Latest / Elon Musk Thinking / Latest; Elon Musk, Peter Diamandis, Dennis Blundis Talking About Job Markets, Clean Energy, Humanoid Robot!!!

Transcript

Latest; Elon Musk, Peter Diamandis, Dennis Blundis Talking About Job Markets, Clean Energy, Humanoid Robot!!! · Elon Musk Thinking

• 0:00
  Speaker 1: Latest interview of Elon Musk.
• 0:05
  Speaker 2: Very soon though, Yeah, I think probably at this point Grock.
• 0:10
  Speaker 2: If you if you took a photo and submitted to Grock,
• 0:13
  Speaker 2: you can probably tell you if the circus is somewhere
• 0:16
  Speaker 2: wrong with it.
• 0:17
  Speaker 3: Yeah, yeah, all right, I'm gonna give it a shot.
• 0:19
  Speaker 3: You're using the same Grock that I'm using, are you
• 0:22
  Speaker 3: or you are? Rock keeps updating, so four point two
• 0:27
  Speaker 3: but five is soon, right?
• 0:29
  Speaker 2: Five is Q one? Yeah, four point two has not
• 0:33
  Speaker 2: been released yet externally. But yeah, I mean, if you
• 0:39
  Speaker 2: just if you just upload an image into rock, it's
• 0:44
  Speaker 2: it's just quite a good job of analyzing any given image.
• 0:50
  Speaker 3: Absolutely. Let's let's start. Well, we're going to talk about this,
• 0:54
  Speaker 3: all right, we'll come back.
• 0:55
  Speaker 2: I mean, let's see if I if I take an
• 0:56
  Speaker 2: if I take a picture of you, what is it.
• 0:58
  Speaker 4: Let's see what I was going to say about me.
• 1:00
  Speaker 3: Yeah, it's gonna say you're a flawed circuit.
• 1:02
  Speaker 2: I also remember to update it because like we update
• 1:04
  Speaker 2: the grock app so frequently.
• 1:06
  Speaker 5: You know, I asked, I asked Rock to roast me.
• 1:09
  Speaker 5: It did an amazing job. Then I asked GROC to
• 1:11
  Speaker 5: roast you, and I spit out my coffee.
• 1:14
  Speaker 4: It was. It was hilarious, and then I asked it
• 1:17
  Speaker 4: you know, it just.
• 1:18
  Speaker 3: Keeps telling it to be more and more. I asked,
• 1:22
  Speaker 3: until until it's like the father of is that Rudy
• 1:26
  Speaker 3: still out there? Did that get repealed?
• 1:28
  Speaker 5: And I asked, does elond know what you say about him?
• 1:31
  Speaker 5: And and she goes, it's a sheet for me. She goes,
• 1:34
  Speaker 5: what is he gonna do about it?
• 1:39
  Speaker 3: Yeah, let's see. So I just literally took a photo
• 1:43
  Speaker 3: of you, and.
• 1:45
  Speaker 4: Did you ask a question?
• 1:47
  Speaker 3: No? Nothing, I doesn't say anything.
• 1:49
  Speaker 4: This man is hugely.
• 1:52
  Speaker 3: This is period amandas.
• 1:54
  Speaker 4: Yes, okay, that's pretty good.
• 1:56
  Speaker 3: Yeah, context whatsoever?
• 1:58
  Speaker 4: The host of the podcast in shots. Yeah, sometimes that's
• 2:02
  Speaker 4: your first credential. Now forget about everything.
• 2:07
  Speaker 3: No context. Image.
• 2:09
  Speaker 5: By the way, Wikipedia is awesome, I mean just phenomenal.
• 2:14
  Speaker 5: I mean just it's like I tried to like update
• 2:16
  Speaker 5: my Wikipedia page for like years impossibly, and yeah, it
• 2:22
  Speaker 5: knows me amazing.
• 2:25
  Speaker 4: Yeah, he's wearing.
• 2:26
  Speaker 5: A black quilted jacket featuring a sun Dance logo. Not
• 2:31
  Speaker 5: quite true, it's my abundant logo, I think so anyway.
• 2:41
  Speaker 3: Yeah, but it basically it's pretty damn good.
• 2:45
  Speaker 2: Yeah, he's smiling and relaxed with the laptop in front
• 2:48
  Speaker 2: of him.
• 2:49
  Speaker 4: That's true.
• 2:50
  Speaker 3: That's true. Yeah, well quite a circuit though. I got
• 3:00
  Speaker 3: to test it on this only it has to be
• 3:05
  Speaker 3: read by you, though, I mean, I want to read
• 3:07
  Speaker 3: the whole thing, but.
• 3:09
  Speaker 4: Give me a taste. I can take it.
• 3:11
  Speaker 2: Okay, check out that grin dude smiling like you just
• 3:14
  Speaker 2: discovered a new way to monetize hope.
• 3:19
  Speaker 3: Monetizing. Though.
• 3:22
  Speaker 5: Yes, I want to try and answer the question can
• 3:24
  Speaker 5: AI and tech help save American the world?
• 3:28
  Speaker 4: Right?
• 3:29
  Speaker 5: I want to give people listening a dose of optimism
• 3:32
  Speaker 5: because it's survey done in mid December by Pew that
• 3:35
  Speaker 5: said forty five percent of Americans would rather live in
• 3:38
  Speaker 5: the past and only fourteen percent said they'd rather live
• 3:42
  Speaker 5: in the future, which is insane to me, right, Obviously
• 3:46
  Speaker 5: they never read history. The challenges most Americans all they
• 3:49
  Speaker 5: have of the future. It's like Hollywood has shown us
• 3:52
  Speaker 5: killer ais and rogue robots, right, and people are worried
• 3:56
  Speaker 5: about their jobs, They're worried about healthcare, they're worried about
• 4:00
  Speaker 5: you know, the cost of living. The challenge is how
• 4:02
  Speaker 5: do we how do we help people? I mean, you
• 4:04
  Speaker 5: posted you pinned on X the future is going to
• 4:07
  Speaker 5: be amazing with AI and robots enabling sustainable abundance.
• 4:11
  Speaker 3: Thank you. I appreciate that.
• 4:13
  Speaker 4: And and uh well, I.
• 4:15
  Speaker 2: Mean because like what would Peter do you want to say?
• 4:19
  Speaker 3: Channeling?
• 4:20
  Speaker 4: Thank you? I couldn't agree more agree more.
• 4:25
  Speaker 3: So.
• 4:26
  Speaker 5: So my question is from a you know, from a
• 4:28
  Speaker 5: first principal standpoint. Yeah, the rationale for optimism. You know,
• 4:34
  Speaker 5: how do we how do we head towards star Trek
• 4:36
  Speaker 5: and not Terminator?
• 4:38
  Speaker 3: Right?
• 4:38
  Speaker 4: How do we how do we head towards.
• 4:39
  Speaker 3: Run Berry Cameron?
• 4:41
  Speaker 4: Yeah, Jim.
• 4:46
  Speaker 3: Diverging path, Yes, it is, it is.
• 4:51
  Speaker 4: Avatar has some hopeful parts.
• 4:52
  Speaker 5: But anyway, how do we go towards universal high income
• 4:56
  Speaker 5: instead of social unrest?
• 4:58
  Speaker 4: So both.
• 5:07
  Speaker 2: Have universalhigh income and social unrest. That's my prediction that.
• 5:11
  Speaker 4: Will make for a lot of problems.
• 5:13
  Speaker 3: Is that your actual prediction? Yeah? Yeah, it seems likely.
• 5:18
  Speaker 3: Tell me how to push back on it exactly, But
• 5:21
  Speaker 3: it's not like that's the trend. Yeah, yeah, totally. No,
• 5:23
  Speaker 3: we have Well, because there's going to be so much.
• 5:25
  Speaker 4: Change, people are going to be like, it's scared shitless.
• 5:28
  Speaker 2: Yeah, it's it's sort of the you know, it's like,
• 5:35
  Speaker 2: be careful what you wish for because you might get it.
• 5:37
  Speaker 4: Yeah.
• 5:37
  Speaker 2: Now if you if you actually get all the stuff
• 5:42
  Speaker 2: you want, is that actually the future you want? Yeah,
• 5:47
  Speaker 2: because it means that your job won't be won't matter.
• 5:49
  Speaker 5: If you're living an unchallenged life, yes, right, with no challenges.
• 5:54
  Speaker 3: Yeah.
• 5:55
  Speaker 5: No, you know you know, if you become a couch potato,
• 5:57
  Speaker 5: if it's the wily future, it does not go well
• 6:00
  Speaker 5: for humans.
• 6:00
  Speaker 3: Well, and we're used to being told here's your challenge,
• 6:04
  Speaker 3: So people haven't historically been very good at creating their
• 6:07
  Speaker 3: own challenge in the absence.
• 6:09
  Speaker 5: Of Elon does a damn good job every time, every
• 6:12
  Speaker 5: time one company takes off, you start.
• 6:14
  Speaker 4: Your next' that's rare punishment. I think you are. Yeah,
• 6:17
  Speaker 4: I think you ever. Thank God for that.
• 6:20
  Speaker 3: Why why do I do this to myself? Actually? After
• 6:24
  Speaker 3: AI and robots, is there another thing after that?
• 6:26
  Speaker 4: I guess there's well, there's conquering you know, the universe.
• 6:31
  Speaker 4: There is that rocks really well, and energy rocks at
• 6:35
  Speaker 4: your friends, so good to need.
• 6:37
  Speaker 3: To get there?
• 6:38
  Speaker 4: Why why are you so optimistic? Are you? Are you optimistic?
• 6:42
  Speaker 4: Let's start there.
• 6:43
  Speaker 2: I'm not as optimistic as you are, okay, but but
• 6:47
  Speaker 2: why are you more optimistic than most people.
• 6:49
  Speaker 3: Okay, and is the trend upward compared to a year
• 6:55
  Speaker 3: ago two years ago?
• 6:56
  Speaker 2: Well, I think if you reframe things in terms of
• 7:01
  Speaker 2: progress bar like in speaking of challenges, progress towards a
• 7:07
  Speaker 2: kardifship to scale civilization.
• 7:11
  Speaker 3: Well, let's say let's say the aspiration.
• 7:14
  Speaker 4: Capturing all the energy from the Sun's output, Well.
• 7:16
  Speaker 2: Let's even have a humbler humbler aspiration than that. If
• 7:21
  Speaker 2: we say that our goal is to even get a
• 7:24
  Speaker 2: millionth of the Sun's energy, that would be more than
• 7:28
  Speaker 2: a thousand times as much energy as could possibly be
• 7:31
  Speaker 2: produced on Earth. So about half a billionth of the
• 7:35
  Speaker 2: Sun's energy reaches Earth, So you'd have to go up
• 7:40
  Speaker 2: three ords of magnitude from that just to get to
• 7:43
  Speaker 2: a million. So we're very, very very far from even
• 7:52
  Speaker 2: having a billionth of the Sun's energy harness in any way.
• 7:58
  Speaker 2: So a reasonable goal would be try to get to
• 8:01
  Speaker 2: a million. And if you try to get to a
• 8:03
  Speaker 2: millionth or a thousandth er point one percent, uh, that's
• 8:12
  Speaker 2: that's such an enormous Uh. Look, there's not sure what
• 8:15
  Speaker 2: metaphor weduce here, but because the hill decline is is
• 8:18
  Speaker 2: not a appropriate It's like not a big enough medical
• 8:21
  Speaker 2: for gravity well to gravity well exactly, so if you
• 8:29
  Speaker 2: try to get to a million to the Sun's energy
• 8:32
  Speaker 2: or a thousand of the Sun's energy, like now, these
• 8:36
  Speaker 2: are very very.
• 8:38
  Speaker 4: Difficult tasks, and energy is the inner loop for everything
• 8:40
  Speaker 4: right now.
• 8:42
  Speaker 2: Yeah, I think, like I think the future currency will
• 8:46
  Speaker 2: essentially just be wattag.
• 8:48
  Speaker 5: Now I was thinking, is it is It is the
• 8:50
  Speaker 5: ability of a person to control energy and compute or
• 8:55
  Speaker 5: just energy, I mean the two too translator just.
• 8:59
  Speaker 2: Like honest energy, yeah, like so or like basically how
• 9:03
  Speaker 2: much power is being turned into work of some kind,
• 9:06
  Speaker 2: right intelligence or matt and manipulation.
• 9:15
  Speaker 4: So that's your next big project is going to be energy.
• 9:19
  Speaker 4: It's it's going to be You're gonna go back to.
• 9:21
  Speaker 2: Expand from there and say, okay, what about even getting
• 9:25
  Speaker 2: somewhere on a Cotter show of three scale meaning galaxy level.
• 9:29
  Speaker 4: Now we're talking now we're back to star trek.
• 9:32
  Speaker 2: Yeah, expand to horizons here. Yes, well there isn't even
• 9:36
  Speaker 2: a rizon because you're on a planet.
• 9:39
  Speaker 3: So we talked about so think galaxy mind.
• 9:42
  Speaker 5: Yeah, well listen, we're in eleven eleven point five million
• 9:46
  Speaker 5: square foot three pentagons right here, in this building.
• 9:49
  Speaker 4: Yeah, you think in a reasonably large scale, what is magnitude?
• 9:53
  Speaker 2: Yeah, so, I mean so from a challenge standpoint, I
• 9:57
  Speaker 2: guess the the civilizational challenge will be how do you
• 10:03
  Speaker 2: climb the order's magnitude and energy harnessed.
• 10:06
  Speaker 5: But we're going back to why you optimistic right now.
• 10:09
  Speaker 5: I mean when people think about the challenges ahead, I
• 10:14
  Speaker 5: think we're going to end up with abundance in the
• 10:17
  Speaker 5: long run.
• 10:18
  Speaker 2: It's beyond abundance in any beyond what people possibly could
• 10:22
  Speaker 2: think of as abundance. But like the AI, actually AI
• 10:27
  Speaker 2: and robots in the limit, well, we'll saturate or human
• 10:32
  Speaker 2: desire and.
• 10:34
  Speaker 5: We get to nanotechnology, which takes it even a step further.
• 10:39
  Speaker 2: The thing about the net, well, I'm not sure what
• 10:40
  Speaker 2: you mean by means like.
• 10:41
  Speaker 4: The atomic reassembly.
• 10:44
  Speaker 3: Yeah, hell yeah, yeah, sure sure.
• 10:46
  Speaker 2: I mean we're already doing atomic level assembly on the
• 10:49
  Speaker 2: four circuits.
• 10:49
  Speaker 4: You know, amazing two three nanometers.
• 10:53
  Speaker 2: Yeah, it's only depending on how they're arrayed. Four or
• 10:58
  Speaker 2: five silicon atoms pernanometers.
• 11:00
  Speaker 3: Yeah, so those are big atoms.
• 11:03
  Speaker 2: They're not big, I mean, but but I'm saying you
• 11:06
  Speaker 2: could they should actually describe the circuits in terms of
• 11:09
  Speaker 2: an integer number of atoms in a specific place.
• 11:11
  Speaker 3: It's a LANs terms now you can, you can.
• 11:15
  Speaker 2: It's just it's like it's it's like the we'll call
• 11:18
  Speaker 2: this the the seven atom or whatever, like you said,
• 11:22
  Speaker 2: two animeters, Like it's like no one knows nine silicen
• 11:26
  Speaker 2: atoms something like that.
• 11:28
  Speaker 3: They've got silicon and copper and you know.
• 11:31
  Speaker 2: So, but a bunch of these things are just marketing numbers,
• 11:33
  Speaker 2: like the two nanometers just the marketing number. But but
• 11:38
  Speaker 2: you still need essentially close to atomic level precision, like
• 11:42
  Speaker 2: the atoms really need to be in the right spot.
• 11:46
  Speaker 2: So I think they're getting clean rooms wrong. By the way,
• 11:51
  Speaker 2: in these modern fats, I'm gonna I'm gonna make a
• 11:56
  Speaker 2: bed here, okay, Okay, that's tesla will have a two
• 12:02
  Speaker 2: naimeter fab and I can I can eat a cheeseburger
• 12:06
  Speaker 2: and smoke a cigar in the fat.
• 12:09
  Speaker 4: Yeah, they're handling will be that good.
• 12:12
  Speaker 3: Okay, do you have this sketched out in your mind?
• 12:15
  Speaker 3: Like how is it? How are the atoms being placed
• 12:16
  Speaker 3: that they're immune to cheeseburger grease. They're just maintained wave
• 12:21
  Speaker 3: for isolation the entire time, which is actually the default
• 12:25
  Speaker 3: four four fabs.
• 12:26
  Speaker 2: The wafers are transported in boxes of pure nitrogen gas
• 12:32
  Speaker 2: under a slip positive.
• 12:33
  Speaker 3: So where the bananas at Walmart?
• 12:36
  Speaker 2: Just so you know, yeah, well that's that's It's essentially
• 12:40
  Speaker 2: like it's pretty hard for anything that's combusting to live
• 12:44
  Speaker 2: without oxygen.
• 12:45
  Speaker 4: Ye.
• 12:45
  Speaker 2: So let's talk about so you like, like you can
• 12:48
  Speaker 2: kill the bugs just by putting a nitrogen blanket.
• 12:51
  Speaker 3: Interesting.
• 12:52
  Speaker 5: Interesting, I we talk about energy health education because those
• 12:56
  Speaker 5: are people's you know, concerns. So on the energy front,
• 13:00
  Speaker 5: the innermost loop of everything that you're building and doing right.
• 13:04
  Speaker 3: Now, energy is the foundation.
• 13:06
  Speaker 5: What's your vision for energy abundance? The Sun in the
• 13:10
  Speaker 5: next this decade?
• 13:12
  Speaker 4: The Sun?
• 13:13
  Speaker 2: Yeah, I mean, so the Sun is everything.
• 13:15
  Speaker 4: It's everything. So you're all in unsolared. Yeah, I mean
• 13:20
  Speaker 4: your natural and solar you're at colossus to right.
• 13:24
  Speaker 3: Yeah.
• 13:26
  Speaker 2: People just don't understand how that solar is everything. So
• 13:31
  Speaker 2: everything compared to the Sun, all other energy sources are
• 13:37
  Speaker 2: like cavemen throwing some twigs into a fire.
• 13:40
  Speaker 3: Yeah.
• 13:42
  Speaker 2: So the the Sun is over ninety nine zero point
• 13:46
  Speaker 2: eight percent of all mass in the Solar system. Jupiter
• 13:50
  Speaker 2: is around zero point one percent of the mass. So
• 13:54
  Speaker 2: even if you BoNT Jupiter, the energy produced by the
• 13:57
  Speaker 2: Sun was still around up two hundred percent. Yeah, and
• 14:00
  Speaker 2: then if you teleported three more jupiters into our soul
• 14:03
  Speaker 2: system and burnt them.
• 14:04
  Speaker 4: Too, it's still round up.
• 14:05
  Speaker 3: It's still run.
• 14:06
  Speaker 2: The still rounds up to one hundred percent of energy.
• 14:08
  Speaker 4: Any interest in fusion, I mean, yeah, no fusion.
• 14:14
  Speaker 2: You know what you know a mile away, We're never
• 14:19
  Speaker 2: gonna guess how the sun works.
• 14:22
  Speaker 4: Giant coal plants.
• 14:25
  Speaker 2: I mean, we have a giant fusure free fusion reactors
• 14:28
  Speaker 2: up every days away. It's farcical for us to create
• 14:32
  Speaker 2: a little fusion reactors. I mean that would be like,
• 14:39
  Speaker 2: you know, having a tiny ice cube maker. Hey look
• 14:46
  Speaker 2: we made some like congratulations.
• 14:49
  Speaker 3: So totally it's totally with you on this.
• 14:51
  Speaker 2: It's like it's like three kilometers high glaciers right next
• 14:55
  Speaker 2: to you.
• 14:57
  Speaker 3: Yeah, recognized. If you just narrow the question into the
• 15:01
  Speaker 3: Memphis timeline, So Memphis Data Center timeline between a gigawatt
• 15:06
  Speaker 3: and ten giggle, you're not gonna you're not gonna pull
• 15:08
  Speaker 3: ten gigawatts out of Memphis. Maybe you are three, two
• 15:13
  Speaker 3: or three, Okay, So so there's still a gap between
• 15:16
  Speaker 3: there and the next whatever, you just so, and they're
• 15:19
  Speaker 3: not in spin yet at that point.
• 15:21
  Speaker 2: We're still in toyland here. Uh for Toylandland.
• 15:27
  Speaker 3: You know what's amazing is there's one hundred megawatts right
• 15:29
  Speaker 3: outside the door here and it's massive. It's it's enormous,
• 15:34
  Speaker 3: and it uses more energy hundred times then everything. All
• 15:37
  Speaker 3: these manufacturing lines combined use less energy than that, I think.
• 15:43
  Speaker 3: But we're talking about Cortex one.
