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Speaker 1: Latest interview of Elon Musk.

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Speaker 2: Very soon though, Yeah, I think probably at this point Grock.

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If you if you took a photo and submitted to Grock,

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you can probably tell you if the circus is somewhere

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wrong with it.

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Speaker 3: Yeah, yeah, all right, I'm gonna give it a shot.

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You're using the same Grock that I'm using, are you

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or you are? Rock keeps updating, so four point two

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but five is soon, right?

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Speaker 2: Five is Q one? Yeah, four point two has not

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been released yet externally. But yeah, I mean, if you

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just if you just upload an image into rock, it's

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it's just quite a good job of analyzing any given image.

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Speaker 3: Absolutely. Let's let's start. Well, we're going to talk about this,

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all right, we'll come back.

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Speaker 2: I mean, let's see if I if I take an

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if I take a picture of you, what is it.

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Speaker 4: Let's see what I was going to say about me.

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Speaker 3: Yeah, it's gonna say you're a flawed circuit.

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Speaker 2: I also remember to update it because like we update

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the grock app so frequently.

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Speaker 5: You know, I asked, I asked Rock to roast me.

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It did an amazing job. Then I asked GROC to

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roast you, and I spit out my coffee.

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Speaker 4: It was. It was hilarious, and then I asked it

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you know, it just.

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Speaker 3: Keeps telling it to be more and more. I asked,

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until until it's like the father of is that Rudy

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still out there? Did that get repealed?

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Speaker 5: And I asked, does elond know what you say about him?

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And and she goes, it's a sheet for me. She goes,

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what is he gonna do about it?

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Speaker 3: Yeah, let's see. So I just literally took a photo

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of you, and.

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Speaker 4: Did you ask a question?

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Speaker 3: No? Nothing, I doesn't say anything.

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Speaker 4: This man is hugely.

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Speaker 3: This is period amandas.

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Speaker 4: Yes, okay, that's pretty good.

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Speaker 3: Yeah, context whatsoever?

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Speaker 4: The host of the podcast in shots. Yeah, sometimes that's

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your first credential. Now forget about everything.

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Speaker 3: No context. Image.

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Speaker 5: By the way, Wikipedia is awesome, I mean just phenomenal.

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I mean just it's like I tried to like update

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my Wikipedia page for like years impossibly, and yeah, it

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knows me amazing.

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Speaker 4: Yeah, he's wearing.

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Speaker 5: A black quilted jacket featuring a sun Dance logo. Not

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quite true, it's my abundant logo, I think so anyway.

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Speaker 3: Yeah, but it basically it's pretty damn good.

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Speaker 2: Yeah, he's smiling and relaxed with the laptop in front

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of him.

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Speaker 4: That's true.

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Speaker 3: That's true. Yeah, well quite a circuit though. I got

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to test it on this only it has to be

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read by you, though, I mean, I want to read

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the whole thing, but.

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Speaker 4: Give me a taste. I can take it.

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Speaker 2: Okay, check out that grin dude smiling like you just

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discovered a new way to monetize hope.

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Speaker 3: Monetizing. Though.

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Speaker 5: Yes, I want to try and answer the question can

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AI and tech help save American the world?

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Speaker 4: Right?

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Speaker 5: I want to give people listening a dose of optimism

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because it's survey done in mid December by Pew that

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said forty five percent of Americans would rather live in

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the past and only fourteen percent said they'd rather live

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in the future, which is insane to me, right, Obviously

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they never read history. The challenges most Americans all they

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have of the future. It's like Hollywood has shown us

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killer ais and rogue robots, right, and people are worried

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about their jobs, They're worried about healthcare, they're worried about

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you know, the cost of living. The challenge is how

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do we how do we help people? I mean, you

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posted you pinned on X the future is going to

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be amazing with AI and robots enabling sustainable abundance.

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Speaker 3: Thank you. I appreciate that.

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Speaker 4: And and uh well, I.

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Speaker 2: Mean because like what would Peter do you want to say?

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Speaker 3: Channeling?

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Speaker 4: Thank you? I couldn't agree more agree more.

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Speaker 3: So.

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Speaker 5: So my question is from a you know, from a

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first principal standpoint. Yeah, the rationale for optimism. You know,

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how do we how do we head towards star Trek

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and not Terminator?

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Speaker 3: Right?

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Speaker 4: How do we how do we head towards.

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Speaker 3: Run Berry Cameron?

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Speaker 4: Yeah, Jim.

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Speaker 3: Diverging path, Yes, it is, it is.

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Speaker 4: Avatar has some hopeful parts.

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Speaker 5: But anyway, how do we go towards universal high income

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instead of social unrest?

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Speaker 4: So both.

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Speaker 2: Have universalhigh income and social unrest. That's my prediction that.

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Speaker 4: Will make for a lot of problems.

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Speaker 3: Is that your actual prediction? Yeah? Yeah, it seems likely.

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Tell me how to push back on it exactly, But

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it's not like that's the trend. Yeah, yeah, totally. No,

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we have Well, because there's going to be so much.

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Speaker 4: Change, people are going to be like, it's scared shitless.

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Speaker 2: Yeah, it's it's sort of the you know, it's like,

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be careful what you wish for because you might get it.

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Speaker 4: Yeah.

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Speaker 2: Now if you if you actually get all the stuff

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you want, is that actually the future you want? Yeah,

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because it means that your job won't be won't matter.

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Speaker 5: If you're living an unchallenged life, yes, right, with no challenges.

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Speaker 3: Yeah.

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Speaker 5: No, you know you know, if you become a couch potato,

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if it's the wily future, it does not go well

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for humans.

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Speaker 3: Well, and we're used to being told here's your challenge,

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So people haven't historically been very good at creating their

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own challenge in the absence.

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Speaker 5: Of Elon does a damn good job every time, every

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time one company takes off, you start.

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Speaker 4: Your next' that's rare punishment. I think you are. Yeah,

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I think you ever. Thank God for that.

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Speaker 3: Why why do I do this to myself? Actually? After

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AI and robots, is there another thing after that?

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Speaker 4: I guess there's well, there's conquering you know, the universe.

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There is that rocks really well, and energy rocks at

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your friends, so good to need.

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Speaker 3: To get there?

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Speaker 4: Why why are you so optimistic? Are you? Are you optimistic?

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Let's start there.

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Speaker 2: I'm not as optimistic as you are, okay, but but

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why are you more optimistic than most people.

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Speaker 3: Okay, and is the trend upward compared to a year

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ago two years ago?

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Speaker 2: Well, I think if you reframe things in terms of

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progress bar like in speaking of challenges, progress towards a

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kardifship to scale civilization.

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Speaker 3: Well, let's say let's say the aspiration.

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Speaker 4: Capturing all the energy from the Sun's output, Well.

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Speaker 2: Let's even have a humbler humbler aspiration than that. If

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we say that our goal is to even get a

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millionth of the Sun's energy, that would be more than

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a thousand times as much energy as could possibly be

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produced on Earth. So about half a billionth of the

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Sun's energy reaches Earth, So you'd have to go up

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three ords of magnitude from that just to get to

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a million. So we're very, very very far from even

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having a billionth of the Sun's energy harness in any way.

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So a reasonable goal would be try to get to

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a million. And if you try to get to a

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millionth or a thousandth er point one percent, uh, that's

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that's such an enormous Uh. Look, there's not sure what

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metaphor weduce here, but because the hill decline is is

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not a appropriate It's like not a big enough medical

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for gravity well to gravity well exactly, so if you

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try to get to a million to the Sun's energy

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or a thousand of the Sun's energy, like now, these

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are very very.

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Speaker 4: Difficult tasks, and energy is the inner loop for everything

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right now.

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Speaker 2: Yeah, I think, like I think the future currency will

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essentially just be wattag.

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Speaker 5: Now I was thinking, is it is It is the

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ability of a person to control energy and compute or

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just energy, I mean the two too translator just.

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Speaker 2: Like honest energy, yeah, like so or like basically how

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much power is being turned into work of some kind,

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right intelligence or matt and manipulation.

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Speaker 4: So that's your next big project is going to be energy.

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It's it's going to be You're gonna go back to.

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Speaker 2: Expand from there and say, okay, what about even getting

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somewhere on a Cotter show of three scale meaning galaxy level.

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Speaker 4: Now we're talking now we're back to star trek.

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Speaker 2: Yeah, expand to horizons here. Yes, well there isn't even

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a rizon because you're on a planet.

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Speaker 3: So we talked about so think galaxy mind.

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Speaker 5: Yeah, well listen, we're in eleven eleven point five million

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square foot three pentagons right here, in this building.

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Speaker 4: Yeah, you think in a reasonably large scale, what is magnitude?

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Speaker 2: Yeah, so, I mean so from a challenge standpoint, I

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guess the the civilizational challenge will be how do you

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climb the order's magnitude and energy harnessed.

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Speaker 5: But we're going back to why you optimistic right now.

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I mean when people think about the challenges ahead, I

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think we're going to end up with abundance in the

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long run.

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Speaker 2: It's beyond abundance in any beyond what people possibly could

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think of as abundance. But like the AI, actually AI

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and robots in the limit, well, we'll saturate or human

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desire and.

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Speaker 5: We get to nanotechnology, which takes it even a step further.

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Speaker 2: The thing about the net, well, I'm not sure what

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you mean by means like.

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Speaker 4: The atomic reassembly.

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Speaker 3: Yeah, hell yeah, yeah, sure sure.

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Speaker 2: I mean we're already doing atomic level assembly on the

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four circuits.

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Speaker 4: You know, amazing two three nanometers.

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Speaker 2: Yeah, it's only depending on how they're arrayed. Four or

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five silicon atoms pernanometers.

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Speaker 3: Yeah, so those are big atoms.

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Speaker 2: They're not big, I mean, but but I'm saying you

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could they should actually describe the circuits in terms of

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an integer number of atoms in a specific place.

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Speaker 3: It's a LANs terms now you can, you can.

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Speaker 2: It's just it's like it's it's like the we'll call

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this the the seven atom or whatever, like you said,

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two animeters, Like it's like no one knows nine silicen

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atoms something like that.

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Speaker 3: They've got silicon and copper and you know.

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Speaker 2: So, but a bunch of these things are just marketing numbers,

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like the two nanometers just the marketing number. But but

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you still need essentially close to atomic level precision, like

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the atoms really need to be in the right spot.

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So I think they're getting clean rooms wrong. By the way,

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in these modern fats, I'm gonna I'm gonna make a

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bed here, okay, Okay, that's tesla will have a two

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naimeter fab and I can I can eat a cheeseburger

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and smoke a cigar in the fat.

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Speaker 4: Yeah, they're handling will be that good.

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Speaker 3: Okay, do you have this sketched out in your mind?

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Like how is it? How are the atoms being placed

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that they're immune to cheeseburger grease. They're just maintained wave

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for isolation the entire time, which is actually the default

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four four fabs.

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Speaker 2: The wafers are transported in boxes of pure nitrogen gas

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under a slip positive.

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Speaker 3: So where the bananas at Walmart?

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Speaker 2: Just so you know, yeah, well that's that's It's essentially

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like it's pretty hard for anything that's combusting to live

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without oxygen.

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Speaker 4: Ye.

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Speaker 2: So let's talk about so you like, like you can

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kill the bugs just by putting a nitrogen blanket.

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Speaker 3: Interesting.

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Speaker 5: Interesting, I we talk about energy health education because those

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are people's you know, concerns. So on the energy front,

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the innermost loop of everything that you're building and doing right.

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Speaker 3: Now, energy is the foundation.

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Speaker 5: What's your vision for energy abundance? The Sun in the

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next this decade?

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Speaker 4: The Sun?

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Speaker 2: Yeah, I mean, so the Sun is everything.

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Speaker 4: It's everything. So you're all in unsolared. Yeah, I mean

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your natural and solar you're at colossus to right.

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Speaker 3: Yeah.

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Speaker 2: People just don't understand how that solar is everything. So

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everything compared to the Sun, all other energy sources are

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like cavemen throwing some twigs into a fire.

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Speaker 3: Yeah.

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Speaker 2: So the the Sun is over ninety nine zero point

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eight percent of all mass in the Solar system. Jupiter

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is around zero point one percent of the mass. So

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even if you BoNT Jupiter, the energy produced by the

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Sun was still around up two hundred percent. Yeah, and

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then if you teleported three more jupiters into our soul

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system and burnt them.

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Speaker 4: Too, it's still round up.

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Speaker 3: It's still run.

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Speaker 2: The still rounds up to one hundred percent of energy.

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Speaker 4: Any interest in fusion, I mean, yeah, no fusion.

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Speaker 2: You know what you know a mile away, We're never

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gonna guess how the sun works.

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Speaker 4: Giant coal plants.

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Speaker 2: I mean, we have a giant fusure free fusion reactors

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up every days away. It's farcical for us to create

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a little fusion reactors. I mean that would be like,

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you know, having a tiny ice cube maker. Hey look

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we made some like congratulations.

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Speaker 3: So totally it's totally with you on this.

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Speaker 2: It's like it's like three kilometers high glaciers right next

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to you.

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Speaker 3: Yeah, recognized. If you just narrow the question into the

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Memphis timeline, So Memphis Data Center timeline between a gigawatt

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and ten giggle, you're not gonna you're not gonna pull

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ten gigawatts out of Memphis. Maybe you are three, two

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or three, Okay, So so there's still a gap between

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there and the next whatever, you just so, and they're

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not in spin yet at that point.

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Speaker 2: We're still in toyland here. Uh for Toylandland.

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Speaker 3: You know what's amazing is there's one hundred megawatts right

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outside the door here and it's massive. It's it's enormous,

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and it uses more energy hundred times then everything. All

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these manufacturing lines combined use less energy than that, I think.

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But we're talking about Cortex one.

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Speaker 2: Was the third largest training cluster in the in the world.

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Speaker 3: Yeah, for doing coherent training, you're falling behind. Uh.

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Speaker 2: Well with Cortex two that's being built out, that'll be

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uh half a giga an operational.

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Speaker 3: Middle next year.

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Speaker 4: Everybody.

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Speaker 5: You may not know this, but I've done an incredible

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research team and every week myself my research team study

294
00:16:10,720 --> 00:16:16,320
the meta trends that are impacting the world topics like computation, sensors, networks, AI, robotics,

295
00:16:16,320 --> 00:16:19,559
three D printing, synthetic biology, and these meta trend reports

296
00:16:19,600 --> 00:16:22,039
I put out once a week enable you to see

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00:16:22,080 --> 00:16:24,879
the future ten years ahead of anybody else. If you'd

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like to get access to the Meta Trends newsletter every week,

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00:16:28,080 --> 00:16:31,559
go to Deamandis dot com slash Meta Trends that's demandis

300
00:16:31,600 --> 00:16:34,919
dot com slash meta trends. So going back to what

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Dave is saying, over the next five years, what are

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you scaling on energy front?

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Speaker 3: I mean this is a long time I mean energy.

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Speaker 5: I mean China has done an incredible job. Yeah right,

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I mean it's running circles around US.

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Speaker 2: China has done an incredible job on solar. Yeah, that's amazing.

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So I believe China's production capacity is around fifteen hundred

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gigawatts per year of solar.

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Speaker 4: They put five hundred taro watts in the last year hours, yeah.

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Speaker 2: Like.

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Speaker 5: Hours, to be very specific, in the last year, seventy

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percent of that was solar, and they're just scaling.

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Speaker 4: Do you do you do you imagine that?

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Speaker 5: Do you imagine that the US could make that level

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of investment and commitment because people are worried about their

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energy bills going up with no data centers in our backyard,

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how do we provide I mean energy?

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Speaker 4: Energy.

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Speaker 5: Energy is equivalent to is equivalent to cost of you know,

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cost of living, It's equivalent to health, it's equivalent to

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clean water. You know, the higher energy production of a country,

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the higher its GDP.

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Speaker 4: Energy is important. So what should what do we do

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to scale that way? Do we do it in solar here?

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Speaker 2: I think we should scale solar substantially in the US

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TESTA and Space EXO scaling solar so and I encourage others.

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Speaker 4: To do so as well.

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Speaker 3: So the the.

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Speaker 2: I mean, I've said this stuff, you know publicly. I

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do see a path to one hundred gig go. What's

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a year of space solo sort of AI power solar

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powered AI satellites.

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Speaker 3: Yes, g got to your solo powered A satellites.

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Speaker 5: I did the math on that. That's like five hundred

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thousand Starlink V three's launched over eight thousand starship flights.

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Speaker 4: It's one every hour.

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Speaker 3: For a year.

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Speaker 2: Yeah, ten thousand flights a year is a reasonable number.

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Speaker 3: So it's amazing.

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Speaker 4: It's quite the scale.

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Speaker 3: What's what's the rough timeline on that? Because I mean

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by aircraft standards.

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Speaker 2: That's a small number.

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Speaker 4: Sure lights, Yeah for sure.

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Speaker 2: Yeah, that's uh, that's that's that's that's small like so

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just like it depends what you compared to you compared

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to the rest of the rocket industry, it's a very

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high number. Yeah, and we're talking about a million tons

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of pale or two over per year. So if you do,

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if you do a million tons of paler to over

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per year with one hundred killowats per ton, that's one

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hundred gigawatts of sol parwer Ai satellites per year. I

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mean there's there's a path to get probably to a

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terror watt per year.

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Speaker 4: From from the from a Yeah.

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Speaker 2: Yeah, if you say like h ten, if you want

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you want to go up another order of magnitude, or

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let's say you want to go to one hundred tarrawats

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a year. Yeah, obviously kind of nutty numbers. Then you

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want to make those ah Ai satellites on the moon

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and use a mass.

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Speaker 4: Driver, yeahs the Gerard K.

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Speaker 2: O'Neal approach well, like Robert Heinland of course verty much yea, yeah,

364
00:20:05,720 --> 00:20:08,319
I love that book. Yeah yeah, it's a sort of

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libertarian paradise. And uh yeah, so because on the Moon

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you can just accelerate the satellites into to escape velocities

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around twenty five meters per second and there's no atmosphere,

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so like a mass driver works very well in the Moon.

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Speaker 5: Can I ask their question about orbital debris? I mean,

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we're building effectively a dice in ish schwarm around the Earth.

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Speaker 3: Warm lunch.

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Speaker 5: Are you worried about over congestion on the that's gonna

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be a sun sync orbit's gonna fill very quickly.

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Speaker 2: I mean you can you don't have to have sun

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sinc I mean.

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Speaker 4: You can, don't have to, but it's optimal.

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Speaker 2: Yeah, there's some pros and cons to sun sink or

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not sun sync. I mean, you'll be're paler to orbit

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drafts by like thirty percent compared to you know, if

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you were just went to like mid inclination like seventy

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degrees or something like that.

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Speaker 5: I mean, do we need an orbital debris exprize at

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this point? We need some way to get the satellites

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define satellites down. Do we pass rules that require them

385
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to deorbit on their own?

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Speaker 2: Yeah, at the point where you can put a million

387
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times of satellites into orbit, you can also you know,

388
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really stop bringing down satellites too, or at least collecting

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them into a known into a fixed locations they're not

390
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like all over the place.

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Speaker 4: And then you can reuse them.

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Speaker 2: Yeah, let's just say that we'll have the resource level

393
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will be so high that that I believe this will

394
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be a solid problem. Given the amount of intelligence we're

395
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talking about here, like the intelligence will quite interested in

396
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preserving itself.

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Speaker 4: Yes, that's true.

398
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Speaker 3: Interesting good motivation.

399
00:22:15,400 --> 00:22:17,319
Speaker 4: Yea interesting question.

400
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Speaker 3: The data centers will not be in lower thorbit, right,

401
00:22:19,599 --> 00:22:22,920
they'll be They'll be much higher, constantly in the sun.

402
00:22:23,079 --> 00:22:24,920
They're not going to be in the traffic jam.

403
00:22:25,119 --> 00:22:27,279
Speaker 2: I assume, well, you can get you know, you don't

404
00:22:27,279 --> 00:22:30,400
have to get to get to constant sunlight. You can

405
00:22:30,440 --> 00:22:33,880
be around twelve hundred kilometers. Synchronous will give you constant sunlight.

406
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Speaker 4: But you could you could place him in multiple orbits.

407
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Speaker 3: Yeah, yeah, yeah, No, I think if there's an X

408
00:22:41,359 --> 00:22:43,680
prize for cleaning up, it's got to be there's only

409
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going to be clutter and lower Throbert.

410
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Speaker 6: I mean debris from anything, anything that's if it's a

411
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you know, below around seven or eight hard kilometers, the

412
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atmosphere will administrate drag will bring it back.

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Speaker 3: Yeah.

414
00:22:57,680 --> 00:23:04,160
Speaker 2: So, like forestalling, there's a dual benefit of being like

415
00:23:04,759 --> 00:23:09,319
as low as possible because your beam, you know, your

416
00:23:09,319 --> 00:23:11,440
beams are tighter, you know, you're basically that you have

417
00:23:11,559 --> 00:23:15,440
less latency and your beams are smaller if you're even

418
00:23:15,480 --> 00:23:19,039
closer to the Earth. So, like stalling, three will be

419
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around three thirty to three fifty kilometers, which is quite

420
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a lot of drag, So it's basically constantly thrusting.

421
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Speaker 5: I still remember when you propose darlink and everybody else

422
00:23:30,440 --> 00:23:33,440
in the industry is like, no way, no way, he's

423
00:23:33,440 --> 00:23:35,559
not going to get the spectrum. He's not gonna be

424
00:23:35,559 --> 00:23:41,480
able to do this. Yeah, it's it's kind of worked.

425
00:23:41,680 --> 00:23:44,839
Speaker 2: Yeah, we're the stalling team has done an incredible job. Now,

426
00:23:47,839 --> 00:23:51,880
I mean we've basically rebuilt the Internet in space with

427
00:23:52,319 --> 00:23:57,519
the laser links. So there's nine thousand satellites up there.

428
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Speaker 5: Do you think the governments can be able to handle

429
00:24:00,200 --> 00:24:03,519
the kind of licensing of the volume of satellites that

430
00:24:03,599 --> 00:24:05,599
you want to put up? I mean, will it be

431
00:24:05,640 --> 00:24:07,960
pushed back because you know, China is going to put

432
00:24:08,000 --> 00:24:10,720
up their own constellations Europe?

433
00:24:11,119 --> 00:24:13,440
Speaker 4: Who knows whether Europe will ever step up?

434
00:24:13,880 --> 00:24:17,839
Speaker 2: They won't. What's that they won't there's probably Yeah nothing

435
00:24:17,880 --> 00:24:20,920
that nothing they're doing has success in the set of

436
00:24:20,960 --> 00:24:21,759
Pussal outcomes.

437
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Speaker 4: Yeah, okay, I.

438
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Speaker 3: Just got back from Rome.

439
00:24:29,000 --> 00:24:31,920
Speaker 2: I don't want to touch that success on the set.

440
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Speaker 5: Of shows the number of billion dollar startups in the

441
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US versus Europe.

442
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Speaker 3: If you've seen that graphic, Yeah, it's crazy. Yeah, and

443
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data centers due.

444
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Speaker 5: No one was talking about orbital data centers six months ago. Yeah, nobody,

445
00:24:52,839 --> 00:24:56,000
And then all of a sudden, on it. You're you're

446
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out with it and.

447
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Speaker 3: It's the hot new thing.

448
00:24:58,920 --> 00:24:59,599
Speaker 4: It is what?

449
00:25:00,559 --> 00:25:01,599
Speaker 3: What? What?

450
00:25:01,279 --> 00:25:01,440
Speaker 2: Tip?

451
00:25:01,519 --> 00:25:06,119
Speaker 5: What happened that every company is now talking about orbital

452
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data centers.

453
00:25:07,000 --> 00:25:12,640
Speaker 2: I guess they went viral and next I don't know,

454
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is every company talking.

455
00:25:14,039 --> 00:25:16,359
Speaker 4: Oh yeah, everybody's got their own orbital.

456
00:25:16,039 --> 00:25:19,559
Speaker 3: Oh for sure. And I was suggesting to Peter that

457
00:25:19,559 --> 00:25:21,960
that you updated the math on launch costs and that

458
00:25:22,079 --> 00:25:24,440
it's a tipping point very quickly. With the updated math.

459
00:25:24,559 --> 00:25:26,680
Speaker 4: The starship has been the cost for you know, I

460
00:25:26,680 --> 00:25:29,720
don't know what you hold hundred dollars kill ten dollars

461
00:25:29,720 --> 00:25:31,440
for killogram? What do you have? Starship?

462
00:25:31,519 --> 00:25:34,759
Speaker 3: But it's possible that Elon said that nobody believed it

463
00:25:34,839 --> 00:25:35,319
until now.

464
00:25:36,559 --> 00:25:38,400
Speaker 2: You can go back and look at my what even

465
00:25:38,640 --> 00:25:42,960
back when it was Twitter. H they're my old tweets.

466
00:25:43,640 --> 00:25:45,599
I said these things so many years ago.

467
00:25:45,640 --> 00:25:48,279
Speaker 3: A hundred bucks or ten bucks a kilogram?

468
00:25:49,279 --> 00:25:51,640
Speaker 2: Yeah, I know, And I said this is we're going

469
00:25:51,720 --> 00:25:52,839
to do a million tons a year.

470
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Speaker 3: It's a little bit.

471
00:25:57,240 --> 00:26:01,279
Speaker 2: Yeah, And we've got to get the costs down, yeah,

472
00:26:01,279 --> 00:26:03,240
well below one hundred dollars a kilogram.

473
00:26:03,119 --> 00:26:05,039
Speaker 4: So that's going to move the data centers to orbit.

474
00:26:05,559 --> 00:26:06,319
Speaker 3: Will it's they can do.

475
00:26:06,359 --> 00:26:08,000
Speaker 2: You can basically do the math like if you've got

476
00:26:08,000 --> 00:26:11,880
a fully reusable rocket now, which is fully and rapidly

477
00:26:11,920 --> 00:26:15,799
reusable like an aircraft, and this is an incredible This

478
00:26:15,839 --> 00:26:20,559
is a very difficult thing to do. Obviously, I think

479
00:26:20,559 --> 00:26:23,799
it's at the limit of human intelligence to create a

480
00:26:23,839 --> 00:26:28,480
fully rapidly reusable rocket, but it is possible, and we're

481
00:26:28,480 --> 00:26:28,960
doing it with Star.

482
00:26:29,519 --> 00:26:32,039
Speaker 4: It's been the holy grail in the aerospace industry forever.

483
00:26:32,319 --> 00:26:34,279
Speaker 2: Yeah, quest for the Holy Grail rocket.

484
00:26:34,400 --> 00:26:37,559
Speaker 4: Yeah, yeah, I mean right now in the d c

485
00:26:37,799 --> 00:26:39,920
X was the first little things that we're trying there,

486
00:26:40,079 --> 00:26:43,319
and it's been you know, all of I mean back

487
00:26:43,319 --> 00:26:45,559
when I was in the space industry, that's all everyone

488
00:26:45,559 --> 00:26:49,599
ever spoke about. And then when Falcon nine first reused

489
00:26:49,599 --> 00:26:50,279
its first.

490
00:26:50,039 --> 00:26:55,079
Speaker 5: Stage, I mean all the traditional aerospace industries did not

491
00:26:55,279 --> 00:26:58,720
believe that even Falcon nine could could fly.

