a lot of, yeah.
link |
We've rearchitected the neural net,
link |
the neural nets in the cars so many times it's crazy.
link |
Oh, so every time there's a new major version,
link |
you'll rename it to something more ridiculous
link |
or memorable and beautiful, sorry.
link |
Not ridiculous, of course.
link |
If you see the full array of neural nets
link |
that are operating in the cars,
link |
it kind of boggles the mind.
link |
There's so many layers, it's crazy.
link |
And we started off with simple neural nets
link |
that were basically image recognition
link |
on a single frame from a single camera
link |
and then trying to knit those together
link |
with C, I should say we're really primarily running C here
link |
because C++ is too much overhead
link |
and we have our own C compiler.
link |
So to get maximum performance,
link |
we actually wrote our own C compiler
link |
and are continuing to optimize our C compiler
link |
for maximum efficiency.
link |
In fact, we've just recently done a new river
link |
on our C compiler that'll compile directly
link |
to our autopilot hardware.
link |
If you want to compile the whole thing down
link |
with your own compiler, like so efficiency here,
link |
because there's all kinds of compute,
link |
there's CPU, GPU, there's like basic types of things
link |
and you have to somehow figure out the scheduling
link |
across all of those things.
link |
And so you're compiling the code down that does all, okay.
link |
So that's why there's a lot of people involved.
link |
There's a lot of hardcore software engineering
link |
at a very sort of bare metal level
link |
because we're trying to do a lot of compute
link |
that's constrained to our full self driving computer.
link |
So we want to try to have the highest frames per second
link |
possible in a sort of very finite amount of compute
link |
So we really put a lot of effort into the efficiency
link |
And so there's actually a lot of work done
link |
by some very talented software engineers at Tesla
link |
that at a very foundational level
link |
to improve the efficiency of compute
link |
and how we use the trip accelerators,
link |
which are basically, you know,
link |
doing matrix math dot products,
link |
like a bazillion dot products.
link |
And it's like, what are neural nets?
link |
It's like compute wise, like 99% dot products.
link |
And you want to achieve as many high frame rates
link |
like a video game.
link |
You want full resolution, high frame rate.
link |
High frame rate, low latency, low jitter.
link |
So I think one of the things we're moving towards now
link |
is no post processing of the image
link |
through the image signal processor.
link |
So like what happens for cameras is that,
link |
almost all cameras is they,
link |
there's a lot of post processing done
link |
in order to make pictures look pretty.
link |
And so we don't care about pictures looking pretty.
link |
We just want the data.
link |
So we're moving just raw photon counts.
link |
So the system will, like the image that the computer sees
link |
is actually much more than what you'd see
link |
if you represented it on a camera.
link |
It's got much more data.
link |
And even in a very low light conditions,
link |
you can see that there's a small photon count difference
link |
between this spot here and that spot there,
link |
so it can see in the dark incredibly well
link |
because it can detect these tiny differences
link |
Like much better than you could possibly imagine.
link |
So, and then we also save 13 milliseconds on a latency.
link |
From removing the post processing on the image?
link |
Cause we've got eight cameras
link |
and then there's roughly, I don't know,
link |
one and a half milliseconds or so,
link |
maybe 1.6 milliseconds of latency for each camera.
link |
And so like going to just,
link |
basically bypassing the image processor
link |
gets us back 13 milliseconds of latency,
link |
which is important.
link |
And we track latency all the way from, you know,
link |
photon hits the camera to, you know,
link |
all the steps that it's got to go through to get,
link |
you know, go through the various neural nets
link |
And there's a little bit of C++ there as well.
link |
Well, I can maybe a lot, but it,
link |
the core stuff is heavy duty computers all in C.
link |
And so we track that latency all the way
link |
to an output command to the drive unit to accelerate
link |
the brakes just to slow down the steering,
link |
you know, turn left or right.
link |
So, cause you go to output a command
link |
that's got to go to a controller.
link |
And like some of these controllers have an update frequency
link |
that's maybe 10 Hertz or something like that,
link |
That's like now you lose a hundred milliseconds potentially.
link |
So, so then we want to update the,
link |
the drivers on the like say steering and braking control
link |
to have more like a hundred Hertz instead of 10 Hertz.
link |
And then you've got a 10 millisecond latency
link |
instead of a hundred millisecond worst case latency.
link |
And actually jitter is more of a challenge than latency.
link |
Cause latency is like, you can, you can,
link |
you can anticipate and predict, but if you're,
link |
but if you've got a stack up of things going
link |
from the camera to the, to the computer through
link |
then a series of other computers,
link |
and finally to an actuator on the car,
link |
if you have a stack up of tolerances of timing tolerances,
link |
then you can have quite a variable latency,
link |
which is called jitter.
link |
And, and that makes it hard to, to, to anticipate exactly
link |
what, how you should turn the car or accelerate,
link |
because if you've got maybe a hundred,
link |
50, 200 milliseconds of jitter,
link |
then you could be off by, you know, up to 0.2 seconds.
link |
And this can make, this could make a big difference.
link |
So you have to interpolate somehow to, to, to,
link |
to deal with the effects of jitter.
link |
So that you can make like robust control decisions.
link |
You have to, so the jitters and the sensor information,
link |
or the jitter can occur at any stage in the pipeline.
link |
You can, if you have just, if you have fixed latency,
link |
you can anticipate and, and like say, okay,
link |
we know that our information is for argument's sake,
link |
150 milliseconds stale.
link |
Like, so for, for, for 150 milliseconds
link |
from photon second camera to where you can measure a change
link |
in the acceleration of the vehicle.
link |
So then, then you can say, okay, well, we're going to enter,
link |
we know it's 150 milliseconds.
link |
So we're going to take that into account
link |
and, and compensate for that latency.
link |
However, if you've got then 150 milliseconds of latency
link |
plus a hundred milliseconds of jitter,
link |
that's which could be anywhere from zero,
link |
zero to a hundred milliseconds on top.
link |
So, so then your latency could be from 150 to 250 milliseconds.
link |
Now you've got a hundred milliseconds
link |
that you don't know what to do with.
link |
And that's basically random.
link |
So getting rid of jitter is extremely important.
link |
And that affects your control decisions
link |
and all those kinds of things.
link |
Yeah, the car's just going to fundamentally maneuver better
link |
with lower jitter.
link |
The cars will maneuver with superhuman ability
link |
and reaction time much faster than a human.
link |
I mean, I think over time the autopilot,
link |
full self driving will be capable of maneuvers
link |
that are far more than what like James Bond could do
link |
in like the best movie type of thing.