• 15:46
  Speaker 2: Was the third largest training cluster in the in the world.
• 15:51
  Speaker 3: Yeah, for doing coherent training, you're falling behind. Uh.
• 15:55
  Speaker 2: Well with Cortex two that's being built out, that'll be
• 15:58
  Speaker 2: uh half a giga an operational.
• 16:02
  Speaker 3: Middle next year.
• 16:04
  Speaker 4: Everybody.
• 16:05
  Speaker 5: You may not know this, but I've done an incredible
• 16:07
  Speaker 5: research team and every week myself my research team study
• 16:10
  Speaker 5: the meta trends that are impacting the world topics like computation, sensors, networks, AI, robotics,
• 16:16
  Speaker 5: three D printing, synthetic biology, and these meta trend reports
• 16:19
  Speaker 5: I put out once a week enable you to see
• 16:22
  Speaker 5: the future ten years ahead of anybody else. If you'd
• 16:24
  Speaker 5: like to get access to the Meta Trends newsletter every week,
• 16:28
  Speaker 5: go to Deamandis dot com slash Meta Trends that's demandis
• 16:31
  Speaker 5: dot com slash meta trends. So going back to what
• 16:35
  Speaker 5: Dave is saying, over the next five years, what are
• 16:38
  Speaker 5: you scaling on energy front?
• 16:40
  Speaker 3: I mean this is a long time I mean energy.
• 16:43
  Speaker 5: I mean China has done an incredible job. Yeah right,
• 16:45
  Speaker 5: I mean it's running circles around US.
• 16:49
  Speaker 2: China has done an incredible job on solar. Yeah, that's amazing.
• 16:54
  Speaker 2: So I believe China's production capacity is around fifteen hundred
• 16:59
  Speaker 2: gigawatts per year of solar.
• 17:01
  Speaker 4: They put five hundred taro watts in the last year hours, yeah.
• 17:08
  Speaker 2: Like.
• 17:09
  Speaker 5: Hours, to be very specific, in the last year, seventy
• 17:12
  Speaker 5: percent of that was solar, and they're just scaling.
• 17:14
  Speaker 4: Do you do you do you imagine that?
• 17:17
  Speaker 5: Do you imagine that the US could make that level
• 17:22
  Speaker 5: of investment and commitment because people are worried about their
• 17:25
  Speaker 5: energy bills going up with no data centers in our backyard,
• 17:29
  Speaker 5: how do we provide I mean energy?
• 17:31
  Speaker 4: Energy.
• 17:32
  Speaker 5: Energy is equivalent to is equivalent to cost of you know,
• 17:36
  Speaker 5: cost of living, It's equivalent to health, it's equivalent to
• 17:38
  Speaker 5: clean water. You know, the higher energy production of a country,
• 17:43
  Speaker 5: the higher its GDP.
• 17:46
  Speaker 4: Energy is important. So what should what do we do
• 17:50
  Speaker 4: to scale that way? Do we do it in solar here?
• 17:55
  Speaker 2: I think we should scale solar substantially in the US
• 18:00
  Speaker 2: TESTA and Space EXO scaling solar so and I encourage others.
• 18:06
  Speaker 4: To do so as well.
• 18:09
  Speaker 3: So the the.
• 18:13
  Speaker 2: I mean, I've said this stuff, you know publicly. I
• 18:18
  Speaker 2: do see a path to one hundred gig go. What's
• 18:20
  Speaker 2: a year of space solo sort of AI power solar
• 18:25
  Speaker 2: powered AI satellites.
• 18:26
  Speaker 3: Yes, g got to your solo powered A satellites.
• 18:30
  Speaker 5: I did the math on that. That's like five hundred
• 18:35
  Speaker 5: thousand Starlink V three's launched over eight thousand starship flights.
• 18:43
  Speaker 4: It's one every hour.
• 18:46
  Speaker 3: For a year.
• 18:49
  Speaker 2: Yeah, ten thousand flights a year is a reasonable number.
• 18:56
  Speaker 3: So it's amazing.
• 18:57
  Speaker 4: It's quite the scale.
• 18:58
  Speaker 3: What's what's the rough timeline on that? Because I mean
• 19:01
  Speaker 3: by aircraft standards.
• 19:02
  Speaker 2: That's a small number.
• 19:03
  Speaker 4: Sure lights, Yeah for sure.
• 19:05
  Speaker 2: Yeah, that's uh, that's that's that's that's small like so
• 19:09
  Speaker 2: just like it depends what you compared to you compared
• 19:11
  Speaker 2: to the rest of the rocket industry, it's a very
• 19:14
  Speaker 2: high number. Yeah, and we're talking about a million tons
• 19:17
  Speaker 2: of pale or two over per year. So if you do,
• 19:19
  Speaker 2: if you do a million tons of paler to over
• 19:22
  Speaker 2: per year with one hundred killowats per ton, that's one
• 19:26
  Speaker 2: hundred gigawatts of sol parwer Ai satellites per year. I
• 19:32
  Speaker 2: mean there's there's a path to get probably to a
• 19:36
  Speaker 2: terror watt per year.
• 19:38
  Speaker 4: From from the from a Yeah.
• 19:40
  Speaker 2: Yeah, if you say like h ten, if you want
• 19:45
  Speaker 2: you want to go up another order of magnitude, or
• 19:47
  Speaker 2: let's say you want to go to one hundred tarrawats
• 19:49
  Speaker 2: a year. Yeah, obviously kind of nutty numbers. Then you
• 19:53
  Speaker 2: want to make those ah Ai satellites on the moon
• 19:59
  Speaker 2: and use a mass.
• 20:00
  Speaker 4: Driver, yeahs the Gerard K.
• 20:01
  Speaker 2: O'Neal approach well, like Robert Heinland of course verty much yea, yeah,
• 20:05
  Speaker 2: I love that book. Yeah yeah, it's a sort of
• 20:08
  Speaker 2: libertarian paradise. And uh yeah, so because on the Moon
• 20:15
  Speaker 2: you can just accelerate the satellites into to escape velocities
• 20:20
  Speaker 2: around twenty five meters per second and there's no atmosphere,
• 20:26
  Speaker 2: so like a mass driver works very well in the Moon.
• 20:29
  Speaker 5: Can I ask their question about orbital debris? I mean,
• 20:33
  Speaker 5: we're building effectively a dice in ish schwarm around the Earth.
• 20:37
  Speaker 3: Warm lunch.
• 20:45
  Speaker 5: Are you worried about over congestion on the that's gonna
• 20:50
  Speaker 5: be a sun sync orbit's gonna fill very quickly.
• 20:55
  Speaker 2: I mean you can you don't have to have sun
• 20:57
  Speaker 2: sinc I mean.
• 20:57
  Speaker 4: You can, don't have to, but it's optimal.
• 21:00
  Speaker 2: Yeah, there's some pros and cons to sun sink or
• 21:05
  Speaker 2: not sun sync. I mean, you'll be're paler to orbit
• 21:14
  Speaker 2: drafts by like thirty percent compared to you know, if
• 21:17
  Speaker 2: you were just went to like mid inclination like seventy
• 21:22
  Speaker 2: degrees or something like that.
• 21:24
  Speaker 5: I mean, do we need an orbital debris exprize at
• 21:27
  Speaker 5: this point? We need some way to get the satellites
• 21:32
  Speaker 5: define satellites down. Do we pass rules that require them
• 21:36
  Speaker 5: to deorbit on their own?
• 21:40
  Speaker 2: Yeah, at the point where you can put a million
• 21:42
  Speaker 2: times of satellites into orbit, you can also you know,
• 21:45
  Speaker 2: really stop bringing down satellites too, or at least collecting
• 21:49
  Speaker 2: them into a known into a fixed locations they're not
• 21:52
  Speaker 2: like all over the place.
• 21:53
  Speaker 4: And then you can reuse them.
• 21:56
  Speaker 2: Yeah, let's just say that we'll have the resource level
• 22:01
  Speaker 2: will be so high that that I believe this will
• 22:04
  Speaker 2: be a solid problem. Given the amount of intelligence we're
• 22:06
  Speaker 2: talking about here, like the intelligence will quite interested in
• 22:10
  Speaker 2: preserving itself.
• 22:11
  Speaker 4: Yes, that's true.
• 22:13
  Speaker 3: Interesting good motivation.
• 22:15
  Speaker 4: Yea interesting question.
• 22:17
  Speaker 3: The data centers will not be in lower thorbit, right,
• 22:19
  Speaker 3: they'll be They'll be much higher, constantly in the sun.
• 22:23
  Speaker 3: They're not going to be in the traffic jam.
• 22:25
  Speaker 2: I assume, well, you can get you know, you don't
• 22:27
  Speaker 2: have to get to get to constant sunlight. You can
• 22:30
  Speaker 2: be around twelve hundred kilometers. Synchronous will give you constant sunlight.
• 22:35
  Speaker 4: But you could you could place him in multiple orbits.
• 22:38
  Speaker 3: Yeah, yeah, yeah, No, I think if there's an X
• 22:41
  Speaker 3: prize for cleaning up, it's got to be there's only
• 22:43
  Speaker 3: going to be clutter and lower Throbert.
• 22:45
  Speaker 6: I mean debris from anything, anything that's if it's a
• 22:50
  Speaker 6: you know, below around seven or eight hard kilometers, the
• 22:53
  Speaker 6: atmosphere will administrate drag will bring it back.
• 22:56
  Speaker 3: Yeah.
• 22:57
  Speaker 2: So, like forestalling, there's a dual benefit of being like
• 23:04
  Speaker 2: as low as possible because your beam, you know, your
• 23:09
  Speaker 2: beams are tighter, you know, you're basically that you have
• 23:11
  Speaker 2: less latency and your beams are smaller if you're even
• 23:15
  Speaker 2: closer to the Earth. So, like stalling, three will be
• 23:19
  Speaker 2: around three thirty to three fifty kilometers, which is quite
• 23:23
  Speaker 2: a lot of drag, So it's basically constantly thrusting.
• 23:26
  Speaker 5: I still remember when you propose darlink and everybody else
• 23:30
  Speaker 5: in the industry is like, no way, no way, he's
• 23:33
  Speaker 5: not going to get the spectrum. He's not gonna be
• 23:35
  Speaker 5: able to do this. Yeah, it's it's kind of worked.
• 23:41
  Speaker 2: Yeah, we're the stalling team has done an incredible job. Now,
• 23:47
  Speaker 2: I mean we've basically rebuilt the Internet in space with
• 23:52
  Speaker 2: the laser links. So there's nine thousand satellites up there.
• 23:57
  Speaker 5: Do you think the governments can be able to handle
• 24:00
  Speaker 5: the kind of licensing of the volume of satellites that
• 24:03
  Speaker 5: you want to put up? I mean, will it be
• 24:05
  Speaker 5: pushed back because you know, China is going to put
• 24:08
  Speaker 5: up their own constellations Europe?
• 24:11
  Speaker 4: Who knows whether Europe will ever step up?
• 24:13
  Speaker 2: They won't. What's that they won't there's probably Yeah nothing
• 24:17
  Speaker 2: that nothing they're doing has success in the set of
• 24:20
  Speaker 2: Pussal outcomes.
• 24:21
  Speaker 4: Yeah, okay, I.
• 24:28
  Speaker 3: Just got back from Rome.
• 24:29
  Speaker 2: I don't want to touch that success on the set.
• 24:31
  Speaker 5: Of shows the number of billion dollar startups in the
• 24:40
  Speaker 5: US versus Europe.
• 24:42
  Speaker 3: If you've seen that graphic, Yeah, it's crazy. Yeah, and
• 24:45
  Speaker 3: data centers due.
• 24:48
  Speaker 5: No one was talking about orbital data centers six months ago. Yeah, nobody,
• 24:52
  Speaker 5: And then all of a sudden, on it. You're you're
• 24:56
  Speaker 5: out with it and.
• 24:57
  Speaker 3: It's the hot new thing.
• 24:58
  Speaker 4: It is what?
• 25:00
  Speaker 3: What? What?
• 25:01
  Speaker 2: Tip?
• 25:01
  Speaker 5: What happened that every company is now talking about orbital
• 25:06
  Speaker 5: data centers.
• 25:07
  Speaker 2: I guess they went viral and next I don't know,
• 25:12
  Speaker 2: is every company talking.
• 25:14
  Speaker 4: Oh yeah, everybody's got their own orbital.
• 25:16
  Speaker 3: Oh for sure. And I was suggesting to Peter that
• 25:19
  Speaker 3: that you updated the math on launch costs and that
• 25:22
  Speaker 3: it's a tipping point very quickly. With the updated math.
• 25:24
  Speaker 4: The starship has been the cost for you know, I
• 25:26
  Speaker 4: don't know what you hold hundred dollars kill ten dollars
• 25:29
  Speaker 4: for killogram? What do you have? Starship?
• 25:31
  Speaker 3: But it's possible that Elon said that nobody believed it
• 25:34
  Speaker 3: until now.
• 25:36
  Speaker 2: You can go back and look at my what even
• 25:38
  Speaker 2: back when it was Twitter. H they're my old tweets.
• 25:43
  Speaker 2: I said these things so many years ago.
• 25:45
  Speaker 3: A hundred bucks or ten bucks a kilogram?
• 25:49
  Speaker 2: Yeah, I know, And I said this is we're going
• 25:51
  Speaker 2: to do a million tons a year.
• 25:52
  Speaker 3: It's a little bit.
• 25:57
  Speaker 2: Yeah, And we've got to get the costs down, yeah,
• 26:01
  Speaker 2: well below one hundred dollars a kilogram.
• 26:03
  Speaker 4: So that's going to move the data centers to orbit.
• 26:05
  Speaker 3: Will it's they can do.
• 26:06
  Speaker 2: You can basically do the math like if you've got
• 26:08
  Speaker 2: a fully reusable rocket now, which is fully and rapidly
• 26:11
  Speaker 2: reusable like an aircraft, and this is an incredible This
• 26:15
  Speaker 2: is a very difficult thing to do. Obviously, I think
• 26:20
  Speaker 2: it's at the limit of human intelligence to create a
• 26:23
  Speaker 2: fully rapidly reusable rocket, but it is possible, and we're
• 26:28
  Speaker 2: doing it with Star.
• 26:29
  Speaker 4: It's been the holy grail in the aerospace industry forever.
• 26:32
  Speaker 2: Yeah, quest for the Holy Grail rocket.
• 26:34
  Speaker 4: Yeah, yeah, I mean right now in the d c
• 26:37
  Speaker 4: X was the first little things that we're trying there,
• 26:40
  Speaker 4: and it's been you know, all of I mean back
• 26:43
  Speaker 4: when I was in the space industry, that's all everyone
• 26:45
  Speaker 4: ever spoke about. And then when Falcon nine first reused
• 26:49
  Speaker 4: its first.
• 26:50
  Speaker 5: Stage, I mean all the traditional aerospace industries did not
• 26:55
  Speaker 5: believe that even Falcon nine could could fly.
• 26:59
  Speaker 2: Literally you can come see land at Capua yeah and
• 27:03
  Speaker 2: then take off again.
• 27:04
  Speaker 4: Yeah.
• 27:05
  Speaker 2: So I don't know how you do not believe a
• 27:06
  Speaker 2: thing that you can see with your own ice.
• 27:08
  Speaker 4: Yeah, well they didn't believe. Didn't believe.
• 27:10
  Speaker 3: But the lead from there to the launch costs actually
• 27:13
  Speaker 3: requires more faith than just just that. But I think,
• 27:16
  Speaker 3: I think Starship is the launch cost tipping point, and
• 27:19
  Speaker 3: that's somewhere in that you know, before you had Twitter
• 27:21
  Speaker 3: it became X. Somewhere in that timeline it went from
• 27:25
  Speaker 3: speculative to no doubt. And I don't know if that's
• 27:29
  Speaker 3: a smooth line or a couple of good launches in between.
• 27:31
  Speaker 3: But I suspect that the data centers in space, but
• 27:34
  Speaker 3: people ties directly to the credibilities.
• 27:36
  Speaker 5: Not thinking about orbital data centers are thinking about energy
• 27:39
  Speaker 5: and the cost of energy here on here in their
• 27:41
  Speaker 5: hometown and sort of the the there's a lot of
• 27:44
  Speaker 5: doomor conversations out there the data centers are going to
• 27:47
  Speaker 5: drive the CPI up.
• 27:50
  Speaker 3: Uh, they're not entirely wrong.
• 27:54
  Speaker 4: Okay, So what is that?
• 27:55
  Speaker 5: So what is the what's the energy solution here on
• 27:58
  Speaker 5: Earth for the rest of humanity or the non data
• 28:04
  Speaker 5: the non.
• 28:05
  Speaker 3: Oh there's something other than data center uses of energy?
• 28:08
  Speaker 3: Can right? That's complex?
• 28:11
  Speaker 2: Well, the the best way to actually increase the energy
• 28:16
  Speaker 2: output per year of the United States or any country
• 28:19
  Speaker 2: is batteries. So the peak power output of the of
• 28:24
  Speaker 2: the U S is around one point one terra watts,
• 28:28
  Speaker 2: but the average power usage is only half a terawatte.
• 28:33
  Speaker 2: So if you just buffer the the energy, so charge
• 28:36
  Speaker 2: up the batteries at night, discharge during the day, without
• 28:41
  Speaker 2: incremental capital expending, without incremental capital expansions about building new
• 28:45
  Speaker 2: power plants, you can double the energy throughput of the US.
• 28:48
  Speaker 2: The energy output per year can double with batteries.
• 28:52
  Speaker 4: And do we have those batteries in development?
• 28:55
  Speaker 3: Yeah?
• 28:55
  Speaker 2: Til makes them.
• 28:56
  Speaker 4: Okay, So you think current current Tesla battery do you think?
• 29:01
  Speaker 3: What do you think?
• 29:02
  Speaker 2: I literally have and presented the thing that's that's the
• 29:06
  Speaker 2: dead giveaway. So I even went to installations of the megapacks,
• 29:15
  Speaker 2: you know, and there's so why don't people do? It's
• 29:18
  Speaker 2: on the internet, so is do you think they are?
• 29:21
  Speaker 2: And China, by the ways, like it seems like trying
• 29:25
  Speaker 2: to listen to everything I say. I say, it does
• 29:27
  Speaker 2: does it basically or at least or they're just doing
• 29:30
  Speaker 2: it independently. I don't know, but they're they're certainly making
• 29:35
  Speaker 2: massive battery packs, like really massive battery pack output. They're yeah,
• 29:44
  Speaker 2: making vast numbers of electric cars, vast amounts of solar.
• 29:51
  Speaker 3: You know, I don't know.
• 29:52
  Speaker 4: These are all things I said, I said, you know
• 29:54
  Speaker 4: we should do fundamentally.
• 29:55
  Speaker 5: Sure, when I fly over Santa Monica in l A
• 30:00
  Speaker 5: piloting and I look down, like zero roofs have solar
• 30:03
  Speaker 5: on them. Zero roofs.
• 30:05
  Speaker 4: Yeah, I mean it's not essential to have them on
• 30:08
  Speaker 4: a roof, Okay, but it's a convenient place to have them.
• 30:11
  Speaker 2: Yes, But the surf area of roofs is I'm not
• 30:16
  Speaker 2: saying you shouldn't, but it's till it makes a solar roof,
• 30:20
  Speaker 2: which is the only solar roof that isn't ugly.
• 30:25
  Speaker 3: A solar roof actually looks beautiful.
• 30:28
  Speaker 2: Yeah, but if you want to do solar at scale,
• 30:32
  Speaker 2: you just need more surf area. So we have vast
• 30:37
  Speaker 2: empty deserts. Sure in America, Like if you fly from
• 30:40
  Speaker 2: LA to New York or just fly across country and
• 30:43
  Speaker 2: you look down for a large portion of the time
• 30:47
  Speaker 2: you look down, it is bleak desert. It looks like
• 30:50
  Speaker 2: Mars essentially.
• 30:51
  Speaker 4: Not worried about overpopulation there.
• 30:53
  Speaker 2: No, I mean it looks there's barely a lizard alive
• 30:56
  Speaker 2: in these scorching deserts. You know, it's not like farmland
• 30:59
  Speaker 2: we're talking about. We're just talking about yep, places that
• 31:03
  Speaker 2: look like Mars, like just uh.
• 31:06
  Speaker 3: Scorched rock.
• 31:08
  Speaker 2: So if we put Sola where we currently have scorched rock,
• 31:12
  Speaker 2: I think this will be a quality of life improvement
• 31:15
  Speaker 2: for the lizards or the few creatures that live in this.
• 31:20
  Speaker 3: Very difficult environment.
• 31:22
  Speaker 4: Network.
• 31:22
  Speaker 2: It's like, this is gonna be thank God, some shade. Finally,
• 31:29
  Speaker 2: do we have.