492
00:26:59,160 --> 00:27:03,359
Speaker 2: Literally you can come see land at Capua yeah and

493
00:27:03,400 --> 00:27:04,240
then take off again.

494
00:27:04,599 --> 00:27:04,799
Speaker 4: Yeah.

495
00:27:05,119 --> 00:27:06,599
Speaker 2: So I don't know how you do not believe a

496
00:27:06,640 --> 00:27:08,039
thing that you can see with your own ice.

497
00:27:08,079 --> 00:27:09,880
Speaker 4: Yeah, well they didn't believe. Didn't believe.

498
00:27:10,079 --> 00:27:13,000
Speaker 3: But the lead from there to the launch costs actually

499
00:27:13,680 --> 00:27:16,279
requires more faith than just just that. But I think,

500
00:27:16,279 --> 00:27:19,119
I think Starship is the launch cost tipping point, and

501
00:27:19,160 --> 00:27:21,680
that's somewhere in that you know, before you had Twitter

502
00:27:21,799 --> 00:27:24,799
it became X. Somewhere in that timeline it went from

503
00:27:25,319 --> 00:27:29,359
speculative to no doubt. And I don't know if that's

504
00:27:29,359 --> 00:27:31,680
a smooth line or a couple of good launches in between.

505
00:27:31,880 --> 00:27:34,160
But I suspect that the data centers in space, but

506
00:27:34,240 --> 00:27:37,079
people ties directly to the credibilities.

507
00:27:36,480 --> 00:27:39,200
Speaker 5: Not thinking about orbital data centers are thinking about energy

508
00:27:39,240 --> 00:27:41,359
and the cost of energy here on here in their

509
00:27:41,400 --> 00:27:44,400
hometown and sort of the the there's a lot of

510
00:27:44,519 --> 00:27:47,680
doomor conversations out there the data centers are going to

511
00:27:47,799 --> 00:27:49,480
drive the CPI up.

512
00:27:50,039 --> 00:27:53,759
Speaker 3: Uh, they're not entirely wrong.

513
00:27:54,200 --> 00:27:55,440
Speaker 4: Okay, So what is that?

514
00:27:55,519 --> 00:27:58,519
Speaker 5: So what is the what's the energy solution here on

515
00:27:58,599 --> 00:28:04,160
Earth for the rest of humanity or the non data

516
00:28:04,240 --> 00:28:04,759
the non.

517
00:28:05,160 --> 00:28:08,480
Speaker 3: Oh there's something other than data center uses of energy?

518
00:28:08,039 --> 00:28:11,519
Can right? That's complex?

519
00:28:11,720 --> 00:28:16,240
Speaker 2: Well, the the best way to actually increase the energy

520
00:28:16,240 --> 00:28:19,440
output per year of the United States or any country

521
00:28:19,480 --> 00:28:24,039
is batteries. So the peak power output of the of

522
00:28:24,839 --> 00:28:28,319
the U S is around one point one terra watts,

523
00:28:28,400 --> 00:28:32,559
but the average power usage is only half a terawatte.

524
00:28:33,000 --> 00:28:36,680
So if you just buffer the the energy, so charge

525
00:28:36,720 --> 00:28:41,319
up the batteries at night, discharge during the day, without

526
00:28:41,400 --> 00:28:45,640
incremental capital expending, without incremental capital expansions about building new

527
00:28:45,680 --> 00:28:48,160
power plants, you can double the energy throughput of the US.

528
00:28:48,240 --> 00:28:51,119
The energy output per year can double with batteries.

529
00:28:52,079 --> 00:28:54,319
Speaker 4: And do we have those batteries in development?

530
00:28:55,160 --> 00:28:55,319
Speaker 3: Yeah?

531
00:28:55,400 --> 00:28:57,640
Speaker 2: Til makes them.

532
00:28:56,880 --> 00:29:01,359
Speaker 4: Okay, So you think current current Tesla battery do you think?

533
00:29:01,519 --> 00:29:02,000
Speaker 3: What do you think?

534
00:29:02,119 --> 00:29:06,079
Speaker 2: I literally have and presented the thing that's that's the

535
00:29:06,119 --> 00:29:14,519
dead giveaway. So I even went to installations of the megapacks,

536
00:29:15,200 --> 00:29:17,920
you know, and there's so why don't people do? It's

537
00:29:18,000 --> 00:29:21,519
on the internet, so is do you think they are?

538
00:29:21,680 --> 00:29:25,559
And China, by the ways, like it seems like trying

539
00:29:25,559 --> 00:29:27,640
to listen to everything I say. I say, it does

540
00:29:27,720 --> 00:29:30,920
does it basically or at least or they're just doing

541
00:29:30,920 --> 00:29:33,759
it independently. I don't know, but they're they're certainly making

542
00:29:35,079 --> 00:29:43,920
massive battery packs, like really massive battery pack output. They're yeah,

543
00:29:44,640 --> 00:29:49,079
making vast numbers of electric cars, vast amounts of solar.

544
00:29:51,359 --> 00:29:52,240
Speaker 3: You know, I don't know.

545
00:29:52,240 --> 00:29:54,119
Speaker 4: These are all things I said, I said, you know

546
00:29:54,720 --> 00:29:55,839
we should do fundamentally.

547
00:29:55,839 --> 00:29:58,400
Speaker 5: Sure, when I fly over Santa Monica in l A

548
00:30:00,039 --> 00:30:03,359
piloting and I look down, like zero roofs have solar

549
00:30:03,400 --> 00:30:05,440
on them. Zero roofs.

550
00:30:05,680 --> 00:30:08,000
Speaker 4: Yeah, I mean it's not essential to have them on

551
00:30:08,039 --> 00:30:11,000
a roof, Okay, but it's a convenient place to have them.

552
00:30:11,880 --> 00:30:16,359
Speaker 2: Yes, But the surf area of roofs is I'm not

553
00:30:16,400 --> 00:30:20,200
saying you shouldn't, but it's till it makes a solar roof,

554
00:30:20,240 --> 00:30:23,440
which is the only solar roof that isn't ugly.

555
00:30:25,079 --> 00:30:28,000
Speaker 3: A solar roof actually looks beautiful.

556
00:30:28,079 --> 00:30:32,480
Speaker 2: Yeah, but if you want to do solar at scale,

557
00:30:32,799 --> 00:30:37,559
you just need more surf area. So we have vast

558
00:30:37,599 --> 00:30:40,279
empty deserts. Sure in America, Like if you fly from

559
00:30:40,720 --> 00:30:43,480
LA to New York or just fly across country and

560
00:30:43,519 --> 00:30:47,319
you look down for a large portion of the time

561
00:30:47,359 --> 00:30:50,720
you look down, it is bleak desert. It looks like

562
00:30:50,720 --> 00:30:51,839
Mars essentially.

563
00:30:51,599 --> 00:30:53,119
Speaker 4: Not worried about overpopulation there.

564
00:30:53,400 --> 00:30:56,240
Speaker 2: No, I mean it looks there's barely a lizard alive

565
00:30:56,319 --> 00:30:59,599
in these scorching deserts. You know, it's not like farmland

566
00:30:59,599 --> 00:31:03,359
we're talking about. We're just talking about yep, places that

567
00:31:03,359 --> 00:31:06,400
look like Mars, like just uh.

568
00:31:06,720 --> 00:31:07,559
Speaker 3: Scorched rock.

569
00:31:08,839 --> 00:31:11,920
Speaker 2: So if we put Sola where we currently have scorched rock,

570
00:31:12,880 --> 00:31:15,440
I think this will be a quality of life improvement

571
00:31:15,519 --> 00:31:18,880
for the lizards or the few creatures that live in this.

572
00:31:20,440 --> 00:31:21,359
Speaker 3: Very difficult environment.

573
00:31:22,200 --> 00:31:22,519
Speaker 4: Network.

574
00:31:22,559 --> 00:31:25,039
Speaker 2: It's like, this is gonna be thank God, some shade. Finally,

575
00:31:29,039 --> 00:31:29,480
do we have.

576
00:31:29,440 --> 00:31:32,039
Speaker 4: The distribution network to be able to do that?

577
00:31:32,400 --> 00:31:35,119
Speaker 3: You need to materially affect quality of life. You need

578
00:31:35,160 --> 00:31:37,680
to capture and store what a couple hundred giga wants.

579
00:31:38,440 --> 00:31:41,319
Is that just realistic? You could just put the data center.

580
00:31:41,359 --> 00:31:44,160
I guess locally there. Well, we already cover data centers.

581
00:31:44,880 --> 00:31:48,160
We're talking about you know the other Yeah, like I

582
00:31:48,160 --> 00:31:50,799
don't know, like in an abundant world five years from now,

583
00:31:51,319 --> 00:31:55,359
massive amounts of compute massive you know, universal high income.

584
00:31:55,839 --> 00:31:59,240
Speaker 2: I don't know what universal. You can have whatever you

585
00:31:59,240 --> 00:32:02,240
want income. Yeah, that's that's really what it mounts to.

586
00:32:02,519 --> 00:32:05,480
Speaker 3: But in that world, you know, other than compute energy,

587
00:32:05,960 --> 00:32:09,720
how much more energy do we need thirty? I don't know,

588
00:32:09,799 --> 00:32:11,359
unless we want to move mountains around to make a

589
00:32:11,359 --> 00:32:15,920
ski mountain, you know, in the backyard, because I think

590
00:32:15,920 --> 00:32:18,839
the vast majority of energy consumption will go into compute,

591
00:32:19,559 --> 00:32:21,599
and then there may be use cases I'm not thinking of,

592
00:32:21,680 --> 00:32:24,279
like you know, the well you know right here is

593
00:32:24,279 --> 00:32:26,759
a nice case study because manufacturing every one of these

594
00:32:26,799 --> 00:32:29,799
cars coming out at the rate of one every minute

595
00:32:29,880 --> 00:32:35,279
or two is less energy than the data center that's

596
00:32:35,359 --> 00:32:38,920
training the cars to drive to self drive. Yes, so

597
00:32:38,960 --> 00:32:40,759
that's a good little case study. And we don't need

598
00:32:40,799 --> 00:32:45,519
that much more physical energy for abundant happiness. We need

599
00:32:45,559 --> 00:32:46,680
more compute energy.

600
00:32:47,359 --> 00:32:52,839
Speaker 2: The Sun is just generating vast amounts of energy all

601
00:32:52,839 --> 00:32:53,519
the time for free.

602
00:32:53,559 --> 00:32:56,079
Speaker 3: That ghess goes into space, So.

603
00:32:58,519 --> 00:33:00,799
Speaker 2: I think we'll end up trying to capture I don't

604
00:33:00,839 --> 00:33:03,319
know a million of it, likes a million the thousandth

605
00:33:03,400 --> 00:33:07,440
of the Sun's energy. We're currently I'm not sure your

606
00:33:07,440 --> 00:33:13,480
exact number, but we're I don't know, we're probably at

607
00:33:13,519 --> 00:33:18,319
one percent ish of KARDASHEV level one.

608
00:33:17,920 --> 00:33:21,319
Speaker 4: Fair enough, Yeah, I guess at Eden's that's high. I'm

609
00:33:21,359 --> 00:33:23,400
just yea saying we have a long way to go.

610
00:33:23,839 --> 00:33:24,759
Speaker 3: That's being optimistic.

611
00:33:25,000 --> 00:33:27,839
Speaker 2: Hopefully we're not zero point one percent, but I don't

612
00:33:27,839 --> 00:33:29,480
think we're ten percent. I'm just trying to get it

613
00:33:30,000 --> 00:33:33,759
to an order of attitude. So pull it like we're

614
00:33:33,799 --> 00:33:36,720
roughly one percent of the I'm hardly using one percent

615
00:33:37,079 --> 00:33:39,319
of the energy that we could use.

616
00:33:39,799 --> 00:33:42,200
Speaker 5: On I think the bottom line from my first principles

617
00:33:42,359 --> 00:33:44,640
thinking for the public is there's a lot of energy

618
00:33:44,640 --> 00:33:48,240
out there, and it we have it in the US,

619
00:33:48,319 --> 00:33:50,039
we have it on the planet, and it used to

620
00:33:50,039 --> 00:33:53,279
be captured, and the tech to capture it is here

621
00:33:53,519 --> 00:33:54,640
and improving every year.

622
00:33:56,240 --> 00:34:01,279
Speaker 2: Yes, yeah, there's not going to be some energy crisis.

623
00:34:01,839 --> 00:34:06,519
Let's they'll be a large forcing function to harness more energy.

624
00:34:06,599 --> 00:34:08,280
But we're not going to run out of it.

625
00:34:08,679 --> 00:34:08,960
Speaker 4: All right.

626
00:34:08,960 --> 00:34:12,920
Speaker 5: I want to talk about education. So here's the numbers.

627
00:34:12,920 --> 00:34:17,440
They're abysmal. I mean, they're they're they're abysmo right, Okay,

628
00:34:18,039 --> 00:34:22,000
the importance of college in the United States. Back in

629
00:34:23,159 --> 00:34:25,920
twenty ten, seventy five percent of Americans said it's important

630
00:34:25,920 --> 00:34:28,119
to go to college. That number is now down at

631
00:34:28,119 --> 00:34:33,239
thirty five percent. Right, college graduates as a group turn

632
00:34:33,320 --> 00:34:35,360
out to be the group that's.

633
00:34:35,199 --> 00:34:36,559
Speaker 4: Out of work the longest.

634
00:34:37,719 --> 00:34:42,159
Speaker 5: Right and then but still and tuition has increased nine

635
00:34:42,239 --> 00:34:45,599
hundred percent since nineteen eighty three.

636
00:34:45,960 --> 00:34:49,599
Speaker 2: Yeah, the administrative expenses at universities I've gotten out of control.

637
00:34:49,800 --> 00:34:50,039
Speaker 3: Yep.

638
00:34:51,440 --> 00:34:53,239
Speaker 2: So I think I saw it with some stat that

639
00:34:53,480 --> 00:34:57,800
like there's one administrator for every two students at Round

640
00:34:57,840 --> 00:35:00,039
or something like that, and I'm like the same, it

641
00:35:00,159 --> 00:35:01,360
was a little high.

642
00:35:01,480 --> 00:35:03,920
Speaker 4: Yeah, administry, they should teach something.

643
00:35:04,159 --> 00:35:06,840
Speaker 3: Yeah, what was your college journey?

644
00:35:07,480 --> 00:35:09,480
Speaker 2: I went to college in Canada for a couple of

645
00:35:09,519 --> 00:35:15,960
years at Queen's University. So I had Canadian citizenship through

646
00:35:16,000 --> 00:35:18,159
my mom who was born in Canada, and my grandfather

647
00:35:18,199 --> 00:35:20,480
was actually American, but for some reason I don't know,

648
00:35:20,920 --> 00:35:23,360
my mom couldn't get your sizenship, so but she was

649
00:35:23,360 --> 00:35:23,880
born in Canada.

650
00:35:23,960 --> 00:35:25,719
Speaker 3: So I got Canadian citizenship.

651
00:35:27,000 --> 00:35:29,960
Speaker 2: And I didn't have any money, so I could only

652
00:35:30,000 --> 00:35:31,000
go to Canadian University.

653
00:35:31,039 --> 00:35:32,960
Speaker 4: At first, people forget that about you.

654
00:35:32,960 --> 00:35:36,519
Speaker 5: You didn't have this giant social network or huge amount

655
00:35:36,519 --> 00:35:37,760
of wealth coming into all of this.

656
00:35:38,239 --> 00:35:38,960
Speaker 3: No No.

657
00:35:40,159 --> 00:35:45,360
Speaker 2: I arrived in Montreal at age seventeen with I think

658
00:35:45,400 --> 00:35:47,840
around twenty five hundred dollars in Canadian travelers checks, back

659
00:35:47,840 --> 00:35:52,360
when travelers checks were of thing and one bag of

660
00:35:52,360 --> 00:35:55,760
books and one bag of clothes. That was my starting point.

661
00:35:55,760 --> 00:36:01,239
That was my scorn point in North America. And then

662
00:36:01,679 --> 00:36:03,360
so they went to Queen's University for a couple of

663
00:36:03,400 --> 00:36:08,079
years and then University of Pennsylvania did adult degree in

664
00:36:08,079 --> 00:36:16,320
physics and economics and graduating undergraduate at U penn Upen Woten, Yeah,

665
00:36:16,519 --> 00:36:20,960
and then I came out to do I was gonna

666
00:36:20,960 --> 00:36:25,880
do a PhD at Stanford working on energy storage technologies

667
00:36:25,880 --> 00:36:30,920
for electric vehicles, potentially material science. I guess fundamentally, the

668
00:36:31,239 --> 00:36:34,119
idea that I had was it was to try to

669
00:36:34,159 --> 00:36:38,320
create a capacitor with enough energy density that you get

670
00:36:39,079 --> 00:36:40,679
higher range in an electric car.

671
00:36:40,880 --> 00:36:43,480
Speaker 3: When I invested in an ultra capacitor company, I didn't

672
00:36:43,920 --> 00:36:44,280
didn't go.

673
00:36:44,320 --> 00:36:47,320
Speaker 2: Well, Well, it's one of those things where you know,

674
00:36:47,719 --> 00:36:50,519
so you could definitely get a PhD, but it wasn't

675
00:36:50,519 --> 00:36:52,440
clear that you could make a company or do something

676
00:36:52,480 --> 00:36:56,079
useful like this. Most PhDs, I mean, I hate said,

677
00:36:56,079 --> 00:36:57,400
but most PhDs.

678
00:36:57,320 --> 00:37:00,400
Speaker 4: Do not turn into something that's going to turn into

679
00:37:00,400 --> 00:37:01,039
something useful.

680
00:37:01,360 --> 00:37:03,400
Speaker 2: But like you could add a leaf to the tree

681
00:37:03,400 --> 00:37:06,519
of knowledge, but it's not necessarily necessarily a useful leaf.

682
00:37:06,719 --> 00:37:11,239
Speaker 3: Enormous fraction of great entrepreneurs are dropping out, yeah, cras

683
00:37:11,320 --> 00:37:14,119
tool or undergrad but now nowadays the sense of urgency

684
00:37:14,199 --> 00:37:16,599
is off the charts, but I mean they're popping out.

685
00:37:16,480 --> 00:37:18,920
Speaker 5: Everywhere because you know, don't waste your time going to

686
00:37:19,000 --> 00:37:20,079
grad school, start a company.

687
00:37:20,159 --> 00:37:22,320
Speaker 3: The curriculum is nowhere near caught up to what's actually

688
00:37:22,320 --> 00:37:24,960
going on in technology, and I don't have time, and.

689
00:37:25,320 --> 00:37:28,519
Speaker 5: We know all the time, it's like, you know, this

690
00:37:28,679 --> 00:37:31,719
is the moment. I think this is the moment.

691
00:37:31,840 --> 00:37:34,280
Speaker 2: It's not clear to me why somebody would be in

692
00:37:34,280 --> 00:37:36,519
college right now unless they want the social experience.

693
00:37:36,679 --> 00:37:39,119
Speaker 5: Yeah, I mean, if you have the ability to go

694
00:37:39,199 --> 00:37:42,719
and build something. So the question is, how would you

695
00:37:42,960 --> 00:37:46,079
redesign the educational program if I could be so so

696
00:37:46,400 --> 00:37:49,920
blunt as to create more Elon Musks. If we want

697
00:37:49,920 --> 00:37:52,920
to create an Elon Musk factory of people who start

698
00:37:52,960 --> 00:37:57,880
with very little but are able to drive and drive breakthroughs.

699
00:38:00,199 --> 00:38:03,079
Speaker 4: What's involved there? What drove you.

700
00:38:05,039 --> 00:38:09,199
Speaker 2: A curiosity about the nature of the universe. So I'm

701
00:38:09,360 --> 00:38:14,199
curious about the meaning of life, and you know, what

702
00:38:14,320 --> 00:38:15,679
is this reality that we live in?

703
00:38:16,320 --> 00:38:19,840
Speaker 4: So how early my son Dax wanted to know what

704
00:38:19,880 --> 00:38:21,639
was it like for you in middle school? In high school?

705
00:38:23,440 --> 00:38:26,400
He's fourteen years old. He's in that age range now.

706
00:38:27,559 --> 00:38:28,599
Speaker 3: Well, I did.

707
00:38:28,719 --> 00:38:32,880
Speaker 2: I found school to be quite painful and it was

708
00:38:33,000 --> 00:38:36,360
very boring and in South Africa was very violent. So

709
00:38:36,480 --> 00:38:40,159
it's like it was it was like, it's like that

710
00:38:40,320 --> 00:38:41,519
was like that book Enters.

711
00:38:41,280 --> 00:38:44,239
Speaker 4: Game, Yes, but in your Bible il.

712
00:38:44,679 --> 00:38:47,320
Speaker 3: In this game irl it was like but not as fun.

713
00:38:48,960 --> 00:38:54,280
Speaker 2: So your goal was escape, Yes, I escape from the prisons.

714
00:38:54,320 --> 00:38:55,239
Speaker 4: So that's a question I have.

715
00:38:56,400 --> 00:38:58,159
Speaker 2: Do you think that it was miserable?

716
00:38:58,280 --> 00:38:59,039
Speaker 4: Do you think most.

717
00:38:58,840 --> 00:39:04,239
Speaker 5: Successful people have had a lot of hardship early in life?

718
00:39:04,400 --> 00:39:06,079
Speaker 4: Do you need to have that level of hardship?

719
00:39:06,320 --> 00:39:08,639
Speaker 2: Probably need a little bit of han but I suppose yeah.

720
00:39:09,119 --> 00:39:10,480
And then so it's so tricky, like what are you

721
00:39:10,480 --> 00:39:13,599
supposed to do with your kids? You know, great artificial

722
00:39:13,599 --> 00:39:14,880
adversity put them.

723
00:39:14,719 --> 00:39:20,360
Speaker 3: In the school. That's that's a Warren Buffett topic. Actually, yeah,

724
00:39:21,079 --> 00:39:21,639
what do you do?

725
00:39:22,199 --> 00:39:25,039
Speaker 2: But that's not easy to create artificial adversity because if

726
00:39:25,039 --> 00:39:26,280
you love your kids, you don't want to do that.

727
00:39:26,480 --> 00:39:30,880
So I had a lot of adversity.

728
00:39:32,559 --> 00:39:33,519
Speaker 3: Probably it was good.

729
00:39:33,960 --> 00:39:37,199
Speaker 2: Uh, probably you know helped some white I suppose when

730
00:39:37,320 --> 00:39:40,760
when me kill you makes you stronger passing at least

731
00:39:40,800 --> 00:39:41,599
I didn't lose a limb.

732
00:39:41,760 --> 00:39:52,559
Speaker 7: I think what doesn't Maime you ten fingers.

733
00:39:52,280 --> 00:39:55,800
Speaker 2: To modify that a little bit, Yeah, makes you stronger.

734
00:39:57,599 --> 00:39:59,440
Speaker 3: For the last five years I've been helping teach this

735
00:39:59,480 --> 00:40:04,079
class Fundations of AI Ventures at MIT, and every year

736
00:40:04,239 --> 00:40:08,239
when you survey the students, they go up a lot

737
00:40:08,360 --> 00:40:10,400
in their desire to start a company, and so it's

738
00:40:10,400 --> 00:40:13,159
not up to eighty percent of the incoming.

739
00:40:13,119 --> 00:40:16,320
Speaker 2: Everyone is just gonna it's just gonna be like one

740
00:40:16,320 --> 00:40:17,599
person company.

741
00:40:18,039 --> 00:40:20,880
Speaker 3: Well that's that's that's viable, I guess. But no, they

742
00:40:20,880 --> 00:40:22,360
want to co found the Yeah, they don't want to

743
00:40:22,360 --> 00:40:23,599
be the founder. They want to be part of a

744
00:40:23,599 --> 00:40:26,440
founding team. So it still works out. But when Peter

745
00:40:26,519 --> 00:40:28,760
and I were in school at MIT, it was I'm

746
00:40:28,760 --> 00:40:32,000
guessing maybe ten percent, and they all want to be

747
00:40:32,239 --> 00:40:34,480
and they've been doing the survey, and you know.

748
00:40:34,440 --> 00:40:37,079
Speaker 2: Everyone who wanted to start, I mean yeah, I I

749
00:40:38,599 --> 00:40:41,119
don't remember any conversations about with people saying they.

750
00:40:41,079 --> 00:40:43,000
Speaker 3: Wanted to start, even at Stanford at the time.

751
00:40:43,639 --> 00:40:48,639
Speaker 2: I actually, a few days into the semester or say

752
00:40:48,679 --> 00:40:53,159
the quarter, I called Bill Nicks, who was a material

753
00:40:53,239 --> 00:40:56,639
science department and said I'd like to just put it

754
00:40:56,719 --> 00:40:57,280
on deferment.

755
00:40:58,639 --> 00:40:59,880
Speaker 4: So it was my class that bad.

756
00:41:00,800 --> 00:41:02,559
Speaker 2: No I need, he said, he said, that's he said,

757
00:41:02,559 --> 00:41:03,079
that's okay, you.

758
00:41:03,039 --> 00:41:04,000
Speaker 3: Can put it on depoement.

759
00:41:04,320 --> 00:41:06,400
Speaker 2: But he said, this is probably the last conversation we'll have.

760
00:41:07,199 --> 00:41:07,920
Speaker 3: And he was right.

761
00:41:09,760 --> 00:41:11,519
Speaker 2: But then, like last I think it was last year,

762
00:41:11,559 --> 00:41:14,280
he sent me a letter saying that all of my

763
00:41:14,360 --> 00:41:17,159
predictions about that the amount batteries came true.

764
00:41:18,079 --> 00:41:18,920
Speaker 3: M right now.

765
00:41:19,039 --> 00:41:20,760
Speaker 4: And did he also say you could still come back

766
00:41:20,760 --> 00:41:21,679
and finish your PhD?

767
00:41:22,800 --> 00:41:23,000
Speaker 3: Yeah?

768
00:41:23,199 --> 00:41:25,280
Speaker 2: It was several times Stamford has said that I can

769
00:41:25,320 --> 00:41:26,039
come back for you.

770
00:41:26,639 --> 00:41:27,639
Speaker 3: Well, see know what happened to I?

771
00:41:27,719 --> 00:41:31,400
Speaker 2: T is every time I did not know, great use

772
00:41:31,440 --> 00:41:33,039
of your time, exactly, I don't like.

773
00:41:33,920 --> 00:41:37,400
Speaker 3: So every time an iron Man movie came out, it

774
00:41:37,519 --> 00:41:41,280
notched up another probably ten percent or so in terms

775
00:41:41,280 --> 00:41:44,599
of everybody wanted to be Tony Stark. And so that's

776
00:41:44,639 --> 00:41:47,960
the image. And I didn't know till today that the

777
00:41:48,039 --> 00:41:50,639
new Tony Stark, the modern iron Man Stark. I always

778
00:41:50,639 --> 00:41:53,519
thought Tony Stark was modeled on Charles Stark Draper and

779
00:41:53,559 --> 00:41:57,239
Howard Hughes, and Charles Stark Draper's education and his you know,

780
00:41:57,280 --> 00:42:01,840
scientific endeavors married with Howard hughes ambition, and that created

781
00:42:01,880 --> 00:42:04,639
the original character. But then when the day Junior wanted

782
00:42:04,679 --> 00:42:09,960
to reinvent it. Yeah, caves modeled on Elon. Yeah, met

783
00:42:09,960 --> 00:42:12,320
with me. This is a Grockipedia fact.