link |
That's exactly what I was imagining in my mind,
link |
It's like an impossible maneuvers
link |
that a human couldn't do.
link |
Well, let me ask sort of looking back the six years,
link |
looking out into the future,
link |
based on your current understanding,
link |
how hard do you think this,
link |
this full self driving problem,
link |
when do you think Tesla will solve level four FSD?
link |
I mean, it's looking quite likely
link |
that it will be next year.
link |
And what does the solution look like?
link |
Is it the current pool of FSD beta candidates,
link |
they start getting greater and greater
link |
as they have been degrees of autonomy,
link |
and then there's a certain level
link |
beyond which they can do their own,
link |
they can read a book.
link |
I mean, you can see that anybody
link |
who's been following the full self driving beta closely
link |
will see that the rate of disengagements
link |
has been dropping rapidly.
link |
So like disengagement be where the driver intervenes
link |
to prevent the car from doing something dangerous,
link |
So the interventions per million miles
link |
has been dropping dramatically at some point.
link |
And that trend looks like it happens next year
link |
is that the probability of an accident on FSD
link |
is less than that of the average human,
link |
and then significantly less than that of the average human.
link |
So it certainly appears like we will get there next year.
link |
Then of course, then there's gonna be a case of,
link |
okay, well, we now have to prove this to regulators
link |
and prove it to, you know, and we want a standard
link |
that is not just equivalent to a human,
link |
but much better than the average human.
link |
I think it's gotta be at least two or three times
link |
two or three times higher safety than a human.
link |
So two or three times lower probability of injury
link |
than a human before we would actually say like,
link |
okay, it's okay to go, it's not gonna be equivalent,
link |
it's gonna be much better.
link |
So if you look, FSD 10.6 just came out recently,
link |
10.7 is on the way, maybe 11 is on the way,
link |
so we're in the future.
link |
Yeah, we were hoping to get 11 out this year,
link |
but 11 actually has a whole bunch of fundamental rewrites
link |
on the neural net architecture,
link |
and some fundamental improvements
link |
in creating vector space, so.
link |
There is some fundamental like leap
link |
that really deserves the 11,
link |
I mean, that's a pretty cool number.
link |
Yeah, 11 would be a single stack
link |
for all, you know, one stack to rule them all.
link |
But there are just some really fundamental
link |
neural net architecture changes
link |
that will allow for much more capability,
link |
but at first they're gonna have issues.
link |
So like we have this working on like sort of alpha software
link |
and it's good, but it's basically taking a whole bunch
link |
of C, C++ code and leading a massive amount of C++ code
link |
and replacing it with a neural net.
link |
And Andre makes this point a lot,
link |
which is like neural nets are kind of eating software.
link |
Over time there's like less and less conventional software,
link |
more and more neural net, which is still software,
link |
but it's, you know, still comes out the lines of software,
link |
but it's more neural net stuff
link |
and less, you know, heuristics basically.
link |
More matrix based stuff and less heuristics based stuff.
link |
And, you know, like one of the big changes will be,
link |
like right now the neural nets will deliver
link |
a giant bag of points to the C++ or C and C++ code.
link |
We call it the giant bag of points.
link |
And it's like, so you've got a pixel and something associated
link |
Like this pixel is probably car.
link |
The pixel is probably lane line.
link |
Then you've got to assemble this giant bag of points
link |
in the C code and turn it into vectors.
link |
And it does a pretty good job of it, but it's,
link |
we want to just, you know,
link |
we need another layer of neural nets on top of that
link |
to take the giant bag of points and distill that down
link |
to a vector space in the neural net part of the software,
link |
as opposed to the heuristics part of the software.
link |
This is a big improvement.
link |
Neural nets all the way down.
link |
That's what you want.
link |
It's not even all neural nets, but this will be just a,
link |
this is a game changer to not have the bag of points,
link |
the giant bag of points that has to be assembled
link |
with many lines of C++ and have the,
link |
and have a neural net just assemble those into a vector.
link |
So the neural net is outputting much, much less data.
link |
It's outputting, this is a lane line.
link |
This is drivable space.
link |
This is a pedestrian or a cyclist or something like that.
link |
It's outputting, it's really outputting proper vectors
link |
to the C, C++ control code,
link |
as opposed to the sort of constructing the vectors in C,
link |
which we've done, I think, quite a good job of,
link |
but we're kind of hitting a local maximum
link |
on how well the C can do this.
link |
So this is really a big deal.
link |
And just all of the networks in the car
link |
need to move to surround video.
link |
There's still some legacy networks that are not surround video.
link |
And all of the training needs to move to surround video
link |
and the efficiency of the training,
link |
it needs to get better and it is.
link |
And then we need to move everything to raw photon counts
link |
as opposed to processed images,
link |
which is quite a big reset on the training
link |
because the system's trained on post processed images.
link |
So we need to redo all the training
link |
to train against the raw photon counts
link |
instead of the post processed image.
link |
So ultimately, it's kind of reducing the complexity
link |
of the whole thing.
link |
So reducing the...
link |
Lines of code will actually go lower.
link |
Yeah, that's fascinating.
link |
So you're doing fusion of all the sensors
link |
and reducing the complexity of having to deal with these...
link |
Fusion of the cameras.
link |
Fusion of the cameras, really.
link |
Well, I guess we've got ears too.
link |
Yeah, we'll actually need to incorporate sound as well
link |
because you need to listen for ambulance sirens
link |
or fire trucks or somebody yelling at you or something.
link |
There's a little bit of audio that needs to be incorporated as well.
link |
Do you need to go back for a break?
link |
Yeah, sure, let's take a break.
link |
Honestly, frankly, the ideas are the easy thing
link |
and the implementation is the hard thing.
link |
The idea of going to the moon is the easy part.
link |
Not going to the moon is the hard part.
link |
It's the hard part.
link |
And there's a lot of hardcore engineering
link |
that's got to get done at the hardware and software level.
link |
Like I said, optimizing the C compiler
link |
and just cutting out latency everywhere.
link |
If we don't do this, the system will not work properly.
link |
So the work of the engineers doing this,
link |
they are like the unsung heroes,
link |
but they are critical to the success of the situation.
link |
I think you made it clear.
link |
I mean, at least to me, it's super exciting.
link |
Everything that's going on outside of what Andre is doing.
link |
Just the whole infrastructure, the software.
link |
I mean, everything is going on with Data Engine,
link |
whatever it's called.
link |
The whole process is just work of art to me.
link |
The sheer scale of it boggles my mind.