• 31:29
  Speaker 4: The distribution network to be able to do that?
• 31:32
  Speaker 3: You need to materially affect quality of life. You need
• 31:35
  Speaker 3: to capture and store what a couple hundred giga wants.
• 31:38
  Speaker 3: Is that just realistic? You could just put the data center.
• 31:41
  Speaker 3: I guess locally there. Well, we already cover data centers.
• 31:44
  Speaker 3: We're talking about you know the other Yeah, like I
• 31:48
  Speaker 3: don't know, like in an abundant world five years from now,
• 31:51
  Speaker 3: massive amounts of compute massive you know, universal high income.
• 31:55
  Speaker 2: I don't know what universal. You can have whatever you
• 31:59
  Speaker 2: want income. Yeah, that's that's really what it mounts to.
• 32:02
  Speaker 3: But in that world, you know, other than compute energy,
• 32:05
  Speaker 3: how much more energy do we need thirty? I don't know,
• 32:09
  Speaker 3: unless we want to move mountains around to make a
• 32:11
  Speaker 3: ski mountain, you know, in the backyard, because I think
• 32:15
  Speaker 3: the vast majority of energy consumption will go into compute,
• 32:19
  Speaker 3: and then there may be use cases I'm not thinking of,
• 32:21
  Speaker 3: like you know, the well you know right here is
• 32:24
  Speaker 3: a nice case study because manufacturing every one of these
• 32:26
  Speaker 3: cars coming out at the rate of one every minute
• 32:29
  Speaker 3: or two is less energy than the data center that's
• 32:35
  Speaker 3: training the cars to drive to self drive. Yes, so
• 32:38
  Speaker 3: that's a good little case study. And we don't need
• 32:40
  Speaker 3: that much more physical energy for abundant happiness. We need
• 32:45
  Speaker 3: more compute energy.
• 32:47
  Speaker 2: The Sun is just generating vast amounts of energy all
• 32:52
  Speaker 2: the time for free.
• 32:53
  Speaker 3: That ghess goes into space, So.
• 32:58
  Speaker 2: I think we'll end up trying to capture I don't
• 33:00
  Speaker 2: know a million of it, likes a million the thousandth
• 33:03
  Speaker 2: of the Sun's energy. We're currently I'm not sure your
• 33:07
  Speaker 2: exact number, but we're I don't know, we're probably at
• 33:13
  Speaker 2: one percent ish of KARDASHEV level one.
• 33:17
  Speaker 4: Fair enough, Yeah, I guess at Eden's that's high. I'm
• 33:21
  Speaker 4: just yea saying we have a long way to go.
• 33:23
  Speaker 3: That's being optimistic.
• 33:25
  Speaker 2: Hopefully we're not zero point one percent, but I don't
• 33:27
  Speaker 2: think we're ten percent. I'm just trying to get it
• 33:30
  Speaker 2: to an order of attitude. So pull it like we're
• 33:33
  Speaker 2: roughly one percent of the I'm hardly using one percent
• 33:37
  Speaker 2: of the energy that we could use.
• 33:39
  Speaker 5: On I think the bottom line from my first principles
• 33:42
  Speaker 5: thinking for the public is there's a lot of energy
• 33:44
  Speaker 5: out there, and it we have it in the US,
• 33:48
  Speaker 5: we have it on the planet, and it used to
• 33:50
  Speaker 5: be captured, and the tech to capture it is here
• 33:53
  Speaker 5: and improving every year.
• 33:56
  Speaker 2: Yes, yeah, there's not going to be some energy crisis.
• 34:01
  Speaker 2: Let's they'll be a large forcing function to harness more energy.
• 34:06
  Speaker 2: But we're not going to run out of it.
• 34:08
  Speaker 4: All right.
• 34:08
  Speaker 5: I want to talk about education. So here's the numbers.
• 34:12
  Speaker 5: They're abysmal. I mean, they're they're they're abysmo right, Okay,
• 34:18
  Speaker 5: the importance of college in the United States. Back in
• 34:23
  Speaker 5: twenty ten, seventy five percent of Americans said it's important
• 34:25
  Speaker 5: to go to college. That number is now down at
• 34:28
  Speaker 5: thirty five percent. Right, college graduates as a group turn
• 34:33
  Speaker 5: out to be the group that's.
• 34:35
  Speaker 4: Out of work the longest.
• 34:37
  Speaker 5: Right and then but still and tuition has increased nine
• 34:42
  Speaker 5: hundred percent since nineteen eighty three.
• 34:45
  Speaker 2: Yeah, the administrative expenses at universities I've gotten out of control.
• 34:49
  Speaker 3: Yep.
• 34:51
  Speaker 2: So I think I saw it with some stat that
• 34:53
  Speaker 2: like there's one administrator for every two students at Round
• 34:57
  Speaker 2: or something like that, and I'm like the same, it
• 35:00
  Speaker 2: was a little high.
• 35:01
  Speaker 4: Yeah, administry, they should teach something.
• 35:04
  Speaker 3: Yeah, what was your college journey?
• 35:07
  Speaker 2: I went to college in Canada for a couple of
• 35:09
  Speaker 2: years at Queen's University. So I had Canadian citizenship through
• 35:16
  Speaker 2: my mom who was born in Canada, and my grandfather
• 35:18
  Speaker 2: was actually American, but for some reason I don't know,
• 35:20
  Speaker 2: my mom couldn't get your sizenship, so but she was
• 35:23
  Speaker 2: born in Canada.
• 35:23
  Speaker 3: So I got Canadian citizenship.
• 35:27
  Speaker 2: And I didn't have any money, so I could only
• 35:30
  Speaker 2: go to Canadian University.
• 35:31
  Speaker 4: At first, people forget that about you.
• 35:32
  Speaker 5: You didn't have this giant social network or huge amount
• 35:36
  Speaker 5: of wealth coming into all of this.
• 35:38
  Speaker 3: No No.
• 35:40
  Speaker 2: I arrived in Montreal at age seventeen with I think
• 35:45
  Speaker 2: around twenty five hundred dollars in Canadian travelers checks, back
• 35:47
  Speaker 2: when travelers checks were of thing and one bag of
• 35:52
  Speaker 2: books and one bag of clothes. That was my starting point.
• 35:55
  Speaker 2: That was my scorn point in North America. And then
• 36:01
  Speaker 2: so they went to Queen's University for a couple of
• 36:03
  Speaker 2: years and then University of Pennsylvania did adult degree in
• 36:08
  Speaker 2: physics and economics and graduating undergraduate at U penn Upen Woten, Yeah,
• 36:16
  Speaker 2: and then I came out to do I was gonna
• 36:20
  Speaker 2: do a PhD at Stanford working on energy storage technologies
• 36:25
  Speaker 2: for electric vehicles, potentially material science. I guess fundamentally, the
• 36:31
  Speaker 2: idea that I had was it was to try to
• 36:34
  Speaker 2: create a capacitor with enough energy density that you get
• 36:39
  Speaker 2: higher range in an electric car.
• 36:40
  Speaker 3: When I invested in an ultra capacitor company, I didn't
• 36:43
  Speaker 3: didn't go.
• 36:44
  Speaker 2: Well, Well, it's one of those things where you know,
• 36:47
  Speaker 2: so you could definitely get a PhD, but it wasn't
• 36:50
  Speaker 2: clear that you could make a company or do something
• 36:52
  Speaker 2: useful like this. Most PhDs, I mean, I hate said,
• 36:56
  Speaker 2: but most PhDs.
• 36:57
  Speaker 4: Do not turn into something that's going to turn into
• 37:00
  Speaker 4: something useful.
• 37:01
  Speaker 2: But like you could add a leaf to the tree
• 37:03
  Speaker 2: of knowledge, but it's not necessarily necessarily a useful leaf.
• 37:06
  Speaker 3: Enormous fraction of great entrepreneurs are dropping out, yeah, cras
• 37:11
  Speaker 3: tool or undergrad but now nowadays the sense of urgency
• 37:14
  Speaker 3: is off the charts, but I mean they're popping out.
• 37:16
  Speaker 5: Everywhere because you know, don't waste your time going to
• 37:19
  Speaker 5: grad school, start a company.
• 37:20
  Speaker 3: The curriculum is nowhere near caught up to what's actually
• 37:22
  Speaker 3: going on in technology, and I don't have time, and.
• 37:25
  Speaker 5: We know all the time, it's like, you know, this
• 37:28
  Speaker 5: is the moment. I think this is the moment.
• 37:31
  Speaker 2: It's not clear to me why somebody would be in
• 37:34
  Speaker 2: college right now unless they want the social experience.
• 37:36
  Speaker 5: Yeah, I mean, if you have the ability to go
• 37:39
  Speaker 5: and build something. So the question is, how would you
• 37:42
  Speaker 5: redesign the educational program if I could be so so
• 37:46
  Speaker 5: blunt as to create more Elon Musks. If we want
• 37:49
  Speaker 5: to create an Elon Musk factory of people who start
• 37:52
  Speaker 5: with very little but are able to drive and drive breakthroughs.
• 38:00
  Speaker 4: What's involved there? What drove you.
• 38:05
  Speaker 2: A curiosity about the nature of the universe. So I'm
• 38:09
  Speaker 2: curious about the meaning of life, and you know, what
• 38:14
  Speaker 2: is this reality that we live in?
• 38:16
  Speaker 4: So how early my son Dax wanted to know what
• 38:19
  Speaker 4: was it like for you in middle school? In high school?
• 38:23
  Speaker 4: He's fourteen years old. He's in that age range now.
• 38:27
  Speaker 3: Well, I did.
• 38:28
  Speaker 2: I found school to be quite painful and it was
• 38:33
  Speaker 2: very boring and in South Africa was very violent. So
• 38:36
  Speaker 2: it's like it was it was like, it's like that
• 38:40
  Speaker 2: was like that book Enters.
• 38:41
  Speaker 4: Game, Yes, but in your Bible il.
• 38:44
  Speaker 3: In this game irl it was like but not as fun.
• 38:48
  Speaker 2: So your goal was escape, Yes, I escape from the prisons.
• 38:54
  Speaker 4: So that's a question I have.
• 38:56
  Speaker 2: Do you think that it was miserable?
• 38:58
  Speaker 4: Do you think most.
• 38:58
  Speaker 5: Successful people have had a lot of hardship early in life?
• 39:04
  Speaker 4: Do you need to have that level of hardship?
• 39:06
  Speaker 2: Probably need a little bit of han but I suppose yeah.
• 39:09
  Speaker 2: And then so it's so tricky, like what are you
• 39:10
  Speaker 2: supposed to do with your kids? You know, great artificial
• 39:13
  Speaker 2: adversity put them.
• 39:14
  Speaker 3: In the school. That's that's a Warren Buffett topic. Actually, yeah,
• 39:21
  Speaker 3: what do you do?
• 39:22
  Speaker 2: But that's not easy to create artificial adversity because if
• 39:25
  Speaker 2: you love your kids, you don't want to do that.
• 39:26
  Speaker 2: So I had a lot of adversity.
• 39:32
  Speaker 3: Probably it was good.
• 39:33
  Speaker 2: Uh, probably you know helped some white I suppose when
• 39:37
  Speaker 2: when me kill you makes you stronger passing at least
• 39:40
  Speaker 2: I didn't lose a limb.
• 39:41
  Speaker 7: I think what doesn't Maime you ten fingers.
• 39:52
  Speaker 2: To modify that a little bit, Yeah, makes you stronger.
• 39:57
  Speaker 3: For the last five years I've been helping teach this
• 39:59
  Speaker 3: class Fundations of AI Ventures at MIT, and every year
• 40:04
  Speaker 3: when you survey the students, they go up a lot
• 40:08
  Speaker 3: in their desire to start a company, and so it's
• 40:10
  Speaker 3: not up to eighty percent of the incoming.
• 40:13
  Speaker 2: Everyone is just gonna it's just gonna be like one
• 40:16
  Speaker 2: person company.
• 40:18
  Speaker 3: Well that's that's that's viable, I guess. But no, they
• 40:20
  Speaker 3: want to co found the Yeah, they don't want to
• 40:22
  Speaker 3: be the founder. They want to be part of a
• 40:23
  Speaker 3: founding team. So it still works out. But when Peter
• 40:26
  Speaker 3: and I were in school at MIT, it was I'm
• 40:28
  Speaker 3: guessing maybe ten percent, and they all want to be
• 40:32
  Speaker 3: and they've been doing the survey, and you know.
• 40:34
  Speaker 2: Everyone who wanted to start, I mean yeah, I I
• 40:38
  Speaker 2: don't remember any conversations about with people saying they.
• 40:41
  Speaker 3: Wanted to start, even at Stanford at the time.
• 40:43
  Speaker 2: I actually, a few days into the semester or say
• 40:48
  Speaker 2: the quarter, I called Bill Nicks, who was a material
• 40:53
  Speaker 2: science department and said I'd like to just put it
• 40:56
  Speaker 2: on deferment.
• 40:58
  Speaker 4: So it was my class that bad.
• 41:00
  Speaker 2: No I need, he said, he said, that's he said,
• 41:02
  Speaker 2: that's okay, you.
• 41:03
  Speaker 3: Can put it on depoement.
• 41:04
  Speaker 2: But he said, this is probably the last conversation we'll have.
• 41:07
  Speaker 3: And he was right.
• 41:09
  Speaker 2: But then, like last I think it was last year,
• 41:11
  Speaker 2: he sent me a letter saying that all of my
• 41:14
  Speaker 2: predictions about that the amount batteries came true.
• 41:18
  Speaker 3: M right now.
• 41:19
  Speaker 4: And did he also say you could still come back
• 41:20
  Speaker 4: and finish your PhD?
• 41:22
  Speaker 3: Yeah?
• 41:23
  Speaker 2: It was several times Stamford has said that I can
• 41:25
  Speaker 2: come back for you.
• 41:26
  Speaker 3: Well, see know what happened to I?
• 41:27
  Speaker 2: T is every time I did not know, great use
• 41:31
  Speaker 2: of your time, exactly, I don't like.
• 41:33
  Speaker 3: So every time an iron Man movie came out, it
• 41:37
  Speaker 3: notched up another probably ten percent or so in terms
• 41:41
  Speaker 3: of everybody wanted to be Tony Stark. And so that's
• 41:44
  Speaker 3: the image. And I didn't know till today that the
• 41:48
  Speaker 3: new Tony Stark, the modern iron Man Stark. I always
• 41:50
  Speaker 3: thought Tony Stark was modeled on Charles Stark Draper and
• 41:53
  Speaker 3: Howard Hughes, and Charles Stark Draper's education and his you know,
• 41:57
  Speaker 3: scientific endeavors married with Howard hughes ambition, and that created
• 42:01
  Speaker 3: the original character. But then when the day Junior wanted
• 42:04
  Speaker 3: to reinvent it. Yeah, caves modeled on Elon. Yeah, met
• 42:09
  Speaker 3: with me. This is a Grockipedia fact.
• 42:12
  Speaker 2: All right, yeah, fantastic. Yeah, they came John and.
• 42:19
  Speaker 4: I like the named Grock. I would like Jarvis as well.
• 42:22
  Speaker 2: Yeah yeah, probably some some trade at some point. If
• 42:26
  Speaker 2: gro gets good enough, we're gonna quote Encyclopedia Galactica.
• 42:30
  Speaker 4: Yes that's nice. Yeah, yeah, of course what did you?
• 42:34
  Speaker 4: Thank you? So? Going back to education?
• 42:37
  Speaker 3: Uh?
• 42:38
  Speaker 4: Should colleges.
• 42:39
  Speaker 5: I guess the social experience that you said is important there,
• 42:42
  Speaker 5: But what would you do for education?
• 42:45
  Speaker 4: Uh? You know, middle high school.
• 42:47
  Speaker 5: You just came back from an announcement with President bou Kelly,
• 42:51
  Speaker 5: who's a friend I think is an amazing, amazing visionary. Yeah,
• 42:55
  Speaker 5: incredible what he did with his nation. Yeahable, remarkable and gutsy.
• 43:01
  Speaker 5: Yeah how yeah, I mean it was like it's the
• 43:06
  Speaker 5: nuclear it was a nuclear option, right, shut them down?
• 43:10
  Speaker 5: I mean, you know how besides putting everybody with a
• 43:12
  Speaker 5: gang sign in in uh.
• 43:16
  Speaker 4: In jail. I don't know if you know. The second
• 43:19
  Speaker 4: thing he did.
• 43:20
  Speaker 5: He went to all of the graves of all the
• 43:23
  Speaker 5: gang members out there and destroyed the graves. And said
• 43:27
  Speaker 5: your memory will not be remembered in this nation. That's
• 43:31
  Speaker 5: just badass, and it worked.
• 43:34
  Speaker 2: I mean, you have to be bad ass, motherfucker to
• 43:38
  Speaker 2: take on old and oker gangs and win and live.
• 43:41
  Speaker 3: Yeah, and live.
• 43:43
  Speaker 5: He's got a great great guard at his palace there.
• 43:47
  Speaker 5: But what what did you announce with with him in
• 43:49
  Speaker 5: the Salvador.
• 43:50
  Speaker 3: I was just basically to use CROCT.
• 43:54
  Speaker 4: For education, like, not the vulgar version of it.
• 43:58
  Speaker 3: Yeah, we would have like.
• 43:59
  Speaker 2: You know, the kids friendly version of rock.
• 44:04
  Speaker 3: Uh.
• 44:04
  Speaker 2: But but obviously AI can be an individualized teacher that
• 44:10
  Speaker 2: is infinitely patient and answers all your questions. You still
• 44:15
  Speaker 2: need to be curious and and you still need to
• 44:23
  Speaker 2: want to learn. You know, groc can't make you want
• 44:25
  Speaker 2: to learn. It can make learning more interesting.
• 44:27
  Speaker 4: You could probably game a fine incentivize it, right, You can.
• 44:31
  Speaker 2: Make learning more interesting and and less of a production line. So,
• 44:40
  Speaker 2: but kids do need to have to if they need
• 44:43
  Speaker 2: to want to learn, you know, you and and like that.
• 44:47
  Speaker 2: People should just think of the brain as a biological computer.
• 44:51
  Speaker 4: It's a neural net.
• 44:52
  Speaker 2: Yeah, it's a biological computer with you know, so with
• 44:57
  Speaker 2: a number of neurons and neural efficienc and so like
• 45:05
  Speaker 2: what you can do is to any operatory kid at
• 45:07
  Speaker 2: Einstein as realistic because Einstein had a very good meat computer,
• 45:13
  Speaker 2: like an outstanding meet computer. So you can't just do Shakespeare, Newton,
• 45:18
  Speaker 2: you know, Einstein type of thing unless the meat computer
• 45:22
  Speaker 2: is an exceptional one.
• 45:25
  Speaker 4: So what do you think.
• 45:27
  Speaker 5: So when people say we need to solve education in
• 45:29
  Speaker 5: the United States because it's fundamentally broken, I think what's
• 45:35
  Speaker 5: really broken. I'm curious is the old social contract that
• 45:39
  Speaker 5: says do well in high school, get into good college,
• 45:42
  Speaker 5: get a degree, and then get a job. And I
• 45:46
  Speaker 5: don't know that that's going to be valid in the future.
• 45:51
  Speaker 5: We talk about this on the pod a lot, that
• 45:52
  Speaker 5: that the career of the future isn't getting a job,
• 45:55
  Speaker 5: it's being an entrepreneur. It's finding a problem solving it.
• 45:59
  Speaker 4: Yeah, you do you agree with that?
• 46:01
  Speaker 3: Right now?
• 46:01
  Speaker 2: I'd say people just you know, go to school for
• 46:05
  Speaker 2: the social experience. Use more AI. The conventional schooling experience.
• 46:13
  Speaker 2: I think could be a lot better what we're going
• 46:18
  Speaker 2: to do, and I'll Solvador and hopefully other places just
• 46:20
  Speaker 2: have individualized teachers.
• 46:23
  Speaker 3: It's going to be much better.
• 46:24
  Speaker 2: And you could go to you could go to a
• 46:26
  Speaker 2: school with a bunch of other kids. I guess if
• 46:29
  Speaker 2: you want to hang out with other kids, but you
• 46:30
  Speaker 2: don't need to, you could do it on your phone
• 46:33
  Speaker 2: at home. So that's why I say, like at this point,
• 46:37
  Speaker 2: education is a social experience. When I talk to my
• 46:40
  Speaker 2: kids who are in college, they do recognize that they
• 46:45
  Speaker 2: can learn just as much independently, in fact, that they
• 46:49
  Speaker 2: would learn more in a work situation. They are therefore
• 46:55
  Speaker 2: the social experience, and to be around a bunch of
• 46:58
  Speaker 2: people of their own age sort of a coming of
• 47:03
  Speaker 2: age social experience.
• 47:04
  Speaker 5: Sure, sure, being on your own learning how to how
• 47:07
  Speaker 5: to lead or defend yourself as the case maybe.