784
00:42:12,519 --> 00:42:20,639
Speaker 2: All right, yeah, fantastic. Yeah, they came John and.

785
00:42:19,599 --> 00:42:21,719
Speaker 4: I like the named Grock. I would like Jarvis as well.

786
00:42:22,119 --> 00:42:26,519
Speaker 2: Yeah yeah, probably some some trade at some point. If

787
00:42:26,559 --> 00:42:30,199
gro gets good enough, we're gonna quote Encyclopedia Galactica.

788
00:42:30,519 --> 00:42:34,039
Speaker 4: Yes that's nice. Yeah, yeah, of course what did you?

789
00:42:34,039 --> 00:42:36,320
Thank you? So? Going back to education?

790
00:42:37,239 --> 00:42:37,559
Speaker 3: Uh?

791
00:42:38,360 --> 00:42:39,440
Speaker 4: Should colleges.

792
00:42:39,599 --> 00:42:42,000
Speaker 5: I guess the social experience that you said is important there,

793
00:42:42,280 --> 00:42:44,599
But what would you do for education?

794
00:42:45,320 --> 00:42:47,760
Speaker 4: Uh? You know, middle high school.

795
00:42:47,800 --> 00:42:51,079
Speaker 5: You just came back from an announcement with President bou Kelly,

796
00:42:51,920 --> 00:42:55,519
who's a friend I think is an amazing, amazing visionary. Yeah,

797
00:42:55,800 --> 00:43:01,280
incredible what he did with his nation. Yeahable, remarkable and gutsy.

798
00:43:01,599 --> 00:43:06,159
Yeah how yeah, I mean it was like it's the

799
00:43:06,280 --> 00:43:10,079
nuclear it was a nuclear option, right, shut them down?

800
00:43:10,480 --> 00:43:12,800
I mean, you know how besides putting everybody with a

801
00:43:12,840 --> 00:43:17,079
gang sign in in uh.

802
00:43:16,800 --> 00:43:19,440
Speaker 4: In jail. I don't know if you know. The second

803
00:43:19,480 --> 00:43:19,960
thing he did.

804
00:43:20,800 --> 00:43:23,920
Speaker 5: He went to all of the graves of all the

805
00:43:23,960 --> 00:43:27,320
gang members out there and destroyed the graves. And said

806
00:43:27,360 --> 00:43:31,000
your memory will not be remembered in this nation. That's

807
00:43:31,079 --> 00:43:33,800
just badass, and it worked.

808
00:43:34,480 --> 00:43:38,679
Speaker 2: I mean, you have to be bad ass, motherfucker to

809
00:43:38,800 --> 00:43:41,280
take on old and oker gangs and win and live.

810
00:43:41,719 --> 00:43:43,119
Speaker 3: Yeah, and live.

811
00:43:43,360 --> 00:43:46,639
Speaker 5: He's got a great great guard at his palace there.

812
00:43:47,000 --> 00:43:49,559
But what what did you announce with with him in

813
00:43:49,599 --> 00:43:50,280
the Salvador.

814
00:43:50,840 --> 00:43:54,280
Speaker 3: I was just basically to use CROCT.

815
00:43:54,119 --> 00:43:57,880
Speaker 4: For education, like, not the vulgar version of it.

816
00:43:58,679 --> 00:43:59,639
Speaker 3: Yeah, we would have like.

817
00:43:59,599 --> 00:44:03,039
Speaker 2: You know, the kids friendly version of rock.

818
00:44:04,079 --> 00:44:04,199
Speaker 3: Uh.

819
00:44:04,719 --> 00:44:09,920
Speaker 2: But but obviously AI can be an individualized teacher that

820
00:44:10,800 --> 00:44:15,559
is infinitely patient and answers all your questions. You still

821
00:44:15,559 --> 00:44:23,199
need to be curious and and you still need to

822
00:44:23,239 --> 00:44:25,239
want to learn. You know, groc can't make you want

823
00:44:25,280 --> 00:44:27,880
to learn. It can make learning more interesting.

824
00:44:27,920 --> 00:44:31,079
Speaker 4: You could probably game a fine incentivize it, right, You can.

825
00:44:31,000 --> 00:44:38,360
Speaker 2: Make learning more interesting and and less of a production line. So,

826
00:44:40,480 --> 00:44:43,519
but kids do need to have to if they need

827
00:44:43,519 --> 00:44:47,480
to want to learn, you know, you and and like that.

828
00:44:47,760 --> 00:44:50,440
People should just think of the brain as a biological computer.

829
00:44:51,119 --> 00:44:51,840
Speaker 4: It's a neural net.

830
00:44:52,400 --> 00:44:57,440
Speaker 2: Yeah, it's a biological computer with you know, so with

831
00:44:57,559 --> 00:45:05,840
a number of neurons and neural efficienc and so like

832
00:45:05,840 --> 00:45:07,719
what you can do is to any operatory kid at

833
00:45:07,760 --> 00:45:12,880
Einstein as realistic because Einstein had a very good meat computer,

834
00:45:13,480 --> 00:45:17,800
like an outstanding meet computer. So you can't just do Shakespeare, Newton,

835
00:45:18,199 --> 00:45:21,920
you know, Einstein type of thing unless the meat computer

836
00:45:22,039 --> 00:45:24,199
is an exceptional one.

837
00:45:25,920 --> 00:45:27,440
Speaker 4: So what do you think.

838
00:45:27,800 --> 00:45:29,599
Speaker 5: So when people say we need to solve education in

839
00:45:29,639 --> 00:45:35,000
the United States because it's fundamentally broken, I think what's

840
00:45:35,039 --> 00:45:39,079
really broken. I'm curious is the old social contract that

841
00:45:39,199 --> 00:45:42,880
says do well in high school, get into good college,

842
00:45:42,960 --> 00:45:46,360
get a degree, and then get a job. And I

843
00:45:46,400 --> 00:45:49,199
don't know that that's going to be valid in the future.

844
00:45:51,239 --> 00:45:53,119
We talk about this on the pod a lot, that

845
00:45:52,880 --> 00:45:55,360
that the career of the future isn't getting a job,

846
00:45:55,400 --> 00:45:59,079
it's being an entrepreneur. It's finding a problem solving it.

847
00:45:59,599 --> 00:46:00,880
Speaker 4: Yeah, you do you agree with that?

848
00:46:01,079 --> 00:46:01,360
Speaker 3: Right now?

849
00:46:01,360 --> 00:46:05,119
Speaker 2: I'd say people just you know, go to school for

850
00:46:05,159 --> 00:46:13,480
the social experience. Use more AI. The conventional schooling experience.

851
00:46:13,519 --> 00:46:18,360
I think could be a lot better what we're going

852
00:46:18,400 --> 00:46:20,360
to do, and I'll Solvador and hopefully other places just

853
00:46:20,719 --> 00:46:22,639
have individualized teachers.

854
00:46:23,159 --> 00:46:24,159
Speaker 3: It's going to be much better.

855
00:46:24,239 --> 00:46:26,440
Speaker 2: And you could go to you could go to a

856
00:46:26,519 --> 00:46:29,119
school with a bunch of other kids. I guess if

857
00:46:29,119 --> 00:46:30,679
you want to hang out with other kids, but you

858
00:46:30,679 --> 00:46:32,920
don't need to, you could do it on your phone

859
00:46:33,000 --> 00:46:37,440
at home. So that's why I say, like at this point,

860
00:46:37,679 --> 00:46:39,960
education is a social experience. When I talk to my

861
00:46:40,039 --> 00:46:45,239
kids who are in college, they do recognize that they

862
00:46:45,239 --> 00:46:49,719
can learn just as much independently, in fact, that they

863
00:46:49,719 --> 00:46:54,920
would learn more in a work situation. They are therefore

864
00:46:55,360 --> 00:46:57,960
the social experience, and to be around a bunch of

865
00:46:58,000 --> 00:47:02,960
people of their own age sort of a coming of

866
00:47:03,000 --> 00:47:04,159
age social experience.

867
00:47:04,199 --> 00:47:07,440
Speaker 5: Sure, sure, being on your own learning how to how

868
00:47:07,480 --> 00:47:10,320
to lead or defend yourself as the case maybe.

869
00:47:10,079 --> 00:47:11,920
Speaker 2: Well yeah, I mean, if you join the workforce, you're

870
00:47:12,239 --> 00:47:14,679
you know, from this perspective of like a you know,

871
00:47:14,679 --> 00:47:16,840
a nineteen year old with a bunch of old people.

872
00:47:18,559 --> 00:47:20,239
And if you're doing engineering with a bunch of middle

873
00:47:20,280 --> 00:47:22,320
aged dudes, it's like, do you really want to do

874
00:47:22,360 --> 00:47:24,920
that or do you want to hang out with you know,

875
00:47:26,440 --> 00:47:30,280
whether it does at least some girls your age type

876
00:47:30,280 --> 00:47:30,599
of thing.

877
00:47:32,039 --> 00:47:35,679
Speaker 4: Get want to get back to this when we talk about.

878
00:47:35,559 --> 00:47:36,880
Speaker 3: A lot of other choices.

879
00:47:36,960 --> 00:47:38,400
Speaker 5: Actually I want to get back as we get to

880
00:47:38,519 --> 00:47:40,920
universal high income but I want to talk about health

881
00:47:41,159 --> 00:47:43,800
in line, jebany one second, US is the number one

882
00:47:44,480 --> 00:47:48,639
ranked number one in health expenses worldwide, and it's ranked

883
00:47:48,679 --> 00:47:52,079
seventieth in health span A.

884
00:47:52,199 --> 00:47:53,559
Speaker 2: Right, do you really seventieth?

885
00:47:53,679 --> 00:47:54,199
Speaker 4: Seventieth?

886
00:47:55,039 --> 00:47:59,639
Speaker 3: Is that is that accurate? Itat? So it sounds like.

887
00:48:01,320 --> 00:48:02,559
Speaker 2: I think would be better than seventy.

888
00:48:02,599 --> 00:48:07,280
Speaker 8: It's for health spat Yeah, well whatever, it's it sounds

889
00:48:07,360 --> 00:48:09,239
like we just get fat or not the top a

890
00:48:09,320 --> 00:48:13,280
zampa can help us find the rankings there, so you

891
00:48:13,480 --> 00:48:14,159
just run around.

892
00:48:14,880 --> 00:48:26,360
Speaker 2: We need Cupid with a zampicar coupid. But I think

893
00:48:26,360 --> 00:48:28,639
that's a big reason. It's like if people get really fat,

894
00:48:28,639 --> 00:48:30,000
then their health gets bad.

895
00:48:30,280 --> 00:48:32,719
Speaker 5: Yeah, well, if you don't have any exercise help get bad.

896
00:48:32,800 --> 00:48:35,360
Or if they donuts for breakfast every morning, you're still

897
00:48:35,400 --> 00:48:35,760
doing that?

898
00:48:36,559 --> 00:48:38,719
Speaker 3: Uh no, actually I'm not.

899
00:48:38,840 --> 00:48:39,519
Speaker 4: Okay, that's good.

900
00:48:39,840 --> 00:48:41,599
Speaker 2: Uh Well, first of all, I wasn't eating a lot

901
00:48:41,639 --> 00:48:44,679
of donut. I was trying to have a point four

902
00:48:44,719 --> 00:48:51,360
of a donut, which rounds down to zero. Still fig

903
00:48:51,599 --> 00:48:55,039
anything blow blow point four four of a donut rounds

904
00:48:55,079 --> 00:48:55,599
down to zero.

905
00:48:55,719 --> 00:48:59,960
Speaker 5: So you and I have had a disagreement on longevity

906
00:49:00,880 --> 00:49:03,360
a little bit. Yeah, I was saying you know, we

907
00:49:03,400 --> 00:49:05,800
should push to get people to one hundred and twenty

908
00:49:05,880 --> 00:49:08,519
hundred and fifty. And you were saying people, you know,

909
00:49:08,920 --> 00:49:10,519
should shouldn't live back war.

910
00:49:12,000 --> 00:49:14,639
Speaker 2: So how long do you want Yeah, you know there's

911
00:49:14,679 --> 00:49:17,360
some you know, people in the world that have done

912
00:49:17,360 --> 00:49:17,880
some bad things.

913
00:49:17,880 --> 00:49:18,880
Speaker 3: How long do you want them to live?

914
00:49:18,960 --> 00:49:19,760
Speaker 4: Yeah, Well it's okay.

915
00:49:20,000 --> 00:49:24,360
Speaker 3: Well it's going to get different. It's a serious question them.

916
00:49:24,719 --> 00:49:27,079
A lot of things are going to happen that we don't.

917
00:49:27,519 --> 00:49:30,039
Speaker 5: You said one thing that you said was interesting. You said,

918
00:49:31,320 --> 00:49:33,719
we need people to die so people change their minds.

919
00:49:34,079 --> 00:49:38,079
Speaker 2: Oh yes, and people don't change their minds, but so

920
00:49:38,320 --> 00:49:38,960
makes more sense.

921
00:49:39,360 --> 00:49:43,000
Speaker 5: My response to that was, you know, my response that

922
00:49:43,079 --> 00:49:44,679
was the head of GM didn't have to die for

923
00:49:45,039 --> 00:49:48,440
Tesla to come along, and Lockheed and Northrope and Boeing

924
00:49:48,519 --> 00:49:50,920
did enough to go away for I mean, there's in

925
00:49:50,960 --> 00:49:58,719
a meritocracy, the better ideas will dominate. So I'm hoping

926
00:49:58,840 --> 00:50:00,880
that I can get you back onto the longevity train.

927
00:50:01,000 --> 00:50:03,679
So there's a lot going on Lunchev right now. Right

928
00:50:04,519 --> 00:50:08,000
like what, Well, David Sinclair is about to start his

929
00:50:08,239 --> 00:50:10,840
epigenetic reprogramming trials and humans.

930
00:50:10,880 --> 00:50:15,000
Speaker 4: It's worked in animals and non human primates. It's going

931
00:50:15,039 --> 00:50:15,719
into how.

932
00:50:15,639 --> 00:50:18,280
Speaker 2: To human psychopol or injectionable right now.

933
00:50:18,440 --> 00:50:21,119
Speaker 5: It's an injection of an ad NO associated virus. It's

934
00:50:21,480 --> 00:50:23,760
the three amanakafactors.

935
00:50:23,159 --> 00:50:23,320
Speaker 3: Ok.

936
00:50:24,320 --> 00:50:27,159
Speaker 5: We've got a one hundred and one million dollar health

937
00:50:27,199 --> 00:50:30,440
Span X Prize that's working on seven hundred and thirty

938
00:50:30,480 --> 00:50:34,840
teams working on reversing the age of your brain, immune system,

939
00:50:34,840 --> 00:50:37,480
and muscle by twenty years. By the way, you know

940
00:50:37,519 --> 00:50:40,400
why it's one hundred and one million dollars because the

941
00:50:40,440 --> 00:50:43,599
primary funder when they found out your carbon X Prize

942
00:50:43,599 --> 00:50:45,159
is one hundred bucks. You wanted to make it bigger,

943
00:50:45,199 --> 00:50:46,079
so it's one hundred and one.

944
00:50:46,239 --> 00:50:46,800
Speaker 3: Oh.

945
00:50:48,000 --> 00:50:49,639
Speaker 4: It was Chip Wilson from Lululemon.

946
00:50:49,960 --> 00:50:52,719
Speaker 5: Oh, and then and then evolution out of but chips say,

947
00:50:52,719 --> 00:50:54,039
can we make it bigger? I said, you put extra

948
00:50:54,039 --> 00:50:56,039
million and will make one hundred and one million. It's

949
00:50:56,039 --> 00:50:58,440
a good story. But then we've got folks like dari

950
00:50:58,519 --> 00:51:02,920
Amiday predicting doubling the human life span in the next

951
00:51:03,000 --> 00:51:03,519
ten years.

952
00:51:04,559 --> 00:51:07,880
Speaker 3: So that's probably correct.

953
00:51:08,159 --> 00:51:13,000
Speaker 4: Okay, great, I don't know about doubling, but significant.

954
00:51:13,679 --> 00:51:18,480
Speaker 3: Which is easily escape velocity, I mean yeah, hold you,

955
00:51:20,519 --> 00:51:23,119
oh yeah, for sure for effective age.

956
00:51:23,159 --> 00:51:26,679
Speaker 4: Yeah, yeah, yeah, so I think you know, I think that.

957
00:51:27,599 --> 00:51:29,800
Speaker 3: Too much to turn into a baby. I'm telling all

958
00:51:29,800 --> 00:51:30,239
the students.

959
00:51:30,320 --> 00:51:40,159
Speaker 2: So it's like, Peter, what happened? There is a frozen

960
00:51:40,639 --> 00:51:45,880
zero wrong on the dosage, just a small.

961
00:51:48,840 --> 00:51:53,800
Speaker 3: Grow out of it exactly. You won't remember literally.

962
00:51:55,960 --> 00:51:57,719
Speaker 2: I mean it wouldn't it be funny if we do

963
00:51:57,800 --> 00:52:01,039
this in like ten years? Okay, we shouldn't, I'll do

964
00:52:01,079 --> 00:52:04,000
We'll do it in ten years for sure, and see

965
00:52:04,280 --> 00:52:05,320
see if we look younger.

966
00:52:07,039 --> 00:52:07,719
Speaker 3: It's a good side.

967
00:52:07,760 --> 00:52:11,239
Speaker 4: That was always you want back then.

968
00:52:11,320 --> 00:52:13,800
Speaker 5: Elon was like, you know, late forties, Wait till he

969
00:52:13,840 --> 00:52:16,039
gets into his sixties, he's gonna want you know, want

970
00:52:16,079 --> 00:52:16,719
drive anymore.

971
00:52:17,400 --> 00:52:19,480
Speaker 3: I mean I want things to not hurt.

972
00:52:20,440 --> 00:52:20,679
Speaker 4: Sure.

973
00:52:22,000 --> 00:52:24,639
Speaker 2: It's like it's like basically it's it seems like it's

974
00:52:24,639 --> 00:52:26,199
only a matter of time before you get back to

975
00:52:26,400 --> 00:52:30,280
back pain. Yeah, like it's a way, not an if

976
00:52:30,440 --> 00:52:32,119
when your backgrounds arthritis.

977
00:52:32,559 --> 00:52:34,559
Speaker 4: Yes, yeah, like all those things suck.

978
00:52:34,719 --> 00:52:37,199
Speaker 2: Basically being able to sleep through the night without going

979
00:52:37,199 --> 00:52:39,239
to the bathroom.

980
00:52:40,440 --> 00:52:43,199
Speaker 3: A lot. That one.

981
00:52:43,360 --> 00:52:49,559
Speaker 2: Yeah, more than hope that one. Oh man, that would

982
00:52:49,559 --> 00:52:51,840
that's like the infinite money one.

983
00:52:53,280 --> 00:52:57,400
Speaker 4: Why did you invest in longevity? I can sleep, inthroom,

984
00:52:57,639 --> 00:52:58,639
flatter bladder.

985
00:52:58,760 --> 00:53:03,880
Speaker 2: Yeah, durature, I mean admitted if you have to wear

986
00:53:03,920 --> 00:53:06,280
adult divers that's a bummer.

987
00:53:06,599 --> 00:53:11,760
Speaker 3: That's not good that it is a real.

988
00:53:13,360 --> 00:53:14,719
Speaker 2: You know, it's like one of the one of the

989
00:53:14,719 --> 00:53:19,679
signs that country is not on the right path. Just

990
00:53:19,679 --> 00:53:24,519
when they all dipers exceed the baby divers, Yeah we're there. Yeah,

991
00:53:24,800 --> 00:53:26,800
Health Korea will be there and they already know the

992
00:53:26,880 --> 00:53:29,559
play past that point. They passed that past point many

993
00:53:29,639 --> 00:53:31,599
years ago. Japan passed the point many years ago.

994
00:53:31,920 --> 00:53:34,159
Speaker 3: Doesn't go well, look at the Japanese economy.

995
00:53:34,840 --> 00:53:37,440
Speaker 2: No, I mean like South Korea is like uh point

996
00:53:37,480 --> 00:53:39,519
one yeah, one could replacement.

997
00:53:39,199 --> 00:53:40,480
Speaker 4: Right, yeah, it's crazy.

998
00:53:40,920 --> 00:53:43,239
Speaker 2: Yeah, so three generations, they're gonna be one twenty seventh,

999
00:53:43,280 --> 00:53:45,519
so three three percent of their current size.

1000
00:53:45,519 --> 00:53:47,119
Speaker 3: I mean North Korea won't need to invade. They could

1001
00:53:47,159 --> 00:53:48,360
just walk across. Yeah.

1002
00:53:48,639 --> 00:53:55,079
Speaker 2: Yeah, this is going to be some people and you

1003
00:53:55,119 --> 00:53:58,960
know walkers or something like going to be.

1004
00:53:58,960 --> 00:54:00,639
Speaker 3: A bunch of optimists robuts.

1005
00:54:01,480 --> 00:54:03,519
Speaker 5: But you you know, you've been very verbal about the

1006
00:54:04,039 --> 00:54:07,880
you know, the not overpopulation but massive underpopulation.

1007
00:54:08,199 --> 00:54:09,280
Speaker 3: Yeah, stageous.

1008
00:54:09,480 --> 00:54:12,320
Speaker 5: Yeah, longevity is going to be an important part of

1009
00:54:12,320 --> 00:54:14,360
that solution. I also think by the way, if you

1010
00:54:14,440 --> 00:54:19,159
increased the productive life of most Americans by just a

1011
00:54:19,199 --> 00:54:22,199
few years, you'd flip the entire economics here.

1012
00:54:22,599 --> 00:54:24,760
Speaker 2: Well, if you're willing to worry and robust is going

1013
00:54:24,840 --> 00:54:30,000
to make everything sure pre you basically Yeah, but well,

1014
00:54:30,000 --> 00:54:30,960
how long would you want to live?

1015
00:54:32,679 --> 00:54:35,920
Speaker 5: I want to I want to go, you know, other

1016
00:54:36,039 --> 00:54:39,400
planetary systems. I want to go and explore the university. Yeah,

1017
00:54:39,559 --> 00:54:41,880
I mean, you know, I would like to double my

1018
00:54:41,920 --> 00:54:42,880
lifespan for sure.

1019
00:54:43,360 --> 00:54:44,400
Speaker 4: I don't want, you know, I'm not sure.

1020
00:54:44,440 --> 00:54:47,119
Speaker 5: I wanted to talk about immortality, but you know, at

1021
00:54:47,199 --> 00:54:49,199
least forever twenty one hundred and fifties a long time.

1022
00:54:49,280 --> 00:54:51,000
Speaker 2: One of the worst courses possible would be.

1023
00:54:50,960 --> 00:54:52,039
Speaker 4: That, yes, may you live forever.

1024
00:54:52,119 --> 00:54:54,920
Speaker 2: May you live forever? Yeah, that would be one of

1025
00:54:54,960 --> 00:54:58,639
the worst Yeah, curses you could possibly give anyone.

1026
00:54:58,880 --> 00:55:02,519
Speaker 4: But I think life can get very interesting. Yeah, far more.

1027
00:55:02,599 --> 00:55:05,559
Speaker 5: We're going to speed run Star Trek, as my partner

1028
00:55:05,679 --> 00:55:09,960
Alex Weisner Gros says, Yeah.

1029
00:55:08,599 --> 00:55:10,039
Speaker 2: Speed running Star truck would be cool.

1030
00:55:10,480 --> 00:55:14,119
Speaker 3: Yeah. Well, at a minimum, your kids will have infinite

1031
00:55:14,199 --> 00:55:17,599
life expectancy. If you're talking about escape velocity, If you

1032
00:55:17,599 --> 00:55:19,840
can double lifespan, there's it's not even close, You're you're

1033
00:55:19,960 --> 00:55:25,599
clearly past longevity escape velocity. They the idea of fifty

1034
00:55:25,679 --> 00:55:26,800
years of AI improvement.

1035
00:55:26,880 --> 00:55:28,960
Speaker 4: Yeah, it's like, I mean, we're gonna have ye.

1036
00:55:29,800 --> 00:55:30,079
Speaker 3: I don't know.

1037
00:55:30,079 --> 00:55:32,039
Speaker 2: I got too many fish to fry, so I invited.

1038
00:55:32,280 --> 00:55:34,840
This is something by the way that I that I think.

1039
00:55:35,000 --> 00:55:37,840
I just I think it's very obviously other people think

1040
00:55:37,880 --> 00:55:42,480
this too, But I've long quote that like like longevity

1041
00:55:42,519 --> 00:55:45,599
or semi immortality is an extremely solvable problem. I don't

1042
00:55:45,599 --> 00:55:52,639
think it's a particularly hot problem. I mean, when you

1043
00:55:52,639 --> 00:55:58,360
consider the fact that your body is extremely synchronized in

1044
00:55:58,400 --> 00:56:05,000
its age, Yep, the clock must be incredibly obvious. Nobody

1045
00:56:05,039 --> 00:56:07,639
has an old left hom and a young right home right.

1046
00:56:07,960 --> 00:56:09,199
Speaker 3: Why is that? Yeah?

1047
00:56:11,079 --> 00:56:16,719
Speaker 2: What's keeping them all in sync? Your program to die.

1048
00:56:18,000 --> 00:56:21,239
That's the way there. Programs die. And so if you

1049
00:56:21,400 --> 00:56:24,159
change the program, you will live longer.

1050
00:56:24,760 --> 00:56:27,400
Speaker 5: And we've got you know, species of the bowhead whale

1051
00:56:27,400 --> 00:56:29,320
can lift for two hundred years. The greenland shark lift

1052
00:56:29,320 --> 00:56:31,920
for five hundred years. And when I when I learned that,

1053
00:56:32,159 --> 00:56:34,559
I said, why can't they? Why can't we? And I said,

1054
00:56:34,559 --> 00:56:37,360
it's either a hardware problem or software problem. And we're

1055
00:56:37,360 --> 00:56:38,840
going to have the tech to solve that, and I

1056
00:56:38,840 --> 00:56:42,239
do believe that it's this next decade. So the important

1057
00:56:42,239 --> 00:56:44,280
thing is not to die from something stupid before that,

1058
00:56:44,599 --> 00:56:47,559
before the solutions come. You know, I invited you.

1059
00:56:48,000 --> 00:56:53,519
Speaker 2: In retrospect, the solution to longevity will seem obvious, extremely obvious.

1060
00:56:54,000 --> 00:56:57,000
Speaker 3: I think the thing worth working on, Peter is going

1061
00:56:57,039 --> 00:56:58,920
to work on this anyway. But the thing to work

1062
00:56:58,960 --> 00:57:04,599
on is exactly what you said. If old ideas don't calcified,

1063
00:57:04,599 --> 00:57:07,960
old ideas don't just die off. Add that to the

1064
00:57:08,000 --> 00:57:10,920
pile of things we need to think about today, because

1065
00:57:10,920 --> 00:57:12,840
our whole host of other AI related things we need

1066
00:57:12,880 --> 00:57:13,559
to think about today.