link |
Like the training, the amount of work done with,
link |
like we've written all this custom software for training and labeling
link |
and to do auto labeling.
link |
Auto labeling is essential.
link |
Because especially when you've got surround video, it's very difficult.
link |
To label surround video from scratch is extremely difficult.
link |
Like take a human such a long time to even label one video clip,
link |
like several hours.
link |
Or the auto label, basically we just apply heavy duty,
link |
like a lot of compute to the video clips to preassign
link |
and guess what all the things are that are going on in the surround video.
link |
And then there's like correcting it.
link |
And then all the human has to do is like tweet,
link |
like say, adjust what is incorrect.
link |
This is like increases productivity by in fact a hundred or more.
link |
So you've presented Tesla Bot as primarily useful in the factory.
link |
First of all, I think humanoid robots are incredible.
link |
From a fan of robotics, I think the elegance of movement
link |
that humanoid robots, that bipedal robots show are just so cool.
link |
So it's really interesting that you're working on this
link |
and also talking about applying the same kind of all the ideas,
link |
some of which we've talked about with Data Engine,
link |
all the things that we're talking about with Tesla Autopilot,
link |
just transferring that over to just yet another robotics problem.
link |
I have to ask, since I care about human robot interaction,
link |
so the human side of that.
link |
So you've talked about mostly in the factory.
link |
Do you see part of this problem that Tesla Bot has to solve
link |
is interacting with humans and potentially having a place like in the home.
link |
So interacting, not just not replacing labor, but also like, I don't know,
link |
being a friend or an assistant or something like that.
link |
Yeah, I think the possibilities are endless.
link |
It's not quite in Tesla's primary mission direction
link |
of accelerating sustainable energy,
link |
but it is an extremely useful thing that we can do for the world,
link |
which is to make a useful humanoid robot that is capable of interacting with the world
link |
and helping in many different ways.
link |
I think if you say extrapolate to many years in the future,
link |
I think work will become optional.
link |
There's a lot of jobs that if people weren't paid to do it,
link |
they wouldn't do it.
link |
It's not fun necessarily.
link |
If you're washing dishes all day,
link |
it's like, you know, even if you really like washing dishes,
link |
you really want to do it for eight hours a day every day.
link |
And then there's like dangerous work.
link |
And basically, if it's dangerous, boring,
link |
it has like potential for repetitive stress injury, that kind of thing.
link |
Then that's really where humanoid robots would add the most value initially.
link |
So that's what we're aiming for is for the humanoid robots to do jobs
link |
that people don't voluntarily want to do.
link |
And then we'll have to pair that obviously
link |
with some kind of universal basic income in the future.
link |
So do you see a world when there's like hundreds of millions of Tesla bots
link |
doing different, performing different tasks throughout the world?
link |
Yeah, I haven't really thought about it that far into the future,
link |
but I guess there may be something like that.
link |
Can I ask a wild question?
link |
So the number of Tesla cars has been accelerating.
link |
There's been close to two million produced.
link |
Many of them have autopilot.
link |
I think we're over two million now.
link |
Do you think there will ever be a time when there will be more Tesla bots
link |
Actually, it's funny you asked this question,
link |
because normally I do try to think pretty far into the future,
link |
but I haven't really thought that far into the future with the Tesla bot,
link |
or it's codenamed Optimus.
link |
I call it Optimus subprime.
link |
It's not like a giant transformer robot.
link |
But it's meant to be a general purpose, helpful bot.
link |
And basically, like the things that we're basically like, like,
link |
Tesla, I think is the has the most advanced real world AI
link |
for interacting with the real world,
link |
which are developed as a function of to make self driving work.
link |
And so along with custom hardware and like a lot of, you know,
link |
hardcore low level software to have it run efficiently
link |
and be power efficient because it's one thing to do neural nets
link |
if you've got a gigantic server room with 10,000 computers.
link |
But now let's say you just you have to now distill that down
link |
into one computer that's running at low power in a humanoid robot or a car.
link |
That's actually very difficult.
link |
A lot of hardcore software work is required for that.
link |
So since we're kind of like solving the navigate the real world
link |
with neural nets problem for cars,
link |
which are kind of robots with four wheels,
link |
then it's like kind of a natural extension of that is to put it
link |
in a robot with arms and legs and actuators.
link |
So like the two hard things are like you basically need to make the
link |
have the robot be intelligent enough to interact in a sensible way
link |
with the environment.
link |
So you need real world AI and you need to be very good at manufacturing,
link |
which is a very hard problem.
link |
Tesla is very good at manufacturing and also has the real world AI.
link |
So making the humanoid robot work is basically means developing custom motors
link |
and sensors that are different from what a car would use.
link |
But we've also we have I think we have the best expertise
link |
in developing advanced electric motors and power electronics.
link |
So it just has to be for humanoid robot application on a car.
link |
Still, you do talk about love sometimes.
link |
This isn't like for like sex robots or something like that.
link |
Love is the answer.
link |
There is something compelling to us, not compelling,
link |
but we connect with humanoid robots or even like robots like with the dog
link |
and shapes of dogs.
link |
It just it seems like, you know, there's a huge amount of loneliness in this world.
link |
All of us seek companionship with other humans, friendship
link |
and all those kinds of things.
link |
We have a lot of here in Austin, a lot of people have dogs.
link |
There seems to be a huge opportunity to also have robots that decrease
link |
the amount of loneliness in the world or help us humans connect with each other.
link |
So in a way that dogs can.
link |
Do you think about that with TeslaBot at all?
link |
Or is it really focused on the problem of performing specific tasks,
link |
not connecting with humans?
link |
I mean, to be honest, I have not actually thought about it from the companionship
link |
standpoint, but I think it actually would end up being it could be actually
link |
a very good companion.
link |
And it could develop like a personality over time that is that is like unique,
link |
like, you know, it's not like they're just all the robots are the same
link |
and that personality could evolve to be, you know,
link |
match the owner or the, you know, yes, the owner.
link |
Well, whatever you want to call it.
link |
The other half, right?
link |
In the same way that friends do.
link |
See, I think that's a huge opportunity.
link |
Yeah, no, that's interesting.
link |
Because, you know, like there's a Japanese phrase I like, Wabi Sabi,
link |
you know, the subtle imperfections are what makes something special.
link |
And the subtle imperfections of the personality of the robot mapped
link |
to the subtle imperfections of the robot's human friend.
link |
I don't know, owner sounds like maybe the wrong word,
link |
but could actually make an incredible buddy, basically.
link |
In that way, the imperfections.
link |
Like R2D2 or like a C3PO sort of thing, you know.