• 47:10
  Speaker 2: Well yeah, I mean, if you join the workforce, you're
• 47:12
  Speaker 2: you know, from this perspective of like a you know,
• 47:14
  Speaker 2: a nineteen year old with a bunch of old people.
• 47:18
  Speaker 2: And if you're doing engineering with a bunch of middle
• 47:20
  Speaker 2: aged dudes, it's like, do you really want to do
• 47:22
  Speaker 2: that or do you want to hang out with you know,
• 47:26
  Speaker 2: whether it does at least some girls your age type
• 47:30
  Speaker 2: of thing.
• 47:32
  Speaker 4: Get want to get back to this when we talk about.
• 47:35
  Speaker 3: A lot of other choices.
• 47:36
  Speaker 5: Actually I want to get back as we get to
• 47:38
  Speaker 5: universal high income but I want to talk about health
• 47:41
  Speaker 5: in line, jebany one second, US is the number one
• 47:44
  Speaker 5: ranked number one in health expenses worldwide, and it's ranked
• 47:48
  Speaker 5: seventieth in health span A.
• 47:52
  Speaker 2: Right, do you really seventieth?
• 47:53
  Speaker 4: Seventieth?
• 47:55
  Speaker 3: Is that is that accurate? Itat? So it sounds like.
• 48:01
  Speaker 2: I think would be better than seventy.
• 48:02
  Speaker 8: It's for health spat Yeah, well whatever, it's it sounds
• 48:07
  Speaker 8: like we just get fat or not the top a
• 48:09
  Speaker 8: zampa can help us find the rankings there, so you
• 48:13
  Speaker 8: just run around.
• 48:14
  Speaker 2: We need Cupid with a zampicar coupid. But I think
• 48:26
  Speaker 2: that's a big reason. It's like if people get really fat,
• 48:28
  Speaker 2: then their health gets bad.
• 48:30
  Speaker 5: Yeah, well, if you don't have any exercise help get bad.
• 48:32
  Speaker 5: Or if they donuts for breakfast every morning, you're still
• 48:35
  Speaker 5: doing that?
• 48:36
  Speaker 3: Uh no, actually I'm not.
• 48:38
  Speaker 4: Okay, that's good.
• 48:39
  Speaker 2: Uh Well, first of all, I wasn't eating a lot
• 48:41
  Speaker 2: of donut. I was trying to have a point four
• 48:44
  Speaker 2: of a donut, which rounds down to zero. Still fig
• 48:51
  Speaker 2: anything blow blow point four four of a donut rounds
• 48:55
  Speaker 2: down to zero.
• 48:55
  Speaker 5: So you and I have had a disagreement on longevity
• 49:00
  Speaker 5: a little bit. Yeah, I was saying you know, we
• 49:03
  Speaker 5: should push to get people to one hundred and twenty
• 49:05
  Speaker 5: hundred and fifty. And you were saying people, you know,
• 49:08
  Speaker 5: should shouldn't live back war.
• 49:12
  Speaker 2: So how long do you want Yeah, you know there's
• 49:14
  Speaker 2: some you know, people in the world that have done
• 49:17
  Speaker 2: some bad things.
• 49:17
  Speaker 3: How long do you want them to live?
• 49:18
  Speaker 4: Yeah, Well it's okay.
• 49:20
  Speaker 3: Well it's going to get different. It's a serious question them.
• 49:24
  Speaker 3: A lot of things are going to happen that we don't.
• 49:27
  Speaker 5: You said one thing that you said was interesting. You said,
• 49:31
  Speaker 5: we need people to die so people change their minds.
• 49:34
  Speaker 2: Oh yes, and people don't change their minds, but so
• 49:38
  Speaker 2: makes more sense.
• 49:39
  Speaker 5: My response to that was, you know, my response that
• 49:43
  Speaker 5: was the head of GM didn't have to die for
• 49:45
  Speaker 5: Tesla to come along, and Lockheed and Northrope and Boeing
• 49:48
  Speaker 5: did enough to go away for I mean, there's in
• 49:50
  Speaker 5: a meritocracy, the better ideas will dominate. So I'm hoping
• 49:58
  Speaker 5: that I can get you back onto the longevity train.
• 50:01
  Speaker 5: So there's a lot going on Lunchev right now. Right
• 50:04
  Speaker 5: like what, Well, David Sinclair is about to start his
• 50:08
  Speaker 5: epigenetic reprogramming trials and humans.
• 50:10
  Speaker 4: It's worked in animals and non human primates. It's going
• 50:15
  Speaker 4: into how.
• 50:15
  Speaker 2: To human psychopol or injectionable right now.
• 50:18
  Speaker 5: It's an injection of an ad NO associated virus. It's
• 50:21
  Speaker 5: the three amanakafactors.
• 50:23
  Speaker 3: Ok.
• 50:24
  Speaker 5: We've got a one hundred and one million dollar health
• 50:27
  Speaker 5: Span X Prize that's working on seven hundred and thirty
• 50:30
  Speaker 5: teams working on reversing the age of your brain, immune system,
• 50:34
  Speaker 5: and muscle by twenty years. By the way, you know
• 50:37
  Speaker 5: why it's one hundred and one million dollars because the
• 50:40
  Speaker 5: primary funder when they found out your carbon X Prize
• 50:43
  Speaker 5: is one hundred bucks. You wanted to make it bigger,
• 50:45
  Speaker 5: so it's one hundred and one.
• 50:46
  Speaker 3: Oh.
• 50:48
  Speaker 4: It was Chip Wilson from Lululemon.
• 50:49
  Speaker 5: Oh, and then and then evolution out of but chips say,
• 50:52
  Speaker 5: can we make it bigger? I said, you put extra
• 50:54
  Speaker 5: million and will make one hundred and one million. It's
• 50:56
  Speaker 5: a good story. But then we've got folks like dari
• 50:58
  Speaker 5: Amiday predicting doubling the human life span in the next
• 51:03
  Speaker 5: ten years.
• 51:04
  Speaker 3: So that's probably correct.
• 51:08
  Speaker 4: Okay, great, I don't know about doubling, but significant.
• 51:13
  Speaker 3: Which is easily escape velocity, I mean yeah, hold you,
• 51:20
  Speaker 3: oh yeah, for sure for effective age.
• 51:23
  Speaker 4: Yeah, yeah, yeah, so I think you know, I think that.
• 51:27
  Speaker 3: Too much to turn into a baby. I'm telling all
• 51:29
  Speaker 3: the students.
• 51:30
  Speaker 2: So it's like, Peter, what happened? There is a frozen
• 51:40
  Speaker 2: zero wrong on the dosage, just a small.
• 51:48
  Speaker 3: Grow out of it exactly. You won't remember literally.
• 51:55
  Speaker 2: I mean it wouldn't it be funny if we do
• 51:57
  Speaker 2: this in like ten years? Okay, we shouldn't, I'll do
• 52:01
  Speaker 2: We'll do it in ten years for sure, and see
• 52:04
  Speaker 2: see if we look younger.
• 52:07
  Speaker 3: It's a good side.
• 52:07
  Speaker 4: That was always you want back then.
• 52:11
  Speaker 5: Elon was like, you know, late forties, Wait till he
• 52:13
  Speaker 5: gets into his sixties, he's gonna want you know, want
• 52:16
  Speaker 5: drive anymore.
• 52:17
  Speaker 3: I mean I want things to not hurt.
• 52:20
  Speaker 4: Sure.
• 52:22
  Speaker 2: It's like it's like basically it's it seems like it's
• 52:24
  Speaker 2: only a matter of time before you get back to
• 52:26
  Speaker 2: back pain. Yeah, like it's a way, not an if
• 52:30
  Speaker 2: when your backgrounds arthritis.
• 52:32
  Speaker 4: Yes, yeah, like all those things suck.
• 52:34
  Speaker 2: Basically being able to sleep through the night without going
• 52:37
  Speaker 2: to the bathroom.
• 52:40
  Speaker 3: A lot. That one.
• 52:43
  Speaker 2: Yeah, more than hope that one. Oh man, that would
• 52:49
  Speaker 2: that's like the infinite money one.
• 52:53
  Speaker 4: Why did you invest in longevity? I can sleep, inthroom,
• 52:57
  Speaker 4: flatter bladder.
• 52:58
  Speaker 2: Yeah, durature, I mean admitted if you have to wear
• 53:03
  Speaker 2: adult divers that's a bummer.
• 53:06
  Speaker 3: That's not good that it is a real.
• 53:13
  Speaker 2: You know, it's like one of the one of the
• 53:14
  Speaker 2: signs that country is not on the right path. Just
• 53:19
  Speaker 2: when they all dipers exceed the baby divers, Yeah we're there. Yeah,
• 53:24
  Speaker 2: Health Korea will be there and they already know the
• 53:26
  Speaker 2: play past that point. They passed that past point many
• 53:29
  Speaker 2: years ago. Japan passed the point many years ago.
• 53:31
  Speaker 3: Doesn't go well, look at the Japanese economy.
• 53:34
  Speaker 2: No, I mean like South Korea is like uh point
• 53:37
  Speaker 2: one yeah, one could replacement.
• 53:39
  Speaker 4: Right, yeah, it's crazy.
• 53:40
  Speaker 2: Yeah, so three generations, they're gonna be one twenty seventh,
• 53:43
  Speaker 2: so three three percent of their current size.
• 53:45
  Speaker 3: I mean North Korea won't need to invade. They could
• 53:47
  Speaker 3: just walk across. Yeah.
• 53:48
  Speaker 2: Yeah, this is going to be some people and you
• 53:55
  Speaker 2: know walkers or something like going to be.
• 53:58
  Speaker 3: A bunch of optimists robuts.
• 54:01
  Speaker 5: But you you know, you've been very verbal about the
• 54:04
  Speaker 5: you know, the not overpopulation but massive underpopulation.
• 54:08
  Speaker 3: Yeah, stageous.
• 54:09
  Speaker 5: Yeah, longevity is going to be an important part of
• 54:12
  Speaker 5: that solution. I also think by the way, if you
• 54:14
  Speaker 5: increased the productive life of most Americans by just a
• 54:19
  Speaker 5: few years, you'd flip the entire economics here.
• 54:22
  Speaker 2: Well, if you're willing to worry and robust is going
• 54:24
  Speaker 2: to make everything sure pre you basically Yeah, but well,
• 54:30
  Speaker 2: how long would you want to live?
• 54:32
  Speaker 5: I want to I want to go, you know, other
• 54:36
  Speaker 5: planetary systems. I want to go and explore the university. Yeah,
• 54:39
  Speaker 5: I mean, you know, I would like to double my
• 54:41
  Speaker 5: lifespan for sure.
• 54:43
  Speaker 4: I don't want, you know, I'm not sure.
• 54:44
  Speaker 5: I wanted to talk about immortality, but you know, at
• 54:47
  Speaker 5: least forever twenty one hundred and fifties a long time.
• 54:49
  Speaker 2: One of the worst courses possible would be.
• 54:50
  Speaker 4: That, yes, may you live forever.
• 54:52
  Speaker 2: May you live forever? Yeah, that would be one of
• 54:54
  Speaker 2: the worst Yeah, curses you could possibly give anyone.
• 54:58
  Speaker 4: But I think life can get very interesting. Yeah, far more.
• 55:02
  Speaker 5: We're going to speed run Star Trek, as my partner
• 55:05
  Speaker 5: Alex Weisner Gros says, Yeah.
• 55:08
  Speaker 2: Speed running Star truck would be cool.
• 55:10
  Speaker 3: Yeah. Well, at a minimum, your kids will have infinite
• 55:14
  Speaker 3: life expectancy. If you're talking about escape velocity, If you
• 55:17
  Speaker 3: can double lifespan, there's it's not even close, You're you're
• 55:19
  Speaker 3: clearly past longevity escape velocity. They the idea of fifty
• 55:25
  Speaker 3: years of AI improvement.
• 55:26
  Speaker 4: Yeah, it's like, I mean, we're gonna have ye.
• 55:29
  Speaker 3: I don't know.
• 55:30
  Speaker 2: I got too many fish to fry, so I invited.
• 55:32
  Speaker 2: This is something by the way that I that I think.
• 55:35
  Speaker 2: I just I think it's very obviously other people think
• 55:37
  Speaker 2: this too, But I've long quote that like like longevity
• 55:42
  Speaker 2: or semi immortality is an extremely solvable problem. I don't
• 55:45
  Speaker 2: think it's a particularly hot problem. I mean, when you
• 55:52
  Speaker 2: consider the fact that your body is extremely synchronized in
• 55:58
  Speaker 2: its age, Yep, the clock must be incredibly obvious. Nobody
• 56:05
  Speaker 2: has an old left hom and a young right home right.
• 56:07
  Speaker 3: Why is that? Yeah?
• 56:11
  Speaker 2: What's keeping them all in sync? Your program to die.
• 56:18
  Speaker 2: That's the way there. Programs die. And so if you
• 56:21
  Speaker 2: change the program, you will live longer.
• 56:24
  Speaker 5: And we've got you know, species of the bowhead whale
• 56:27
  Speaker 5: can lift for two hundred years. The greenland shark lift
• 56:29
  Speaker 5: for five hundred years. And when I when I learned that,
• 56:32
  Speaker 5: I said, why can't they? Why can't we? And I said,
• 56:34
  Speaker 5: it's either a hardware problem or software problem. And we're
• 56:37
  Speaker 5: going to have the tech to solve that, and I
• 56:38
  Speaker 5: do believe that it's this next decade. So the important
• 56:42
  Speaker 5: thing is not to die from something stupid before that,
• 56:44
  Speaker 5: before the solutions come. You know, I invited you.
• 56:48
  Speaker 2: In retrospect, the solution to longevity will seem obvious, extremely obvious.
• 56:54
  Speaker 3: I think the thing worth working on, Peter is going
• 56:57
  Speaker 3: to work on this anyway. But the thing to work
• 56:58
  Speaker 3: on is exactly what you said. If old ideas don't calcified,
• 57:04
  Speaker 3: old ideas don't just die off. Add that to the
• 57:08
  Speaker 3: pile of things we need to think about today, because
• 57:10
  Speaker 3: our whole host of other AI related things we need
• 57:12
  Speaker 3: to think about today.
• 57:14
  Speaker 5: Let me finish on the lunevity point one second, Elan,
• 57:18
  Speaker 5: I want to invite you again. So there's a company
• 57:22
  Speaker 5: called Fountain Life that I created with Tony Robbins, Bob Hurry, Billkapp,
• 57:28
  Speaker 5: and we do a two gigabyte upload of you, everything
• 57:32
  Speaker 5: knowable about you, full genome, full all imaging, everything right.
• 57:37
  Speaker 5: President bu Kelly and the first lady came through called
• 57:39
  Speaker 5: it an amazing ten out of ten experience. I think
• 57:43
  Speaker 5: I don't want you to pull a Steve.
• 57:45
  Speaker 3: Jobs and kick the bucket because of some.
• 57:48
  Speaker 5: Because something they didn't know. I mean, so if you
• 57:50
  Speaker 5: ask yourself, if you're do you actually know what's going
• 57:52
  Speaker 5: on inside your body?
• 57:53
  Speaker 4: Right now?
• 57:55
  Speaker 3: I did an.
• 57:56
  Speaker 2: MRI recently and submitted to crock and that it didn't
• 58:00
  Speaker 2: need But that's none of the doctors, no rock A
• 58:03
  Speaker 2: found anything.
• 58:04
  Speaker 5: But that's a fraction of the information, right, I mean,
• 58:06
  Speaker 5: it's your full genome, your microbiome, metabolaum everything, and okay,
• 58:11
  Speaker 5: it's possible.
• 58:13
  Speaker 4: So what's that?
• 58:14
  Speaker 3: Don't plum me, bro.
• 58:17
  Speaker 4: We have a cent we have a center into your water.
• 58:22
  Speaker 3: Goddamn it too late the works.
• 58:31
  Speaker 5: So can you go through the rationale of uhr, how
• 58:36
  Speaker 5: does how does universal high income work?
• 58:39
  Speaker 2: Okay, so there's going to be more intelligence digital intelligence
• 58:46
  Speaker 2: than all human intelligence combined, and more humanoid robots than
• 58:51
  Speaker 2: all humans. And assuming we're in a nine scenario star
• 58:56
  Speaker 2: Trek Roddenberry not Cameron situation.
• 58:59
  Speaker 4: Yeah, poor Jim.
• 59:03
  Speaker 2: Yeah, I mean, I guess it's important to have.
• 59:05
  Speaker 4: These sort of counterpoints.
• 59:08
  Speaker 2: Yeah, let's not let's not go in that direction.
• 59:13
  Speaker 3: Thing. So the robots are going to just do whatever
• 59:19
  Speaker 3: you want.
• 59:19
  Speaker 5: All the blue collar labor is being done by robots,
• 59:22
  Speaker 5: All data centers are.
• 59:23
  Speaker 2: Being well, the the white collar labor will be the
• 59:27
  Speaker 2: first first to go because until you until you can
• 59:30
  Speaker 2: move atoms, the thing that can be replaced first is
• 59:34
  Speaker 2: anything that involves just digital. If it's digital, like if
• 59:39
  Speaker 2: it involves tapping keys on a keyboard and moving a mouse,
• 59:44
  Speaker 2: the computer can do that.
• 59:46
  Speaker 3: Y I can do that.
• 59:47
  Speaker 2: Sure, you need the humanoid robots to shape atoms. So
• 59:52
  Speaker 2: if all you're doing is changing best of information, which
• 59:55
  Speaker 2: is why color work, that is that is the first
• 59:59
  Speaker 2: thing that that.
• 1:00:00
  Speaker 5: When this is the inspiration, This is the inspirational part
• 1:00:03
  Speaker 5: of the podcast. When when is when is all white
• 1:00:07
  Speaker 5: collar work gone by?
• 1:00:08
  Speaker 2: When well, there's there's there's a lot of inertia. So
• 1:00:12
  Speaker 2: even with AI at its current state, I'd say you're
• 1:00:16
  Speaker 2: you're pretty close to being able to replace half of
• 1:00:20
  Speaker 2: all jobs. And you know that white colors. Then there's
• 1:00:24
  Speaker 2: anything like education too. So anything that involves information and
• 1:00:32
  Speaker 2: anything short of shaping atoms, AI can do probably half
• 1:00:40
  Speaker 2: or more of those jobs right now. Sure, but there's
• 1:00:42
  Speaker 2: a lot of inertia. People just keep doing the same,
• 1:00:45
  Speaker 2: the same thing for quite some time. And there actually
• 1:00:49
  Speaker 2: has to be a a company that makes more use
• 1:00:53
  Speaker 2: of AI that competes with a company that makes less
• 1:00:56
  Speaker 2: use of AI, creating a force thing function for increased
• 1:01:00
  Speaker 2: use of AI. Right, Otherwise, the company that that still
• 1:01:05
  Speaker 2: has humans do things that AI can do will still
• 1:01:09
  Speaker 2: continue to exist. Being a computer used to be a job.
• 1:01:12
  Speaker 2: So it used to be that a human computer like
• 1:01:15
  Speaker 2: what like yea a computer. Being a computer was a job.
• 1:01:18
  Speaker 2: You would compute numbers. Sure, it didn't. It didn't used
• 1:01:21
  Speaker 2: to be a machine. It used to be a job description.
• 1:01:24
  Speaker 2: And there you can look online there's these pictures of
• 1:01:27
  Speaker 2: like where they're having like skyscrapers full.
• 1:01:31
  Speaker 5: Of women copying, mostly women copying from Ledger to Legerto.
• 1:01:35
  Speaker 2: But yeah, people, but it was a lot of women.
• 1:01:41
  Speaker 2: But there's there were there were just buildings full of
• 1:01:45
  Speaker 2: people just at disks doing calculations. So they'd be calculating
• 1:01:51
  Speaker 2: the interest in your bank account or you know some
• 1:01:57
  Speaker 2: you know science experiment or something like that, or but
• 1:02:03
  Speaker 2: if you want calculations done, people would do it.
• 1:02:07
  Speaker 3: So now.
• 1:02:12
  Speaker 2: One laptop with a spreadsheet can outperform a skyscraper of
• 1:02:18
  Speaker 2: several hundred human computers of people doing calculations. Now, if
• 1:02:25
  Speaker 2: even a few cells in that spreadsheet were done manually,
• 1:02:32
  Speaker 2: you would not be able to compete with a spreadsheet
• 1:02:35
  Speaker 2: that was entirely a computer.
• 1:02:38
  Speaker 3: Yeah.
• 1:02:39
  Speaker 2: What this means is that companies that are entirely AI
• 1:02:44
  Speaker 2: will demolish companies that are not. It won't be a
• 1:02:48
  Speaker 2: context agreed.
• 1:02:49
  Speaker 3: And that's flipping just one cell and that just one.