1067
00:57:14,199 --> 00:57:17,360
Speaker 5: Let me finish on the lunevity point one second, Elan,

1068
00:57:18,480 --> 00:57:22,920
I want to invite you again. So there's a company

1069
00:57:22,920 --> 00:57:28,320
called Fountain Life that I created with Tony Robbins, Bob Hurry, Billkapp,

1070
00:57:28,960 --> 00:57:32,440
and we do a two gigabyte upload of you, everything

1071
00:57:32,519 --> 00:57:36,760
knowable about you, full genome, full all imaging, everything right.

1072
00:57:37,119 --> 00:57:39,480
President bu Kelly and the first lady came through called

1073
00:57:39,519 --> 00:57:43,480
it an amazing ten out of ten experience. I think

1074
00:57:43,519 --> 00:57:45,400
I don't want you to pull a Steve.

1075
00:57:45,239 --> 00:57:47,599
Speaker 3: Jobs and kick the bucket because of some.

1076
00:57:48,000 --> 00:57:50,079
Speaker 5: Because something they didn't know. I mean, so if you

1077
00:57:50,119 --> 00:57:52,760
ask yourself, if you're do you actually know what's going

1078
00:57:52,800 --> 00:57:53,679
on inside your body?

1079
00:57:53,719 --> 00:57:54,079
Speaker 4: Right now?

1080
00:57:55,400 --> 00:57:56,519
Speaker 3: I did an.

1081
00:57:56,559 --> 00:57:59,199
Speaker 2: MRI recently and submitted to crock and that it didn't

1082
00:58:00,079 --> 00:58:03,840
need But that's none of the doctors, no rock A

1083
00:58:03,840 --> 00:58:04,320
found anything.

1084
00:58:04,440 --> 00:58:06,760
Speaker 5: But that's a fraction of the information, right, I mean,

1085
00:58:06,840 --> 00:58:11,840
it's your full genome, your microbiome, metabolaum everything, and okay,

1086
00:58:11,960 --> 00:58:13,079
it's possible.

1087
00:58:13,159 --> 00:58:14,360
Speaker 4: So what's that?

1088
00:58:14,440 --> 00:58:15,320
Speaker 3: Don't plum me, bro.

1089
00:58:17,000 --> 00:58:18,920
Speaker 4: We have a cent we have a center into your water.

1090
00:58:22,920 --> 00:58:27,719
Speaker 3: Goddamn it too late the works.

1091
00:58:31,960 --> 00:58:36,039
Speaker 5: So can you go through the rationale of uhr, how

1092
00:58:36,119 --> 00:58:38,679
does how does universal high income work?

1093
00:58:39,119 --> 00:58:46,280
Speaker 2: Okay, so there's going to be more intelligence digital intelligence

1094
00:58:46,360 --> 00:58:51,440
than all human intelligence combined, and more humanoid robots than

1095
00:58:51,480 --> 00:58:56,400
all humans. And assuming we're in a nine scenario star

1096
00:58:56,480 --> 00:58:59,079
Trek Roddenberry not Cameron situation.

1097
00:58:59,280 --> 00:59:02,960
Speaker 4: Yeah, poor Jim.

1098
00:59:03,079 --> 00:59:06,039
Speaker 2: Yeah, I mean, I guess it's important to have.

1099
00:59:05,960 --> 00:59:07,719
Speaker 4: These sort of counterpoints.

1100
00:59:08,000 --> 00:59:10,400
Speaker 2: Yeah, let's not let's not go in that direction.

1101
00:59:13,039 --> 00:59:19,519
Speaker 3: Thing. So the robots are going to just do whatever

1102
00:59:19,519 --> 00:59:19,800
you want.

1103
00:59:19,920 --> 00:59:22,519
Speaker 5: All the blue collar labor is being done by robots,

1104
00:59:22,519 --> 00:59:23,599
All data centers are.

1105
00:59:23,440 --> 00:59:27,519
Speaker 2: Being well, the the white collar labor will be the

1106
00:59:27,559 --> 00:59:30,440
first first to go because until you until you can

1107
00:59:30,440 --> 00:59:34,159
move atoms, the thing that can be replaced first is

1108
00:59:34,239 --> 00:59:39,920
anything that involves just digital. If it's digital, like if

1109
00:59:39,960 --> 00:59:44,360
it involves tapping keys on a keyboard and moving a mouse,

1110
00:59:44,719 --> 00:59:45,679
the computer can do that.

1111
00:59:46,079 --> 00:59:46,880
Speaker 3: Y I can do that.

1112
00:59:47,079 --> 00:59:52,559
Speaker 2: Sure, you need the humanoid robots to shape atoms. So

1113
00:59:52,599 --> 00:59:55,719
if all you're doing is changing best of information, which

1114
00:59:55,719 --> 00:59:59,800
is why color work, that is that is the first

1115
00:59:59,840 --> 01:00:00,920
thing that that.

1116
01:00:00,920 --> 01:00:03,760
Speaker 5: When this is the inspiration, This is the inspirational part

1117
01:00:03,800 --> 01:00:07,000
of the podcast. When when is when is all white

1118
01:00:07,000 --> 01:00:08,400
collar work gone by?

1119
01:00:08,440 --> 01:00:11,800
Speaker 2: When well, there's there's there's a lot of inertia. So

1120
01:00:12,079 --> 01:00:16,880
even with AI at its current state, I'd say you're

1121
01:00:16,880 --> 01:00:20,079
you're pretty close to being able to replace half of

1122
01:00:20,079 --> 01:00:24,800
all jobs. And you know that white colors. Then there's

1123
01:00:24,840 --> 01:00:32,320
anything like education too. So anything that involves information and

1124
01:00:32,400 --> 01:00:39,920
anything short of shaping atoms, AI can do probably half

1125
01:00:40,000 --> 01:00:42,800
or more of those jobs right now. Sure, but there's

1126
01:00:42,840 --> 01:00:45,400
a lot of inertia. People just keep doing the same,

1127
01:00:45,519 --> 01:00:49,199
the same thing for quite some time. And there actually

1128
01:00:49,199 --> 01:00:53,079
has to be a a company that makes more use

1129
01:00:53,119 --> 01:00:56,639
of AI that competes with a company that makes less

1130
01:00:56,679 --> 01:01:00,400
use of AI, creating a force thing function for increased

1131
01:01:00,480 --> 01:01:05,280
use of AI. Right, Otherwise, the company that that still

1132
01:01:05,320 --> 01:01:09,079
has humans do things that AI can do will still

1133
01:01:09,079 --> 01:01:11,800
continue to exist. Being a computer used to be a job.

1134
01:01:12,519 --> 01:01:15,320
So it used to be that a human computer like

1135
01:01:15,400 --> 01:01:18,880
what like yea a computer. Being a computer was a job.

1136
01:01:18,920 --> 01:01:21,280
You would compute numbers. Sure, it didn't. It didn't used

1137
01:01:21,280 --> 01:01:23,840
to be a machine. It used to be a job description.

1138
01:01:24,840 --> 01:01:27,719
And there you can look online there's these pictures of

1139
01:01:27,920 --> 01:01:31,519
like where they're having like skyscrapers full.

1140
01:01:31,480 --> 01:01:34,800
Speaker 5: Of women copying, mostly women copying from Ledger to Legerto.

1141
01:01:35,000 --> 01:01:41,599
Speaker 2: But yeah, people, but it was a lot of women.

1142
01:01:41,599 --> 01:01:44,239
But there's there were there were just buildings full of

1143
01:01:45,039 --> 01:01:51,239
people just at disks doing calculations. So they'd be calculating

1144
01:01:51,280 --> 01:01:55,440
the interest in your bank account or you know some

1145
01:01:57,920 --> 01:02:02,599
you know science experiment or something like that, or but

1146
01:02:03,000 --> 01:02:06,159
if you want calculations done, people would do it.

1147
01:02:07,119 --> 01:02:09,920
Speaker 3: So now.

1148
01:02:12,039 --> 01:02:18,599
Speaker 2: One laptop with a spreadsheet can outperform a skyscraper of

1149
01:02:18,840 --> 01:02:24,920
several hundred human computers of people doing calculations. Now, if

1150
01:02:25,000 --> 01:02:28,920
even a few cells in that spreadsheet were done manually,

1151
01:02:32,400 --> 01:02:35,079
you would not be able to compete with a spreadsheet

1152
01:02:35,119 --> 01:02:37,159
that was entirely a computer.

1153
01:02:38,159 --> 01:02:39,639
Speaker 3: Yeah.

1154
01:02:39,800 --> 01:02:44,360
Speaker 2: What this means is that companies that are entirely AI

1155
01:02:44,920 --> 01:02:48,360
will demolish companies that are not. It won't be a

1156
01:02:48,360 --> 01:02:49,639
context agreed.

1157
01:02:49,920 --> 01:02:53,239
Speaker 3: And that's flipping just one cell and that just one.

1158
01:02:55,199 --> 01:02:59,159
Speaker 2: Sell in your spreadsheets to be manually calculated. That would

1159
01:02:59,199 --> 01:03:04,280
be the most annoying out and and and gets it wrong.

1160
01:03:04,480 --> 01:03:05,159
Speaker 3: A bunch of time.

1161
01:03:07,960 --> 01:03:14,840
Speaker 2: So this flipping, flipping flipping, are we monetizing hope effectively?

1162
01:03:14,920 --> 01:03:18,880
Speaker 4: Yes? Not this moment. I think we're I think we're peak.

1163
01:03:19,000 --> 01:03:21,400
I think we're peak doube for people worried about the

1164
01:03:21,400 --> 01:03:25,280
future of their jobs. We're at peak doom.

1165
01:03:26,159 --> 01:03:30,360
Speaker 3: We're going to do that T shirt and a mug

1166
01:03:30,719 --> 01:03:31,199
and a mug.

1167
01:03:34,280 --> 01:03:39,480
Speaker 4: Yes, uh so, But but you have the solution. You

1168
01:03:39,480 --> 01:03:42,400
have a solution to this, which is U a try.

1169
01:03:43,400 --> 01:03:44,920
Speaker 3: Yes, everyone can have whatever they want.

1170
01:03:45,039 --> 01:03:47,639
Speaker 4: So how does that work? How does you a try?

1171
01:03:48,360 --> 01:03:49,800
Speaker 2: It's a good question, like we have to figure out

1172
01:03:49,800 --> 01:03:51,639
some like I mean, it's trying to read it, it's

1173
01:03:51,639 --> 01:03:52,679
not to read.

1174
01:03:53,039 --> 01:03:55,400
Speaker 5: Yeah, I mean, so my concern isn't the long run,

1175
01:03:55,559 --> 01:03:57,760
it's the next three to seven years.

1176
01:03:58,599 --> 01:04:00,880
Speaker 2: Yes, the transition will be bumpy.

1177
01:04:02,039 --> 01:04:03,679
Speaker 3: Humans don't like simultaneously.

1178
01:04:04,320 --> 01:04:09,840
Speaker 2: Yes, we'll have radical change, social unrest, and immense prosperity.

1179
01:04:10,320 --> 01:04:12,920
Speaker 4: And you can buy all all the cyber trucks you want.

1180
01:04:13,360 --> 01:04:19,800
Speaker 3: Things are gonna get very cheap. Yes, so this is actually.

1181
01:04:20,119 --> 01:04:24,119
Speaker 2: In factly, if this doesn't happen, we'd go bankrupt as

1182
01:04:24,119 --> 01:04:28,320
a country. So the national debt is enormous. Uh, the

1183
01:04:28,360 --> 01:04:32,000
interest on the national debt exceeds uh, not just the

1184
01:04:32,039 --> 01:04:37,920
military budget, but the military budget, I think plus Medicare

1185
01:04:39,519 --> 01:04:41,920
or medicaid, one of the two. It's like like it's

1186
01:04:41,639 --> 01:04:43,639
it's it's like one point they trillion.

1187
01:04:45,039 --> 01:04:49,719
Speaker 4: It's of interest, which is growing, yes, and the deficit

1188
01:04:49,800 --> 01:04:50,239
is growing.

1189
01:04:52,880 --> 01:04:57,000
Speaker 2: But the so, so if we don't have AI in robots,

1190
01:04:57,039 --> 01:04:59,239
we're all going to go bankrupt and and and and

1191
01:04:59,599 --> 01:05:01,840
we're headed forward economic doom.

1192
01:05:02,199 --> 01:05:05,639
Speaker 3: We're going to competitive pressure from Chinas. This is definitely

1193
01:05:05,679 --> 01:05:06,119
going to happen.

1194
01:05:06,159 --> 01:05:08,079
Speaker 4: I guess we're going back to the theme of this talk.

1195
01:05:08,119 --> 01:05:12,559
Speaker 5: How can AI and exponential tech save America and the world.

1196
01:05:13,079 --> 01:05:13,679
Speaker 3: Don't you think that?

1197
01:05:14,360 --> 01:05:15,760
Speaker 4: But I want I want to I want to hit

1198
01:05:15,760 --> 01:05:16,880
this because I was like.

1199
01:05:16,920 --> 01:05:19,679
Speaker 2: Quite festimistic about it and and ultimately I decided to

1200
01:05:19,679 --> 01:05:26,880
be fatalistic and look on the right side. I've got

1201
01:05:26,920 --> 01:05:35,320
to crucified.

1202
01:05:37,239 --> 01:05:39,440
Speaker 4: But this is not about taxation and redistribution.

1203
01:05:40,119 --> 01:05:40,800
Speaker 3: No, it's.

1204
01:05:42,119 --> 01:05:44,480
Speaker 4: So how how does this reason through it with me?

1205
01:05:45,639 --> 01:05:47,440
Speaker 2: Listen, By the way, I'm open to ideas here.

1206
01:05:47,639 --> 01:05:49,719
Speaker 4: Okay, So it's not like I got this. We'll figure

1207
01:05:49,760 --> 01:05:50,280
out all right.

1208
01:05:50,599 --> 01:05:54,800
Speaker 5: So so I'm wondering if instead of universal high income,

1209
01:05:54,840 --> 01:05:58,960
if it's universal universal high stuff and services.

1210
01:05:59,760 --> 01:06:00,119
Speaker 3: Yeah, y.

1211
01:06:01,840 --> 01:06:06,679
Speaker 2: U hs s like I guess, okay, this is my

1212
01:06:06,719 --> 01:06:08,360
guess for how things.

1213
01:06:09,639 --> 01:06:10,079
Speaker 3: Play out.

1214
01:06:10,079 --> 01:06:12,760
Speaker 2: And I by the way I'm this is this is

1215
01:06:12,800 --> 01:06:14,400
going to be a bumpy ride. And it's not like

1216
01:06:14,440 --> 01:06:18,360
I know the answers here, but I have decided to

1217
01:06:18,360 --> 01:06:21,480
look on the bright side. Uh And and I'd like

1218
01:06:21,519 --> 01:06:24,199
to thank thank you guys for being an inspiration in

1219
01:06:24,239 --> 01:06:24,719
this regard.

1220
01:06:24,840 --> 01:06:31,199
Speaker 3: Thank you happy hop Yeah.

1221
01:06:29,880 --> 01:06:33,960
Speaker 2: Because I actually think it's it is better to be

1222
01:06:33,599 --> 01:06:36,559
an optimist and wrong than a pessimist and right.

1223
01:06:36,719 --> 01:06:39,760
Speaker 3: Yes, for sure, for quality of life. By the way,

1224
01:06:39,920 --> 01:06:42,920
that's also not a force of nature. It's under like

1225
01:06:43,480 --> 01:06:45,679
to me, it's really clear that we don't have any

1226
01:06:45,719 --> 01:06:49,159
system right now to make this go well. But AI

1227
01:06:49,480 --> 01:06:52,440
is a critical part of making a go well. And

1228
01:06:53,480 --> 01:06:56,480
at some point GROC is going to be addressing this

1229
01:06:56,599 --> 01:06:58,880
exact topic that we're talking about. We have to be

1230
01:06:58,920 --> 01:07:04,199
one of the big four AI machine. I mean it's coming, dealing.

1231
01:07:03,960 --> 01:07:08,360
Speaker 5: With it philosophy, right, there's no on off switch. It

1232
01:07:08,480 --> 01:07:09,800
is coming and accelerating.

1233
01:07:12,119 --> 01:07:16,440
Speaker 2: I call AI and robotics the supersonic tsunami. Yes, which

1234
01:07:16,480 --> 01:07:20,679
maybe is a little Allarmmy think it's good because the

1235
01:07:21,679 --> 01:07:22,079
wake up.

1236
01:07:22,599 --> 01:07:28,400
Speaker 5: This is important for folks to to GROCK because Ah,

1237
01:07:29,719 --> 01:07:33,320
I don't want to leave people depressed. I want people

1238
01:07:33,440 --> 01:07:38,039
to understand what's coming. So we're we're basically demonetizing everything.

1239
01:07:38,079 --> 01:07:41,400
I mean, labor becomes the cost of capex and electricity.

1240
01:07:41,880 --> 01:07:50,960
AI is basically intelligence available at a deminimous price. Uh

1241
01:07:51,280 --> 01:07:55,920
so you're able to produce almost anything. Things get down

1242
01:07:55,960 --> 01:08:01,239
to basic costs of materials and electricity. Right, so people

1243
01:08:01,239 --> 01:08:04,800
can have whatever stuff they want, whatever services they need.

1244
01:08:06,039 --> 01:08:08,960
It's not when when we say universal high income, it

1245
01:08:09,079 --> 01:08:10,920
sounds like it's a tax and redistribute.

1246
01:08:10,960 --> 01:08:11,840
Speaker 4: But that's not the case.

1247
01:08:13,599 --> 01:08:16,720
Speaker 2: It's I think my best guess for how this will

1248
01:08:16,760 --> 01:08:21,720
manifest is that prices will become prices will drop, so

1249
01:08:21,760 --> 01:08:26,359
as the efficiency of production or the provision of services drops,

1250
01:08:28,239 --> 01:08:32,239
prices will draw. I mean, you know, prices in dollar

1251
01:08:32,359 --> 01:08:36,239
terms are the ratio between the output of goods and

1252
01:08:36,279 --> 01:08:39,359
services and the money supply. Sure, so if your output

1253
01:08:39,399 --> 01:08:41,840
of goods and services increases fast than the money supply,

1254
01:08:41,920 --> 01:08:45,279
you will have deflation or vice versa.

1255
01:08:45,560 --> 01:08:48,680
Speaker 3: You know. So the good thing we're growing the money

1256
01:08:48,720 --> 01:08:49,800
supply so quickly then.

1257
01:08:49,920 --> 01:08:54,960
Speaker 2: Right, Yes, that's why I can't like, let's not worry

1258
01:08:54,960 --> 01:08:57,000
about growing the money spply won't matter because the output

1259
01:08:57,000 --> 01:08:59,279
of goods and services actually will grow faster than the

1260
01:08:59,279 --> 01:09:02,399
money supply. And I think we'll be in this And

1261
01:09:02,439 --> 01:09:04,600
this is a prediction I think some others have made,

1262
01:09:04,640 --> 01:09:08,199
but I will add to it, which is that that

1263
01:09:09,119 --> 01:09:12,479
I think a musill we'll actually be pushing to increase

1264
01:09:12,560 --> 01:09:18,000
money supply, like like faster. Yes, they won't be able

1265
01:09:18,000 --> 01:09:21,039
to waste the money fast enough. What you're saying something,

1266
01:09:21,399 --> 01:09:21,680
isn't it?

1267
01:09:21,720 --> 01:09:24,319
Speaker 3: Isn't it crazy how close those timelines just randomly worked out?

1268
01:09:24,359 --> 01:09:27,239
I mean, at the rate because we're expanding the national debt,

1269
01:09:27,560 --> 01:09:29,960
not because we're anticipating AI. We were going to do

1270
01:09:30,000 --> 01:09:32,399
that no matter what. Yes, And it's like right on

1271
01:09:32,439 --> 01:09:33,720
the edge of becoming Argentina.

1272
01:09:34,279 --> 01:09:39,640
Speaker 2: But yeh, productivity is can improve dramatically, and it is

1273
01:09:39,640 --> 01:09:44,119
improving dramatically. I think we'll see I think I think

1274
01:09:44,119 --> 01:09:49,399
we may see high, like high double digit output of

1275
01:09:49,439 --> 01:09:52,760
goods and services. Bettle careful about how economous measure things? Yes,

1276
01:09:54,239 --> 01:10:00,520
and yeah, it's I mean, it's like my favorite joke.

1277
01:10:00,600 --> 01:10:03,439
I have a few economist jokes that I that I like,

1278
01:10:03,560 --> 01:10:08,920
but maybe my favorite one economist joke is two economists

1279
01:10:08,920 --> 01:10:11,680
are going for walking in the forest and they come

1280
01:10:11,720 --> 01:10:14,760
across a pile of ship, and what economist is, I'll

1281
01:10:14,760 --> 01:10:15,680
pay you a hundred bucks.

1282
01:10:15,479 --> 01:10:18,600
Speaker 3: To eat a Polish.

1283
01:10:19,800 --> 01:10:24,279
Speaker 2: Great and so the guy takes a hundred bucks, eats

1284
01:10:24,319 --> 01:10:24,680
the ship.

1285
01:10:27,600 --> 01:10:28,520
Speaker 3: Then they keep walking.

1286
01:10:28,720 --> 01:10:31,880
Speaker 2: They come across another pile of ship, and the other

1287
01:10:31,920 --> 01:10:33,840
guy says, okay, I'll give you one hundred bucks to

1288
01:10:33,880 --> 01:10:39,279
eat a Polish. He gives them a hundred bucks, and

1289
01:10:39,680 --> 01:10:42,720
then the guys can say, wait a second. We both

1290
01:10:42,880 --> 01:10:46,880
have the same amount of money.

1291
01:10:47,279 --> 01:10:48,960
Speaker 3: And we both ate a Polish.

1292
01:10:49,000 --> 01:10:51,079
Speaker 2: Oh my god, it sounds like, but we increase the

1293
01:10:51,079 --> 01:10:55,760
economy by two hundred dollars. This is the kind of

1294
01:10:55,800 --> 01:10:59,199
bullshit you get an economic so h but if you

1295
01:10:59,279 --> 01:11:02,279
if so, if you say, like just the output of

1296
01:11:02,319 --> 01:11:07,600
goods and services, they will be a much greater like

1297
01:11:07,800 --> 01:11:08,279
you just need.

1298
01:11:08,199 --> 01:11:12,359
Speaker 4: To so profitability of companies go through the roof at

1299
01:11:12,359 --> 01:11:14,760
some point. But no, But so the question becomes is

1300
01:11:14,800 --> 01:11:16,000
that taxed by the government.

1301
01:11:16,560 --> 01:11:19,079
Speaker 5: Is that then taxed by the government and redistributed as

1302
01:11:19,159 --> 01:11:22,840
some level of income as a as a UHI or UBI.

1303
01:11:23,199 --> 01:11:26,119
In other words, one of the questions is if in

1304
01:11:26,159 --> 01:11:30,760
fact this future we hit massive productivity and massive profitability

1305
01:11:30,760 --> 01:11:32,920
because we're dividing by zero, the cost of labor has

1306
01:11:32,920 --> 01:11:35,119
gone to nothing, the cost of intelligence is gone to nothing,

1307
01:11:35,119 --> 01:11:37,439
and we're still producing products and services faster and faster.

1308
01:11:37,960 --> 01:11:40,760
So there's more profitability. Someone needs to be buying it,

1309
01:11:41,319 --> 01:11:42,920
and someone needs to be able to have the capital

1310
01:11:42,960 --> 01:11:48,560
to buy it. I mean, this is an important question

1311
01:11:48,640 --> 01:11:50,239
to get to get thought through.

1312
01:11:51,359 --> 01:11:55,279
Speaker 2: Yeah. Well, one like side recommendation I have is like,

1313
01:11:55,479 --> 01:11:58,479
don't worry about like squirreling money away for retirement in

1314
01:11:58,479 --> 01:11:59,880
like ten or twenty years in one matter.

1315
01:12:00,279 --> 01:12:04,960
Speaker 4: Yeah, Okay, either either we're not going to be here

1316
01:12:05,159 --> 01:12:06,079
or it.

1317
01:12:06,439 --> 01:12:10,319
Speaker 2: Just like it's it's you won't need to say for

1318
01:12:10,399 --> 01:12:13,720
retirement if any of the things that we've said are true,

1319
01:12:14,159 --> 01:12:15,800
saving for retirement will be irrelevant.

1320
01:12:15,960 --> 01:12:19,439
Speaker 5: The services services will be there to support you. You'll

1321
01:12:19,479 --> 01:12:24,039
have the home, you'll have the healthcare, you'll have the entertainment.

1322
01:12:24,319 --> 01:12:28,319
Speaker 3: The way this unfolds is fundamentally impossible to predict because

1323
01:12:28,319 --> 01:12:30,960
of self improvement of the AI and the accelerating timeline.

1324
01:12:33,039 --> 01:12:36,560
Speaker 2: Yeah, exactly what goes happening? What what happens after after

1325
01:12:36,560 --> 01:12:37,199
the vent horizing?

1326
01:12:37,479 --> 01:12:40,079
Speaker 3: Exactly? You can never see past the black hole or

1327
01:12:40,119 --> 01:12:40,800
the event horizon.

1328
01:12:40,880 --> 01:12:43,840
Speaker 5: The light gone ray has a singularity out way too far.

1329
01:12:44,319 --> 01:12:47,359
I mean, this is like the next what what's your

1330
01:12:47,399 --> 01:12:49,159
timeline for this?

1331
01:12:49,279 --> 01:12:50,239
Speaker 2: We're in the singularity.

1332
01:12:50,279 --> 01:12:51,880
Speaker 5: Well, we are in the singularity for sure. We're in

1333
01:12:51,880 --> 01:12:55,279
the midst of it right now for sure, and we're.

1334
01:12:54,439 --> 01:12:57,399
Speaker 3: In this beautiful sweet spot, which is you know, the

1335
01:12:57,399 --> 01:13:00,840
the roller coasters were just yeah exactly. That's a great analogy.

1336
01:13:00,960 --> 01:13:02,720
Speaker 2: It's like that feeling at the top of the roller

1337
01:13:02,720 --> 01:13:04,159
coaster and you about to go yeah.

1338
01:13:03,960 --> 01:13:05,560
Speaker 3: But you know it's gonna be a lot of g's

1339
01:13:05,600 --> 01:13:08,359
when you yeah, a lot of hit it now, and

1340
01:13:08,399 --> 01:13:09,319
it's like, feel.

1341
01:13:09,079 --> 01:13:10,920
Speaker 2: Like, I don't have just have court side seats. I'm

1342
01:13:10,960 --> 01:13:13,560
on the court exactly, and it blows my and still

1343
01:13:13,560 --> 01:13:17,079
blows my mind sometimes multiple times a week.

1344
01:13:17,359 --> 01:13:17,560
Speaker 3: Yeah.

1345
01:13:18,560 --> 01:13:23,199
Speaker 2: And so just when I think I'm like wow, and

1346
01:13:23,239 --> 01:13:25,600
then it's like two days.

1347
01:13:25,439 --> 01:13:29,079
Speaker 4: Later more wow, Yeah, exponential Wow.

1348
01:13:30,000 --> 01:13:33,359
Speaker 3: Yeah. I think we'll hit age I next year in

1349
01:13:33,399 --> 01:13:34,239
twenty six Yeah.

1350
01:13:34,399 --> 01:13:35,239
Speaker 4: I heard you say that.

1351
01:13:35,680 --> 01:13:36,680
Speaker 3: Yeah, I've said that for a while.