link |
So from a machine learning perspective,
link |
I think the flaws being a feature is really nice.
link |
You could be quite terrible at being a robot for quite a while
link |
in the general home environment or in general world.
link |
And that's kind of adorable.
link |
And that's like, those are your flaws and you fall in love with those flaws.
link |
So it's very different than autonomous driving
link |
where it's a very high stakes environment you cannot mess up.
link |
And so it's more fun to be a robot in the home.
link |
Yeah, in fact, if you think of like C3PO and R2D2,
link |
like they actually had a lot of like flaws and imperfections
link |
and silly things and they would argue with each other.
link |
Were they actually good at doing anything?
link |
I'm not exactly sure.
link |
They definitely added a lot to the story.
link |
But there's sort of quirky elements and, you know,
link |
that they would like make mistakes and do things.
link |
It was like it made them relatable, I don't know, enduring.
link |
So yeah, I think that that could be something that probably would happen.
link |
But our initial focus is just to make it useful.
link |
So I'm confident we'll get it done.
link |
I'm not sure what the exact timeframe is,
link |
but like we'll probably have, I don't know,
link |
a decent prototype towards the end of next year or something like that.
link |
And it's cool that it's connected to Tesla, the car.
link |
Yeah, it's using a lot of, you know,
link |
it would use the autopilot inference computer
link |
and a lot of the training that we've done for cars
link |
in terms of recognizing real world things
link |
could be applied directly to the robot.
link |
But there's a lot of custom actuators and sensors that need to be developed.
link |
And an extra module on top of the vector space for love.
link |
That's what I'm saying.
link |
We can add that to the car too.
link |
Yeah, it could be useful in all environments.
link |
Like you said, a lot of people argue in the car,
link |
so maybe we can help them out.
link |
You're a student of history,
link |
fan of Dan Carlin's Hardcore History podcast.
link |
Greatest podcast ever?
link |
Yeah, I think it is actually.
link |
It almost doesn't really count as a podcast.
link |
It's more like an audio book.
link |
So you were on the podcast with Dan.
link |
I just had a chat with him about it.
link |
He said you guys went military and all that kind of stuff.
link |
Yeah, it was basically, it should be titled Engineer Wars, essentially.
link |
Like when there's a rapid change in the rate of technology,
link |
then engineering plays a pivotal role in victory and battle.
link |
How far back in history did you go?
link |
Did you go World War II?
link |
Well, it was supposed to be a deep dive on fighters and bomber technology in World War II,
link |
but that ended up being more wide ranging than that,
link |
because I just went down the total rathole of studying all of the fighters and bombers of World War II
link |
and the constant rock, paper, scissors game that one country would make this plane,
link |
then it would make a plane to beat that, and that country would make a plane to beat that.
link |
And really what matters is the pace of innovation
link |
and also access to high quality fuel and raw materials.
link |
Germany had some amazing designs, but they couldn't make them
link |
because they couldn't get the raw materials,
link |
and they had a real problem with the oil and fuel, basically.
link |
The fuel quality was extremely variable.
link |
So the design wasn't the bottleneck?
link |
Yeah, the U.S. had kickass fuel that was very consistent.
link |
The problem is if you make a very high performance aircraft engine,
link |
in order to make it high performance, the fuel, the aviation gas,
link |
has to be a consistent mixture and it has to have a high octane.
link |
High octane is the most important thing, but it also can't have impurities and stuff
link |
because you'll foul up the engine.
link |
And Germany just never had good access to oil.
link |
They tried to get it by invading the Caucasus, but that didn't work too well.
link |
It never worked so well.
link |
It didn't work out for them.
link |
Germany was always struggling with basically shitty oil,
link |
and they couldn't count on high quality fuel for their aircraft,
link |
so they had to have all these additives and stuff.
link |
Whereas the U.S. had awesome fuel, and they provided that to Britain as well.
link |
So that allowed the British and the Americans to design aircraft engines
link |
that were super high performance, better than anything else in the world.
link |
Germany could design the engines, they just didn't have the fuel.
link |
And then also the quality of the aluminum alloys that they were getting
link |
was also not that great.
link |
Is this like, you talked about all this with Dan?
link |
Broadly looking at history, when you look at Genghis Khan,
link |
when you look at Stalin, Hitler, the darkest moments of human history,
link |
what do you take away from those moments?
link |
Does it help you gain insight about human nature, about human behavior today,
link |
whether it's the wars or the individuals or just the behavior of people,
link |
any aspects of history?
link |
Yeah, I find history fascinating.
link |
There's just a lot of incredible things that have been done, good and bad,
link |
that they help you understand the nature of civilization and individuals.
link |
Does it make you sad that humans do these kinds of things to each other?
link |
You look at the 20th century, World War II, the cruelty, the abuse of power,
link |
talk about communism, Marxism, and Stalin.
link |
I mean, there's a lot of human history.
link |
Most of it is actually people just getting on with their lives,
link |
and it's not like human history is just nonstop war and disaster.
link |
Those are actually just, those are intermittent and rare.
link |
If they weren't, then humans would soon cease to exist.
link |
But it's just that wars tend to be written about a lot,
link |
whereas something being like, well,
link |
a normal year where nothing major happened doesn't get written about much.
link |
But that's, most people just like farming and kind of living their life,
link |
being a villager somewhere.
link |
And every now and again, there's a war.
link |
And I would have to say, there aren't very many books where I just had to stop reading
link |
because it was just too dark.
link |
But the book about Stalin, The Court of the Red Tsar, I had to stop reading.
link |
It was just too dark and rough.
link |
The 30s, there's a lot of lessons there to me,
link |
in particular that it feels like humans,
link |
like all of us have that, it's the old Solzhenitsyn line,
link |
that the line between good and evil runs through the heart of every man,
link |
that all of us are capable of evil, all of us are capable of good.
link |
It's almost like this kind of responsibility that all of us have
link |
to tend towards the good.
link |
And so to me, looking at history is almost like an example of,
link |
look, you have some charismatic leader that convinces you of things.
link |
It's too easy, based on that story, to do evil onto each other,
link |
onto your family, onto others.
link |
And so it's like our responsibility to do good.
link |
It's not like now is somehow different from history.
link |
That can happen again. All of it can happen again.
link |
And yes, most of the time, you're right,
link |
the optimistic view here is mostly people are just living life.
link |
And as you've often memed about, the quality of life was way worse
link |
back in the day, and this keeps improving over time
link |
through innovation, through technology.
link |
But still, it's somehow notable that these blimps of atrocities happen.
link |
Yeah, I mean, life was really tough for most of history.