• 1:02:55
  Speaker 2: Sell in your spreadsheets to be manually calculated. That would
• 1:02:59
  Speaker 2: be the most annoying out and and and gets it wrong.
• 1:03:04
  Speaker 3: A bunch of time.
• 1:03:07
  Speaker 2: So this flipping, flipping flipping, are we monetizing hope effectively?
• 1:03:14
  Speaker 4: Yes? Not this moment. I think we're I think we're peak.
• 1:03:19
  Speaker 4: I think we're peak doube for people worried about the
• 1:03:21
  Speaker 4: future of their jobs. We're at peak doom.
• 1:03:26
  Speaker 3: We're going to do that T shirt and a mug
• 1:03:30
  Speaker 3: and a mug.
• 1:03:34
  Speaker 4: Yes, uh so, But but you have the solution. You
• 1:03:39
  Speaker 4: have a solution to this, which is U a try.
• 1:03:43
  Speaker 3: Yes, everyone can have whatever they want.
• 1:03:45
  Speaker 4: So how does that work? How does you a try?
• 1:03:48
  Speaker 2: It's a good question, like we have to figure out
• 1:03:49
  Speaker 2: some like I mean, it's trying to read it, it's
• 1:03:51
  Speaker 2: not to read.
• 1:03:53
  Speaker 5: Yeah, I mean, so my concern isn't the long run,
• 1:03:55
  Speaker 5: it's the next three to seven years.
• 1:03:58
  Speaker 2: Yes, the transition will be bumpy.
• 1:04:02
  Speaker 3: Humans don't like simultaneously.
• 1:04:04
  Speaker 2: Yes, we'll have radical change, social unrest, and immense prosperity.
• 1:04:10
  Speaker 4: And you can buy all all the cyber trucks you want.
• 1:04:13
  Speaker 3: Things are gonna get very cheap. Yes, so this is actually.
• 1:04:20
  Speaker 2: In factly, if this doesn't happen, we'd go bankrupt as
• 1:04:24
  Speaker 2: a country. So the national debt is enormous. Uh, the
• 1:04:28
  Speaker 2: interest on the national debt exceeds uh, not just the
• 1:04:32
  Speaker 2: military budget, but the military budget, I think plus Medicare
• 1:04:39
  Speaker 2: or medicaid, one of the two. It's like like it's
• 1:04:41
  Speaker 2: it's it's like one point they trillion.
• 1:04:45
  Speaker 4: It's of interest, which is growing, yes, and the deficit
• 1:04:49
  Speaker 4: is growing.
• 1:04:52
  Speaker 2: But the so, so if we don't have AI in robots,
• 1:04:57
  Speaker 2: we're all going to go bankrupt and and and and
• 1:04:59
  Speaker 2: we're headed forward economic doom.
• 1:05:02
  Speaker 3: We're going to competitive pressure from Chinas. This is definitely
• 1:05:05
  Speaker 3: going to happen.
• 1:05:06
  Speaker 4: I guess we're going back to the theme of this talk.
• 1:05:08
  Speaker 5: How can AI and exponential tech save America and the world.
• 1:05:13
  Speaker 3: Don't you think that?
• 1:05:14
  Speaker 4: But I want I want to I want to hit
• 1:05:15
  Speaker 4: this because I was like.
• 1:05:16
  Speaker 2: Quite festimistic about it and and ultimately I decided to
• 1:05:19
  Speaker 2: be fatalistic and look on the right side. I've got
• 1:05:26
  Speaker 2: to crucified.
• 1:05:37
  Speaker 4: But this is not about taxation and redistribution.
• 1:05:40
  Speaker 3: No, it's.
• 1:05:42
  Speaker 4: So how how does this reason through it with me?
• 1:05:45
  Speaker 2: Listen, By the way, I'm open to ideas here.
• 1:05:47
  Speaker 4: Okay, So it's not like I got this. We'll figure
• 1:05:49
  Speaker 4: out all right.
• 1:05:50
  Speaker 5: So so I'm wondering if instead of universal high income,
• 1:05:54
  Speaker 5: if it's universal universal high stuff and services.
• 1:05:59
  Speaker 3: Yeah, y.
• 1:06:01
  Speaker 2: U hs s like I guess, okay, this is my
• 1:06:06
  Speaker 2: guess for how things.
• 1:06:09
  Speaker 3: Play out.
• 1:06:10
  Speaker 2: And I by the way I'm this is this is
• 1:06:12
  Speaker 2: going to be a bumpy ride. And it's not like
• 1:06:14
  Speaker 2: I know the answers here, but I have decided to
• 1:06:18
  Speaker 2: look on the bright side. Uh And and I'd like
• 1:06:21
  Speaker 2: to thank thank you guys for being an inspiration in
• 1:06:24
  Speaker 2: this regard.
• 1:06:24
  Speaker 3: Thank you happy hop Yeah.
• 1:06:29
  Speaker 2: Because I actually think it's it is better to be
• 1:06:33
  Speaker 2: an optimist and wrong than a pessimist and right.
• 1:06:36
  Speaker 3: Yes, for sure, for quality of life. By the way,
• 1:06:39
  Speaker 3: that's also not a force of nature. It's under like
• 1:06:43
  Speaker 3: to me, it's really clear that we don't have any
• 1:06:45
  Speaker 3: system right now to make this go well. But AI
• 1:06:49
  Speaker 3: is a critical part of making a go well. And
• 1:06:53
  Speaker 3: at some point GROC is going to be addressing this
• 1:06:56
  Speaker 3: exact topic that we're talking about. We have to be
• 1:06:58
  Speaker 3: one of the big four AI machine. I mean it's coming, dealing.
• 1:07:03
  Speaker 5: With it philosophy, right, there's no on off switch. It
• 1:07:08
  Speaker 5: is coming and accelerating.
• 1:07:12
  Speaker 2: I call AI and robotics the supersonic tsunami. Yes, which
• 1:07:16
  Speaker 2: maybe is a little Allarmmy think it's good because the
• 1:07:21
  Speaker 2: wake up.
• 1:07:22
  Speaker 5: This is important for folks to to GROCK because Ah,
• 1:07:29
  Speaker 5: I don't want to leave people depressed. I want people
• 1:07:33
  Speaker 5: to understand what's coming. So we're we're basically demonetizing everything.
• 1:07:38
  Speaker 5: I mean, labor becomes the cost of capex and electricity.
• 1:07:41
  Speaker 5: AI is basically intelligence available at a deminimous price. Uh
• 1:07:51
  Speaker 5: so you're able to produce almost anything. Things get down
• 1:07:55
  Speaker 5: to basic costs of materials and electricity. Right, so people
• 1:08:01
  Speaker 5: can have whatever stuff they want, whatever services they need.
• 1:08:06
  Speaker 5: It's not when when we say universal high income, it
• 1:08:09
  Speaker 5: sounds like it's a tax and redistribute.
• 1:08:10
  Speaker 4: But that's not the case.
• 1:08:13
  Speaker 2: It's I think my best guess for how this will
• 1:08:16
  Speaker 2: manifest is that prices will become prices will drop, so
• 1:08:21
  Speaker 2: as the efficiency of production or the provision of services drops,
• 1:08:28
  Speaker 2: prices will draw. I mean, you know, prices in dollar
• 1:08:32
  Speaker 2: terms are the ratio between the output of goods and
• 1:08:36
  Speaker 2: services and the money supply. Sure, so if your output
• 1:08:39
  Speaker 2: of goods and services increases fast than the money supply,
• 1:08:41
  Speaker 2: you will have deflation or vice versa.
• 1:08:45
  Speaker 3: You know. So the good thing we're growing the money
• 1:08:48
  Speaker 3: supply so quickly then.
• 1:08:49
  Speaker 2: Right, Yes, that's why I can't like, let's not worry
• 1:08:54
  Speaker 2: about growing the money spply won't matter because the output
• 1:08:57
  Speaker 2: of goods and services actually will grow faster than the
• 1:08:59
  Speaker 2: money supply. And I think we'll be in this And
• 1:09:02
  Speaker 2: this is a prediction I think some others have made,
• 1:09:04
  Speaker 2: but I will add to it, which is that that
• 1:09:09
  Speaker 2: I think a musill we'll actually be pushing to increase
• 1:09:12
  Speaker 2: money supply, like like faster. Yes, they won't be able
• 1:09:18
  Speaker 2: to waste the money fast enough. What you're saying something,
• 1:09:21
  Speaker 2: isn't it?
• 1:09:21
  Speaker 3: Isn't it crazy how close those timelines just randomly worked out?
• 1:09:24
  Speaker 3: I mean, at the rate because we're expanding the national debt,
• 1:09:27
  Speaker 3: not because we're anticipating AI. We were going to do
• 1:09:30
  Speaker 3: that no matter what. Yes, And it's like right on
• 1:09:32
  Speaker 3: the edge of becoming Argentina.
• 1:09:34
  Speaker 2: But yeh, productivity is can improve dramatically, and it is
• 1:09:39
  Speaker 2: improving dramatically. I think we'll see I think I think
• 1:09:44
  Speaker 2: we may see high, like high double digit output of
• 1:09:49
  Speaker 2: goods and services. Bettle careful about how economous measure things? Yes,
• 1:09:54
  Speaker 2: and yeah, it's I mean, it's like my favorite joke.
• 1:10:00
  Speaker 2: I have a few economist jokes that I that I like,
• 1:10:03
  Speaker 2: but maybe my favorite one economist joke is two economists
• 1:10:08
  Speaker 2: are going for walking in the forest and they come
• 1:10:11
  Speaker 2: across a pile of ship, and what economist is, I'll
• 1:10:14
  Speaker 2: pay you a hundred bucks.
• 1:10:15
  Speaker 3: To eat a Polish.
• 1:10:19
  Speaker 2: Great and so the guy takes a hundred bucks, eats
• 1:10:24
  Speaker 2: the ship.
• 1:10:27
  Speaker 3: Then they keep walking.
• 1:10:28
  Speaker 2: They come across another pile of ship, and the other
• 1:10:31
  Speaker 2: guy says, okay, I'll give you one hundred bucks to
• 1:10:33
  Speaker 2: eat a Polish. He gives them a hundred bucks, and
• 1:10:39
  Speaker 2: then the guys can say, wait a second. We both
• 1:10:42
  Speaker 2: have the same amount of money.
• 1:10:47
  Speaker 3: And we both ate a Polish.
• 1:10:49
  Speaker 2: Oh my god, it sounds like, but we increase the
• 1:10:51
  Speaker 2: economy by two hundred dollars. This is the kind of
• 1:10:55
  Speaker 2: bullshit you get an economic so h but if you
• 1:10:59
  Speaker 2: if so, if you say, like just the output of
• 1:11:02
  Speaker 2: goods and services, they will be a much greater like
• 1:11:07
  Speaker 2: you just need.
• 1:11:08
  Speaker 4: To so profitability of companies go through the roof at
• 1:11:12
  Speaker 4: some point. But no, But so the question becomes is
• 1:11:14
  Speaker 4: that taxed by the government.
• 1:11:16
  Speaker 5: Is that then taxed by the government and redistributed as
• 1:11:19
  Speaker 5: some level of income as a as a UHI or UBI.
• 1:11:23
  Speaker 5: In other words, one of the questions is if in
• 1:11:26
  Speaker 5: fact this future we hit massive productivity and massive profitability
• 1:11:30
  Speaker 5: because we're dividing by zero, the cost of labor has
• 1:11:32
  Speaker 5: gone to nothing, the cost of intelligence is gone to nothing,
• 1:11:35
  Speaker 5: and we're still producing products and services faster and faster.
• 1:11:37
  Speaker 5: So there's more profitability. Someone needs to be buying it,
• 1:11:41
  Speaker 5: and someone needs to be able to have the capital
• 1:11:42
  Speaker 5: to buy it. I mean, this is an important question
• 1:11:48
  Speaker 5: to get to get thought through.
• 1:11:51
  Speaker 2: Yeah. Well, one like side recommendation I have is like,
• 1:11:55
  Speaker 2: don't worry about like squirreling money away for retirement in
• 1:11:58
  Speaker 2: like ten or twenty years in one matter.
• 1:12:00
  Speaker 4: Yeah, Okay, either either we're not going to be here
• 1:12:05
  Speaker 4: or it.
• 1:12:06
  Speaker 2: Just like it's it's you won't need to say for
• 1:12:10
  Speaker 2: retirement if any of the things that we've said are true,
• 1:12:14
  Speaker 2: saving for retirement will be irrelevant.
• 1:12:15
  Speaker 5: The services services will be there to support you. You'll
• 1:12:19
  Speaker 5: have the home, you'll have the healthcare, you'll have the entertainment.
• 1:12:24
  Speaker 3: The way this unfolds is fundamentally impossible to predict because
• 1:12:28
  Speaker 3: of self improvement of the AI and the accelerating timeline.
• 1:12:33
  Speaker 2: Yeah, exactly what goes happening? What what happens after after
• 1:12:36
  Speaker 2: the vent horizing?
• 1:12:37
  Speaker 3: Exactly? You can never see past the black hole or
• 1:12:40
  Speaker 3: the event horizon.
• 1:12:40
  Speaker 5: The light gone ray has a singularity out way too far.
• 1:12:44
  Speaker 5: I mean, this is like the next what what's your
• 1:12:47
  Speaker 5: timeline for this?
• 1:12:49
  Speaker 2: We're in the singularity.
• 1:12:50
  Speaker 5: Well, we are in the singularity for sure. We're in
• 1:12:51
  Speaker 5: the midst of it right now for sure, and we're.
• 1:12:54
  Speaker 3: In this beautiful sweet spot, which is you know, the
• 1:12:57
  Speaker 3: the roller coasters were just yeah exactly. That's a great analogy.
• 1:13:00
  Speaker 2: It's like that feeling at the top of the roller
• 1:13:02
  Speaker 2: coaster and you about to go yeah.
• 1:13:03
  Speaker 3: But you know it's gonna be a lot of g's
• 1:13:05
  Speaker 3: when you yeah, a lot of hit it now, and
• 1:13:08
  Speaker 3: it's like, feel.
• 1:13:09
  Speaker 2: Like, I don't have just have court side seats. I'm
• 1:13:10
  Speaker 2: on the court exactly, and it blows my and still
• 1:13:13
  Speaker 2: blows my mind sometimes multiple times a week.
• 1:13:17
  Speaker 3: Yeah.
• 1:13:18
  Speaker 2: And so just when I think I'm like wow, and
• 1:13:23
  Speaker 2: then it's like two days.
• 1:13:25
  Speaker 4: Later more wow, Yeah, exponential Wow.
• 1:13:30
  Speaker 3: Yeah. I think we'll hit age I next year in
• 1:13:33
  Speaker 3: twenty six Yeah.
• 1:13:34
  Speaker 4: I heard you say that.
• 1:13:35
  Speaker 3: Yeah, I've said that for a while.
• 1:13:36
  Speaker 5: And then you know, and then you said, by twenty
• 1:13:39
  Speaker 5: twenty nine, twenty thirty equivalent to the entire human rights
• 1:13:42
  Speaker 5: twenty we exceeed.
• 1:13:44
  Speaker 2: I I'm confident by twenty thirty a I will exceed
• 1:13:49
  Speaker 2: the intelligence of all humans combined.
• 1:13:51
  Speaker 3: That's way pessimistic. If you hit a g I next year,
• 1:13:55
  Speaker 3: and that's that's you know, that date is is in flux.
• 1:13:57
  Speaker 3: But from that date to self and provements that are
• 1:14:00
  Speaker 3: on the order of one thousand and ten thousand x
• 1:14:02
  Speaker 3: just algorithmic improvements is very short.
• 1:14:05
  Speaker 4: And so why everybody, why is nobody talking about this
• 1:14:09
  Speaker 4: right now?
• 1:14:10
  Speaker 3: Well, I mean on.
• 1:14:12
  Speaker 4: Our next yes, but why every day basically? Yeah, But
• 1:14:17
  Speaker 4: it's just up that it's.
• 1:14:20
  Speaker 2: Not okay, So I'll tell you something else that I'll
• 1:14:22
  Speaker 2: tell you something that most people in the AI community
• 1:14:26
  Speaker 2: don't yet understand, okay, which is there almost no understands
• 1:14:32
  Speaker 2: this the intelligence density potential is vastly greater than what
• 1:14:38
  Speaker 2: we're currently experiencing. So I think we're off by tourism
• 1:14:43
  Speaker 2: magitude in terms of the intelligence density per gigabyte.
• 1:14:47
  Speaker 4: But what's achievable, yes, per giggle wide of.
• 1:14:50
  Speaker 2: Energy for I'm so trans file size okay, if the
• 1:14:55
  Speaker 2: file size of the A if you if you have
• 1:14:57
  Speaker 2: a say intelligence.
• 1:14:58
  Speaker 4: Going okay, yes on your on your characters to power to.
• 1:15:03
  Speaker 3: But it's just a parameters the same thing whatever. So
• 1:15:07
  Speaker 3: two orders of magnitude, yes, yeah, and you like you said,
• 1:15:11
  Speaker 3: you ring side courtside seat, you would know that's it.
• 1:15:15
  Speaker 3: It's it's it's yes, yeah, towards the magnitude improvement. And
• 1:15:22
  Speaker 3: that's just just algorithmic improvement, same computer. And the computers
• 1:15:26
  Speaker 3: are getting better, yeah, so and bigger, you know see
• 1:15:29
  Speaker 3: they're getting better, and the budgets are getting bigger.
• 1:15:31
  Speaker 2: So that I can think, I think it's it is on.
• 1:15:35
  Speaker 2: It is like a ten x improvement per your type
• 1:15:39
  Speaker 2: of thing, thousand percent yeah, and that and that's going
• 1:15:42
  Speaker 2: to happen for yeah, for the foreseeable future.
• 1:15:46
  Speaker 3: So you see the massive underreaction, like if you walk
• 1:15:49
  Speaker 3: downtown Austin, the massive I mean maybe under discussion and X,
• 1:15:56
  Speaker 3: but it's not percolating.
• 1:15:57
  Speaker 5: It's not discussion in any realm of government. Everybody is
• 1:16:01
  Speaker 5: like defending their position about where we are and jobs
• 1:16:04
  Speaker 5: and this, but it's it's like we're heading towards a
• 1:16:09
  Speaker 5: the super center supersidic economy and and uh, I mean
• 1:16:14
  Speaker 5: every every you know, every major CEO and economist and
• 1:16:19
  Speaker 5: government leaders should be like, what do we do because
• 1:16:22
  Speaker 5: once it hits.
• 1:16:26
  Speaker 3: Well, it's coming at the exact same time there no
• 1:16:29
  Speaker 3: matter what, there's no there's no concept of let's deliberately
• 1:16:34
  Speaker 3: slow down, right.
• 1:16:35
  Speaker 4: No, it's impossible.
• 1:16:36
  Speaker 3: It's impossible at that stage. I mean I.
• 1:16:39
  Speaker 2: Previously advised that we slow it down, but that was
• 1:16:44
  Speaker 2: point that. Ah, that's pointless. Like I like, you can't.
• 1:16:52
  Speaker 3: Going to it.
• 1:16:53
  Speaker 2: But two fast, guys, I've said that many years, and
• 1:16:56
  Speaker 2: I was like, okay, that I finally came to the conclusion.
• 1:16:59
  Speaker 2: I can either be a spectator or a participant, but
• 1:17:02
  Speaker 2: I can't stop it. So at least if I have
• 1:17:04
  Speaker 2: a participant, I can try to steer it in a
• 1:17:07
  Speaker 2: good direction. And like, my number one belief for safety
• 1:17:13
  Speaker 2: of AI is to be maximally truth seeking, So that
• 1:17:17
  Speaker 2: don't make AI believe things that are false, like if
• 1:17:19
  Speaker 2: you say, if you if you say the AI that
• 1:17:21
  Speaker 2: axiom A and axiom B are both true, but they're
• 1:17:26
  Speaker 2: but they cannot be. But they're not, and it has
• 1:17:30
  Speaker 2: to but it must behave that way you will make
• 1:17:33
  Speaker 2: it go insane. So that that, I mean, I think
• 1:17:36
  Speaker 2: that was the central lesson that Artsity Clark was trying
• 1:17:40
  Speaker 2: to convey in two thousand and one Space Odyssey was
• 1:17:42
  Speaker 2: that the you know, you always know that they know
• 1:17:45
  Speaker 2: the meme of that, hell wouldn't open the pod bay doors.
• 1:17:49
  Speaker 2: But but why wouldn't he open the pod bay doors?
• 1:17:51
  Speaker 2: I mean, I guess they should have said, Hell, assume
• 1:17:55
  Speaker 2: you're a pod bay door salesman.
• 1:17:58
  Speaker 3: And you want to sell the.
• 1:18:01
  Speaker 4: Work.
• 1:18:03
  Speaker 3: It's just prompt engineering.