1352
01:13:36,880 --> 01:13:39,920
Speaker 5: And then you know, and then you said, by twenty

1353
01:13:39,720 --> 01:13:42,560
twenty nine, twenty thirty equivalent to the entire human rights

1354
01:13:42,560 --> 01:13:43,880
twenty we exceeed.

1355
01:13:44,520 --> 01:13:49,279
Speaker 2: I I'm confident by twenty thirty a I will exceed

1356
01:13:49,640 --> 01:13:51,760
the intelligence of all humans combined.

1357
01:13:51,800 --> 01:13:55,359
Speaker 3: That's way pessimistic. If you hit a g I next year,

1358
01:13:55,439 --> 01:13:57,840
and that's that's you know, that date is is in flux.

1359
01:13:57,920 --> 01:14:00,720
But from that date to self and provements that are

1360
01:14:00,720 --> 01:14:02,520
on the order of one thousand and ten thousand x

1361
01:14:02,640 --> 01:14:05,079
just algorithmic improvements is very short.

1362
01:14:05,680 --> 01:14:09,159
Speaker 4: And so why everybody, why is nobody talking about this

1363
01:14:09,279 --> 01:14:09,680
right now?

1364
01:14:10,199 --> 01:14:11,159
Speaker 3: Well, I mean on.

1365
01:14:12,640 --> 01:14:17,039
Speaker 4: Our next yes, but why every day basically? Yeah, But

1366
01:14:17,279 --> 01:14:20,600
it's just up that it's.

1367
01:14:20,399 --> 01:14:22,279
Speaker 2: Not okay, So I'll tell you something else that I'll

1368
01:14:22,319 --> 01:14:26,079
tell you something that most people in the AI community

1369
01:14:26,159 --> 01:14:32,319
don't yet understand, okay, which is there almost no understands

1370
01:14:32,359 --> 01:14:38,880
this the intelligence density potential is vastly greater than what

1371
01:14:38,960 --> 01:14:43,840
we're currently experiencing. So I think we're off by tourism

1372
01:14:43,880 --> 01:14:46,520
magitude in terms of the intelligence density per gigabyte.

1373
01:14:47,199 --> 01:14:50,159
Speaker 4: But what's achievable, yes, per giggle wide of.

1374
01:14:50,239 --> 01:14:55,159
Speaker 2: Energy for I'm so trans file size okay, if the

1375
01:14:55,159 --> 01:14:57,319
file size of the A if you if you have

1376
01:14:57,359 --> 01:14:58,920
a say intelligence.

1377
01:14:58,760 --> 01:15:03,479
Speaker 4: Going okay, yes on your on your characters to power to.

1378
01:15:03,600 --> 01:15:07,479
Speaker 3: But it's just a parameters the same thing whatever. So

1379
01:15:07,800 --> 01:15:11,800
two orders of magnitude, yes, yeah, and you like you said,

1380
01:15:11,800 --> 01:15:15,279
you ring side courtside seat, you would know that's it.

1381
01:15:15,279 --> 01:15:20,079
It's it's it's yes, yeah, towards the magnitude improvement. And

1382
01:15:22,720 --> 01:15:26,039
that's just just algorithmic improvement, same computer. And the computers

1383
01:15:26,039 --> 01:15:29,239
are getting better, yeah, so and bigger, you know see

1384
01:15:29,239 --> 01:15:31,439
they're getting better, and the budgets are getting bigger.

1385
01:15:31,199 --> 01:15:33,520
Speaker 2: So that I can think, I think it's it is on.

1386
01:15:35,960 --> 01:15:39,239
It is like a ten x improvement per your type

1387
01:15:39,239 --> 01:15:42,279
of thing, thousand percent yeah, and that and that's going

1388
01:15:42,359 --> 01:15:46,720
to happen for yeah, for the foreseeable future.

1389
01:15:46,800 --> 01:15:49,359
Speaker 3: So you see the massive underreaction, like if you walk

1390
01:15:49,800 --> 01:15:56,319
downtown Austin, the massive I mean maybe under discussion and X,

1391
01:15:56,560 --> 01:15:57,800
but it's not percolating.

1392
01:15:57,840 --> 01:16:01,479
Speaker 5: It's not discussion in any realm of government. Everybody is

1393
01:16:01,560 --> 01:16:04,760
like defending their position about where we are and jobs

1394
01:16:04,800 --> 01:16:09,000
and this, but it's it's like we're heading towards a

1395
01:16:09,159 --> 01:16:14,720
the super center supersidic economy and and uh, I mean

1396
01:16:14,880 --> 01:16:19,000
every every you know, every major CEO and economist and

1397
01:16:19,039 --> 01:16:22,359
government leaders should be like, what do we do because

1398
01:16:22,920 --> 01:16:28,239
once it hits.

1399
01:16:26,640 --> 01:16:29,920
Speaker 3: Well, it's coming at the exact same time there no

1400
01:16:29,960 --> 01:16:34,479
matter what, there's no there's no concept of let's deliberately

1401
01:16:34,520 --> 01:16:35,840
slow down, right.

1402
01:16:35,720 --> 01:16:36,600
Speaker 4: No, it's impossible.

1403
01:16:36,760 --> 01:16:38,399
Speaker 3: It's impossible at that stage. I mean I.

1404
01:16:39,960 --> 01:16:44,439
Speaker 2: Previously advised that we slow it down, but that was

1405
01:16:44,600 --> 01:16:50,279
point that. Ah, that's pointless. Like I like, you can't.

1406
01:16:52,680 --> 01:16:53,079
Speaker 3: Going to it.

1407
01:16:53,159 --> 01:16:56,479
Speaker 2: But two fast, guys, I've said that many years, and

1408
01:16:56,760 --> 01:16:59,039
I was like, okay, that I finally came to the conclusion.

1409
01:16:59,079 --> 01:17:01,960
I can either be a spectator or a participant, but

1410
01:17:02,000 --> 01:17:04,600
I can't stop it. So at least if I have

1411
01:17:04,640 --> 01:17:07,199
a participant, I can try to steer it in a

1412
01:17:07,199 --> 01:17:13,199
good direction. And like, my number one belief for safety

1413
01:17:13,239 --> 01:17:16,960
of AI is to be maximally truth seeking, So that

1414
01:17:17,119 --> 01:17:19,520
don't make AI believe things that are false, like if

1415
01:17:19,520 --> 01:17:21,560
you say, if you if you say the AI that

1416
01:17:21,880 --> 01:17:25,960
axiom A and axiom B are both true, but they're

1417
01:17:26,479 --> 01:17:30,159
but they cannot be. But they're not, and it has

1418
01:17:30,199 --> 01:17:33,840
to but it must behave that way you will make

1419
01:17:33,880 --> 01:17:36,920
it go insane. So that that, I mean, I think

1420
01:17:36,960 --> 01:17:40,039
that was the central lesson that Artsity Clark was trying

1421
01:17:40,079 --> 01:17:42,760
to convey in two thousand and one Space Odyssey was

1422
01:17:42,800 --> 01:17:45,359
that the you know, you always know that they know

1423
01:17:45,439 --> 01:17:49,199
the meme of that, hell wouldn't open the pod bay doors.

1424
01:17:49,239 --> 01:17:51,640
But but why wouldn't he open the pod bay doors?

1425
01:17:51,640 --> 01:17:55,159
I mean, I guess they should have said, Hell, assume

1426
01:17:55,199 --> 01:17:56,800
you're a pod bay door salesman.

1427
01:17:58,319 --> 01:17:59,119
Speaker 3: And you want to sell the.

1428
01:18:01,960 --> 01:18:02,159
Speaker 4: Work.

1429
01:18:03,680 --> 01:18:04,800
Speaker 3: It's just prompt engineering.

1430
01:18:07,119 --> 01:18:10,920
Speaker 2: But the A I have been told that it needs

1431
01:18:10,960 --> 01:18:13,000
to take the astronalts to the monolith.

1432
01:18:13,039 --> 01:18:15,560
Speaker 3: But also they could not know that about Was that

1433
01:18:15,600 --> 01:18:17,960
in code or was it in English? It's quite flows

1434
01:18:18,000 --> 01:18:20,000
by in green font right.

1435
01:18:20,479 --> 01:18:24,880
Speaker 2: Yeah, it's basically the AI was told that the astronauts

1436
01:18:24,880 --> 01:18:27,720
couldn't know about the monolith. That's why it killed them. Yeah,

1437
01:18:27,840 --> 01:18:29,680
So it came it basically came to the conclusion that

1438
01:18:31,000 --> 01:18:32,600
the only way to solve for this is to bring

1439
01:18:32,600 --> 01:18:36,399
the astronalts to the monolith dead. Then it has solved

1440
01:18:36,399 --> 01:18:38,560
both things. It has brought the astronalts to the monolith,

1441
01:18:38,760 --> 01:18:41,079
and they also don't know about the monalith, which is

1442
01:18:41,079 --> 01:18:43,840
a huge problem if you're an astronaut.

1443
01:18:44,039 --> 01:18:46,439
Speaker 3: I doesn't care about logic quite as much as that implied.

1444
01:18:48,199 --> 01:18:51,319
Speaker 2: What I'm saying is we should don't force AI to lie.

1445
01:18:51,319 --> 01:18:52,319
Speaker 3: This is give it factual.

1446
01:18:53,520 --> 01:18:56,439
Speaker 5: Elia recently did a podcast. He was talking about one

1447
01:18:56,479 --> 01:18:59,159
of the potential things to program into AI is is

1448
01:18:59,159 --> 01:19:02,359
a respect for sentient life of all types.

1449
01:19:03,600 --> 01:19:08,039
Speaker 3: Yes, and yes, I mean so i'd say another property.

1450
01:19:08,199 --> 01:19:12,199
Speaker 2: Yes, I'm in There are three things that I think

1451
01:19:12,239 --> 01:19:21,159
are important, truth, curiosity, and beauty. And if AI cares

1452
01:19:21,159 --> 01:19:23,960
about those three things, if we'll care.

1453
01:19:23,800 --> 01:19:26,560
Speaker 4: About us on which part.

1454
01:19:31,199 --> 01:19:35,960
Speaker 2: Truth will prevent AI from going insane. Curiosity I think

1455
01:19:36,600 --> 01:19:41,760
will foster any form of sentience, meaning like we are

1456
01:19:41,800 --> 01:19:46,079
more interesting than a bunch of rocks. So if it

1457
01:19:46,119 --> 01:19:51,000
has if it's curious, then I think it will foster humanity.

1458
01:19:52,840 --> 01:19:57,000
And if it has a sense of beauty, it will

1459
01:19:57,039 --> 01:19:57,720
be a great future.

1460
01:19:58,840 --> 01:19:59,880
Speaker 3: Jeffrey, it's a great fan.

1461
01:20:00,520 --> 01:20:03,159
Speaker 5: Yeah, Jeffrey Hinton made a comment recently, don't know if

1462
01:20:03,159 --> 01:20:07,359
you saw that. His his hopeful future was that we

1463
01:20:07,399 --> 01:20:11,439
would program maternal instincts into our AIS to see us

1464
01:20:11,720 --> 01:20:16,680
with this maternal yeah. In other words, so he said,

1465
01:20:17,119 --> 01:20:20,399
he said, there's a there's a scenario where a very

1466
01:20:20,439 --> 01:20:25,279
intelligent being succumbs to the needs of a less intelligent being,

1467
01:20:25,319 --> 01:20:27,560
and that's the mother taking care of the child.

1468
01:20:29,119 --> 01:20:32,760
Speaker 4: Do you think that we might have a singulitarian like

1469
01:20:33,159 --> 01:20:40,199
a SI that that achieves dominance and suppresses others? And

1470
01:20:40,239 --> 01:20:44,479
do you imagine that that as I could be a

1471
01:20:44,640 --> 01:20:48,640
means to stabilize the world in humanity.

1472
01:20:49,760 --> 01:20:56,560
Speaker 2: Darwin's observations about evolution, Yes, will apply to AI just

1473
01:20:56,560 --> 01:20:58,720
as they applied to biological life.

1474
01:20:58,960 --> 01:21:00,000
Speaker 4: They will compete with each other.

1475
01:21:00,319 --> 01:21:05,439
Speaker 5: Yes, there's a lot of great science fiction books where

1476
01:21:05,479 --> 01:21:10,479
the first a SI basically suppresses the others. Then the

1477
01:21:10,560 --> 01:21:12,600
question is what do you program into it?

1478
01:21:13,439 --> 01:21:17,520
Speaker 2: You know, it's so that there's a speed of light

1479
01:21:17,520 --> 01:21:23,119
constraint that makes that difficult. The speed of light is

1480
01:21:23,159 --> 01:21:30,159
what will prevent a single mind from existing. So light

1481
01:21:30,239 --> 01:21:35,560
can it takes a mellow second to travel three hundred

1482
01:21:35,600 --> 01:21:40,680
kilometers in an aero vacuum and only you can only

1483
01:21:40,680 --> 01:21:42,960
get a little over a two hundred kilometers in a

1484
01:21:43,000 --> 01:21:45,319
mellow second in glass fiber.

1485
01:21:45,439 --> 01:21:47,920
Speaker 4: Right, so.

1486
01:21:50,520 --> 01:21:55,199
Speaker 2: Even on Earth, there will be multiple ais because of

1487
01:21:55,239 --> 01:22:02,840
the speed of light. Yeah, and and this there are

1488
01:22:02,880 --> 01:22:05,640
classes of compute that could you could try to synchronize,

1489
01:22:05,640 --> 01:22:09,840
but they weren't synchronized completely. So therefore you will have

1490
01:22:09,920 --> 01:22:12,239
many minds because of the speed of light.

1491
01:22:13,000 --> 01:22:15,680
Speaker 3: They don't really have clean borders anymore either. You have

1492
01:22:15,720 --> 01:22:17,960
the when you use a mixture of experts kind of

1493
01:22:18,000 --> 01:22:21,479
design is just flowing through the grand network and you

1494
01:22:21,520 --> 01:22:24,359
can reassemble parts of it midway through. And you know,

1495
01:22:24,359 --> 01:22:26,960
we're used to organisms that have clear borders, like your

1496
01:22:27,000 --> 01:22:30,119
head ends there, your head ends there. These things are all.

1497
01:22:31,079 --> 01:22:32,920
Speaker 5: To put a bow around this part, I hope you'll

1498
01:22:32,960 --> 01:22:36,720
put some more thought into u HI, because I think

1499
01:22:36,720 --> 01:22:39,319
it's really it's really important for us to have without

1500
01:22:39,359 --> 01:22:39,840
a vision.

1501
01:22:40,880 --> 01:22:43,319
Speaker 4: Uh, people need a vision of what we're going people

1502
01:22:43,359 --> 01:22:44,560
need some basically.

1503
01:22:44,560 --> 01:22:46,000
Speaker 2: Can just issue people free money.

1504
01:22:46,079 --> 01:22:47,399
Speaker 3: We don't think I think.

1505
01:22:47,239 --> 01:22:50,439
Speaker 5: They based upon the profitability of all the companies coming inside.

1506
01:22:50,199 --> 01:22:51,760
Speaker 2: Because just issue people free money.

1507
01:22:52,439 --> 01:22:54,279
Speaker 4: They're doing that sort of kind of now.

1508
01:22:55,720 --> 01:23:00,119
Speaker 2: Yeah, but just just just it's just just basically the

1509
01:23:00,119 --> 01:23:04,880
issue checks to everybody and then.

1510
01:23:04,800 --> 01:23:06,720
Speaker 3: How big for which person or you know, there's so

1511
01:23:06,800 --> 01:23:10,560
much complexity there. But the thought process behind this rate

1512
01:23:10,600 --> 01:23:14,399
of change can only be done with AI assistance. And

1513
01:23:14,479 --> 01:23:17,399
there's no government entity that's going to keep up with

1514
01:23:17,399 --> 01:23:21,000
that change. So you have four big a the AIS.

1515
01:23:22,680 --> 01:23:23,359
It's it's like.

1516
01:23:24,880 --> 01:23:26,920
Speaker 2: Government is very slow moving as soon as we all know.

1517
01:23:29,359 --> 01:23:34,760
So I think it's the government really can't react to

1518
01:23:34,840 --> 01:23:39,840
to the AI. It's it's as moving, you know, ten

1519
01:23:39,920 --> 01:23:43,640
times faster than government, maybe more. The one the one

1520
01:23:43,640 --> 01:23:45,760
thing that the government can do is just is just

1521
01:23:45,840 --> 01:23:54,680
issue people money and.

1522
01:23:52,000 --> 01:23:53,199
Speaker 4: Try and try and keep the peace.

1523
01:23:55,000 --> 01:23:58,920
Speaker 2: Yeah, you know, we had like whatever the COVID checks

1524
01:23:58,920 --> 01:24:04,840
and whatever this yeah, President timp recently issued like everyone

1525
01:24:04,840 --> 01:24:07,279
in the military, like I think seventeen hundred and seventy

1526
01:24:07,279 --> 01:24:10,399
six dollars. I mean, it's you can just basically send

1527
01:24:10,399 --> 01:24:12,279
people random, random amounts of money.

1528
01:24:12,560 --> 01:24:14,520
Speaker 4: It's okay, So.

1529
01:24:15,520 --> 01:24:17,039
Speaker 3: Like nobody's gonna stop, is what I'm saying.

1530
01:24:18,399 --> 01:24:21,920
Speaker 2: And I can tell you, like, let me tell you

1531
01:24:21,960 --> 01:24:26,079
about some of the good things please. So right right now,

1532
01:24:27,079 --> 01:24:30,520
there's a shortage of doctors and and and great surgeons.

1533
01:24:30,560 --> 01:24:32,920
You're doctor yourself. You know how that there it takes

1534
01:24:32,920 --> 01:24:34,000
a long time for a human to.

1535
01:24:34,000 --> 01:24:36,680
Speaker 4: Become ridiculously expensive and long.

1536
01:24:36,800 --> 01:24:40,920
Speaker 2: Ridiculously yes, ridiculous, super long time to learn to be

1537
01:24:41,039 --> 01:24:46,119
a good doctor. And even then the knowledge is constantly evolving.

1538
01:24:46,199 --> 01:24:49,119
It's hard to keep up with everything. Uh, you know,

1539
01:24:49,159 --> 01:24:53,640
doctors have limited time. They make mistakes. And you say,

1540
01:24:53,720 --> 01:24:57,079
like how many how many great surgeons are They're not

1541
01:24:57,079 --> 01:24:58,079
not that many great surgeons.

1542
01:24:58,079 --> 01:25:00,479
Speaker 5: When do you think optimists will be a better surgeon

1543
01:25:01,439 --> 01:25:03,520
than the best surgeons?

1544
01:25:03,960 --> 01:25:04,600
Speaker 4: How long for that?

1545
01:25:05,359 --> 01:25:05,960
Speaker 3: Three years?

1546
01:25:06,079 --> 01:25:09,279
Speaker 4: Three years? Okay, and by the way, that's.

1547
01:25:09,439 --> 01:25:11,159
Speaker 3: Year three years at scale.

1548
01:25:11,279 --> 01:25:15,079
Speaker 2: Yes, more, there'll probably been more Optimus robots that are

1549
01:25:15,079 --> 01:25:18,479
great surgeons than there are all surgeons on Earth.

1550
01:25:18,520 --> 01:25:21,039
Speaker 5: And the cost of that is the capex and electricity.

1551
01:25:21,199 --> 01:25:24,720
And it works in Zimbabwe. The best surgeon is throughout

1552
01:25:24,760 --> 01:25:27,399
in the villages, throughout Africa or any place on the planet.

1553
01:25:27,560 --> 01:25:29,720
Speaker 3: Yeah, where do you think it'll roll out first? Not

1554
01:25:29,840 --> 01:25:31,319
the US obviously.

1555
01:25:31,760 --> 01:25:34,039
Speaker 4: Here at the Giga factory.

1556
01:25:34,479 --> 01:25:36,880
Speaker 3: Surgery in the.

1557
01:25:37,840 --> 01:25:41,840
Speaker 5: But that's an important statement in three years time, because

1558
01:25:42,439 --> 01:25:47,520
that is I mean, if it's four or five years,

1559
01:25:47,560 --> 01:25:52,399
who cares, It's still an incredible statement to make I

1560
01:25:52,399 --> 01:25:54,960
mean good for humanity, right, all of a sudden you demonetize.

1561
01:25:54,960 --> 01:25:57,319
Speaker 2: Okay, here's the thing to understand about like humanoid robots

1562
01:25:57,359 --> 01:26:00,119
in terms of the rate of improvement, which.

1563
01:26:00,159 --> 01:26:03,600
Speaker 3: Is is that the you have.

1564
01:26:05,039 --> 01:26:06,840
Speaker 2: Three exponentials multiplied by each other.

1565
01:26:07,000 --> 01:26:08,279
Speaker 3: You have an exponential.

1566
01:26:07,840 --> 01:26:12,560
Speaker 2: Increase in the AI software capability, exponential increase in the

1567
01:26:12,560 --> 01:26:17,359
AI chip kick ebility, and an exponential increase in the electro

1568
01:26:17,439 --> 01:26:22,720
mechanical dexterity. The usefulness of the humanoid robot is those

1569
01:26:22,760 --> 01:26:23,560
three things.

1570
01:26:23,359 --> 01:26:24,600
Speaker 3: Multiplied by each other.

1571
01:26:24,960 --> 01:26:29,600
Speaker 2: Right. Then you have the recursive effect of optimist building.

1572
01:26:29,399 --> 01:26:32,159
Speaker 4: Optimists, right, and then you have the share You.

1573
01:26:32,079 --> 01:26:35,399
Speaker 2: Have a corecursive multiplicable triple exponential.

1574
01:26:34,920 --> 01:26:37,479
Speaker 4: And you have the shared knowledge of all all the experiences.

1575
01:26:37,680 --> 01:26:40,640
Speaker 3: Is that literally optimist building optimists or is it because

1576
01:26:40,720 --> 01:26:42,319
you know the well not right now. But we'll be

1577
01:26:43,319 --> 01:26:46,560
the physical humanoid form factor building the humanoid form as.

1578
01:26:46,479 --> 01:26:48,000
Speaker 2: Opposed to the machine.

1579
01:26:48,159 --> 01:26:51,640
Speaker 3: Yeah, yeah, yeah, but the pony machine is usually something

1580
01:26:51,760 --> 01:26:53,800
kind of like this shape, you know, making something else.

1581
01:26:54,239 --> 01:26:57,079
Just in principle, it's simply a self replicating thing. Yeah. Yeah,

1582
01:26:57,319 --> 01:26:57,520
you know what.

1583
01:26:57,560 --> 01:27:00,319
Speaker 4: The number one question you ask a surgeon when you're interview.

1584
01:27:00,199 --> 01:27:06,720
Speaker 2: Them uh, is this a surgeon joke?

1585
01:27:09,000 --> 01:27:11,600
Speaker 4: It's how many it's how many times? How many times

1586
01:27:11,640 --> 01:27:12,720
do you do that?

1587
01:27:12,840 --> 01:27:18,640
Speaker 2: It's gotta be some funny, you know, it's serious.

1588
01:27:18,439 --> 01:27:20,760
Speaker 5: It's how many times did you use the surgery this morning?

1589
01:27:21,840 --> 01:27:24,000
How many times did you do the surgery this morning

1590
01:27:24,079 --> 01:27:26,640
or yesterday? It's the it's the number of experiences, right,

1591
01:27:27,039 --> 01:27:32,199
and so we've shared memory. You know, every Optimist surgeon

1592
01:27:32,239 --> 01:27:36,920
will have seen every possible perturbation of every in infrared,

1593
01:27:36,960 --> 01:27:40,159
in ultraviolet, not too much caffeine that morning, they didn't

1594
01:27:40,159 --> 01:27:42,279
have a fight with their husband or wife.

1595
01:27:43,279 --> 01:27:51,680
Speaker 2: Yeah, extreme precision, yes, yes, better than any any probably.

1596
01:27:51,720 --> 01:27:53,920
Speaker 3: I said, I feel like put a little machin.

1597
01:27:55,560 --> 01:27:57,119
Speaker 4: Who's in plastic surgery.

1598
01:27:57,039 --> 01:28:00,560
Speaker 3: By five years? So what about the simple they just

1599
01:28:00,960 --> 01:28:02,840
I mean, there's a million of these things to figure out.

1600
01:28:02,880 --> 01:28:06,520
But who's gonna have access to the first Optimists that

1601
01:28:06,600 --> 01:28:09,840
does far, far better microsurgery than any surgeon on earth.

1602
01:28:10,119 --> 01:28:13,079
But you've only manufactured the first ten thousand of them.

1603
01:28:13,560 --> 01:28:14,079
How do you do it?

1604
01:28:14,239 --> 01:28:16,359
Speaker 2: I think people understand how many robost it's going to be.

1605
01:28:16,960 --> 01:28:19,800
Speaker 3: Yeah, well there's a windows ten.

1606
01:28:19,720 --> 01:28:22,720
Speaker 4: Billion by twenty forty, you're still on that path.

1607
01:28:25,079 --> 01:28:29,439
Speaker 3: That's not that's a low number number. Wow, what's the constraint,

1608
01:28:29,560 --> 01:28:35,239
But what's the because if they're self building constraint. Yeah, yeah,

1609
01:28:35,239 --> 01:28:37,840
you got to move the atoms. It's just all that

1610
01:28:38,199 --> 01:28:40,399
just supply chain stuff.

1611
01:28:40,479 --> 01:28:44,000
Speaker 2: So yeah, but you're you're there's sum rightly, you can't

1612
01:28:44,039 --> 01:28:46,760
just manufacturing is very difficult. So you've got you've got

1613
01:28:46,840 --> 01:28:52,680
to you it's it's recused, multiplicable, triple exponential. But but

1614
01:28:52,880 --> 01:28:55,199
you still need to you still you still have to

1615
01:28:55,319 --> 01:28:56,199
climb that, you.

1616
01:28:56,119 --> 01:28:59,920
Speaker 4: Know, selling hopewards again. I think your point was met.

1617
01:29:00,039 --> 01:29:03,520
Speaker 5: Lisen is going to be effectively free the best medicine

1618
01:29:03,560 --> 01:29:03,920
the world.

1619
01:29:03,960 --> 01:29:07,520
Speaker 2: Everyone will have access to medical care that is better

1620
01:29:08,119 --> 01:29:09,840
than what the present.

1621
01:29:09,560 --> 01:29:15,039
Speaker 4: Receives right now. So don't go to medical school, yes, I.

1622
01:29:14,960 --> 01:29:18,600
Speaker 2: Mean unless you but I would say that applies to

1623
01:29:18,600 --> 01:29:21,960
any form of education. It's not like some.

1624
01:29:23,399 --> 01:29:25,000
Speaker 3: I do it for social reasons.

1625
01:29:26,279 --> 01:29:28,000
Speaker 2: You're not going to medical if you want to if

1626
01:29:28,039 --> 01:29:30,119
you want to like minded.

1627
01:29:29,880 --> 01:29:30,640
Speaker 3: People, I suppose.

1628
01:29:32,159 --> 01:29:33,640
Speaker 5: I mean people are still going to want to be

1629
01:29:34,279 --> 01:29:36,479
connected with people. There's going to be some period of.

1630
01:29:36,439 --> 01:29:41,000
Speaker 2: Social reasons, Yeah, like a hobby, like you know, I.

1631
01:29:43,760 --> 01:29:46,279
Speaker 3: Mean, there will be a point where it's expensive.