link |
I mean, for most of human history, a good year would be one
link |
where not that many people in your village died of the plague,
link |
starvation, freezing to death, or being killed by a neighboring village.
link |
It's like, well, it wasn't that bad.
link |
It was only like we lost 5% this year.
link |
That was a good year.
link |
That would be par for the course.
link |
Just not starving to death would have been the primary goal
link |
of most people throughout history,
link |
is making sure we'll have enough food to last through the winter
link |
and not freeze or whatever.
link |
So, now food is plentiful.
link |
I have an obesity problem.
link |
Well, yeah, the lesson there is to be grateful for the way things are now
link |
We've spoken about this offline.
link |
I'd love to get your thought about it here.
link |
If I sat down for a long form in person conversation with the President of Russia,
link |
Vladimir Putin, would you potentially want to call in for a few minutes
link |
to join in on a conversation with him, moderated and translated by me?
link |
Sure, I'd be happy to do that.
link |
You've shown interest in the Russian language.
link |
Is this grounded in your interest in history of linguistics, culture, general curiosity?
link |
I think it sounds cool.
link |
Sounds cool and that looks cool.
link |
Well, it takes a moment to read Cyrillic.
link |
Once you know what the Cyrillic characters stand for,
link |
actually then reading Russian becomes a lot easier
link |
because there are a lot of words that are actually the same.
link |
Like bank is bank.
link |
So find the words that are exactly the same and now you start to understand Cyrillic.
link |
If you can sound it out, there's at least some commonality of words.
link |
What about the culture?
link |
You love great engineering, physics.
link |
There's a tradition of the sciences there.
link |
You look at the 20th century from rocketry.
link |
Some of the greatest rockets, some of the space exploration has been done in the former Soviet Union.
link |
So do you draw inspiration from that history?
link |
Just how this culture that in many ways, one of the sad things is because of the language,
link |
a lot of it is lost to history because it's not translated.
link |
Because it is in some ways an isolated culture.
link |
It flourishes within its borders.
link |
So do you draw inspiration from those folks, from the history of science engineering there?
link |
The Soviet Union, Russia and Ukraine as well have a really strong history in space flight.
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Some of the most advanced and impressive things in history were done by the Soviet Union.
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So one cannot help but admire the impressive rocket technology that was developed.
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After the fall of the Soviet Union, there's much less that then happened.
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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.
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Yeah, there's Roscosmos, the Russian agency.
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I look forward to a time when those countries with China are working together.
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The United States are all working together.
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Maybe a little bit of friendly competition.
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I think friendly competition is good.
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Governments are slow and the only thing slower than one government is a collection of governments.
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So the Olympics would be boring if everyone just crossed the finishing line at the same time.
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Nobody would watch.
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And people wouldn't try hard to run fast and stuff.
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So I think friendly competition is a good thing.
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This is also a good place to give a shout out to a video titled,
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The Entire Soviet Rocket Engine Family Tree by Tim Dodd, AKA Everyday Astronaut.
link |
It's like an hour and a half.
link |
It gives the full history of Soviet rockets.
link |
And people should definitely go check out and support Tim in general.
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That guy is super excited about the future, super excited about space flight.
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Every time I see anything by him, I just have a stupid smile on my face because he's so excited about stuff.
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Yeah, Tim Dodd is really great.
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If you're interested in anything to do with space, he's, in terms of explaining rocket technology to your average person, he's awesome.
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The best, I'd say.
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And I should say like the part of the reason like I switched us from like Rafter at one point was going to be a hydrogen engine.
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But hydrogen has a lot of challenges.
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It's very low density.
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It's a deep cryogen.
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So it's only liquid at a very, very close to absolute zero.
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Requires a lot of insulation.
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So it is a lot of challenges there.
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And I was actually reading a bit about Russian rocket engine developments.
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And at least the impression I had was that the Soviet Union, Russia and Ukraine primarily were actually in the process of switching to Methalox.
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And there were some interesting tests and data for ISP.
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Like they were able to get like up to like a 380 second ISP with the Methalox engine.
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And I was like, well, OK, that's actually really impressive.
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So I think you could actually get a much lower cost, like in optimizing cost per ton to orbit, cost per ton to Mars.
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I think Methalox is the way to go.
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And I was partly inspired by the Russian work on the test stands with Methalox engines.
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And now for something completely different.
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Do you mind doing a bit of a meme review in the spirit of the great, the powerful PewDiePie?
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Let's say 1 to 11.
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Just go over a few documents printed out.
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I present to you document numero uno.
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Vladimir Impaler discovers marshmallows.
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So you get it? Because he likes impaling things.
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I don't know, three, whatever.
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That's not very good.
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This is grounded in some engineering, some history.
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Yeah, give us an eight out of ten.
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What do you think about nuclear power?
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I'm in favor of nuclear power.
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I think in a place that is not subject to extreme natural disasters, I think nuclear power is a great way to generate electricity.
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I don't think we should be shutting down nuclear power stations.
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Yeah, but what about Chernobyl?
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I think there's a lot of fear of radiation and stuff.
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The problem is a lot of people just don't study engineering or physics.
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Just the word radiation just sounds scary.
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They can't calibrate what radiation means.
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But radiation is much less dangerous than you think.
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For example, Fukushima, when the Fukushima problem happened due to the tsunami,
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I got people in California asking me if they should worry about radiation from Fukushima.
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I'm like, definitely not, not even slightly, not at all.
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Just to show this is how the danger is so much overplayed compared to what it really is that I actually flew to Fukushima.
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I donated a solar power system for a water treatment plant, and I made a point of eating locally grown vegetables on TV in Fukushima.
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So it's not even that the risk of these events is low, but the impact of them is...
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The impact is greatly exaggerated.
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It's human nature.
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People don't know what radiation is.
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I've had people ask me, what about radiation from cell phones causing brain cancer?
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I'm like, when you say radiation, do you mean photons or particles?
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They're like, I don't know, what do you mean photons or particles?
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Do you mean, let's say, photons?
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What frequency or wavelength?
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And they're like, I have no idea.
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Do you know that everything's radiating all the time?
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Like, yeah, everything's radiating all the time.
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Photons are being emitted by all objects all the time, basically.
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And if you want to know what it means to stand in front of nuclear fire, go outside.
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The sun is a gigantic thermonuclear reactor that you're staring right at it.
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Are you still alive?
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Yeah, I guess radiation is one of the words that could be used as a tool to fear monger by certain people.
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I think people just don't understand.
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I mean, that's the way to fight that fear, I suppose, is to understand, is to learn.