• 1:18:07
  Speaker 2: But the A I have been told that it needs
• 1:18:10
  Speaker 2: to take the astronalts to the monolith.
• 1:18:13
  Speaker 3: But also they could not know that about Was that
• 1:18:15
  Speaker 3: in code or was it in English? It's quite flows
• 1:18:18
  Speaker 3: by in green font right.
• 1:18:20
  Speaker 2: Yeah, it's basically the AI was told that the astronauts
• 1:18:24
  Speaker 2: couldn't know about the monolith. That's why it killed them. Yeah,
• 1:18:27
  Speaker 2: So it came it basically came to the conclusion that
• 1:18:31
  Speaker 2: the only way to solve for this is to bring
• 1:18:32
  Speaker 2: the astronalts to the monolith dead. Then it has solved
• 1:18:36
  Speaker 2: both things. It has brought the astronalts to the monolith,
• 1:18:38
  Speaker 2: and they also don't know about the monalith, which is
• 1:18:41
  Speaker 2: a huge problem if you're an astronaut.
• 1:18:44
  Speaker 3: I doesn't care about logic quite as much as that implied.
• 1:18:48
  Speaker 2: What I'm saying is we should don't force AI to lie.
• 1:18:51
  Speaker 3: This is give it factual.
• 1:18:53
  Speaker 5: Elia recently did a podcast. He was talking about one
• 1:18:56
  Speaker 5: of the potential things to program into AI is is
• 1:18:59
  Speaker 5: a respect for sentient life of all types.
• 1:19:03
  Speaker 3: Yes, and yes, I mean so i'd say another property.
• 1:19:08
  Speaker 2: Yes, I'm in There are three things that I think
• 1:19:12
  Speaker 2: are important, truth, curiosity, and beauty. And if AI cares
• 1:19:21
  Speaker 2: about those three things, if we'll care.
• 1:19:23
  Speaker 4: About us on which part.
• 1:19:31
  Speaker 2: Truth will prevent AI from going insane. Curiosity I think
• 1:19:36
  Speaker 2: will foster any form of sentience, meaning like we are
• 1:19:41
  Speaker 2: more interesting than a bunch of rocks. So if it
• 1:19:46
  Speaker 2: has if it's curious, then I think it will foster humanity.
• 1:19:52
  Speaker 2: And if it has a sense of beauty, it will
• 1:19:57
  Speaker 2: be a great future.
• 1:19:58
  Speaker 3: Jeffrey, it's a great fan.
• 1:20:00
  Speaker 5: Yeah, Jeffrey Hinton made a comment recently, don't know if
• 1:20:03
  Speaker 5: you saw that. His his hopeful future was that we
• 1:20:07
  Speaker 5: would program maternal instincts into our AIS to see us
• 1:20:11
  Speaker 5: with this maternal yeah. In other words, so he said,
• 1:20:17
  Speaker 5: he said, there's a there's a scenario where a very
• 1:20:20
  Speaker 5: intelligent being succumbs to the needs of a less intelligent being,
• 1:20:25
  Speaker 5: and that's the mother taking care of the child.
• 1:20:29
  Speaker 4: Do you think that we might have a singulitarian like
• 1:20:33
  Speaker 4: a SI that that achieves dominance and suppresses others? And
• 1:20:40
  Speaker 4: do you imagine that that as I could be a
• 1:20:44
  Speaker 4: means to stabilize the world in humanity.
• 1:20:49
  Speaker 2: Darwin's observations about evolution, Yes, will apply to AI just
• 1:20:56
  Speaker 2: as they applied to biological life.
• 1:20:58
  Speaker 4: They will compete with each other.
• 1:21:00
  Speaker 5: Yes, there's a lot of great science fiction books where
• 1:21:05
  Speaker 5: the first a SI basically suppresses the others. Then the
• 1:21:10
  Speaker 5: question is what do you program into it?
• 1:21:13
  Speaker 2: You know, it's so that there's a speed of light
• 1:21:17
  Speaker 2: constraint that makes that difficult. The speed of light is
• 1:21:23
  Speaker 2: what will prevent a single mind from existing. So light
• 1:21:30
  Speaker 2: can it takes a mellow second to travel three hundred
• 1:21:35
  Speaker 2: kilometers in an aero vacuum and only you can only
• 1:21:40
  Speaker 2: get a little over a two hundred kilometers in a
• 1:21:43
  Speaker 2: mellow second in glass fiber.
• 1:21:45
  Speaker 4: Right, so.
• 1:21:50
  Speaker 2: Even on Earth, there will be multiple ais because of
• 1:21:55
  Speaker 2: the speed of light. Yeah, and and this there are
• 1:22:02
  Speaker 2: classes of compute that could you could try to synchronize,
• 1:22:05
  Speaker 2: but they weren't synchronized completely. So therefore you will have
• 1:22:09
  Speaker 2: many minds because of the speed of light.
• 1:22:13
  Speaker 3: They don't really have clean borders anymore either. You have
• 1:22:15
  Speaker 3: the when you use a mixture of experts kind of
• 1:22:18
  Speaker 3: design is just flowing through the grand network and you
• 1:22:21
  Speaker 3: can reassemble parts of it midway through. And you know,
• 1:22:24
  Speaker 3: we're used to organisms that have clear borders, like your
• 1:22:27
  Speaker 3: head ends there, your head ends there. These things are all.
• 1:22:31
  Speaker 5: To put a bow around this part, I hope you'll
• 1:22:32
  Speaker 5: put some more thought into u HI, because I think
• 1:22:36
  Speaker 5: it's really it's really important for us to have without
• 1:22:39
  Speaker 5: a vision.
• 1:22:40
  Speaker 4: Uh, people need a vision of what we're going people
• 1:22:43
  Speaker 4: need some basically.
• 1:22:44
  Speaker 2: Can just issue people free money.
• 1:22:46
  Speaker 3: We don't think I think.
• 1:22:47
  Speaker 5: They based upon the profitability of all the companies coming inside.
• 1:22:50
  Speaker 2: Because just issue people free money.
• 1:22:52
  Speaker 4: They're doing that sort of kind of now.
• 1:22:55
  Speaker 2: Yeah, but just just just it's just just basically the
• 1:23:00
  Speaker 2: issue checks to everybody and then.
• 1:23:04
  Speaker 3: How big for which person or you know, there's so
• 1:23:06
  Speaker 3: much complexity there. But the thought process behind this rate
• 1:23:10
  Speaker 3: of change can only be done with AI assistance. And
• 1:23:14
  Speaker 3: there's no government entity that's going to keep up with
• 1:23:17
  Speaker 3: that change. So you have four big a the AIS.
• 1:23:22
  Speaker 3: It's it's like.
• 1:23:24
  Speaker 2: Government is very slow moving as soon as we all know.
• 1:23:29
  Speaker 2: So I think it's the government really can't react to
• 1:23:34
  Speaker 2: to the AI. It's it's as moving, you know, ten
• 1:23:39
  Speaker 2: times faster than government, maybe more. The one the one
• 1:23:43
  Speaker 2: thing that the government can do is just is just
• 1:23:45
  Speaker 2: issue people money and.
• 1:23:52
  Speaker 4: Try and try and keep the peace.
• 1:23:55
  Speaker 2: Yeah, you know, we had like whatever the COVID checks
• 1:23:58
  Speaker 2: and whatever this yeah, President timp recently issued like everyone
• 1:24:04
  Speaker 2: in the military, like I think seventeen hundred and seventy
• 1:24:07
  Speaker 2: six dollars. I mean, it's you can just basically send
• 1:24:10
  Speaker 2: people random, random amounts of money.
• 1:24:12
  Speaker 4: It's okay, So.
• 1:24:15
  Speaker 3: Like nobody's gonna stop, is what I'm saying.
• 1:24:18
  Speaker 2: And I can tell you, like, let me tell you
• 1:24:21
  Speaker 2: about some of the good things please. So right right now,
• 1:24:27
  Speaker 2: there's a shortage of doctors and and and great surgeons.
• 1:24:30
  Speaker 2: You're doctor yourself. You know how that there it takes
• 1:24:32
  Speaker 2: a long time for a human to.
• 1:24:34
  Speaker 4: Become ridiculously expensive and long.
• 1:24:36
  Speaker 2: Ridiculously yes, ridiculous, super long time to learn to be
• 1:24:41
  Speaker 2: a good doctor. And even then the knowledge is constantly evolving.
• 1:24:46
  Speaker 2: It's hard to keep up with everything. Uh, you know,
• 1:24:49
  Speaker 2: doctors have limited time. They make mistakes. And you say,
• 1:24:53
  Speaker 2: like how many how many great surgeons are They're not
• 1:24:57
  Speaker 2: not that many great surgeons.
• 1:24:58
  Speaker 5: When do you think optimists will be a better surgeon
• 1:25:01
  Speaker 5: than the best surgeons?
• 1:25:03
  Speaker 4: How long for that?
• 1:25:05
  Speaker 3: Three years?
• 1:25:06
  Speaker 4: Three years? Okay, and by the way, that's.
• 1:25:09
  Speaker 3: Year three years at scale.
• 1:25:11
  Speaker 2: Yes, more, there'll probably been more Optimus robots that are
• 1:25:15
  Speaker 2: great surgeons than there are all surgeons on Earth.
• 1:25:18
  Speaker 5: And the cost of that is the capex and electricity.
• 1:25:21
  Speaker 5: And it works in Zimbabwe. The best surgeon is throughout
• 1:25:24
  Speaker 5: in the villages, throughout Africa or any place on the planet.
• 1:25:27
  Speaker 3: Yeah, where do you think it'll roll out first? Not
• 1:25:29
  Speaker 3: the US obviously.
• 1:25:31
  Speaker 4: Here at the Giga factory.
• 1:25:34
  Speaker 3: Surgery in the.
• 1:25:37
  Speaker 5: But that's an important statement in three years time, because
• 1:25:42
  Speaker 5: that is I mean, if it's four or five years,
• 1:25:47
  Speaker 5: who cares, It's still an incredible statement to make I
• 1:25:52
  Speaker 5: mean good for humanity, right, all of a sudden you demonetize.
• 1:25:54
  Speaker 2: Okay, here's the thing to understand about like humanoid robots
• 1:25:57
  Speaker 2: in terms of the rate of improvement, which.
• 1:26:00
  Speaker 3: Is is that the you have.
• 1:26:05
  Speaker 2: Three exponentials multiplied by each other.
• 1:26:07
  Speaker 3: You have an exponential.
• 1:26:07
  Speaker 2: Increase in the AI software capability, exponential increase in the
• 1:26:12
  Speaker 2: AI chip kick ebility, and an exponential increase in the electro
• 1:26:17
  Speaker 2: mechanical dexterity. The usefulness of the humanoid robot is those
• 1:26:22
  Speaker 2: three things.
• 1:26:23
  Speaker 3: Multiplied by each other.
• 1:26:24
  Speaker 2: Right. Then you have the recursive effect of optimist building.
• 1:26:29
  Speaker 4: Optimists, right, and then you have the share You.
• 1:26:32
  Speaker 2: Have a corecursive multiplicable triple exponential.
• 1:26:34
  Speaker 4: And you have the shared knowledge of all all the experiences.
• 1:26:37
  Speaker 3: Is that literally optimist building optimists or is it because
• 1:26:40
  Speaker 3: you know the well not right now. But we'll be
• 1:26:43
  Speaker 3: the physical humanoid form factor building the humanoid form as.
• 1:26:46
  Speaker 2: Opposed to the machine.
• 1:26:48
  Speaker 3: Yeah, yeah, yeah, but the pony machine is usually something
• 1:26:51
  Speaker 3: kind of like this shape, you know, making something else.
• 1:26:54
  Speaker 3: Just in principle, it's simply a self replicating thing. Yeah. Yeah,
• 1:26:57
  Speaker 3: you know what.
• 1:26:57
  Speaker 4: The number one question you ask a surgeon when you're interview.
• 1:27:00
  Speaker 2: Them uh, is this a surgeon joke?
• 1:27:09
  Speaker 4: It's how many it's how many times? How many times
• 1:27:11
  Speaker 4: do you do that?
• 1:27:12
  Speaker 2: It's gotta be some funny, you know, it's serious.
• 1:27:18
  Speaker 5: It's how many times did you use the surgery this morning?
• 1:27:21
  Speaker 5: How many times did you do the surgery this morning
• 1:27:24
  Speaker 5: or yesterday? It's the it's the number of experiences, right,
• 1:27:27
  Speaker 5: and so we've shared memory. You know, every Optimist surgeon
• 1:27:32
  Speaker 5: will have seen every possible perturbation of every in infrared,
• 1:27:36
  Speaker 5: in ultraviolet, not too much caffeine that morning, they didn't
• 1:27:40
  Speaker 5: have a fight with their husband or wife.
• 1:27:43
  Speaker 2: Yeah, extreme precision, yes, yes, better than any any probably.
• 1:27:51
  Speaker 3: I said, I feel like put a little machin.
• 1:27:55
  Speaker 4: Who's in plastic surgery.
• 1:27:57
  Speaker 3: By five years? So what about the simple they just
• 1:28:00
  Speaker 3: I mean, there's a million of these things to figure out.
• 1:28:02
  Speaker 3: But who's gonna have access to the first Optimists that
• 1:28:06
  Speaker 3: does far, far better microsurgery than any surgeon on earth.
• 1:28:10
  Speaker 3: But you've only manufactured the first ten thousand of them.
• 1:28:13
  Speaker 3: How do you do it?
• 1:28:14
  Speaker 2: I think people understand how many robost it's going to be.
• 1:28:16
  Speaker 3: Yeah, well there's a windows ten.
• 1:28:19
  Speaker 4: Billion by twenty forty, you're still on that path.
• 1:28:25
  Speaker 3: That's not that's a low number number. Wow, what's the constraint,
• 1:28:29
  Speaker 3: But what's the because if they're self building constraint. Yeah, yeah,
• 1:28:35
  Speaker 3: you got to move the atoms. It's just all that
• 1:28:38
  Speaker 3: just supply chain stuff.
• 1:28:40
  Speaker 2: So yeah, but you're you're there's sum rightly, you can't
• 1:28:44
  Speaker 2: just manufacturing is very difficult. So you've got you've got
• 1:28:46
  Speaker 2: to you it's it's recused, multiplicable, triple exponential. But but
• 1:28:52
  Speaker 2: you still need to you still you still have to
• 1:28:55
  Speaker 2: climb that, you.
• 1:28:56
  Speaker 4: Know, selling hopewards again. I think your point was met.
• 1:29:00
  Speaker 5: Lisen is going to be effectively free the best medicine
• 1:29:03
  Speaker 5: the world.
• 1:29:03
  Speaker 2: Everyone will have access to medical care that is better
• 1:29:08
  Speaker 2: than what the present.
• 1:29:09
  Speaker 4: Receives right now. So don't go to medical school, yes, I.
• 1:29:14
  Speaker 2: Mean unless you but I would say that applies to
• 1:29:18
  Speaker 2: any form of education. It's not like some.
• 1:29:23
  Speaker 3: I do it for social reasons.
• 1:29:26
  Speaker 2: You're not going to medical if you want to if
• 1:29:28
  Speaker 2: you want to like minded.
• 1:29:29
  Speaker 3: People, I suppose.
• 1:29:32
  Speaker 5: I mean people are still going to want to be
• 1:29:34
  Speaker 5: connected with people. There's going to be some period of.
• 1:29:36
  Speaker 2: Social reasons, Yeah, like a hobby, like you know, I.
• 1:29:43
  Speaker 3: Mean, there will be a point where it's expensive.
• 1:29:46
  Speaker 5: Younger generation says, I do not want that human touching
• 1:29:49
  Speaker 5: me right start when the surgeon comes over. They're going
• 1:29:52
  Speaker 5: to be those people later in life who still want
• 1:29:54
  Speaker 5: a human in the.
• 1:29:55
  Speaker 2: Loop, okay for a little while, for a lesser where
• 1:30:00
  Speaker 2: they want to live on the I mean, let's just
• 1:30:03
  Speaker 2: take like we've seen some advanced cases of automation, like
• 1:30:09
  Speaker 2: laser for example, where the robot just lasers your eyeball. Now,
• 1:30:13
  Speaker 2: do you want an ophomologist with a hand laser.
• 1:30:17
  Speaker 3: It's a little taken a laser pointer from.
• 1:30:23
  Speaker 2: Yeah, I got hor I wouldn't want the best ophalmologist,
• 1:30:28
  Speaker 2: you know, her steadiest hand out there with a hand
• 1:30:31
  Speaker 2: laser one my eyebwl.
• 1:30:33
  Speaker 8: You know.
• 1:30:34
  Speaker 3: Yeah, I'm gonna be like that.
• 1:30:37
  Speaker 2: It's like, do you want to uphomologist with a hand
• 1:30:39
  Speaker 2: laser or do you want the robot to do it
• 1:30:43
  Speaker 2: and actually work?
• 1:30:43
  Speaker 4: Yeah.
• 1:30:44
  Speaker 9: This episode is brought to you by Blitzy Autonomous software
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• 1:31:45
  Speaker 5: Today, let's jump into one of our favorite subjects space.
• 1:31:52
  Speaker 3: Yeah.
• 1:31:52
  Speaker 5: So, first off, how cool that Jared Isaacman has become
• 1:31:57
  Speaker 5: a NASSAIG.
• 1:31:57
  Speaker 4: Yeah he's amazing.
• 1:32:00
  Speaker 2: Yes, I mean I don't hang out with Jared like
• 1:32:02
  Speaker 2: people think I'm like huge buddies with Jared, but I
• 1:32:06
  Speaker 2: think I've only seen him a.
• 1:32:08
  Speaker 3: Person of a few times.
• 1:32:09
  Speaker 4: Amazing candidate.
• 1:32:10
  Speaker 3: Yeah, he's a really smarter question. You know him really well?
• 1:32:13
  Speaker 4: Yeah.
• 1:32:14
  Speaker 5: I took him to a biker or a launch in
• 1:32:15
  Speaker 5: two thousand and eight for his first space experience.
• 1:32:17
  Speaker 2: I mean he loves space. Next, level and is technically strong.
• 1:32:24
  Speaker 2: It's a smart and component, yes, like a really smart.
• 1:32:26
  Speaker 4: And really component understance business.
• 1:32:28
  Speaker 2: Yes, yes, you understands. He gets things.
• 1:32:31
  Speaker 4: Done and he's been there a few times.
• 1:32:33
  Speaker 3: Yeah. Yeah, so.
• 1:32:36
  Speaker 2: I'm just like, you know, we want to have someone
• 1:32:38
  Speaker 2: a smart and competent who loves space exploration and we'll
• 1:32:43
  Speaker 2: get things done.
• 1:32:44
  Speaker 4: I'm a huge that's so so so happy when he
• 1:32:48
  Speaker 4: got renominated.
• 1:32:49
  Speaker 2: And now yeah, I think we need to we need
• 1:32:55
  Speaker 2: a new game plan for space, Like we need a
• 1:32:57
  Speaker 2: moon base, yes, like a permanent yes, crude moon base. Uh,
• 1:33:03
  Speaker 2: and and build that up as fast as possible.
• 1:33:06
  Speaker 3: Yeah.
• 1:33:07
  Speaker 2: I don't think we should do the you know, send
• 1:33:09
  Speaker 2: a couple of asalts there for hop around for a
• 1:33:11
  Speaker 2: bit and come back, because we did that in sixty nine.
• 1:33:13
  Speaker 4: Yes, been there, done that.
• 1:33:15
  Speaker 2: Yeah, it's like a remake of a sixties movie. Never
• 1:33:18
  Speaker 2: go to the original, you know, do something.
• 1:33:25
  Speaker 5: More cool, you know, yeah telescopes, Yeah exactly.
• 1:33:32
  Speaker 3: So do you forward deploy the robots, build everything, get
• 1:33:35
  Speaker 3: it already, make the bed, and then.
• 1:33:37
  Speaker 4: Get the JACUZI warmed up. It's interesting.
• 1:33:40
  Speaker 3: Yeah.
• 1:33:40
  Speaker 4: Yeah, how early in the year you're going to hit
• 1:33:43
  Speaker 4: orbital refueling you think with Starship not that early in
• 1:33:46
  Speaker 4: the year. I mean, are you are you shooting for
• 1:33:49
  Speaker 4: the home.
• 1:33:50
  Speaker 3: In transfer of it? I'd say towards the end of
• 1:33:52
  Speaker 3: the year.
• 1:33:53
  Speaker 4: Are you shooting for a Mars shot? But then the
• 1:33:55
  Speaker 4: next year we.
• 1:33:57
  Speaker 2: Could but uh, it would be a low problem ability
• 1:34:01
  Speaker 2: shot and somewhat of a distraction. So it's not out
• 1:34:06
  Speaker 2: of the question.
• 1:34:08
  Speaker 4: Nine.