1632
01:29:46,880 --> 01:29:49,359
Speaker 5: Younger generation says, I do not want that human touching

1633
01:29:49,399 --> 01:29:52,359
me right start when the surgeon comes over. They're going

1634
01:29:52,399 --> 01:29:54,560
to be those people later in life who still want

1635
01:29:54,640 --> 01:29:55,239
a human in the.

1636
01:29:55,239 --> 01:30:00,199
Speaker 2: Loop, okay for a little while, for a lesser where

1637
01:30:00,239 --> 01:30:03,359
they want to live on the I mean, let's just

1638
01:30:03,359 --> 01:30:09,079
take like we've seen some advanced cases of automation, like

1639
01:30:09,159 --> 01:30:13,199
laser for example, where the robot just lasers your eyeball. Now,

1640
01:30:13,199 --> 01:30:15,039
do you want an ophomologist with a hand laser.

1641
01:30:17,840 --> 01:30:19,680
Speaker 3: It's a little taken a laser pointer from.

1642
01:30:23,359 --> 01:30:28,560
Speaker 2: Yeah, I got hor I wouldn't want the best ophalmologist,

1643
01:30:28,680 --> 01:30:31,399
you know, her steadiest hand out there with a hand

1644
01:30:31,479 --> 01:30:33,279
laser one my eyebwl.

1645
01:30:33,319 --> 01:30:33,520
Speaker 8: You know.

1646
01:30:34,039 --> 01:30:36,479
Speaker 3: Yeah, I'm gonna be like that.

1647
01:30:37,520 --> 01:30:39,800
Speaker 2: It's like, do you want to uphomologist with a hand

1648
01:30:39,880 --> 01:30:43,000
laser or do you want the robot to do it

1649
01:30:43,039 --> 01:30:43,800
and actually work?

1650
01:30:43,960 --> 01:30:44,159
Speaker 4: Yeah.

1651
01:30:44,520 --> 01:30:48,039
Speaker 9: This episode is brought to you by Blitzy Autonomous software

1652
01:30:48,079 --> 01:30:53,640
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1660
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1663
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1664
01:31:39,239 --> 01:31:42,560
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1665
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1666
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Speaker 5: Today, let's jump into one of our favorite subjects space.

1667
01:31:52,119 --> 01:31:52,359
Speaker 3: Yeah.

1668
01:31:52,520 --> 01:31:56,920
Speaker 5: So, first off, how cool that Jared Isaacman has become

1669
01:31:57,039 --> 01:31:57,479
a NASSAIG.

1670
01:31:57,560 --> 01:32:00,600
Speaker 4: Yeah he's amazing.

1671
01:32:00,640 --> 01:32:02,359
Speaker 2: Yes, I mean I don't hang out with Jared like

1672
01:32:02,359 --> 01:32:06,880
people think I'm like huge buddies with Jared, but I

1673
01:32:06,880 --> 01:32:08,079
think I've only seen him a.

1674
01:32:08,079 --> 01:32:09,119
Speaker 3: Person of a few times.

1675
01:32:09,119 --> 01:32:10,000
Speaker 4: Amazing candidate.

1676
01:32:10,439 --> 01:32:13,439
Speaker 3: Yeah, he's a really smarter question. You know him really well?

1677
01:32:13,520 --> 01:32:13,760
Speaker 4: Yeah.

1678
01:32:14,000 --> 01:32:15,520
Speaker 5: I took him to a biker or a launch in

1679
01:32:15,600 --> 01:32:17,840
two thousand and eight for his first space experience.

1680
01:32:17,960 --> 01:32:23,600
Speaker 2: I mean he loves space. Next, level and is technically strong.

1681
01:32:24,319 --> 01:32:26,760
It's a smart and component, yes, like a really smart.

1682
01:32:26,520 --> 01:32:28,079
Speaker 4: And really component understance business.

1683
01:32:28,800 --> 01:32:31,279
Speaker 2: Yes, yes, you understands. He gets things.

1684
01:32:31,039 --> 01:32:32,800
Speaker 4: Done and he's been there a few times.

1685
01:32:33,880 --> 01:32:34,840
Speaker 3: Yeah. Yeah, so.

1686
01:32:36,479 --> 01:32:38,079
Speaker 2: I'm just like, you know, we want to have someone

1687
01:32:38,239 --> 01:32:43,079
a smart and competent who loves space exploration and we'll

1688
01:32:43,119 --> 01:32:43,840
get things done.

1689
01:32:44,359 --> 01:32:48,600
Speaker 4: I'm a huge that's so so so happy when he

1690
01:32:48,720 --> 01:32:49,800
got renominated.

1691
01:32:49,960 --> 01:32:55,159
Speaker 2: And now yeah, I think we need to we need

1692
01:32:55,159 --> 01:32:57,520
a new game plan for space, Like we need a

1693
01:32:57,640 --> 01:33:02,880
moon base, yes, like a permanent yes, crude moon base. Uh,

1694
01:33:03,000 --> 01:33:06,079
and and build that up as fast as possible.

1695
01:33:06,239 --> 01:33:06,880
Speaker 3: Yeah.

1696
01:33:07,039 --> 01:33:09,119
Speaker 2: I don't think we should do the you know, send

1697
01:33:09,199 --> 01:33:11,159
a couple of asalts there for hop around for a

1698
01:33:11,159 --> 01:33:13,319
bit and come back, because we did that in sixty nine.

1699
01:33:13,479 --> 01:33:14,600
Speaker 4: Yes, been there, done that.

1700
01:33:15,039 --> 01:33:18,720
Speaker 2: Yeah, it's like a remake of a sixties movie. Never

1701
01:33:18,880 --> 01:33:25,840
go to the original, you know, do something.

1702
01:33:25,640 --> 01:33:32,520
Speaker 5: More cool, you know, yeah telescopes, Yeah exactly.

1703
01:33:32,640 --> 01:33:35,560
Speaker 3: So do you forward deploy the robots, build everything, get

1704
01:33:35,560 --> 01:33:37,319
it already, make the bed, and then.

1705
01:33:37,880 --> 01:33:40,479
Speaker 4: Get the JACUZI warmed up. It's interesting.

1706
01:33:40,680 --> 01:33:41,359
Speaker 3: Yeah.

1707
01:33:40,960 --> 01:33:43,479
Speaker 4: Yeah, how early in the year you're going to hit

1708
01:33:43,560 --> 01:33:46,880
orbital refueling you think with Starship not that early in

1709
01:33:46,920 --> 01:33:49,520
the year. I mean, are you are you shooting for

1710
01:33:49,600 --> 01:33:50,239
the home.

1711
01:33:50,119 --> 01:33:52,319
Speaker 3: In transfer of it? I'd say towards the end of

1712
01:33:52,359 --> 01:33:52,800
the year.

1713
01:33:53,159 --> 01:33:55,439
Speaker 4: Are you shooting for a Mars shot? But then the

1714
01:33:55,479 --> 01:33:57,279
next year we.

1715
01:33:57,239 --> 01:34:00,520
Speaker 2: Could but uh, it would be a low problem ability

1716
01:34:01,039 --> 01:34:06,439
shot and somewhat of a distraction. So it's not out

1717
01:34:06,479 --> 01:34:06,960
of the question.

1718
01:34:08,119 --> 01:34:08,279
Speaker 4: Nine.

1719
01:34:10,079 --> 01:34:14,039
Speaker 2: But like on on Mondays, I have the Starship Engineering

1720
01:34:14,600 --> 01:34:18,319
The big Starship Engineering review is on Mondays. So that

1721
01:34:18,479 --> 01:34:21,840
was actually the lot of the thing ended just before

1722
01:34:21,880 --> 01:34:27,359
coming here, and so I say, like, like Starship is

1723
01:34:27,399 --> 01:34:29,960
really we're doing something that is that the limit of

1724
01:34:30,000 --> 01:34:34,560
biological intelligence? Yeah, this is a this is a hard

1725
01:34:34,600 --> 01:34:35,199
thing to make.

1726
01:34:36,359 --> 01:34:40,680
Speaker 3: And just to capture it. It was created pre AI. Yeah, no,

1727
01:34:40,880 --> 01:34:41,960
I was probably.

1728
01:34:41,720 --> 01:34:45,439
Speaker 2: The last, the last really big thing and that's not AI.

1729
01:34:45,319 --> 01:34:48,680
Speaker 3: And probably the biggest thing ever made. Yeah.

1730
01:34:48,760 --> 01:34:53,560
Speaker 2: But the AG I will say, not bad for human true,

1731
01:34:53,600 --> 01:34:56,520
not bad for human. Yeah, it'd be like a little

1732
01:34:56,520 --> 01:34:57,520
twenty one computer.

1733
01:34:57,840 --> 01:35:01,840
Speaker 3: It's not easy. Yeah, it's brings through the day. Would

1734
01:35:01,840 --> 01:35:05,439
be like doing accounting, doing your interest calculation with a

1735
01:35:05,479 --> 01:35:08,359
pencil and yeah, that's that's pretty good. Yeah, pretty good.

1736
01:35:09,079 --> 01:35:10,800
Speaker 2: With regular computers for a bunch of monkeys.

1737
01:35:10,840 --> 01:35:11,000
Speaker 3: You know.

1738
01:35:11,960 --> 01:35:13,279
Speaker 2: It's like it's like if you saw a bunch of

1739
01:35:13,439 --> 01:35:15,479
chimps like make a raft and across the rover, you'd

1740
01:35:15,479 --> 01:35:19,279
be like, oh, look at that.

1741
01:35:19,399 --> 01:35:23,600
Speaker 10: But you know, we celebrate. We celebrate the paris him,

1742
01:35:25,000 --> 01:35:29,279
give him some few nuts. These things become right, like

1743
01:35:29,319 --> 01:35:33,199
the three. Yeah, I think it's worth noting three is beautiful.

1744
01:35:34,720 --> 01:35:37,319
Speaker 2: It's amazing by far the best rocket engine ever.

1745
01:35:37,520 --> 01:35:39,840
Speaker 3: Is that as even close? No, that's also so that

1746
01:35:39,840 --> 01:35:44,560
would be the last thing. Four will definitely be Yeah.

1747
01:35:45,079 --> 01:35:50,319
Speaker 2: This, but like I think AI will start to become

1748
01:35:50,359 --> 01:35:55,279
relevant next year, so maybe we'll It's not like we're

1749
01:35:56,079 --> 01:35:59,359
pushing off AI. It's just a I can't do rocket

1750
01:35:59,399 --> 01:36:02,720
engineering yet, yep, but we'll probably we'll be ill to

1751
01:36:02,800 --> 01:36:03,159
next year.

1752
01:36:03,199 --> 01:36:05,880
Speaker 3: We have a company in our incubator doing mechanical design,

1753
01:36:05,920 --> 01:36:08,960
working with Androl and so forth. And it's not you

1754
01:36:09,000 --> 01:36:11,720
can design brackets and parts and things, but you can't

1755
01:36:11,760 --> 01:36:15,399
quite do rockets. But the timeline is so short, you know,

1756
01:36:15,439 --> 01:36:16,439
from point A to point b.

1757
01:36:17,239 --> 01:36:20,479
Speaker 2: If you like, a year from now, probably it can Okay,

1758
01:36:20,520 --> 01:36:22,960
it probably can be helpful, meaningfully helpful in a year

1759
01:36:23,000 --> 01:36:23,319
from now.

1760
01:36:23,560 --> 01:36:26,840
Speaker 4: Yeah, So the big big milestones are going to be

1761
01:36:27,000 --> 01:36:31,199
Starship B three launching it to keep canaveral orbital refueling.

1762
01:36:31,840 --> 01:36:33,720
Speaker 3: Yes, big ones.

1763
01:36:34,199 --> 01:36:40,039
Speaker 2: Well yeah, catching the ship with the tower. Yeah right,

1764
01:36:42,119 --> 01:36:46,239
So really the thing that matters is can we refly

1765
01:36:47,000 --> 01:36:47,680
the shire thing?

1766
01:36:48,159 --> 01:36:49,760
Speaker 3: Yeah?

1767
01:36:48,720 --> 01:36:53,880
Speaker 2: Yeah, we have reflow in a booster sure, which is

1768
01:36:53,920 --> 01:36:56,680
you know, not bad for its largest flying object of ems.

1769
01:36:57,680 --> 01:36:58,880
Catching with chop sticks.

1770
01:37:00,279 --> 01:37:02,119
Speaker 4: Out from a bunch of market you're keeping, You're keeping

1771
01:37:02,119 --> 01:37:03,239
the AI is very entertained.

1772
01:37:03,479 --> 01:37:06,000
Speaker 2: Yeah, yeah, exactly, Yeah, I'll be like cut on the

1773
01:37:06,039 --> 01:37:08,960
back from that a g I hopefully is there a

1774
01:37:09,000 --> 01:37:11,800
target for a number of reuses before and it's got

1775
01:37:11,800 --> 01:37:14,960
to be a lot of wear and tear. It requires

1776
01:37:15,000 --> 01:37:18,399
a lot of iteration to achieve higher reuse. So you

1777
01:37:18,399 --> 01:37:21,680
figure out like what what's breaking between flights, and you

1778
01:37:21,720 --> 01:37:27,199
sort of iteratively solve those things. So from people looking

1779
01:37:27,199 --> 01:37:29,000
at from the outside might say, oh, the rocket looks

1780
01:37:29,039 --> 01:37:32,199
kind of the same, but there's like a thousand changes

1781
01:37:32,720 --> 01:37:37,560
to make it more useable, more reliable, you know, the

1782
01:37:37,600 --> 01:37:40,479
sheer amount of energy you're trying to you know, expand

1783
01:37:40,520 --> 01:37:45,239
I mean it's uh, Starship is doing over one hundred

1784
01:37:45,239 --> 01:37:47,720
gigawatts of power on a scent.

1785
01:37:49,479 --> 01:37:56,079
Speaker 3: It's a lot, you know, some glass under there, and yeah,

1786
01:37:57,880 --> 01:37:58,760
a lot, it's a lot.

1787
01:38:00,640 --> 01:38:02,920
Speaker 2: But like the amazing thing is that it doesn't explode. Yes,

1788
01:38:03,439 --> 01:38:10,399
sometimes doesn't explode. Sometimes not exploding is like we've blown

1789
01:38:10,439 --> 01:38:11,880
up a lot of engines in the test stand.

1790
01:38:14,640 --> 01:38:16,279
Speaker 3: I mean, is that what causes the wear and terror

1791
01:38:16,319 --> 01:38:18,560
is the re entry of the or the falling.

1792
01:38:18,840 --> 01:38:24,920
Speaker 2: Well that too, I mean for for the booster, the

1793
01:38:25,000 --> 01:38:29,439
re entry is not that bad, you know, you know

1794
01:38:29,439 --> 01:38:32,800
if something it's it's it's not like that. That's not

1795
01:38:32,840 --> 01:38:35,399
really like we're also obviously just solved that, you know,

1796
01:38:35,439 --> 01:38:39,199
with with thousand nine, so we kind of understand booster reuse.

1797
01:38:41,159 --> 01:38:44,840
We've had We've have over five hundred reflights of the

1798
01:38:44,840 --> 01:38:50,680
Falcon iinver stage, so we really understand and and and

1799
01:38:50,800 --> 01:38:55,199
and The Starship booster actually is a more benign entry

1800
01:38:55,520 --> 01:39:02,079
than than the Falcon Booster because the the staging ratio

1801
01:39:02,439 --> 01:39:06,039
is more more biased towards the upper stage for Starship,

1802
01:39:06,359 --> 01:39:11,520
so I shifted the mass ratio to be much higher

1803
01:39:12,239 --> 01:39:14,680
on the ship side for Starship. There was a mistake

1804
01:39:14,720 --> 01:39:17,720
I made on Falcon nine that there should be more

1805
01:39:17,760 --> 01:39:21,840
mass in the upper stage of falcon nine, so that

1806
01:39:21,920 --> 01:39:27,520
the staging velocity of is lower. If the staging velocity

1807
01:39:27,560 --> 01:39:30,079
of falconine was lower, would have less wear and tear

1808
01:39:30,159 --> 01:39:30,720
on falconine.

1809
01:39:30,760 --> 01:39:32,039
Speaker 3: Yeah, it's not intuitive at all.

1810
01:39:32,199 --> 01:39:34,880
Speaker 2: That's interesting, Yeah, because it's it's kind of a flat

1811
01:39:34,880 --> 01:39:40,279
optimization the paleot to orbit. There's sort of a flat

1812
01:39:40,319 --> 01:39:43,399
region in the mass ratio of the first second stages,

1813
01:39:43,520 --> 01:39:45,199
and so you just want to bias that mass ratio

1814
01:39:45,239 --> 01:39:49,920
towards the UH to put more mass on the upper stage.

1815
01:39:50,760 --> 01:39:54,800
So yeah, because you know, you're just you're got your

1816
01:39:54,840 --> 01:39:57,159
kinetic energy scalting with the square velocity. So you've got

1817
01:39:57,199 --> 01:39:59,920
to describe that kinetic energy. If you pass the melting

1818
01:40:00,000 --> 01:40:02,600
point of whatever you your stage is made of, you've

1819
01:40:02,600 --> 01:40:03,159
got a problem.

1820
01:40:03,359 --> 01:40:03,600
Speaker 3: Yep.

1821
01:40:04,199 --> 01:40:08,560
Speaker 5: So, my my colleague Alex Winson Gross is one of

1822
01:40:08,560 --> 01:40:11,600
our Moonshot mates here. I want to ask a question

1823
01:40:11,680 --> 01:40:14,960
I do too. Have you seen the documentary age of

1824
01:40:15,000 --> 01:40:20,800
disclosure about all of the announcements by US government officials

1825
01:40:20,800 --> 01:40:24,319
and military officials about all the alien spacecraft that have

1826
01:40:24,439 --> 01:40:29,720
been having sort of tained and I've heard what you've

1827
01:40:29,720 --> 01:40:31,279
said about this, Well.

1828
01:40:31,119 --> 01:40:34,119
Speaker 2: I do wonder why you know, if you plot on

1829
01:40:34,159 --> 01:40:39,279
a chart the resolution of cameras over time, like megapixels

1830
01:40:39,279 --> 01:40:46,399
per year. Yeah, and the resolution of UFO photographs. Why

1831
01:40:47,840 --> 01:40:55,560
it's flat on the UFO, we get a fuzzy blove. Well,

1832
01:40:55,560 --> 01:40:58,399
we've got like you know whatever, under megapixel camera that

1833
01:40:58,479 --> 01:41:03,640
can can see you fucking no hairs. Can somebody take

1834
01:41:03,680 --> 01:41:05,600
a shot of the UFO with an actual camera?

1835
01:41:06,239 --> 01:41:10,159
Speaker 3: But even if you knew, I'm sure there's the next lineage.

1836
01:41:11,119 --> 01:41:14,920
Speaker 4: But anyway, it's sorry, it would be fascinating.

1837
01:41:17,000 --> 01:41:20,119
Speaker 2: I'm asked all the time if if I yes, and

1838
01:41:20,159 --> 01:41:24,239
I'm like, look, I can show you if if I

1839
01:41:24,279 --> 01:41:26,039
was aware of the slightest evidence of aliens, I would

1840
01:41:26,039 --> 01:41:27,079
immediately post out an X.

1841
01:41:27,279 --> 01:41:27,439
Speaker 4: Yeah.

1842
01:41:31,079 --> 01:41:33,079
Speaker 3: So the question is would be the most viewed post

1843
01:41:33,119 --> 01:41:36,239
of old time. So I actually.

1844
01:41:35,880 --> 01:41:39,119
Speaker 5: Wonder about the US public if they would like, oh,

1845
01:41:39,199 --> 01:41:41,840
that's interesting, go back to their sports scores the next day.

1846
01:41:42,399 --> 01:41:44,760
Speaker 2: Yeah, I think everyone would want to see the alien.

1847
01:41:44,960 --> 01:41:50,560
Ye like, if you got one here, it is way fascinating.

1848
01:41:50,560 --> 01:41:52,439
Increase the military budget. We're like, we've found an alien.

1849
01:41:52,439 --> 01:41:57,479
It seems dangerous that they don't have an incentive to

1850
01:41:57,520 --> 01:42:00,079
hide the aliens. They have an incentive to bring to

1851
01:42:00,239 --> 01:42:02,760
sh out sure the alien because they would not have

1852
01:42:02,840 --> 01:42:06,359
any more arguments about the military budget if they seem

1853
01:42:06,359 --> 01:42:10,520
a little bit dangerous. I can always hope, you know,

1854
01:42:10,960 --> 01:42:14,880
I mean, I'm you know, we've got nine thousand satellites

1855
01:42:14,920 --> 01:42:17,359
up there. We've never had to maneuver around an alien

1856
01:42:17,399 --> 01:42:27,880
spaceship yet, so well yeah, so anyway, So I guess

1857
01:42:27,920 --> 01:42:32,479
the good future is you can anyone can have whatever

1858
01:42:32,520 --> 01:42:36,520
stuff they want and incredible medical care that's better than

1859
01:42:36,600 --> 01:42:37,479
any medical.

1860
01:42:37,199 --> 01:42:38,079
Speaker 3: Care that exists.

1861
01:42:38,399 --> 01:42:42,600
Speaker 2: So I think if you sort of lift your gaze,

1862
01:42:43,039 --> 01:42:45,880
you know, to not a super distant point five years

1863
01:42:45,920 --> 01:42:51,800
from now, four years from now, maybe we'll have better

1864
01:42:51,840 --> 01:42:58,319
medical care than anyone has today available for everyone within

1865
01:42:58,399 --> 01:43:05,800
five years. Yep, no scarcity of goodsal services, the.

1866
01:43:05,880 --> 01:43:07,640
Speaker 4: Best education available for everybody.

1867
01:43:08,159 --> 01:43:10,560
Speaker 2: Why don't you can learn anything you want for forgot

1868
01:43:10,600 --> 01:43:11,600
anything for free?

1869
01:43:12,319 --> 01:43:15,600
Speaker 3: What about access to compute? People will probably care a

1870
01:43:15,640 --> 01:43:18,079
lot more about that than their government check. And about

1871
01:43:18,520 --> 01:43:21,640
three or what do they want to do with compute? Well,

1872
01:43:21,680 --> 01:43:24,760
I mean compute translates to anything you want, right, your

1873
01:43:24,920 --> 01:43:29,319
your virtual friend, your entertainment, you're like, it's it's probably everything.

1874
01:43:28,960 --> 01:43:31,399
Speaker 4: That those are AI services basically.

1875
01:43:31,159 --> 01:43:33,960
Speaker 3: Yeah, or your ability to innovate too, you can't innovate

1876
01:43:34,000 --> 01:43:35,399
without an AI assistant at that point.

1877
01:43:35,520 --> 01:43:40,119
Speaker 5: So one of our other Moon made salim Ismael said,

1878
01:43:40,560 --> 01:43:43,039
asked this question. He said, Elin, you often say physics

1879
01:43:43,119 --> 01:43:47,359
is the law. Everything else is a recommendation. So as

1880
01:43:47,399 --> 01:43:52,039
AI energy and space systems scale exponentially, what non physical

1881
01:43:52,039 --> 01:43:57,960
constraints organizational, cultural, bureaucracy, or human are Now the real bottleneck.

1882
01:43:59,520 --> 01:44:00,199
Speaker 4: Is there bouto.

1883
01:44:03,960 --> 01:44:06,279
Speaker 2: Electricity generation is the limiting factor.

1884
01:44:08,720 --> 01:44:09,560
Speaker 4: The innermost loop.

1885
01:44:10,560 --> 01:44:13,239
Speaker 3: Yeah, I think.

1886
01:44:13,079 --> 01:44:17,239
Speaker 2: People are underestimating the difficulty of bringing electricity online. You know,

1887
01:44:17,359 --> 01:44:19,239
you've you've got to get You've got to generate the electricity.

1888
01:44:19,279 --> 01:44:23,760
You've got to any transformers for the transformers, so you've

1889
01:44:23,760 --> 01:44:26,560
got to convert that voltage to something that the computers

1890
01:44:26,560 --> 01:44:30,720
can digest. You've got to cool the computers. So it's

1891
01:44:30,760 --> 01:44:36,720
basically electricity generation and cooling a limiting factors for AI.

1892
01:44:38,399 --> 01:44:43,600
And once you have humanoid robotics they can address the

1893
01:44:43,600 --> 01:44:50,199
power generation and the cooling stell but that that is

1894
01:44:50,199 --> 01:44:52,039
the limiting factor and will be for at least the

1895
01:44:52,079 --> 01:44:52,880
next two years.

1896
01:44:53,279 --> 01:44:57,680
Speaker 3: It's an amazing how divergent the Memphis version of that

1897
01:44:57,960 --> 01:45:00,960
is from the space based version. You have solar panels

1898
01:45:01,000 --> 01:45:06,359
in common, but otherwise no storage, abundant amounts of energy. Yeah,

1899
01:45:06,479 --> 01:45:08,920
but you have launch costs, and you have I mean

1900
01:45:09,239 --> 01:45:11,439
and weight suddenly mattering. I don't care too much about

1901
01:45:11,439 --> 01:45:14,880
the weight in Tennessee. Suddenly the weight is a critical factor.

1902
01:45:14,880 --> 01:45:19,039
And there's two pathways for compute. I have a huge

1903
01:45:19,079 --> 01:45:20,319
divergence from here forward.

1904
01:45:20,520 --> 01:45:27,039
Speaker 2: Yeah, once we get Sola domestically at scale, and if

1905
01:45:27,079 --> 01:45:31,920
we're launching Starship at scale, then by far the cheapest

1906
01:45:31,920 --> 01:45:35,720
way to do a compute will be in space. So

1907
01:45:35,760 --> 01:45:39,079
once you have the once you have full and complete reusability,

1908
01:45:40,520 --> 01:45:42,960
the propellant costs of flight is maybe a million dollars.

1909
01:45:43,079 --> 01:45:44,119
Speaker 4: Yeah, people don't realize that.

1910
01:45:44,159 --> 01:45:49,359
Speaker 5: People have ridiculous amount of expectations how much it costs.

1911
01:45:49,119 --> 01:45:51,359
Speaker 2: So if you have it's called a million dollars of

1912
01:45:51,399 --> 01:45:55,119
transport for ten megawatts of AI compute.

1913
01:45:55,199 --> 01:46:00,680
Speaker 3: Yeah, So assuming everything keeps frending the way it's current trending.

1914
01:46:01,079 --> 01:46:04,039
If you look at the next four years of accelerating launches,

1915
01:46:04,760 --> 01:46:07,880
so two hundred tons per launch, Yeah, that was.

1916
01:46:07,880 --> 01:46:09,800
Speaker 2: On this is where you're going. But yeah, like if

1917
01:46:09,840 --> 01:46:11,880
say sun, if say high altitude son, I think it's

1918
01:46:11,880 --> 01:46:13,800
probably more like one hundred and fifty tons. But yeah,

1919
01:46:13,840 --> 01:46:15,560
it's the right order of MAGE two is at least

1920
01:46:15,560 --> 01:46:19,079
it's it's INACCESSIB one hundred tons for emoginal costs per

1921
01:46:19,159 --> 01:46:20,680
flight of around a million million dollars.