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Yeah, just say, okay, how many people have actually died from nuclear accidents?
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It's practically nothing.
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And say, how many people have died from coal plants?
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And it's a very big number.
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So, like, obviously we should not be starting up coal plants and shutting down nuclear plants.
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It just doesn't make any sense at all.
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Coal plants, like, I don't know, 100 to 1,000 times worse for health than nuclear power plants.
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You want to go to the next one?
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This is really bad.
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It's 90, 180, and 360 degrees.
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Everybody loves the math.
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Nobody gives a shit about 270.
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It's not super funny.
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I don't know, like, 203.
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This is not a, you know, LOL situation.
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That was pretty good.
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The United States oscillating between establishing and destroying dictatorships.
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It's like a metronome.
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Is that a metronome?
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Yeah, it's out of 7 out of 10.
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It's kind of true.
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Oh, yeah, this is kind of personal for me.
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Or it's like referring to Leica or something?
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As Leica's, like, husband.
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Your wife was launched into space.
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And then the last one is him with his eyes closed and a bottle of vodka.
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Leica didn't come back.
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They don't tell you the full story of, you know, what the impact they had on the loved
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It's like 711 for me.
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The Soviet shadow.
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This keeps going on the Russian theme.
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First man in space.
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First man on the moon.
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Well, I think people do care.
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Yuri Gagarin's name will be forever in history, I think.
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There is something special about placing, like, stepping foot onto another totally foreign
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It's not the journey, like, people that explore the oceans.
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It's not as important to explore the oceans as to land on a whole new continent.
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Well, this is about you.
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Oh, yeah, I'd love to get your comment on this.
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Elon Musk, after sending 6.6 billion dollars to the UN to end world hunger, you have three
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Yeah, well, I mean, obviously, 6 billion dollars is not going to end world hunger.
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So I mean, the reality is at this point, the world is producing far more food than it can
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Like, we don't have a caloric constraint at this point.
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So where there is hunger, it is almost always due to, like, civil war or strife or some
link |
like, it's not a thing that is extremely rare for it to be just a matter of, like, lack
link |
It's like, you know, it's like some civil war in some country and like one part of the
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country is literally trying to starve the other part of the country.
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So it's much more complex than something that money could solve.
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It's a lot of things.
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It's human nature.
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It's money, monetary systems, all that kind of stuff.
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Yeah, food is extremely cheap these days.
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It's like, I mean, the US at this point, you know, among low income families, obesity is
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actually another problem.
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It's not, like, obesity, it's not hunger.
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It's like too much, you know, too many calories.
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So it's not that nobody's hungry anywhere.
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It's just, this is not a simple matter of adding money and solving it.
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What do you think that one gets?
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We're just going after empires, world, where did you get those artifacts?
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The British Museum.
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Shout out to Monty Python.
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The British Museum is pretty great.
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I mean, admittedly Britain did take these historical artifacts from all around the world
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and put them in London, but, you know, it's not like people can't go see them.
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So it is a convenient place to see these ancient artifacts is London for, you know, for a large
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segment of the world.
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So I think, you know, on balance, the British Museum is a net good, although I'm sure a
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lot of countries will argue about that.
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It's like you want to make these historical artifacts accessible to as many people as
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possible and the British Museum, I think, does a good job of that.
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Even if there's a darker aspect to like the history of empire in general, whatever the
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empire is, however things were done, it is the history that happened.
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You can't sort of erase that history, unfortunately.
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You could just become better in the future.
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I mean, it's like, well, how are we going to pass moral judgment on these things?
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Like it's like if, you know, if one is going to judge, say, the Russian Empire, you've
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got to judge, you know, what everyone was doing at the time and how were the British
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relative to everyone.
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And I think the British would actually get like a relatively good grade, relatively good
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grade, not in absolute terms, but compared to what everyone else was doing, they were
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Like I said, you got to look at these things in the context of the history at the time
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and say, what were the alternatives and what are you comparing it against?
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And I do not think it would be the case that Britain would get a bad grade when looking
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at history at the time.
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You know, if you judge history from, you know, from what is morally acceptable today, you
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basically are going to give everyone a failing grade.
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It's not, I don't think anyone would get a passing grade in their morality of like you
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could go back 300 years ago, like who's getting a passing grade?
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And we might not get a passing grade from generations that come after us.
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What does that one get?
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For the Monty Python, maybe.
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I always love Monty Python.
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The Life of Brian and the Quest of the Holy Grail are incredible.
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Those serious eyebrows.
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How important do you think is facial hair to great leadership?
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Well, you got a new haircut.
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How does that affect your leadership?
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Is that the second no one?
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The second is no one.
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There is no one competing with Brezhnev.
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Those are like epic eyebrows.
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That's ridiculous.
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Give it a six or seven, I don't know.
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I like this Shakespearean analysis of memes.
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Brezhnev, he had a flair for drama as well.
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Like, you know, showmanship.
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It must come from the eyebrows.
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Invention, great engineering, look what I invented, that's the best thing since ripped
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Because they invented sliced bread, am I just explaining memes at this point?
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This is where my life has become a meme, what it like, you know, like a scribe that like
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runs around with the kings and just like writes down memes.
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I mean, when was the cheeseburger invented?
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That's like an epic invention.
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Versus just like a burger or a burger, I guess a burger in general is like, you know, then
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there's like, what is a burger, what's a sandwich, and then you start getting a pizza sandwich
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and what is the original, it gets into an ontology argument.
link |
But everybody knows like if you order like a burger or cheeseburger or whatever and you
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like, you got like, you know, tomato and some lettuce and onions and whatever and, you know,
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mayor and ketchup and mustard, it's like epic.
link |
But I'm sure they've had bread and meat separately for a long time and it was kind of a burger
link |
on the same plate, but somebody who actually combined them into the same thing and then
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you bite it and hold it makes it convenient.
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It's a materials problem.
link |
Like your hands don't get dirty and whatever.
link |
Well, that is not what I would have guessed, but everyone knows like you, if you order
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a cheeseburger, you know what you're getting, you know, it's not like some obtuse, like,
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well, I wonder what I'll get, you know, um, you know, uh, fries are, I mean, great.
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I mean, they were the devil, but fries are awesome.
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And uh, yeah, pizza is incredible.
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Food innovation doesn't get enough love, I guess is what we're getting at.
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Um, uh, what about the, uh, Matthew McConaughey, Austinite here, uh, president Kennedy, do
link |
you know how to put men on the moon yet?
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President Kennedy, it'd be a lot cooler if you did.
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Pretty much sure, six, six or seven, I suppose.
link |
And this is the last one that's funny.