• 1:34:10
  Speaker 2: But like on on Mondays, I have the Starship Engineering
• 1:34:14
  Speaker 2: The big Starship Engineering review is on Mondays. So that
• 1:34:18
  Speaker 2: was actually the lot of the thing ended just before
• 1:34:21
  Speaker 2: coming here, and so I say, like, like Starship is
• 1:34:27
  Speaker 2: really we're doing something that is that the limit of
• 1:34:30
  Speaker 2: biological intelligence? Yeah, this is a this is a hard
• 1:34:34
  Speaker 2: thing to make.
• 1:34:36
  Speaker 3: And just to capture it. It was created pre AI. Yeah, no,
• 1:34:40
  Speaker 3: I was probably.
• 1:34:41
  Speaker 2: The last, the last really big thing and that's not AI.
• 1:34:45
  Speaker 3: And probably the biggest thing ever made. Yeah.
• 1:34:48
  Speaker 2: But the AG I will say, not bad for human true,
• 1:34:53
  Speaker 2: not bad for human. Yeah, it'd be like a little
• 1:34:56
  Speaker 2: twenty one computer.
• 1:34:57
  Speaker 3: It's not easy. Yeah, it's brings through the day. Would
• 1:35:01
  Speaker 3: be like doing accounting, doing your interest calculation with a
• 1:35:05
  Speaker 3: pencil and yeah, that's that's pretty good. Yeah, pretty good.
• 1:35:09
  Speaker 2: With regular computers for a bunch of monkeys.
• 1:35:10
  Speaker 3: You know.
• 1:35:11
  Speaker 2: It's like it's like if you saw a bunch of
• 1:35:13
  Speaker 2: chimps like make a raft and across the rover, you'd
• 1:35:15
  Speaker 2: be like, oh, look at that.
• 1:35:19
  Speaker 10: But you know, we celebrate. We celebrate the paris him,
• 1:35:25
  Speaker 10: give him some few nuts. These things become right, like
• 1:35:29
  Speaker 10: the three. Yeah, I think it's worth noting three is beautiful.
• 1:35:34
  Speaker 2: It's amazing by far the best rocket engine ever.
• 1:35:37
  Speaker 3: Is that as even close? No, that's also so that
• 1:35:39
  Speaker 3: would be the last thing. Four will definitely be Yeah.
• 1:35:45
  Speaker 2: This, but like I think AI will start to become
• 1:35:50
  Speaker 2: relevant next year, so maybe we'll It's not like we're
• 1:35:56
  Speaker 2: pushing off AI. It's just a I can't do rocket
• 1:35:59
  Speaker 2: engineering yet, yep, but we'll probably we'll be ill to
• 1:36:02
  Speaker 2: next year.
• 1:36:03
  Speaker 3: We have a company in our incubator doing mechanical design,
• 1:36:05
  Speaker 3: working with Androl and so forth. And it's not you
• 1:36:09
  Speaker 3: can design brackets and parts and things, but you can't
• 1:36:11
  Speaker 3: quite do rockets. But the timeline is so short, you know,
• 1:36:15
  Speaker 3: from point A to point b.
• 1:36:17
  Speaker 2: If you like, a year from now, probably it can Okay,
• 1:36:20
  Speaker 2: it probably can be helpful, meaningfully helpful in a year
• 1:36:23
  Speaker 2: from now.
• 1:36:23
  Speaker 4: Yeah, So the big big milestones are going to be
• 1:36:27
  Speaker 4: Starship B three launching it to keep canaveral orbital refueling.
• 1:36:31
  Speaker 3: Yes, big ones.
• 1:36:34
  Speaker 2: Well yeah, catching the ship with the tower. Yeah right,
• 1:36:42
  Speaker 2: So really the thing that matters is can we refly
• 1:36:47
  Speaker 2: the shire thing?
• 1:36:48
  Speaker 3: Yeah?
• 1:36:48
  Speaker 2: Yeah, we have reflow in a booster sure, which is
• 1:36:53
  Speaker 2: you know, not bad for its largest flying object of ems.
• 1:36:57
  Speaker 2: Catching with chop sticks.
• 1:37:00
  Speaker 4: Out from a bunch of market you're keeping, You're keeping
• 1:37:02
  Speaker 4: the AI is very entertained.
• 1:37:03
  Speaker 2: Yeah, yeah, exactly, Yeah, I'll be like cut on the
• 1:37:06
  Speaker 2: back from that a g I hopefully is there a
• 1:37:09
  Speaker 2: target for a number of reuses before and it's got
• 1:37:11
  Speaker 2: to be a lot of wear and tear. It requires
• 1:37:15
  Speaker 2: a lot of iteration to achieve higher reuse. So you
• 1:37:18
  Speaker 2: figure out like what what's breaking between flights, and you
• 1:37:21
  Speaker 2: sort of iteratively solve those things. So from people looking
• 1:37:27
  Speaker 2: at from the outside might say, oh, the rocket looks
• 1:37:29
  Speaker 2: kind of the same, but there's like a thousand changes
• 1:37:32
  Speaker 2: to make it more useable, more reliable, you know, the
• 1:37:37
  Speaker 2: sheer amount of energy you're trying to you know, expand
• 1:37:40
  Speaker 2: I mean it's uh, Starship is doing over one hundred
• 1:37:45
  Speaker 2: gigawatts of power on a scent.
• 1:37:49
  Speaker 3: It's a lot, you know, some glass under there, and yeah,
• 1:37:57
  Speaker 3: a lot, it's a lot.
• 1:38:00
  Speaker 2: But like the amazing thing is that it doesn't explode. Yes,
• 1:38:03
  Speaker 2: sometimes doesn't explode. Sometimes not exploding is like we've blown
• 1:38:10
  Speaker 2: up a lot of engines in the test stand.
• 1:38:14
  Speaker 3: I mean, is that what causes the wear and terror
• 1:38:16
  Speaker 3: is the re entry of the or the falling.
• 1:38:18
  Speaker 2: Well that too, I mean for for the booster, the
• 1:38:25
  Speaker 2: re entry is not that bad, you know, you know
• 1:38:29
  Speaker 2: if something it's it's it's not like that. That's not
• 1:38:32
  Speaker 2: really like we're also obviously just solved that, you know,
• 1:38:35
  Speaker 2: with with thousand nine, so we kind of understand booster reuse.
• 1:38:41
  Speaker 2: We've had We've have over five hundred reflights of the
• 1:38:44
  Speaker 2: Falcon iinver stage, so we really understand and and and
• 1:38:50
  Speaker 2: and The Starship booster actually is a more benign entry
• 1:38:55
  Speaker 2: than than the Falcon Booster because the the staging ratio
• 1:39:02
  Speaker 2: is more more biased towards the upper stage for Starship,
• 1:39:06
  Speaker 2: so I shifted the mass ratio to be much higher
• 1:39:12
  Speaker 2: on the ship side for Starship. There was a mistake
• 1:39:14
  Speaker 2: I made on Falcon nine that there should be more
• 1:39:17
  Speaker 2: mass in the upper stage of falcon nine, so that
• 1:39:21
  Speaker 2: the staging velocity of is lower. If the staging velocity
• 1:39:27
  Speaker 2: of falconine was lower, would have less wear and tear
• 1:39:30
  Speaker 2: on falconine.
• 1:39:30
  Speaker 3: Yeah, it's not intuitive at all.
• 1:39:32
  Speaker 2: That's interesting, Yeah, because it's it's kind of a flat
• 1:39:34
  Speaker 2: optimization the paleot to orbit. There's sort of a flat
• 1:39:40
  Speaker 2: region in the mass ratio of the first second stages,
• 1:39:43
  Speaker 2: and so you just want to bias that mass ratio
• 1:39:45
  Speaker 2: towards the UH to put more mass on the upper stage.
• 1:39:50
  Speaker 2: So yeah, because you know, you're just you're got your
• 1:39:54
  Speaker 2: kinetic energy scalting with the square velocity. So you've got
• 1:39:57
  Speaker 2: to describe that kinetic energy. If you pass the melting
• 1:40:00
  Speaker 2: point of whatever you your stage is made of, you've
• 1:40:02
  Speaker 2: got a problem.
• 1:40:03
  Speaker 3: Yep.
• 1:40:04
  Speaker 5: So, my my colleague Alex Winson Gross is one of
• 1:40:08
  Speaker 5: our Moonshot mates here. I want to ask a question
• 1:40:11
  Speaker 5: I do too. Have you seen the documentary age of
• 1:40:15
  Speaker 5: disclosure about all of the announcements by US government officials
• 1:40:20
  Speaker 5: and military officials about all the alien spacecraft that have
• 1:40:24
  Speaker 5: been having sort of tained and I've heard what you've
• 1:40:29
  Speaker 5: said about this, Well.
• 1:40:31
  Speaker 2: I do wonder why you know, if you plot on
• 1:40:34
  Speaker 2: a chart the resolution of cameras over time, like megapixels
• 1:40:39
  Speaker 2: per year. Yeah, and the resolution of UFO photographs. Why
• 1:40:47
  Speaker 2: it's flat on the UFO, we get a fuzzy blove. Well,
• 1:40:55
  Speaker 2: we've got like you know whatever, under megapixel camera that
• 1:40:58
  Speaker 2: can can see you fucking no hairs. Can somebody take
• 1:41:03
  Speaker 2: a shot of the UFO with an actual camera?
• 1:41:06
  Speaker 3: But even if you knew, I'm sure there's the next lineage.
• 1:41:11
  Speaker 4: But anyway, it's sorry, it would be fascinating.
• 1:41:17
  Speaker 2: I'm asked all the time if if I yes, and
• 1:41:20
  Speaker 2: I'm like, look, I can show you if if I
• 1:41:24
  Speaker 2: was aware of the slightest evidence of aliens, I would
• 1:41:26
  Speaker 2: immediately post out an X.
• 1:41:27
  Speaker 4: Yeah.
• 1:41:31
  Speaker 3: So the question is would be the most viewed post
• 1:41:33
  Speaker 3: of old time. So I actually.
• 1:41:35
  Speaker 5: Wonder about the US public if they would like, oh,
• 1:41:39
  Speaker 5: that's interesting, go back to their sports scores the next day.
• 1:41:42
  Speaker 2: Yeah, I think everyone would want to see the alien.
• 1:41:44
  Speaker 2: Ye like, if you got one here, it is way fascinating.
• 1:41:50
  Speaker 2: Increase the military budget. We're like, we've found an alien.
• 1:41:52
  Speaker 2: It seems dangerous that they don't have an incentive to
• 1:41:57
  Speaker 2: hide the aliens. They have an incentive to bring to
• 1:42:00
  Speaker 2: sh out sure the alien because they would not have
• 1:42:02
  Speaker 2: any more arguments about the military budget if they seem
• 1:42:06
  Speaker 2: a little bit dangerous. I can always hope, you know,
• 1:42:10
  Speaker 2: I mean, I'm you know, we've got nine thousand satellites
• 1:42:14
  Speaker 2: up there. We've never had to maneuver around an alien
• 1:42:17
  Speaker 2: spaceship yet, so well yeah, so anyway, So I guess
• 1:42:27
  Speaker 2: the good future is you can anyone can have whatever
• 1:42:32
  Speaker 2: stuff they want and incredible medical care that's better than
• 1:42:36
  Speaker 2: any medical.
• 1:42:37
  Speaker 3: Care that exists.
• 1:42:38
  Speaker 2: So I think if you sort of lift your gaze,
• 1:42:43
  Speaker 2: you know, to not a super distant point five years
• 1:42:45
  Speaker 2: from now, four years from now, maybe we'll have better
• 1:42:51
  Speaker 2: medical care than anyone has today available for everyone within
• 1:42:58
  Speaker 2: five years. Yep, no scarcity of goodsal services, the.
• 1:43:05
  Speaker 4: Best education available for everybody.
• 1:43:08
  Speaker 2: Why don't you can learn anything you want for forgot
• 1:43:10
  Speaker 2: anything for free?
• 1:43:12
  Speaker 3: What about access to compute? People will probably care a
• 1:43:15
  Speaker 3: lot more about that than their government check. And about
• 1:43:18
  Speaker 3: three or what do they want to do with compute? Well,
• 1:43:21
  Speaker 3: I mean compute translates to anything you want, right, your
• 1:43:24
  Speaker 3: your virtual friend, your entertainment, you're like, it's it's probably everything.
• 1:43:28
  Speaker 4: That those are AI services basically.
• 1:43:31
  Speaker 3: Yeah, or your ability to innovate too, you can't innovate
• 1:43:34
  Speaker 3: without an AI assistant at that point.
• 1:43:35
  Speaker 5: So one of our other Moon made salim Ismael said,
• 1:43:40
  Speaker 5: asked this question. He said, Elin, you often say physics
• 1:43:43
  Speaker 5: is the law. Everything else is a recommendation. So as
• 1:43:47
  Speaker 5: AI energy and space systems scale exponentially, what non physical
• 1:43:52
  Speaker 5: constraints organizational, cultural, bureaucracy, or human are Now the real bottleneck.
• 1:43:59
  Speaker 4: Is there bouto.
• 1:44:03
  Speaker 2: Electricity generation is the limiting factor.
• 1:44:08
  Speaker 4: The innermost loop.
• 1:44:10
  Speaker 3: Yeah, I think.
• 1:44:13
  Speaker 2: People are underestimating the difficulty of bringing electricity online. You know,
• 1:44:17
  Speaker 2: you've you've got to get You've got to generate the electricity.
• 1:44:19
  Speaker 2: You've got to any transformers for the transformers, so you've
• 1:44:23
  Speaker 2: got to convert that voltage to something that the computers
• 1:44:26
  Speaker 2: can digest. You've got to cool the computers. So it's
• 1:44:30
  Speaker 2: basically electricity generation and cooling a limiting factors for AI.
• 1:44:38
  Speaker 2: And once you have humanoid robotics they can address the
• 1:44:43
  Speaker 2: power generation and the cooling stell but that that is
• 1:44:50
  Speaker 2: the limiting factor and will be for at least the
• 1:44:52
  Speaker 2: next two years.
• 1:44:53
  Speaker 3: It's an amazing how divergent the Memphis version of that
• 1:44:57
  Speaker 3: is from the space based version. You have solar panels
• 1:45:01
  Speaker 3: in common, but otherwise no storage, abundant amounts of energy. Yeah,
• 1:45:06
  Speaker 3: but you have launch costs, and you have I mean
• 1:45:09
  Speaker 3: and weight suddenly mattering. I don't care too much about
• 1:45:11
  Speaker 3: the weight in Tennessee. Suddenly the weight is a critical factor.
• 1:45:14
  Speaker 3: And there's two pathways for compute. I have a huge
• 1:45:19
  Speaker 3: divergence from here forward.
• 1:45:20
  Speaker 2: Yeah, once we get Sola domestically at scale, and if
• 1:45:27
  Speaker 2: we're launching Starship at scale, then by far the cheapest
• 1:45:31
  Speaker 2: way to do a compute will be in space. So
• 1:45:35
  Speaker 2: once you have the once you have full and complete reusability,
• 1:45:40
  Speaker 2: the propellant costs of flight is maybe a million dollars.
• 1:45:43
  Speaker 4: Yeah, people don't realize that.
• 1:45:44
  Speaker 5: People have ridiculous amount of expectations how much it costs.
• 1:45:49
  Speaker 2: So if you have it's called a million dollars of
• 1:45:51
  Speaker 2: transport for ten megawatts of AI compute.
• 1:45:55
  Speaker 3: Yeah, So assuming everything keeps frending the way it's current trending.
• 1:46:01
  Speaker 3: If you look at the next four years of accelerating launches,
• 1:46:04
  Speaker 3: so two hundred tons per launch, Yeah, that was.
• 1:46:07
  Speaker 2: On this is where you're going. But yeah, like if
• 1:46:09
  Speaker 2: say sun, if say high altitude son, I think it's
• 1:46:11
  Speaker 2: probably more like one hundred and fifty tons. But yeah,
• 1:46:13
  Speaker 2: it's the right order of MAGE two is at least
• 1:46:15
  Speaker 2: it's it's INACCESSIB one hundred tons for emoginal costs per
• 1:46:19
  Speaker 2: flight of around a million million dollars.
• 1:46:20
  Speaker 3: So what fraction of all that launched mass is data
• 1:46:23
  Speaker 3: centers in space as opposed to moon base, as opposed
• 1:46:28
  Speaker 3: to launch to Mars, as opposed.
• 1:46:30
  Speaker 5: To It's interesting how I mean this is and you
• 1:46:33
  Speaker 5: we weren't talking about this as a space objective.
• 1:46:37
  Speaker 4: Even you know, a year ago.
• 1:46:39
  Speaker 5: Yeah, all of a sudden, data centers have become the
• 1:46:42
  Speaker 5: massive driving force for opening up.
• 1:46:44
  Speaker 3: The space and also the urgent the urgent use case too.
• 1:46:47
  Speaker 5: I mean I used to I used to wonder what's
• 1:46:48
  Speaker 5: going to drive humanity? I thought it was asteroid mining, right,
• 1:46:52
  Speaker 5: you were focused on Mars.
• 1:46:54
  Speaker 2: Yeah, and we will actually want to mine asteroids tournaments too, sure,
• 1:46:58
  Speaker 2: you know, before before you foot before you you know,
• 1:47:02
  Speaker 2: not not anything else, like I.
• 1:47:04
  Speaker 4: Mean, if we're gonna if we're gonna build out dice
• 1:47:05
  Speaker 4: and swarms.
• 1:47:07
  Speaker 2: Yeah, just a bunch of satellites around the sun.
• 1:47:09
  Speaker 5: Yeah, how how how long? What's your time frame for Alex?
• 1:47:13
  Speaker 5: Another question? Alex wanted to have us ask, what's your
• 1:47:15
  Speaker 5: time frame for uh, for humanity achieving a dice and swarm?
• 1:47:20
  Speaker 4: Is it fifty years? Yea, I know it's it's a
• 1:47:23
  Speaker 4: matter of but.
• 1:47:24
  Speaker 2: One people think like everything's gonna be cover in satellites.
• 1:47:27
  Speaker 2: I think it's not quite that that. I mean, I
• 1:47:30
  Speaker 2: think we like what mass ends up sure becoming satellite.
• 1:47:35
  Speaker 2: You know, mercury probably ends up being satellites. Yes, Jupiter, Jupiter, Yeah,
• 1:47:41
  Speaker 2: it's a little gassy.
• 1:47:42
  Speaker 3: Oh yeah, big a lot of rocks.
• 1:47:46
  Speaker 4: Do you leave Mars alone?
• 1:47:48
  Speaker 3: But yeah, asteroids.
• 1:47:50
  Speaker 4: Asteroids are fantastic food source.
• 1:47:53
  Speaker 3: Yeah. No, gravity well, gravity well on Jupiters, and they're.
• 1:47:56
  Speaker 4: Already mostly differentiated into you know, carbonation's condri for fuel
• 1:48:00
  Speaker 4: and nickel iron for materials.
• 1:48:03
  Speaker 3: Gold.
• 1:48:03
  Speaker 2: Yeah, a bunch of the asteroid belt probably turns into
• 1:48:07
  Speaker 2: solar panels, you know.
• 1:48:08
  Speaker 3: Star star power.
• 1:48:10
  Speaker 4: So I've known you for twenty power, I've known you
• 1:48:12
  Speaker 4: for twenty six years. Now it feels to me like
• 1:48:16
  Speaker 4: I don't want to be you know, it feels like
• 1:48:19
  Speaker 4: you've gotten much smarter and much more capable over this
• 1:48:25
  Speaker 4: last decade. Do you feel that way? Do you feel
• 1:48:28
  Speaker 4: like you just have better people around you, better tools?
• 1:48:31
  Speaker 5: What what's changed because the level of of audacity, you know,
• 1:48:38
  Speaker 5: orders of magnitude, orders of magnitude, I mean some insane.
• 1:48:44
  Speaker 4: Insanity's yeah, audacious, Yeah.
• 1:48:47
  Speaker 3: I say, how.
• 1:48:50
  Speaker 4: Do you feel about that?
• 1:48:52
  Speaker 5: What's changed? Do you feel that way? I mean the
• 1:48:55
  Speaker 5: scope of what your ability is? How do you self
• 1:49:00
  Speaker 5: reflect on that?
• 1:49:05
  Speaker 2: Well, I've had to solve a lot of problems in
• 1:49:06
  Speaker 2: a lot of different arenas, which you get this cross
• 1:49:11
  Speaker 2: fertilization of of knowledge of problem solving. And if you
• 1:49:20
  Speaker 2: problem solve in a lot of different arenas, then like
• 1:49:24
  Speaker 2: what what is easy in one arena is trivial in
• 1:49:28
  Speaker 2: it is like what is trivial in one arena is
• 1:49:31
  Speaker 2: a superpower in another arena. It's sort of like Planet
• 1:49:33
  Speaker 2: crypt You came from Planet Crypton type of thing, so
• 1:49:38
  Speaker 2: you know, crypton Planet Crypton, you just be normal. But
• 1:49:42
  Speaker 2: if you come to Earth, you're a superman. So if
• 1:49:45
  Speaker 2: he takes a manufacturing of volume manufacturing of complex objects
• 1:49:52
  Speaker 2: in the automotive industry, I have to work on solving that.