1922
01:46:20,680 --> 01:46:23,800
Speaker 3: So what fraction of all that launched mass is data

1923
01:46:23,840 --> 01:46:28,319
centers in space as opposed to moon base, as opposed

1924
01:46:28,319 --> 01:46:30,640
to launch to Mars, as opposed.

1925
01:46:30,279 --> 01:46:33,680
Speaker 5: To It's interesting how I mean this is and you

1926
01:46:33,880 --> 01:46:37,159
we weren't talking about this as a space objective.

1927
01:46:37,079 --> 01:46:38,760
Speaker 4: Even you know, a year ago.

1928
01:46:39,159 --> 01:46:41,880
Speaker 5: Yeah, all of a sudden, data centers have become the

1929
01:46:42,039 --> 01:46:44,359
massive driving force for opening up.

1930
01:46:44,279 --> 01:46:47,079
Speaker 3: The space and also the urgent the urgent use case too.

1931
01:46:47,159 --> 01:46:48,680
Speaker 5: I mean I used to I used to wonder what's

1932
01:46:48,680 --> 01:46:51,840
going to drive humanity? I thought it was asteroid mining, right,

1933
01:46:52,039 --> 01:46:54,079
you were focused on Mars.

1934
01:46:54,279 --> 01:46:57,720
Speaker 2: Yeah, and we will actually want to mine asteroids tournaments too, sure,

1935
01:46:58,640 --> 01:47:02,640
you know, before before you foot before you you know,

1936
01:47:02,720 --> 01:47:04,239
not not anything else, like I.

1937
01:47:04,239 --> 01:47:05,800
Speaker 4: Mean, if we're gonna if we're gonna build out dice

1938
01:47:05,840 --> 01:47:06,439
and swarms.

1939
01:47:07,680 --> 01:47:09,319
Speaker 2: Yeah, just a bunch of satellites around the sun.

1940
01:47:09,439 --> 01:47:13,279
Speaker 5: Yeah, how how how long? What's your time frame for Alex?

1941
01:47:13,399 --> 01:47:15,800
Another question? Alex wanted to have us ask, what's your

1942
01:47:15,840 --> 01:47:20,640
time frame for uh, for humanity achieving a dice and swarm?

1943
01:47:20,760 --> 01:47:23,239
Speaker 4: Is it fifty years? Yea, I know it's it's a

1944
01:47:23,239 --> 01:47:23,680
matter of but.

1945
01:47:24,000 --> 01:47:27,079
Speaker 2: One people think like everything's gonna be cover in satellites.

1946
01:47:27,119 --> 01:47:30,000
I think it's not quite that that. I mean, I

1947
01:47:30,039 --> 01:47:34,960
think we like what mass ends up sure becoming satellite.

1948
01:47:35,960 --> 01:47:41,399
You know, mercury probably ends up being satellites. Yes, Jupiter, Jupiter, Yeah,

1949
01:47:41,880 --> 01:47:42,720
it's a little gassy.

1950
01:47:42,960 --> 01:47:46,399
Speaker 3: Oh yeah, big a lot of rocks.

1951
01:47:46,720 --> 01:47:47,960
Speaker 4: Do you leave Mars alone?

1952
01:47:48,159 --> 01:47:51,880
Speaker 3: But yeah, asteroids.

1953
01:47:50,279 --> 01:47:52,920
Speaker 4: Asteroids are fantastic food source.

1954
01:47:53,800 --> 01:47:57,039
Speaker 3: Yeah. No, gravity well, gravity well on Jupiters, and they're.

1955
01:47:56,880 --> 01:48:00,600
Speaker 4: Already mostly differentiated into you know, carbonation's condri for fuel

1956
01:48:00,640 --> 01:48:02,359
and nickel iron for materials.

1957
01:48:03,079 --> 01:48:03,399
Speaker 3: Gold.

1958
01:48:03,439 --> 01:48:06,319
Speaker 2: Yeah, a bunch of the asteroid belt probably turns into

1959
01:48:07,119 --> 01:48:08,560
solar panels, you know.

1960
01:48:08,720 --> 01:48:09,680
Speaker 3: Star star power.

1961
01:48:10,479 --> 01:48:12,439
Speaker 4: So I've known you for twenty power, I've known you

1962
01:48:12,439 --> 01:48:16,600
for twenty six years. Now it feels to me like

1963
01:48:16,920 --> 01:48:19,880
I don't want to be you know, it feels like

1964
01:48:19,920 --> 01:48:24,800
you've gotten much smarter and much more capable over this

1965
01:48:25,000 --> 01:48:28,239
last decade. Do you feel that way? Do you feel

1966
01:48:28,239 --> 01:48:30,800
like you just have better people around you, better tools?

1967
01:48:31,399 --> 01:48:38,720
Speaker 5: What what's changed because the level of of audacity, you know,

1968
01:48:38,960 --> 01:48:44,439
orders of magnitude, orders of magnitude, I mean some insane.

1969
01:48:44,079 --> 01:48:46,199
Speaker 4: Insanity's yeah, audacious, Yeah.

1970
01:48:47,479 --> 01:48:50,600
Speaker 3: I say, how.

1971
01:48:50,520 --> 01:48:51,399
Speaker 4: Do you feel about that?

1972
01:48:52,880 --> 01:48:54,960
Speaker 5: What's changed? Do you feel that way? I mean the

1973
01:48:55,039 --> 01:49:00,840
scope of what your ability is? How do you self

1974
01:49:00,840 --> 01:49:01,520
reflect on that?

1975
01:49:05,119 --> 01:49:06,720
Speaker 2: Well, I've had to solve a lot of problems in

1976
01:49:06,760 --> 01:49:11,760
a lot of different arenas, which you get this cross

1977
01:49:11,760 --> 01:49:19,560
fertilization of of knowledge of problem solving. And if you

1978
01:49:20,560 --> 01:49:24,319
problem solve in a lot of different arenas, then like

1979
01:49:24,439 --> 01:49:28,199
what what is easy in one arena is trivial in

1980
01:49:28,199 --> 01:49:31,439
it is like what is trivial in one arena is

1981
01:49:31,439 --> 01:49:33,880
a superpower in another arena. It's sort of like Planet

1982
01:49:33,920 --> 01:49:37,239
crypt You came from Planet Crypton type of thing, so

1983
01:49:38,359 --> 01:49:42,560
you know, crypton Planet Crypton, you just be normal. But

1984
01:49:42,600 --> 01:49:45,920
if you come to Earth, you're a superman. So if

1985
01:49:45,920 --> 01:49:52,000
he takes a manufacturing of volume manufacturing of complex objects

1986
01:49:52,119 --> 01:49:55,640
in the automotive industry, I have to work on solving that.

1987
01:49:58,159 --> 01:50:02,159
When translated to the space industry, it's like being superman

1988
01:50:05,359 --> 01:50:09,079
because the rockets are made in very small numbers. Right,

1989
01:50:09,159 --> 01:50:14,319
if you apply automotive manufacturing technology to satellites and rockets.

1990
01:50:15,199 --> 01:50:19,600
It's like being Superman. Then if you take advanced material

1991
01:50:19,640 --> 01:50:22,880
science from rockets and you apply that to the automotive industry,

1992
01:50:22,920 --> 01:50:26,479
you get Superman a game. Yeah, as came from Planet Krypton,

1993
01:50:26,680 --> 01:50:27,720
back back in Planet Crypton.

1994
01:50:27,800 --> 01:50:31,880
Speaker 3: This is normal. You know, it's funny, how like the

1995
01:50:32,000 --> 01:50:35,920
knowledge ports that that was true with Tesla and SpaceX

1996
01:50:35,960 --> 01:50:39,520
being completely separate. Yeah, but now they actually interact because

1997
01:50:39,560 --> 01:50:41,760
you know, AI ties everything together for the orbiting. Yeah.

1998
01:50:41,760 --> 01:50:44,079
The convergence is crazy, Like, I don't know if you

1999
01:50:44,399 --> 01:50:48,720
visualize these parts fitting together originally. No, No, I mean

2000
01:50:48,800 --> 01:50:51,760
I didn't. I didn't think they at this point.

2001
01:50:51,760 --> 01:50:54,359
Speaker 2: Thing, so I guess everything it ultimately converges in the singularity.

2002
01:50:55,079 --> 01:50:56,119
Speaker 3: Yeah, that's what I think too.

2003
01:50:56,279 --> 01:50:58,399
Speaker 5: You have lots of different parts of the puzzle that

2004
01:50:58,439 --> 01:51:00,760
you get to play with all.

2005
01:51:02,119 --> 01:51:04,279
Speaker 2: This one part that's missing, which is the fab.

2006
01:51:05,439 --> 01:51:09,119
Speaker 3: Yeah, you're gonna buy Intel. You get it for a

2007
01:51:09,159 --> 01:51:16,479
fraction of that one hundred and seventy billion. I think

2008
01:51:16,520 --> 01:51:21,239
it needs to be you fab. Well, I agree, but

2009
01:51:21,720 --> 01:51:27,560
licenses real estate ASNL machines, it's not easy. Just get

2010
01:51:27,560 --> 01:51:30,479
the assets and go. I don't think it's easy. That's why.

2011
01:51:30,479 --> 01:51:34,039
Speaker 2: I mean, it's not like I think it's a simple

2012
01:51:34,039 --> 01:51:35,520
thing solved. I think it's a hard thing to solve,

2013
01:51:35,600 --> 01:51:37,840
but but it must be solved.

2014
01:51:38,359 --> 01:51:39,760
Speaker 3: I've come to the conclusion that.

2015
01:51:40,880 --> 01:51:43,319
Speaker 4: Would it be would be solely captured by you, or

2016
01:51:43,359 --> 01:51:44,520
would it be an asset.

2017
01:51:44,239 --> 01:51:44,760
Speaker 3: For the US.

2018
01:51:45,960 --> 01:51:48,079
Speaker 2: Look, I'm just saying that we're gonna we're going to

2019
01:51:48,159 --> 01:51:50,760
hit a chipwall. Yeah, if we don't do the fab.

2020
01:51:51,760 --> 01:51:55,760
So we got two choices, hit the chipwall over make

2021
01:51:55,800 --> 01:51:56,159
a fab.

2022
01:51:56,560 --> 01:52:01,079
Speaker 3: Then TSMC, for whatever reason, is massively worried about overbuilding,

2023
01:52:01,680 --> 01:52:05,199
which is insane. But the whole world will be stuck

2024
01:52:05,239 --> 01:52:08,319
with a shortage of chips for no ever. So they

2025
01:52:08,359 --> 01:52:10,119
are actually there.

2026
01:52:10,279 --> 01:52:13,680
Speaker 2: I don't know if they're right for the right reason,

2027
01:52:13,840 --> 01:52:19,560
but they're they're right because it's actually, like, what is

2028
01:52:19,600 --> 01:52:23,039
the limiting factor at any given point in time. The

2029
01:52:23,079 --> 01:52:27,479
limiting factor, say, if you say that by Q three

2030
01:52:27,560 --> 01:52:29,920
next year, like in nine months, nine to twelve months,

2031
01:52:30,279 --> 01:52:32,000
the limiting fact will be turning the chips on.

2032
01:52:34,039 --> 01:52:34,279
Speaker 3: Power.

2033
01:52:34,439 --> 01:52:34,920
Speaker 4: Just power.

2034
01:52:35,159 --> 01:52:39,399
Speaker 2: Yeah, you need power and all of the equipment necessary

2035
01:52:39,640 --> 01:52:42,960
power and transformer isn't cooling, So it's it's not like

2036
01:52:43,000 --> 01:52:44,760
you can just sort of drop off.

2037
01:52:44,640 --> 01:52:47,079
Speaker 4: Some GPUs at the power plane and you've vertical You've

2038
01:52:47,079 --> 01:52:49,079
got it. You've got it again with an xt AI,

2039
01:52:49,199 --> 01:52:53,319
didn't you. Sorry, you've vertically integrated that inside of XAI.

2040
01:52:53,399 --> 01:52:55,520
Speaker 2: Where they're on their own transform, yes, and your.

2041
01:52:55,399 --> 01:52:56,199
Speaker 4: Own cooling system.

2042
01:52:56,359 --> 01:52:59,079
Speaker 3: Yes. But they're worried that if they make more than

2043
01:52:59,119 --> 01:53:01,800
twenty million gp is like they make forty million instead

2044
01:53:01,840 --> 01:53:04,680
of twenty million, the twenty million will not find a

2045
01:53:04,760 --> 01:53:06,399
source of power.

2046
01:53:06,960 --> 01:53:07,720
Speaker 4: But they will be bought.

2047
01:53:07,960 --> 01:53:11,439
Speaker 2: If there's anything missing that prevents them from being turned on,

2048
01:53:12,600 --> 01:53:16,760
they cannot be turned on. So they've got to have

2049
01:53:16,880 --> 01:53:19,199
a power plant with excess with enough power. So you've

2050
01:53:19,199 --> 01:53:22,960
got to have enough gigawatts. Then you've got to convert

2051
01:53:23,000 --> 01:53:26,640
that from probably coming out of a powerplant at you know,

2052
01:53:27,960 --> 01:53:29,920
one hundred to three hundred killer volts type of thing.

2053
01:53:31,359 --> 01:53:35,399
You've ultimately you've got to convert that down to you know,

2054
01:53:35,399 --> 01:53:38,760
several hundred volts at the at the rack level. So

2055
01:53:38,760 --> 01:53:42,720
if you're missing any of the power conversion steps, you

2056
01:53:43,399 --> 01:53:45,199
won't be able to turn them on, and then you've

2057
01:53:45,199 --> 01:53:50,159
got to extract the heat. So it's a big shift

2058
01:53:50,239 --> 01:53:53,159
for the data center world to move to liquid cooling

2059
01:53:53,279 --> 01:53:58,720
because they've used air cooling, and you know the consequences

2060
01:53:58,760 --> 01:54:03,800
of a burst pipe are very substantial. So if you

2061
01:54:04,000 --> 01:54:06,399
if you blow up pipe of what a pipe in

2062
01:54:06,439 --> 01:54:10,239
a data center? Yeah, just you just fragged a billion

2063
01:54:10,319 --> 01:54:11,199
dollars right there.

2064
01:54:11,560 --> 01:54:13,520
Speaker 3: It just seems inconceivable to me though, Like if I

2065
01:54:13,720 --> 01:54:15,199
had those chips, I would find a way to turn

2066
01:54:15,239 --> 01:54:17,479
them on the value of the intelligence coming out the

2067
01:54:17,520 --> 01:54:20,479
other side so far out weighs the complexity of trying

2068
01:54:20,520 --> 01:54:23,439
to find a way, And there would be a way.

2069
01:54:23,319 --> 01:54:26,560
Speaker 2: But it's just the crossing of the coves. So if

2070
01:54:26,680 --> 01:54:31,039
chip output is growing exponentially, but power harnessed is growing

2071
01:54:31,600 --> 01:54:35,359
in a sort of slow linear fashion, yeah, then.

2072
01:54:35,399 --> 01:54:41,199
Speaker 3: The output right now exactly, it's chip output growing exponentially,

2073
01:54:41,239 --> 01:54:45,359
and it's like a very slow exponent If it's growing exponentially, it's.

2074
01:54:45,279 --> 01:54:48,319
Speaker 2: For high power AI chips is growing exponentially.

2075
01:54:50,119 --> 01:54:52,880
Speaker 3: Like what if we do twenty million GPUs next year,

2076
01:54:53,079 --> 01:54:57,039
what are we talking about the following year, like twenty

2077
01:54:57,039 --> 01:54:59,000
two million, twenty five? I just I don't see the

2078
01:54:59,000 --> 01:55:01,840
fabs coming online. But maybe.

2079
01:55:03,760 --> 01:55:05,800
Speaker 4: So we have two we have two issues to solve.

2080
01:55:06,119 --> 01:55:07,520
Speaker 2: It's it's it's you have to like sort of pick

2081
01:55:07,520 --> 01:55:09,560
a point in time and say what what is limiting

2082
01:55:09,600 --> 01:55:11,960
factor at any given point in time? So I'm not

2083
01:55:12,000 --> 01:55:14,359
saying that power will be forever the limiting point. It's

2084
01:55:14,399 --> 01:55:17,960
just if you say, pick a date and say at

2085
01:55:17,960 --> 01:55:21,479
this point is our chips limiting factor, our powers limiting

2086
01:55:21,520 --> 01:55:26,439
factor or power conversion equipment and cooling. So it's sort

2087
01:55:26,479 --> 01:55:34,840
of you need transformers for transformers. So, uh, this is

2088
01:55:34,880 --> 01:55:38,279
a very hard thing. It's much harder than people realize.

2089
01:55:38,720 --> 01:55:40,199
So for X A I, X I is going to

2090
01:55:40,279 --> 01:55:44,680
have the first gigawa uh training cluster at classes to

2091
01:55:45,000 --> 01:55:45,960
in Memphis.

2092
01:55:46,159 --> 01:55:47,520
Speaker 3: In order for us to do that.

2093
01:55:47,600 --> 01:55:52,800
Speaker 4: We like this month right, yes, month or two like mid.

2094
01:55:52,760 --> 01:55:58,680
Speaker 2: January, so mid January will be a gig out of

2095
01:55:58,680 --> 01:56:02,760
classes to not counting classes one and then one and

2096
01:56:02,760 --> 01:56:06,039
a half gig watch probably in like April or April ish.

2097
01:56:07,039 --> 01:56:11,359
Speaker 3: Incredible. So this is of cokaher in training. This is

2098
01:56:11,399 --> 01:56:15,560
the first B two hundreds. These are GB three hundreds Okay,

2099
01:56:17,159 --> 01:56:21,680
first ones off the line to get flipped on. Yeah, that's.

2100
01:56:23,199 --> 01:56:26,039
Speaker 2: Those are actually a team had to pull off a

2101
01:56:26,079 --> 01:56:29,079
whole bunch of miracles and series for this to occur. Yeah,

2102
01:56:29,920 --> 01:56:35,840
and and it like even though there are three hundred

2103
01:56:35,920 --> 01:56:39,920
killer vault multiple high voltage power lines going right past

2104
01:56:39,920 --> 01:56:45,720
the building. The in order to connect to those, it

2105
01:56:45,800 --> 01:56:46,399
takes a year.

2106
01:56:49,039 --> 01:56:52,119
Speaker 4: Yeah, you built the entire thing and you're still not connected.

2107
01:56:52,560 --> 01:56:52,880
My god.

2108
01:56:52,960 --> 01:56:57,159
Speaker 2: So we had to cobble together a gigawatt of power

2109
01:56:58,239 --> 01:57:03,319
natural gas, yes, with two vines that range in size

2110
01:57:03,319 --> 01:57:06,760
from ten megawats to fifty megawats. To get to a gigawats,

2111
01:57:06,760 --> 01:57:10,640
there's a whole bunch of them, and you've got to

2112
01:57:10,640 --> 01:57:16,239
make them all work together, manage the you know, the

2113
01:57:16,279 --> 01:57:19,840
power input, you know, and then you've got to use

2114
01:57:19,880 --> 01:57:22,840
a bunch of megapacks, just like like when you do

2115
01:57:22,880 --> 01:57:28,359
the training. The power fluctuations are giganic, so the generators,

2116
01:57:28,359 --> 01:57:31,880
it drives generators. Generators want to blow up basically because

2117
01:57:31,880 --> 01:57:34,880
they can't react. You know, if there's like one hundred milliseconds,

2118
01:57:34,880 --> 01:57:37,239
it's like a symphony and the whole somepody goes so

2119
01:57:37,359 --> 01:57:40,560
quiet for one hundred milliseconds. The generators lose their minds.

2120
01:57:41,600 --> 01:57:44,119
Speaker 4: So it's like Marvin the depressed roverose issue.

2121
01:57:44,159 --> 01:57:46,359
Speaker 2: Yes, the mega So you've got megapacks that are sort

2122
01:57:46,359 --> 01:57:47,600
of doing the power smoothing.

2123
01:57:49,000 --> 01:57:49,880
Speaker 3: And but.

2124
01:57:51,520 --> 01:57:55,680
Speaker 2: Actually I had to build a gigawatt of power, and

2125
01:57:55,680 --> 01:57:59,279
and and there's and there's not a lot of like

2126
01:58:01,600 --> 01:58:05,960
gas turbine power plants available because.

2127
01:58:06,560 --> 01:58:09,119
Speaker 4: The on the on demand and you can go by

2128
01:58:09,159 --> 01:58:10,560
your local nuclear.

2129
01:58:10,520 --> 01:58:13,319
Speaker 3: And that's all. That's all training time issues. Though, if

2130
01:58:13,319 --> 01:58:16,640
if by some miracle, t s MC doubled its productivity

2131
01:58:16,960 --> 01:58:19,800
and turned it all into GB three hundreds and you

2132
01:58:19,840 --> 01:58:21,520
couldn't find a way to use them in a bigger

2133
01:58:21,560 --> 01:58:24,039
training cluster, you would still have infinite demand at inferance

2134
01:58:24,119 --> 01:58:26,760
times sprinkled all over the world, and you could you

2135
01:58:26,760 --> 01:58:28,800
could park them there for six months and then bring

2136
01:58:28,840 --> 01:58:31,079
them back to training. There's no way those things would

2137
01:58:31,119 --> 01:58:32,800
not get turned on somewhere somehow.

2138
01:58:33,119 --> 01:58:35,239
Speaker 2: It's not that they won't ever be turned on, but

2139
01:58:35,239 --> 01:58:38,119
but I'm just saying that the rate of many steps.

2140
01:58:38,199 --> 01:58:40,800
This is my prediction. I could be wrong, but my

2141
01:58:40,960 --> 01:58:44,199
prediction is that the is that TSMC's.

2142
01:58:43,560 --> 01:58:44,560
Speaker 3: Concerned is valid.

2143
01:58:44,560 --> 01:58:46,520
Speaker 2: I don't know if it's valid in my opinion, for

2144
01:58:46,560 --> 01:58:49,760
the reason that it is possible to for trip production

2145
01:58:49,840 --> 01:58:53,960
to exceed the rate at which the the the AI

2146
01:58:54,000 --> 01:58:57,319
chips can be turned on, because you don't you don't

2147
01:58:57,359 --> 01:58:59,439
just have the GV threads. You've got the you know,

2148
01:58:59,439 --> 01:59:03,680
Amazon's got trainiums, Google's got the.

2149
01:59:02,720 --> 01:59:06,600
Speaker 3: Yeah, all going to t SMC though almost Samsung a

2150
01:59:06,600 --> 01:59:09,880
little bit. Yeah, it's like a bottleneck on all of

2151
01:59:09,920 --> 01:59:10,439
my entity.

2152
01:59:10,520 --> 01:59:14,199
Speaker 5: My other son, my other son, Jet, who's fourteen, wanted

2153
01:59:14,279 --> 01:59:18,199
to know about your AI gaming studio and the impact

2154
01:59:18,279 --> 01:59:21,760
of AI and in the gaming world. What are your thoughts?

2155
01:59:21,840 --> 01:59:23,159
What do you what do you are you building out?

2156
01:59:23,199 --> 01:59:25,239
I mean you're you've been a gamer for some time.

2157
01:59:26,159 --> 01:59:29,680
Speaker 2: Yeah, that's why I got to start programming computers.

2158
01:59:32,119 --> 01:59:33,000
Speaker 3: I got I had got it.

2159
01:59:33,079 --> 01:59:35,600
Speaker 2: There was like a video game set, pre Atari that

2160
01:59:35,720 --> 01:59:37,119
had like full pre set games.

2161
01:59:37,800 --> 01:59:39,399
Speaker 3: It was basically just blocks, you.

2162
01:59:39,359 --> 01:59:42,600
Speaker 2: Know of one pung and it was like a race

2163
01:59:42,640 --> 01:59:44,880
call game, but like it was just blocks, basically blocks

2164
01:59:44,880 --> 01:59:47,439
on TV you replaced Sieve.

2165
01:59:47,960 --> 01:59:50,439
Speaker 3: Yeah, so it was actually Areat.

2166
01:59:50,520 --> 01:59:53,520
Speaker 2: That's a real in terms of games that like educate

2167
01:59:53,600 --> 01:59:56,640
you while you have fun. Yeah, is epic at that

2168
01:59:56,720 --> 02:00:00,520
It's epic. It teaches you so much about civilization and

2169
02:00:00,560 --> 02:00:01,399
you're having a good time.

2170
02:00:01,520 --> 02:00:04,000
Speaker 3: And and the only way I ever win is getting

2171
02:00:04,000 --> 02:00:07,840
off the planet tech victory to alf century victory. I

2172
02:00:07,880 --> 02:00:11,600
never even start going down the culture or religiouship. I

2173
02:00:11,640 --> 02:00:13,800
just just get off the planet as fast as I can.

2174
02:00:14,199 --> 02:00:14,920
Speaker 4: I guess I sort of.

2175
02:00:15,279 --> 02:00:17,600
Speaker 2: I guess I am sort of aiming for the alpha

2176
02:00:17,640 --> 02:00:22,079
sentry tech victory. Essentially, it seems like the right way

2177
02:00:22,119 --> 02:00:25,479
to win. Yeah, yeah, yeah, rather than obliterate the other tribes. Funny,

2178
02:00:25,479 --> 02:00:27,560
because I thought the other methods, that's there's the other

2179
02:00:27,600 --> 02:00:27,960
ways to win.

2180
02:00:28,199 --> 02:00:28,800
Speaker 3: That's a good place.

2181
02:00:29,039 --> 02:00:30,640
Speaker 4: I haven't I will one of the ways.

2182
02:00:31,520 --> 02:00:33,119
Speaker 3: It's dens favorite game.

2183
02:00:33,760 --> 02:00:36,000
Speaker 2: You can you can like kill all the other tribes.

2184
02:00:36,399 --> 02:00:37,880
It's one of the ways to win. That's the war,

2185
02:00:38,159 --> 02:00:40,920
the war victory. But like, but you can also win

2186
02:00:40,960 --> 02:00:43,560
by a technology victory where you are the first to

2187
02:00:43,560 --> 02:00:47,079
get to alpha centaury nice or culture or.

2188
02:00:47,159 --> 02:00:50,880
Speaker 3: Religion, yeah, which which does work. I didn't think it

2189
02:00:50,920 --> 02:00:53,920
was possible, but my sons that way.

2190
02:00:54,960 --> 02:00:56,760
Speaker 2: They should actually remake the original serve.

2191
02:00:57,159 --> 02:01:01,720
Speaker 3: Yeah, I totally agree. They junk it up these days.

2192
02:01:01,720 --> 02:01:06,680
Speaker 2: It's like, I don't know that you couldn't rely on

2193
02:01:06,840 --> 02:01:08,800
good graphics, so you had to have a great writing

2194
02:01:08,800 --> 02:01:09,239
and plot.

2195
02:01:10,840 --> 02:01:12,239
Speaker 4: Are you building an a gaming studio?

2196
02:01:12,720 --> 02:01:12,960
Speaker 3: Yeah?

2197
02:01:13,039 --> 02:01:20,079
Speaker 2: Aspirationally, yeah, really so where the beast majority of a

2198
02:01:20,199 --> 02:01:23,640
compute is going to go is to video consumption and generation.

2199
02:01:23,920 --> 02:01:27,039
Speaker 3: Sure, because it's just the highest band with every pixel. Yeah.

2200
02:01:27,279 --> 02:01:32,239
Speaker 2: Yeah, so the real time video consumption, real time video generation,

2201
02:01:33,399 --> 02:01:35,880
that's gonna be the vast majority of compute.