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Someone drew a bunch of dicks all over the walls, 16 chapel boys bath.
link |
I'll give it a nine.
link |
This is our highest ranking meme for today.
link |
I mean, it's true.
link |
Like, how do they get away with it?
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Lots of nakedness.
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I mean, dick pics are, I mean, just something throughout history.
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Uh, as long as people can draw things, there's been a dick pic.
link |
It's a staple of human history.
link |
It's just throughout human history.
link |
You tweeted that you aspire to comedy.
link |
You're friends with Joe Rogan.
link |
Might you, uh, do a short standup comedy set at some point in the future, maybe, um, open
link |
for Joe, something like that.
link |
Is that, is that...
link |
Actual, just full on standup?
link |
Is that in there or is that...
link |
It's extremely difficult if, uh, at least that's what, uh, like Joe says and the comedians
link |
I wonder if I could, um, I mean, I, I, you know, I, I have done standup for friends,
link |
just, uh, impromptu, you know, I'll get, get on like a roof, uh, and they, they do laugh,
link |
but they're our friends too.
link |
So I don't know if, if you've got to call, you know, like a room of strangers, are they
link |
going to actually also find it funny, but I could try, see what happens.
link |
I think you'd learn something either way.
link |
I kind of love, um, both the, when you bomb and when, when you do great, just watching
link |
people, how they deal with it, it's so difficult.
link |
It's so, you're so fragile up there.
link |
It's just you and you, you think you're going to be funny.
link |
And when it completely falls flat, it's just, it's beautiful to see people deal with like
link |
I might have enough material to do standup.
link |
I've never thought about it, but I might have enough material.
link |
Um, I don't know, like 15 minutes or something.
link |
Do a Netflix special.
link |
Um, what's your favorite Rick and Morty concept, uh, just to spring that on you.
link |
Is there, there's a lot of sort of scientific engineering ideas explored there.
link |
There's the butter robot.
link |
That's a great, uh, that's a great show.
link |
Rick and Morty is awesome.
link |
Somebody that's exactly like you from an alternate dimension showed up there.
link |
Yeah, that's right.
link |
Rick and Morty certainly explores a lot of interesting concepts.
link |
Uh, so like what's the favorite one?
link |
The butter robot certainly is, uh, you know, it's like, it's certainly possible to have
link |
too much sentience in a device.
link |
Um, like you don't want to have your toast to be like a super genius toaster.
link |
It's going to hate, hate life cause all it could do is make his toast.
link |
But if it's like, you don't want to have like super intelligent stuck in a very limited
link |
Um, do you think it's too easy from a, if we're talking about from the engineering perspective
link |
of super intelligence, like with Marvin the robot, like, is it, it seems like it might
link |
be very easy to engineer just the depressed robot.
link |
Like it's not obvious to engineer and robot that's going to find a fulfilling existence.
link |
Sometimes humans I suppose, but, um, I wonder if that's like the default, if you don't do
link |
a good job on building a robot, it's going to be sad a lot.
link |
Well we can reprogram robots easier than we can reprogram humans.
link |
So I guess if you let it evolve without tinkering, then it might get a sad, uh, but you can change
link |
the optimization function and have it be a cheery robot.
link |
You uh, like I mentioned with, with SpaceX, you give a lot of people hope and a lot of
link |
people look up to you.
link |
Millions of people look up to you.
link |
Uh, if we think about young people in high school, maybe in college, um, what advice
link |
would you give to them about if they want to try to do something big in this world,
link |
they want to really have a big positive impact.
link |
What advice would you give them about their career, maybe about life in general?
link |
Um, you know, do things that are useful to your fellow human beings, to the world.
link |
It's very hard to be useful.
link |
Um, you know, are you contributing more than you consume?
link |
You know, like, uh, like can you try to have a positive net contribution to society?
link |
Um, I think that's the thing to aim for, you know, not, not to try to be sort of a leader
link |
for just for the sake of being a leader or whatever.
link |
Um, a lot of time people, a lot of times the people you want as leaders are the people
link |
who don't want to be leaders.
link |
So, um, if you live a useful life, that is a good life, a life worth having lived.
link |
Um, you know, and I, like I said, I would, I would encourage people to use the mental
link |
tools of physics and apply them broadly in life.
link |
There are the best tools.
link |
When you think about education and self education, what do you recommend?
link |
So there's the university, there's a self study, there is a hands on sort of finding
link |
a company or a place or a set of people that do the thing you're passionate about and joining
link |
them as early as possible.
link |
Um, there's, uh, taking a road trip across Europe for a few years and writing some poetry,
link |
which, uh, which, which trajectory do you suggest?
link |
In terms of learning about how you can become useful, as you mentioned, how you can have
link |
the most positive impact.
link |
Well, I encourage people to read a lot of books, just read, basically try to ingest
link |
as much information as you can, uh, and try to also just develop a good general knowledge.
link |
Um, so, so you at least have like a rough lay of the land of the knowledge landscape.
link |
Like try to learn a little bit about a lot of things, um, cause you might not know what
link |
you're really interested in.
link |
How would you know what you're really interested in if you at least aren't like doing a peripheral
link |
explore exploration of broadly of, of the knowledge landscape?
link |
Um, and you talk to people from different walks of life and different, uh, industries
link |
and professions and skills and occupations, like just try to learn as much as possible.
link |
Man's search for meaning.
link |
Isn't the whole thing a search for meaning?
link |
What's the meaning of life and all, you know, but just generally, like I said, I would encourage
link |
people to read broadly, um, in many different subject areas, um, and, and, and then try
link |
to find something where there's an overlap of your talents and, and what you're interested
link |
So people may, may, may be good at something, but, or they may have skill at a particular
link |
thing, but they don't like doing it.
link |
Um, so you want to try to find a thing where you have your, that's a good, a good, a combination
link |
of, of your, of the things that you're inherently good at, but you also like doing, um, and,
link |
And reading is a super fast shortcut to, to figure out which, where are you, you both
link |
You like doing it and it will actually have positive impact.
link |
Well, you got to learn about things somehow.
link |
So read, reading a broad range, just really read, read it.
link |
You know, one point was that kid I read through the encyclopedia, uh, so that was pretty helpful.
link |
Um, and, uh, there are also things that I didn't even know existed a lot, so obviously
link |
It's like as broad as it gets.
link |
Encyclopedias were digestible, I think, uh, you know, whatever, 40 years ago.
link |
Um, so, um, you know, maybe read through the, the condensed version of the encyclopedia
link |
And that, um, you can always like skip subjects or you read a few paragraphs and you know
link |
you're not interested, just jump to the next one.