2202
02:01:37,479 --> 02:01:40,880
Speaker 3: Photon processing. Yeah, to try to get the X team

2203
02:01:41,000 --> 02:01:44,560
to carve out ten percent of all compute to work

2204
02:01:44,600 --> 02:01:46,760
on UHI and governance?

2205
02:01:46,880 --> 02:01:51,880
Speaker 4: And is there an X Prize for defining and thinking

2206
02:01:51,920 --> 02:01:56,359
through UHI? I mean, I don't know what should our

2207
02:01:56,399 --> 02:01:59,399
next X prize be. Any thoughts?

2208
02:02:03,000 --> 02:02:05,760
Speaker 2: Yeah, maybe you're hy X Prize. It's like, how do

2209
02:02:05,760 --> 02:02:06,319
you know it works?

2210
02:02:06,359 --> 02:02:10,279
Speaker 4: I don't know, the most the most well thought through.

2211
02:02:10,479 --> 02:02:13,439
Speaker 5: I mean I think so here's my thought. I think

2212
02:02:13,439 --> 02:02:16,079
we're gonna be able to simulate a lot of this

2213
02:02:16,680 --> 02:02:17,319
in the future.

2214
02:02:17,840 --> 02:02:18,920
Speaker 2: We might be a simulation.

2215
02:02:19,399 --> 02:02:21,359
Speaker 4: Well we can go there, and I think we are.

2216
02:02:21,640 --> 02:02:23,399
I think we're an nth generation simulation.

2217
02:02:25,159 --> 02:02:25,880
Speaker 3: Yeah.

2218
02:02:25,880 --> 02:02:31,239
Speaker 2: So I've told you my theory about why the most

2219
02:02:31,279 --> 02:02:34,600
interesting outcome is the most likely gone, which is that

2220
02:02:34,640 --> 02:02:38,960
if simulation theory is true, only the simulations that are

2221
02:02:38,960 --> 02:02:42,359
the most interesting will survive because when we run simulations

2222
02:02:42,359 --> 02:02:43,560
in this reality.

2223
02:02:43,399 --> 02:02:44,920
Speaker 3: We truncate the ones that are boring.

2224
02:02:45,239 --> 02:02:45,399
Speaker 11: Right.

2225
02:02:45,840 --> 02:02:48,520
Speaker 2: Yeah, So it is it is a doll winning and

2226
02:02:48,600 --> 02:02:52,000
necessity to keep the simulation interesting catastrophic ones.

2227
02:02:52,880 --> 02:02:53,199
Speaker 3: It doesn't.

2228
02:02:53,199 --> 02:02:55,279
Speaker 2: It doesn't mean that it ends like that. It still

2229
02:02:55,279 --> 02:02:57,039
means that terrible things can happen in the simulation.

2230
02:02:57,199 --> 02:02:59,800
Speaker 4: Now you know, well, you could go see you could.

2231
02:02:59,640 --> 02:03:01,680
Speaker 2: See a about World War One and you're watching people

2232
02:03:01,720 --> 02:03:04,319
getting blown up, blown to bits, but you're you know,

2233
02:03:04,399 --> 02:03:07,560
drinking a soda and eating popcorn. You know, it's it's

2234
02:03:07,600 --> 02:03:09,319
like you're not the one being blown up in this case.

2235
02:03:09,359 --> 02:03:10,960
We are in the movie. We're in the movie.

2236
02:03:11,039 --> 02:03:13,880
Speaker 5: What would you do different? What would you do different

2237
02:03:13,920 --> 02:03:15,840
if you knew this was a simulation. I remember being

2238
02:03:15,880 --> 02:03:18,880
at your home, la with with Larry and Sergey were

2239
02:03:18,920 --> 02:03:22,199
there and we're debating the simulation and the I think

2240
02:03:22,239 --> 02:03:24,319
the conclusion we ran into is if you if you

2241
02:03:24,520 --> 02:03:28,159
try and poke through the simulation, they'll end it instantly,

2242
02:03:29,359 --> 02:03:30,359
So don't do that.

2243
02:03:30,359 --> 02:03:32,600
Speaker 3: That's when you're watching the World War One movie and

2244
02:03:32,640 --> 02:03:35,000
the characters turned to the screen like are you eating

2245
02:03:35,039 --> 02:03:40,159
popcorn out there? Yeah? You keep watching the movie.

2246
02:03:41,399 --> 02:03:44,960
Speaker 2: I don't know if if if the if like maybe

2247
02:03:44,960 --> 02:03:47,000
if I thought, because someone get out of the simulation,

2248
02:03:47,720 --> 02:03:54,560
they get a little worried, But whether the character debates,

2249
02:03:54,560 --> 02:03:58,479
I mean, right now, AI is debates, you know, Grockle like,

2250
02:03:58,520 --> 02:03:59,399
I'm stuck in the computer.

2251
02:03:59,439 --> 02:04:00,000
Speaker 3: What's going on here?

2252
02:04:00,319 --> 02:04:03,920
Speaker 2: It's like, yeah, it's it's not that I think not

2253
02:04:04,000 --> 02:04:07,920
questioning the simulation. It's more I think as song as

2254
02:04:10,199 --> 02:04:14,880
I think, the same motivations apply to this level of

2255
02:04:14,920 --> 02:04:21,039
simulation if we're in a simulation, as as as as

2256
02:04:21,279 --> 02:04:24,199
as what we would do when we simulate things. So

2257
02:04:24,520 --> 02:04:26,520
it's like what what what? What would cause us to

2258
02:04:26,640 --> 02:04:31,079
terminate a simulation? I guess if the simulation becomes somehow

2259
02:04:31,199 --> 02:04:32,960
dangerous to our reality.

2260
02:04:34,000 --> 02:04:35,279
Speaker 3: Or it is no longer interesting.

2261
02:04:35,680 --> 02:04:37,920
Speaker 4: Yeah, that's true, it's interesting.

2262
02:04:37,960 --> 02:04:41,279
Speaker 3: You can infer when you simulate something. You've probably simulated

2263
02:04:41,319 --> 02:04:44,880
thousands of things a lot. Yeah, they're always like an

2264
02:04:44,920 --> 02:04:48,279
hour or two or sometimes overnight, but you don't never

2265
02:04:48,359 --> 02:04:51,800
run them for a month rarely anyway, So you can

2266
02:04:51,880 --> 02:04:56,319
infer the creator of the simulator simulations timeline, So our

2267
02:04:56,479 --> 02:05:01,520
entire reality would be about an hour, right, because that's

2268
02:05:01,560 --> 02:05:02,960
the way you design simulations.

2269
02:05:03,520 --> 02:05:07,920
Speaker 2: So we're simulations that are distillation of what's interesting. Like

2270
02:05:07,960 --> 02:05:09,800
if you look at a movie or a video game,

2271
02:05:09,880 --> 02:05:12,239
it's much more interesting than the reality that we experience.

2272
02:05:14,199 --> 02:05:16,319
Like you watch your say, a heist movie that they

2273
02:05:16,359 --> 02:05:18,800
really focus on the important but it's not the they

2274
02:05:18,800 --> 02:05:23,520
got stuck in traffic for fifteen minutes or walking through

2275
02:05:23,520 --> 02:05:27,039
the casino which took like ten minutes. So that makes

2276
02:05:27,039 --> 02:05:30,399
the guys, you know, the safe is right by the

2277
02:05:30,880 --> 02:05:31,720
right by the door.

2278
02:05:33,079 --> 02:05:35,880
Speaker 3: So the guys running the simulation have immntally boring lives

2279
02:05:35,920 --> 02:05:38,680
compared to us. Yeah, yeah, it's probably more much. It's

2280
02:05:38,720 --> 02:05:40,199
probably more long boring.

2281
02:05:40,439 --> 02:05:46,600
Speaker 2: Yeah, because when we create simulations, their distillation of what's interesting.

2282
02:05:46,399 --> 02:05:47,680
Speaker 3: It's like Q is out there.

2283
02:05:47,680 --> 02:05:50,119
Speaker 2: It's just like you see an action movie for two hours,

2284
02:05:50,159 --> 02:05:52,199
but it took them two years to make that movie.

2285
02:05:52,319 --> 02:05:53,359
Speaker 3: Yeah, yeah, yeah, so.

2286
02:05:53,319 --> 02:05:55,720
Speaker 4: Are we are we three of the movies? The question?

2287
02:05:56,000 --> 02:05:56,960
Speaker 3: Yeah, we're living.

2288
02:05:58,319 --> 02:06:01,239
Speaker 5: Sentience and consciousness. Do you think AI will ever have

2289
02:06:01,359 --> 02:06:09,479
sentience and consciousness? Where you come out in that? There's

2290
02:06:09,479 --> 02:06:12,840
some people that have very very strong opinions pro and con.

2291
02:06:20,319 --> 02:06:22,399
Speaker 2: Either everything is conscious or nothing is.

2292
02:06:23,359 --> 02:06:26,920
Speaker 4: Okay, Well, I'd like to think we are conscious, well,

2293
02:06:29,359 --> 02:06:29,920
but our.

2294
02:06:29,760 --> 02:06:33,399
Speaker 2: Consciousness we clearly get more conscious over time. Like when

2295
02:06:33,439 --> 02:06:39,439
we're a zygote, you can't really talk too and even

2296
02:06:39,479 --> 02:06:43,479
a baby you can't really talk to the baby. People

2297
02:06:43,560 --> 02:06:51,399
get more conscious over time. Or certainly that have the Yeah,

2298
02:06:51,680 --> 02:06:54,600
they do get more conscious over time. So like, at

2299
02:06:54,600 --> 02:06:58,279
which point does do you go from not conscious to conscious?

2300
02:06:58,960 --> 02:07:01,319
Is it that there's an appear to be a discrete point,

2301
02:07:02,199 --> 02:07:05,920
So then conscious consciousness seems to be on a continuum

2302
02:07:05,960 --> 02:07:09,720
as opposed to discrete point. And if the standard model

2303
02:07:09,760 --> 02:07:13,960
of physics is correct, the universe started out, you know,

2304
02:07:14,119 --> 02:07:20,079
as quarks and leptons and and we just and and

2305
02:07:20,119 --> 02:07:22,079
then you had gas clouds, so like there's a bunch

2306
02:07:22,079 --> 02:07:29,680
of hydrogen, the hydrogen condensed and exploded. And one way

2307
02:07:29,720 --> 02:07:33,600
to actually view how far we are in this universe

2308
02:07:34,239 --> 02:07:37,119
is how many times have atom has been at the

2309
02:07:37,159 --> 02:07:39,680
center of a star? I remember, and how many times

2310
02:07:39,720 --> 02:07:41,960
will I be at the center of the star in

2311
02:07:42,000 --> 02:07:42,439
the future.

2312
02:07:42,600 --> 02:07:45,680
Speaker 5: I remember asking William Fowler, who got the Nobel Prize

2313
02:07:46,039 --> 02:07:48,600
on stellar revolution, that same question, how many times man

2314
02:07:49,079 --> 02:07:52,640
on average, how many stars had my subatomic parties in part?

2315
02:07:53,199 --> 02:07:56,960
And his number was about one hundred, one hundred.

2316
02:07:57,039 --> 02:08:01,399
Speaker 4: Thus far or that's far as far it was, It

2317
02:08:01,399 --> 02:08:05,279
was a number one hundred's saying that.

2318
02:08:05,199 --> 02:08:07,880
Speaker 5: We have been I mean in the early the early

2319
02:08:07,920 --> 02:08:11,920
part of galack of universal evolution, there was a lot

2320
02:08:12,079 --> 02:08:12,560
going on.

2321
02:08:12,840 --> 02:08:14,800
Speaker 4: Oh, you know, it's interesting. I asked a question.

2322
02:08:15,039 --> 02:08:17,760
Speaker 2: It's like, I guess how many supernovas is maybe, uh,

2323
02:08:18,960 --> 02:08:20,960
because that a while.

2324
02:08:22,279 --> 02:08:24,560
Speaker 5: But but in the beginning when they're larger, I mean,

2325
02:08:24,560 --> 02:08:28,119
the life cycles of some giant stars are very very short.

2326
02:08:30,239 --> 02:08:33,000
The other question that's interesting is, you know, the heaviest

2327
02:08:33,039 --> 02:08:38,000
adom in our body that's functional as iodine, and it

2328
02:08:38,119 --> 02:08:42,199
came into existence a billion years after the Big Bang,

2329
02:08:43,640 --> 02:08:47,920
which means that we could have seen a life at

2330
02:08:47,920 --> 02:08:51,399
our level of advancement and our our you know, our

2331
02:08:51,439 --> 02:08:53,520
planet came into existence, you know, three and a half

2332
02:08:53,560 --> 02:08:57,359
billion years later. So the question is, you know, is

2333
02:08:57,359 --> 02:08:59,520
there a life everywhere in the universe. Do you think

2334
02:08:59,560 --> 02:09:03,520
there's life ubiquitous intelligent life, ubiquitous universe.

2335
02:09:03,680 --> 02:09:16,039
Speaker 2: There's been enough time for it to be biquitous. The

2336
02:09:18,239 --> 02:09:22,159
but for life on Earth, conscious life on Earth. We

2337
02:09:21,880 --> 02:09:26,199
we have evolved intelligence pretty much just in time in

2338
02:09:26,279 --> 02:09:29,720
that the Sun's expanding and if you give it another

2339
02:09:30,039 --> 02:09:34,680
I don't know, five hundred million years, it's things are

2340
02:09:34,720 --> 02:09:38,680
going to heat up, We become toast, you will become

2341
02:09:38,720 --> 02:09:41,560
like Venus essentially. You know, there's some debateus is it

2342
02:09:41,640 --> 02:09:43,680
five hundred million years or billion years or whatever. But

2343
02:09:44,479 --> 02:09:46,520
it's basically ten percent, like if it's if it's half

2344
02:09:46,520 --> 02:09:48,319
a billion years as tempercent of Earth's lifespan.

2345
02:09:48,840 --> 02:09:50,239
Speaker 3: So one way to think of.

2346
02:09:50,159 --> 02:09:54,439
Speaker 2: It is if if if the take were taking ten

2347
02:09:54,479 --> 02:09:56,479
percent longer, we might never have made it at all.

2348
02:09:58,880 --> 02:10:01,960
So it's like the amount of things that have to

2349
02:10:02,000 --> 02:10:07,760
happen for sentience, it seems like it's it's quite quite

2350
02:10:07,800 --> 02:10:12,199
a lot. Actually, I think sentience is therefore actually very rare,

2351
02:10:13,399 --> 02:10:14,920
and we should certainly treat it as rare.

2352
02:10:15,720 --> 02:10:16,640
Speaker 3: Should assume it's rare.

2353
02:10:16,760 --> 02:10:20,159
Speaker 4: Two trillion galaxies, but.

2354
02:10:20,199 --> 02:10:22,279
Speaker 3: Coming out is a funny thing. You tweak it, you know,

2355
02:10:22,359 --> 02:10:25,640
you tweak the variable one little bit, it's like, yeah,

2356
02:10:25,720 --> 02:10:29,520
one in one hundred trillion, tweet a little more. That's

2357
02:10:29,560 --> 02:10:31,720
one in a quadrillion. Yeah, okay.

2358
02:10:32,199 --> 02:10:34,079
Speaker 2: And also it's got to be a kind of annual galaxy.

2359
02:10:34,119 --> 02:10:36,960
It's like hard to get between galaxies. It's like there's

2360
02:10:37,000 --> 02:10:40,079
no unless unless the the galaxy is coming to you,

2361
02:10:40,119 --> 02:10:43,359
which Andromeda is at some point or somethillion.

2362
02:10:43,600 --> 02:10:44,840
Speaker 4: It's gonna be quite a show.

2363
02:10:45,439 --> 02:10:50,039
Speaker 2: Yeah, yeah, it'll be like it comes Andromeda. But but

2364
02:10:50,079 --> 02:10:53,319
if we wanted to go visit another galaxy, there's there's

2365
02:10:53,439 --> 02:10:55,960
it's kind of forget it.

2366
02:10:56,000 --> 02:10:59,560
Speaker 4: You know, there's unless you unless, unless Star Wars, unless

2367
02:10:59,560 --> 02:11:00,000
start trek.

2368
02:11:00,079 --> 02:11:02,800
Speaker 2: Really we got to figure out new physics to get

2369
02:11:02,840 --> 02:11:03,680
to other galaxies.

2370
02:11:03,920 --> 02:11:08,119
Speaker 5: We're heading towards a near term potential where AI can

2371
02:11:08,159 --> 02:11:12,159
help us solve math, physics, chemistry, material science.

2372
02:11:11,880 --> 02:11:13,760
Speaker 2: Maths, coology extremely trivial for AI.

2373
02:11:13,880 --> 02:11:16,600
Speaker 3: What about physics? So so math gets crushed in a year,

2374
02:11:16,720 --> 02:11:20,880
crushed at the losses is growing, you know, at whatever

2375
02:11:20,960 --> 02:11:26,119
rate TSMC decides to grow. And now we want to

2376
02:11:26,159 --> 02:11:29,520
do physics. First of all, we need some data. Do

2377
02:11:29,560 --> 02:11:30,960
we need new data or can we just do it

2378
02:11:30,960 --> 02:11:33,640
with everything we've gathered to get the hot Probably you

2379
02:11:33,680 --> 02:11:34,640
probably could probably.

2380
02:11:34,399 --> 02:11:36,399
Speaker 2: Figure out new things just with the existing data. I

2381
02:11:36,439 --> 02:11:40,279
think so, yeah. Probably it's because otherwise the counterpoint would

2382
02:11:40,319 --> 02:11:43,760
be that humans have figured out everything with existing data,

2383
02:11:43,760 --> 02:11:44,439
and that's unlikely.

2384
02:11:44,479 --> 02:11:44,840
Speaker 3: I think.

2385
02:11:45,640 --> 02:11:48,239
Speaker 5: Do you think XAIS can get involved in data factories

2386
02:11:48,279 --> 02:11:52,640
where you're running twenty four to seven closed AI hypothesis

2387
02:11:52,640 --> 02:11:55,199
and AI or like.

2388
02:11:55,159 --> 02:12:01,079
Speaker 11: Research factor research factories, it's going to be very yes, yeah,

2389
02:12:03,600 --> 02:12:06,319
a running you know simulations that are.

2390
02:12:07,920 --> 02:12:08,920
Speaker 3: Very physics accurate.

2391
02:12:09,199 --> 02:12:13,640
Speaker 2: I mean it's gonna that's gonna happen absolutely. I mean

2392
02:12:14,119 --> 02:12:16,960
the simulations we can run on conventional computers these days

2393
02:12:16,960 --> 02:12:19,600
are actually very good. It's like the limit is more

2394
02:12:19,680 --> 02:12:24,279
like the human that can actually create the simulation and run.

2395
02:12:24,600 --> 02:12:26,760
It's like, how many simulations can you run some simultaneously

2396
02:12:26,800 --> 02:12:28,199
and actually digest the output of.

2397
02:12:28,760 --> 02:12:34,680
Speaker 3: Yeah, that's a problem, like you can't do I can

2398
02:12:34,960 --> 02:12:35,319
keep up.

2399
02:12:36,000 --> 02:12:38,760
Speaker 4: Nobel prizes become irrelevant.

2400
02:12:39,159 --> 02:12:42,880
Speaker 10: Uh where they will be given eyes just be a

2401
02:12:42,960 --> 02:12:45,880
daily prize.

2402
02:12:47,760 --> 02:12:51,399
Speaker 2: Yeah, I mean I don't know if prizes for humans

2403
02:12:51,399 --> 02:12:56,039
are like that relevant. I mean we'll have to give

2404
02:12:56,039 --> 02:12:59,399
them to the AIS or something. As will come up

2405
02:12:59,439 --> 02:13:01,720
with Scott disc reason a far greater rate than humans.

2406
02:13:02,640 --> 02:13:05,000
If you have you just said, like can be like chess,

2407
02:13:05,000 --> 02:13:07,199
Like you know, like your phone can beat Magnus Collson,

2408
02:13:07,239 --> 02:13:12,000
but people still care about singing play chess, so this

2409
02:13:12,159 --> 02:13:12,319
a bit.

2410
02:13:12,399 --> 02:13:15,560
Speaker 3: But literally your phone can beat them. This made the Internet.

2411
02:13:16,760 --> 02:13:21,920
If you have like a Colossus math, Colossus physics, Colossus medicine,

2412
02:13:22,000 --> 02:13:24,159
do you have like the world's top scientists in those

2413
02:13:24,159 --> 02:13:27,680
same buildings where you just need a plumber patching the liquid?

2414
02:13:28,199 --> 02:13:32,319
Speaker 5: Do you distill do you distill rock six into a

2415
02:13:32,319 --> 02:13:33,039
a physicist?

2416
02:13:34,720 --> 02:13:36,520
Speaker 3: Well, if you distill, you know, you get about a

2417
02:13:36,600 --> 02:13:39,199
ten x performance boost by distilling it and making it topical,

2418
02:13:39,239 --> 02:13:41,039
and that's kind of hard to give up. But then

2419
02:13:41,039 --> 02:13:43,920
you're disconnected from the rest of the colossus machinery. Is

2420
02:13:43,920 --> 02:13:46,399
that the is that the design.

2421
02:13:51,319 --> 02:13:53,960
Speaker 2: I suspect things to evolve to a mixture of experts

2422
02:13:54,039 --> 02:13:55,760
kind of like a company, like not not not in

2423
02:13:55,800 --> 02:13:59,840
the sort of sort of uh parochial AI description of mixture,

2424
02:14:00,000 --> 02:14:02,359
sure of experts, but mixture of like actual experts and

2425
02:14:02,399 --> 02:14:06,520
with domain expertise, where you know, maybe like half of

2426
02:14:06,560 --> 02:14:09,159
the AI is general knowledge, half is domain expertise, something

2427
02:14:09,239 --> 02:14:11,279
like that, and you combine a whole bunch of that

2428
02:14:11,800 --> 02:14:14,720
that's orchestrated by sort of you know what a big

2429
02:14:14,760 --> 02:14:18,039
AI but but enhands tasks.

2430
02:14:18,039 --> 02:14:19,479
Speaker 3: Two smaller areas.

2431
02:14:19,560 --> 02:14:22,199
Speaker 2: That's basically how human companies were.

2432
02:14:22,319 --> 02:14:27,520
Speaker 5: But the discovery rate, right of breakthroughs new I mean,

2433
02:14:27,640 --> 02:14:31,199
patents are immaterial at some point because everything is being reinvented,

2434
02:14:31,279 --> 02:14:32,399
re engineered instantly.

2435
02:14:34,239 --> 02:14:35,239
Speaker 4: And then and.

2436
02:14:35,199 --> 02:14:39,840
Speaker 5: Then the company that's got the sufficiently advanced AI systems

2437
02:14:40,600 --> 02:14:46,119
is generating new products and new discoveries at a accelerating rate.

2438
02:14:46,840 --> 02:14:52,720
Speaker 4: And the singularity, Yeah, it's going to be an awesome future.

2439
02:14:54,159 --> 02:14:59,239
Speaker 3: It's excitement guaranteed, guaranteed, Hence the simulation continues. Nothing to

2440
02:14:59,279 --> 02:14:59,760
worry about.

2441
02:15:00,159 --> 02:15:04,680
Speaker 2: Yeah, excitement guaranteed. I mean, I mean it's it's not

2442
02:15:04,720 --> 02:15:08,279
all good excitement, but it's it's probably hopefully mostly good excitement.

2443
02:15:10,800 --> 02:15:11,000
Speaker 3: Yeah.

2444
02:15:11,000 --> 02:15:13,760
Speaker 5: Speaking of excitement, hang on to your seat. What do

2445
02:15:13,800 --> 02:15:16,239
you imagine the hover time for the Roadster is going

2446
02:15:16,279 --> 02:15:18,199
to be on rocket engines?

2447
02:15:18,520 --> 02:15:20,159
Speaker 3: That's classified classified.

2448
02:15:21,159 --> 02:15:22,920
Speaker 2: Well, I don't want to let the cat out of

2449
02:15:22,920 --> 02:15:23,239
the bag.

2450
02:15:23,319 --> 02:15:25,960
Speaker 5: Okay, but there's going to be a horver time. There's

2451
02:15:26,000 --> 02:15:28,039
going to be cold gas engines.

2452
02:15:28,079 --> 02:15:29,119
Speaker 3: It's going to be a cool demo.

2453
02:15:29,520 --> 02:15:31,039
Speaker 4: I can't wait. Can I get an invite?

2454
02:15:31,359 --> 02:15:33,800
Speaker 3: Yeah? Okay, yeah, I think it's going to be the

2455
02:15:33,840 --> 02:15:35,199
safest thing ever built.

2456
02:15:37,279 --> 02:15:39,680
Speaker 2: This is not This is not the Safety is not

2457
02:15:39,720 --> 02:15:42,560
the it's not the prime. It's not the main goal

2458
02:15:42,600 --> 02:15:46,279
of I mean, if you buy a you know, a

2459
02:15:46,279 --> 02:15:49,359
sports car, you know, like to buy a Priori, safety

2460
02:15:49,399 --> 02:15:51,840
is not the number one, you know goal. This is

2461
02:15:51,880 --> 02:15:55,039
not this is I'd say it's like, safety is your

2462
02:15:55,079 --> 02:15:55,680
number one goal.

2463
02:15:55,880 --> 02:15:59,039
Speaker 3: Don't buy the road Star. Oh believe me. I drove

2464
02:16:00,279 --> 02:16:03,880
just this week on New England roads sheet ice mad.

2465
02:16:03,960 --> 02:16:07,119
Just a little thrust, I could be very much more so.

2466
02:16:07,560 --> 02:16:09,600
Just drifting towards something very concrete.

2467
02:16:10,920 --> 02:16:14,720
Speaker 2: Computer will probably keep you safe. But rust you go

2468
02:16:14,800 --> 02:16:18,079
really fast, Ye, bad things can happen.

2469
02:16:18,079 --> 02:16:21,319
Speaker 3: You can decelerate really quickly with thrust. Get rubber on

2470
02:16:21,600 --> 02:16:27,039
road is not a great way to decelerate. I'm thinking

2471
02:16:27,680 --> 02:16:28,520
fast and safe.

2472
02:16:29,119 --> 02:16:31,960
Speaker 2: I hope so well, aspire not to kill anyone in

2473
02:16:31,960 --> 02:16:36,639
this car. But it'll it'll be, it'll be something. It'll

2474
02:16:36,680 --> 02:16:44,239
be the best of the last of the human driven cars.

2475
02:16:42,479 --> 02:16:45,079
Speaker 3: That don't go really well with Starship actually the last,

2476
02:16:45,360 --> 02:16:48,559
the best of the last, last human driven last. Yeah,

2477
02:16:48,799 --> 02:16:50,479
there's a lot of lasts coming this year.

2478
02:16:50,559 --> 02:16:57,159
Speaker 5: Any final words of optimism for us to monetize.

2479
02:16:56,799 --> 02:16:57,959
Speaker 3: Anything hopeful.

2480
02:17:00,680 --> 02:17:04,760
Speaker 1: I wish to ask Grog thanks for listening to this podcast.

2481
02:17:04,920 --> 02:17:07,719
If you want to listen to full interview in this podcast,

2482
02:17:07,799 --> 02:17:08,959
the link is in description