link |
That sort of read the encyclopedia or scan, skim, skim through it.
link |
Um, and, um, but I, you know, I put a lot of stock and certainly have a lot of respect
link |
for someone who puts in an honest day's work, uh, to do useful things and, and just generally
link |
to have like a, not a zero sum mindset, um, or, uh, like have, have more of a grow the
link |
Like the, if you, if you sort of say like when, when I see people like perhaps, um,
link |
including some very smart people kind of taking an attitude of, uh, like, like, like doing
link |
things that seem like morally questionable, it's often because they have at a base sort
link |
of axiomatic level, a zero sum mindset.
link |
Um, and, and they, without realizing it, they don't realize they have a zero sum mindset
link |
or at least that they don't realize it consciously.
link |
Um, and so if you have a zero sum mindset, then the only way to get ahead is by taking
link |
things from others.
link |
If it's like, if the, if the, if the pie is fixed, then the only way to have more pie
link |
is to take someone else's pie.
link |
But this is false.
link |
Like obviously the pie has grown dramatically over time, the economic pie.
link |
Um, so the reality, in reality you can have the, so overuse this analogy, if you have
link |
a lot of, there's a lot of pie, pie is not fixed.
link |
Um, uh, so you really want to make sure you don't, you're not operating, um, without realizing
link |
it from a zero sum mindset where, where the only way to get ahead is to take things from
link |
And you take, try to take things from others, which is not, not good.
link |
It's much better to work on, uh, adding to the economic pie, maybe, you know, so creating,
link |
like I said, create, creating more than you consume, uh, doing more than you.
link |
Um, so that's, that's a big deal.
link |
Um, I think there's like, you know, a fair number of people in, in finance that, uh,
link |
do have a bit of a zero sum mindset.
link |
I mean, it's all walks of life.
link |
I've seen that one of the, one of the reasons, uh, Rogan inspires me is he celebrates others
link |
There's not, not creating a constant competition.
link |
Like there's a scarcity of resources.
link |
What happens when you celebrate others and you promote others, the ideas of others, it,
link |
it, uh, it actually grows that pie.
link |
I mean, it, every, like the, uh, the resource, the resources become less scarce and that,
link |
that applies in a lot of kinds of domains.
link |
It applies in academia where a lot of people are very, uh, see some funding for academic
link |
research is zero sum and it is not.
link |
If you celebrate each other, if you make, if you get everybody to be excited about AI,
link |
about physics, above mathematics, I think it, there'll be more and more funding and
link |
I think everybody wins.
link |
That applies, I think broadly.
link |
yeah, yeah, exactly.
link |
So last, last question about love and meaning, uh, what is the role of love?
link |
In the human condition, broadly and more specific to you, how has love, romantic love or otherwise
link |
made you a better person, a better human being?
link |
Now you're asking really perplexing questions.
link |
Um, it's hard to give a, I mean, there are many books, poems and songs written about
link |
what is love and what is, what exactly, you know, um, you know, what is love, baby don't
link |
Um, that's one of the great ones.
link |
You've, you've earlier quoted Shakespeare, but that that's really up there.
link |
Love is a many splinter thing.
link |
Uh, I mean there's, um, it's cause we've talked about so many inspiring things like be useful
link |
in the world, sort of like solve problems, alleviate suffering, but it seems like connection
link |
between humans is a source, you know, it's a, it's a source of joys, a source of meaning
link |
and that, that's what love is, friendship, love.
link |
I just wonder if you think about that kind of thing where you talk about preserving the
link |
light of human consciousness and us becoming a multi planetary, multi planetary species.
link |
I mean, to me at least, um, that, that means like if we're just alone and conscious and
link |
intelligent and it doesn't mean nearly as much as if we're with others, right?
link |
And there's some magic created when we're together, the, uh, the, the friendship of
link |
And I think the highest form of it is love, which I think broadly is, is much bigger than
link |
just sort of romantic, but also yes, romantic love and, um, family and those kinds of things.
link |
Well, I mean, the reason I guess I care about us becoming multi planet species in a space
link |
frank civilization is foundationally, I love humanity, um, and, and so I wish to see it
link |
prosper and do great things and be happy and, um, and if I did not love humanity, I would
link |
not care about these things.
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So when you look at the whole of it, the human history, all the people who's ever lived,
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all the people live now, it's pretty, we're, we're okay.
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On the whole, we're pretty interesting bunch.
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All things considered, and I've read a lot of history, including the darkest, worst parts
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of it, and, uh, despite all that, I think on balance, I still love humanity.
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You joked about it with the 42, uh, what do you, what do you think is the meaning of this
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Is like, is there a non numerical representation?
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Well, really, I think what Douglas Adams was saying in Hitchhiker's Guide to the Galaxy
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is that, um, the universe is the answer and, uh, what we really need to figure out are
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what questions to ask about the answer that is the universe and that the question is the
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really the hard part.
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And if you can properly frame the question, then the answer, relatively speaking, is easy.
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Uh, so, so, so therefore, if you want to understand what questions to ask about the universe,
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you want to understand the meaning of life, we need to expand the scope and scale of consciousness
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so that we're better able to understand the nature of the universe and, and understand
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the meaning of life.
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And ultimately, the most important part would be to ask the right question, thereby elevating
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the role of the interviewer as the most important human in the room.
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Good questions are, you know, it's a hard, it's hard to come up with good questions.
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Um, but yeah, like, it's like that, that is the foundation of my philosophy is that, um,
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I am curious about the nature of the universe and, uh, you know, and obviously I will die.
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I don't know when I'll die, but I won't live forever.
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Um, but I would like to know that we are on a path to understanding the nature of the
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universe and the meaning of life and what questions to ask about the answer that is
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And, um, and so if we expand the scope and scale of humanity and consciousness in general,
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um, which includes silicon consciousness, then that, you know, that, that, that seems
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like a fundamentally good thing.
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Elon, like I said, um, I'm deeply grateful that you would spend your extremely valuable
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time with me today and also that you have given millions of people hope in this difficult
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time, this divisive time, in this, uh, cynical time.
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So I hope you do continue doing what you're doing.
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Thank you so much for talking today.
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Oh, you're welcome.
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Uh, thanks for your excellent questions.
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Thanks for listening to this conversation with Elon Musk.
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To support this podcast, please check out our sponsors in the description.
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And now let me leave you with some words from Elon Musk himself.
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When something is important enough, you do it, even if the odds are not in your favor.
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Thank you for listening and hope to see you next time.