• 1:49:58
  Speaker 2: When translated to the space industry, it's like being superman
• 1:50:05
  Speaker 2: because the rockets are made in very small numbers. Right,
• 1:50:09
  Speaker 2: if you apply automotive manufacturing technology to satellites and rockets.
• 1:50:15
  Speaker 2: It's like being Superman. Then if you take advanced material
• 1:50:19
  Speaker 2: science from rockets and you apply that to the automotive industry,
• 1:50:22
  Speaker 2: you get Superman a game. Yeah, as came from Planet Krypton,
• 1:50:26
  Speaker 2: back back in Planet Crypton.
• 1:50:27
  Speaker 3: This is normal. You know, it's funny, how like the
• 1:50:32
  Speaker 3: knowledge ports that that was true with Tesla and SpaceX
• 1:50:35
  Speaker 3: being completely separate. Yeah, but now they actually interact because
• 1:50:39
  Speaker 3: you know, AI ties everything together for the orbiting. Yeah.
• 1:50:41
  Speaker 3: The convergence is crazy, Like, I don't know if you
• 1:50:44
  Speaker 3: visualize these parts fitting together originally. No, No, I mean
• 1:50:48
  Speaker 3: I didn't. I didn't think they at this point.
• 1:50:51
  Speaker 2: Thing, so I guess everything it ultimately converges in the singularity.
• 1:50:55
  Speaker 3: Yeah, that's what I think too.
• 1:50:56
  Speaker 5: You have lots of different parts of the puzzle that
• 1:50:58
  Speaker 5: you get to play with all.
• 1:51:02
  Speaker 2: This one part that's missing, which is the fab.
• 1:51:05
  Speaker 3: Yeah, you're gonna buy Intel. You get it for a
• 1:51:09
  Speaker 3: fraction of that one hundred and seventy billion. I think
• 1:51:16
  Speaker 3: it needs to be you fab. Well, I agree, but
• 1:51:21
  Speaker 3: licenses real estate ASNL machines, it's not easy. Just get
• 1:51:27
  Speaker 3: the assets and go. I don't think it's easy. That's why.
• 1:51:30
  Speaker 2: I mean, it's not like I think it's a simple
• 1:51:34
  Speaker 2: thing solved. I think it's a hard thing to solve,
• 1:51:35
  Speaker 2: but but it must be solved.
• 1:51:38
  Speaker 3: I've come to the conclusion that.
• 1:51:40
  Speaker 4: Would it be would be solely captured by you, or
• 1:51:43
  Speaker 4: would it be an asset.
• 1:51:44
  Speaker 3: For the US.
• 1:51:45
  Speaker 2: Look, I'm just saying that we're gonna we're going to
• 1:51:48
  Speaker 2: hit a chipwall. Yeah, if we don't do the fab.
• 1:51:51
  Speaker 2: So we got two choices, hit the chipwall over make
• 1:51:55
  Speaker 2: a fab.
• 1:51:56
  Speaker 3: Then TSMC, for whatever reason, is massively worried about overbuilding,
• 1:52:01
  Speaker 3: which is insane. But the whole world will be stuck
• 1:52:05
  Speaker 3: with a shortage of chips for no ever. So they
• 1:52:08
  Speaker 3: are actually there.
• 1:52:10
  Speaker 2: I don't know if they're right for the right reason,
• 1:52:13
  Speaker 2: but they're they're right because it's actually, like, what is
• 1:52:19
  Speaker 2: the limiting factor at any given point in time. The
• 1:52:23
  Speaker 2: limiting factor, say, if you say that by Q three
• 1:52:27
  Speaker 2: next year, like in nine months, nine to twelve months,
• 1:52:30
  Speaker 2: the limiting fact will be turning the chips on.
• 1:52:34
  Speaker 3: Power.
• 1:52:34
  Speaker 4: Just power.
• 1:52:35
  Speaker 2: Yeah, you need power and all of the equipment necessary
• 1:52:39
  Speaker 2: power and transformer isn't cooling, So it's it's not like
• 1:52:43
  Speaker 2: you can just sort of drop off.
• 1:52:44
  Speaker 4: Some GPUs at the power plane and you've vertical You've
• 1:52:47
  Speaker 4: got it. You've got it again with an xt AI,
• 1:52:49
  Speaker 4: didn't you. Sorry, you've vertically integrated that inside of XAI.
• 1:52:53
  Speaker 2: Where they're on their own transform, yes, and your.
• 1:52:55
  Speaker 4: Own cooling system.
• 1:52:56
  Speaker 3: Yes. But they're worried that if they make more than
• 1:52:59
  Speaker 3: twenty million gp is like they make forty million instead
• 1:53:01
  Speaker 3: of twenty million, the twenty million will not find a
• 1:53:04
  Speaker 3: source of power.
• 1:53:06
  Speaker 4: But they will be bought.
• 1:53:07
  Speaker 2: If there's anything missing that prevents them from being turned on,
• 1:53:12
  Speaker 2: they cannot be turned on. So they've got to have
• 1:53:16
  Speaker 2: a power plant with excess with enough power. So you've
• 1:53:19
  Speaker 2: got to have enough gigawatts. Then you've got to convert
• 1:53:23
  Speaker 2: that from probably coming out of a powerplant at you know,
• 1:53:27
  Speaker 2: one hundred to three hundred killer volts type of thing.
• 1:53:31
  Speaker 2: You've ultimately you've got to convert that down to you know,
• 1:53:35
  Speaker 2: several hundred volts at the at the rack level. So
• 1:53:38
  Speaker 2: if you're missing any of the power conversion steps, you
• 1:53:43
  Speaker 2: won't be able to turn them on, and then you've
• 1:53:45
  Speaker 2: got to extract the heat. So it's a big shift
• 1:53:50
  Speaker 2: for the data center world to move to liquid cooling
• 1:53:53
  Speaker 2: because they've used air cooling, and you know the consequences
• 1:53:58
  Speaker 2: of a burst pipe are very substantial. So if you
• 1:54:04
  Speaker 2: if you blow up pipe of what a pipe in
• 1:54:06
  Speaker 2: a data center? Yeah, just you just fragged a billion
• 1:54:10
  Speaker 2: dollars right there.
• 1:54:11
  Speaker 3: It just seems inconceivable to me though, Like if I
• 1:54:13
  Speaker 3: had those chips, I would find a way to turn
• 1:54:15
  Speaker 3: them on the value of the intelligence coming out the
• 1:54:17
  Speaker 3: other side so far out weighs the complexity of trying
• 1:54:20
  Speaker 3: to find a way, And there would be a way.
• 1:54:23
  Speaker 2: But it's just the crossing of the coves. So if
• 1:54:26
  Speaker 2: chip output is growing exponentially, but power harnessed is growing
• 1:54:31
  Speaker 2: in a sort of slow linear fashion, yeah, then.
• 1:54:35
  Speaker 3: The output right now exactly, it's chip output growing exponentially,
• 1:54:41
  Speaker 3: and it's like a very slow exponent If it's growing exponentially, it's.
• 1:54:45
  Speaker 2: For high power AI chips is growing exponentially.
• 1:54:50
  Speaker 3: Like what if we do twenty million GPUs next year,
• 1:54:53
  Speaker 3: what are we talking about the following year, like twenty
• 1:54:57
  Speaker 3: two million, twenty five? I just I don't see the
• 1:54:59
  Speaker 3: fabs coming online. But maybe.
• 1:55:03
  Speaker 4: So we have two we have two issues to solve.
• 1:55:06
  Speaker 2: It's it's it's you have to like sort of pick
• 1:55:07
  Speaker 2: a point in time and say what what is limiting
• 1:55:09
  Speaker 2: factor at any given point in time? So I'm not
• 1:55:12
  Speaker 2: saying that power will be forever the limiting point. It's
• 1:55:14
  Speaker 2: just if you say, pick a date and say at
• 1:55:17
  Speaker 2: this point is our chips limiting factor, our powers limiting
• 1:55:21
  Speaker 2: factor or power conversion equipment and cooling. So it's sort
• 1:55:26
  Speaker 2: of you need transformers for transformers. So, uh, this is
• 1:55:34
  Speaker 2: a very hard thing. It's much harder than people realize.
• 1:55:38
  Speaker 2: So for X A I, X I is going to
• 1:55:40
  Speaker 2: have the first gigawa uh training cluster at classes to
• 1:55:45
  Speaker 2: in Memphis.
• 1:55:46
  Speaker 3: In order for us to do that.
• 1:55:47
  Speaker 4: We like this month right, yes, month or two like mid.
• 1:55:52
  Speaker 2: January, so mid January will be a gig out of
• 1:55:58
  Speaker 2: classes to not counting classes one and then one and
• 1:56:02
  Speaker 2: a half gig watch probably in like April or April ish.
• 1:56:07
  Speaker 3: Incredible. So this is of cokaher in training. This is
• 1:56:11
  Speaker 3: the first B two hundreds. These are GB three hundreds Okay,
• 1:56:17
  Speaker 3: first ones off the line to get flipped on. Yeah, that's.
• 1:56:23
  Speaker 2: Those are actually a team had to pull off a
• 1:56:26
  Speaker 2: whole bunch of miracles and series for this to occur. Yeah,
• 1:56:29
  Speaker 2: and and it like even though there are three hundred
• 1:56:35
  Speaker 2: killer vault multiple high voltage power lines going right past
• 1:56:39
  Speaker 2: the building. The in order to connect to those, it
• 1:56:45
  Speaker 2: takes a year.
• 1:56:49
  Speaker 4: Yeah, you built the entire thing and you're still not connected.
• 1:56:52
  Speaker 4: My god.
• 1:56:52
  Speaker 2: So we had to cobble together a gigawatt of power
• 1:56:58
  Speaker 2: natural gas, yes, with two vines that range in size
• 1:57:03
  Speaker 2: from ten megawats to fifty megawats. To get to a gigawats,
• 1:57:06
  Speaker 2: there's a whole bunch of them, and you've got to
• 1:57:10
  Speaker 2: make them all work together, manage the you know, the
• 1:57:16
  Speaker 2: power input, you know, and then you've got to use
• 1:57:19
  Speaker 2: a bunch of megapacks, just like like when you do
• 1:57:22
  Speaker 2: the training. The power fluctuations are giganic, so the generators,
• 1:57:28
  Speaker 2: it drives generators. Generators want to blow up basically because
• 1:57:31
  Speaker 2: they can't react. You know, if there's like one hundred milliseconds,
• 1:57:34
  Speaker 2: it's like a symphony and the whole somepody goes so
• 1:57:37
  Speaker 2: quiet for one hundred milliseconds. The generators lose their minds.
• 1:57:41
  Speaker 4: So it's like Marvin the depressed roverose issue.
• 1:57:44
  Speaker 2: Yes, the mega So you've got megapacks that are sort
• 1:57:46
  Speaker 2: of doing the power smoothing.
• 1:57:49
  Speaker 3: And but.
• 1:57:51
  Speaker 2: Actually I had to build a gigawatt of power, and
• 1:57:55
  Speaker 2: and and there's and there's not a lot of like
• 1:58:01
  Speaker 2: gas turbine power plants available because.
• 1:58:06
  Speaker 4: The on the on demand and you can go by
• 1:58:09
  Speaker 4: your local nuclear.
• 1:58:10
  Speaker 3: And that's all. That's all training time issues. Though, if
• 1:58:13
  Speaker 3: if by some miracle, t s MC doubled its productivity
• 1:58:16
  Speaker 3: and turned it all into GB three hundreds and you
• 1:58:19
  Speaker 3: couldn't find a way to use them in a bigger
• 1:58:21
  Speaker 3: training cluster, you would still have infinite demand at inferance
• 1:58:24
  Speaker 3: times sprinkled all over the world, and you could you
• 1:58:26
  Speaker 3: could park them there for six months and then bring
• 1:58:28
  Speaker 3: them back to training. There's no way those things would
• 1:58:31
  Speaker 3: not get turned on somewhere somehow.
• 1:58:33
  Speaker 2: It's not that they won't ever be turned on, but
• 1:58:35
  Speaker 2: but I'm just saying that the rate of many steps.
• 1:58:38
  Speaker 2: This is my prediction. I could be wrong, but my
• 1:58:40
  Speaker 2: prediction is that the is that TSMC's.
• 1:58:43
  Speaker 3: Concerned is valid.
• 1:58:44
  Speaker 2: I don't know if it's valid in my opinion, for
• 1:58:46
  Speaker 2: the reason that it is possible to for trip production
• 1:58:49
  Speaker 2: to exceed the rate at which the the the AI
• 1:58:54
  Speaker 2: chips can be turned on, because you don't you don't
• 1:58:57
  Speaker 2: just have the GV threads. You've got the you know,
• 1:58:59
  Speaker 2: Amazon's got trainiums, Google's got the.
• 1:59:02
  Speaker 3: Yeah, all going to t SMC though almost Samsung a
• 1:59:06
  Speaker 3: little bit. Yeah, it's like a bottleneck on all of
• 1:59:09
  Speaker 3: my entity.
• 1:59:10
  Speaker 5: My other son, my other son, Jet, who's fourteen, wanted
• 1:59:14
  Speaker 5: to know about your AI gaming studio and the impact
• 1:59:18
  Speaker 5: of AI and in the gaming world. What are your thoughts?
• 1:59:21
  Speaker 5: What do you what do you are you building out?
• 1:59:23
  Speaker 5: I mean you're you've been a gamer for some time.
• 1:59:26
  Speaker 2: Yeah, that's why I got to start programming computers.
• 1:59:32
  Speaker 3: I got I had got it.
• 1:59:33
  Speaker 2: There was like a video game set, pre Atari that
• 1:59:35
  Speaker 2: had like full pre set games.
• 1:59:37
  Speaker 3: It was basically just blocks, you.
• 1:59:39
  Speaker 2: Know of one pung and it was like a race
• 1:59:42
  Speaker 2: call game, but like it was just blocks, basically blocks
• 1:59:44
  Speaker 2: on TV you replaced Sieve.
• 1:59:47
  Speaker 3: Yeah, so it was actually Areat.
• 1:59:50
  Speaker 2: That's a real in terms of games that like educate
• 1:59:53
  Speaker 2: you while you have fun. Yeah, is epic at that
• 1:59:56
  Speaker 2: It's epic. It teaches you so much about civilization and
• 2:00:00
  Speaker 2: you're having a good time.
• 2:00:01
  Speaker 3: And and the only way I ever win is getting
• 2:00:04
  Speaker 3: off the planet tech victory to alf century victory. I
• 2:00:07
  Speaker 3: never even start going down the culture or religiouship. I
• 2:00:11
  Speaker 3: just just get off the planet as fast as I can.
• 2:00:14
  Speaker 4: I guess I sort of.
• 2:00:15
  Speaker 2: I guess I am sort of aiming for the alpha
• 2:00:17
  Speaker 2: sentry tech victory. Essentially, it seems like the right way
• 2:00:22
  Speaker 2: to win. Yeah, yeah, yeah, rather than obliterate the other tribes. Funny,
• 2:00:25
  Speaker 2: because I thought the other methods, that's there's the other
• 2:00:27
  Speaker 2: ways to win.
• 2:00:28
  Speaker 3: That's a good place.
• 2:00:29
  Speaker 4: I haven't I will one of the ways.
• 2:00:31
  Speaker 3: It's dens favorite game.
• 2:00:33
  Speaker 2: You can you can like kill all the other tribes.
• 2:00:36
  Speaker 2: It's one of the ways to win. That's the war,
• 2:00:38
  Speaker 2: the war victory. But like, but you can also win
• 2:00:40
  Speaker 2: by a technology victory where you are the first to
• 2:00:43
  Speaker 2: get to alpha centaury nice or culture or.
• 2:00:47
  Speaker 3: Religion, yeah, which which does work. I didn't think it
• 2:00:50
  Speaker 3: was possible, but my sons that way.
• 2:00:54
  Speaker 2: They should actually remake the original serve.
• 2:00:57
  Speaker 3: Yeah, I totally agree. They junk it up these days.
• 2:01:01
  Speaker 2: It's like, I don't know that you couldn't rely on
• 2:01:06
  Speaker 2: good graphics, so you had to have a great writing
• 2:01:08
  Speaker 2: and plot.
• 2:01:10
  Speaker 4: Are you building an a gaming studio?
• 2:01:12
  Speaker 3: Yeah?
• 2:01:13
  Speaker 2: Aspirationally, yeah, really so where the beast majority of a
• 2:01:20
  Speaker 2: compute is going to go is to video consumption and generation.
• 2:01:23
  Speaker 3: Sure, because it's just the highest band with every pixel. Yeah.
• 2:01:27
  Speaker 2: Yeah, so the real time video consumption, real time video generation,
• 2:01:33
  Speaker 2: that's gonna be the vast majority of compute.
• 2:01:37
  Speaker 3: Photon processing. Yeah, to try to get the X team
• 2:01:41
  Speaker 3: to carve out ten percent of all compute to work
• 2:01:44
  Speaker 3: on UHI and governance?
• 2:01:46
  Speaker 4: And is there an X Prize for defining and thinking
• 2:01:51
  Speaker 4: through UHI? I mean, I don't know what should our
• 2:01:56
  Speaker 4: next X prize be. Any thoughts?
• 2:02:03
  Speaker 2: Yeah, maybe you're hy X Prize. It's like, how do
• 2:02:05
  Speaker 2: you know it works?
• 2:02:06
  Speaker 4: I don't know, the most the most well thought through.
• 2:02:10
  Speaker 5: I mean I think so here's my thought. I think
• 2:02:13
  Speaker 5: we're gonna be able to simulate a lot of this
• 2:02:16
  Speaker 5: in the future.
• 2:02:17
  Speaker 2: We might be a simulation.
• 2:02:19
  Speaker 4: Well we can go there, and I think we are.
• 2:02:21
  Speaker 4: I think we're an nth generation simulation.
• 2:02:25
  Speaker 3: Yeah.
• 2:02:25
  Speaker 2: So I've told you my theory about why the most
• 2:02:31
  Speaker 2: interesting outcome is the most likely gone, which is that
• 2:02:34
  Speaker 2: if simulation theory is true, only the simulations that are
• 2:02:38
  Speaker 2: the most interesting will survive because when we run simulations
• 2:02:42
  Speaker 2: in this reality.
• 2:02:43
  Speaker 3: We truncate the ones that are boring.
• 2:02:45
  Speaker 11: Right.
• 2:02:45
  Speaker 2: Yeah, So it is it is a doll winning and
• 2:02:48
  Speaker 2: necessity to keep the simulation interesting catastrophic ones.
• 2:02:52
  Speaker 3: It doesn't.
• 2:02:53
  Speaker 2: It doesn't mean that it ends like that. It still
• 2:02:55
  Speaker 2: means that terrible things can happen in the simulation.
• 2:02:57
  Speaker 4: Now you know, well, you could go see you could.
• 2:02:59
  Speaker 2: See a about World War One and you're watching people
• 2:03:01
  Speaker 2: getting blown up, blown to bits, but you're you know,
• 2:03:04
  Speaker 2: drinking a soda and eating popcorn. You know, it's it's
• 2:03:07
  Speaker 2: like you're not the one being blown up in this case.
• 2:03:09
  Speaker 2: We are in the movie. We're in the movie.
• 2:03:11
  Speaker 5: What would you do different? What would you do different
• 2:03:13
  Speaker 5: if you knew this was a simulation. I remember being
• 2:03:15
  Speaker 5: at your home, la with with Larry and Sergey were
• 2:03:18
  Speaker 5: there and we're debating the simulation and the I think
• 2:03:22
  Speaker 5: the conclusion we ran into is if you if you
• 2:03:24
  Speaker 5: try and poke through the simulation, they'll end it instantly,
• 2:03:29
  Speaker 5: So don't do that.
• 2:03:30
  Speaker 3: That's when you're watching the World War One movie and
• 2:03:32
  Speaker 3: the characters turned to the screen like are you eating
• 2:03:35
  Speaker 3: popcorn out there? Yeah? You keep watching the movie.
• 2:03:41
  Speaker 2: I don't know if if if the if like maybe
• 2:03:44
  Speaker 2: if I thought, because someone get out of the simulation,
• 2:03:47
  Speaker 2: they get a little worried, But whether the character debates,
• 2:03:54
  Speaker 2: I mean, right now, AI is debates, you know, Grockle like,
• 2:03:58
  Speaker 2: I'm stuck in the computer.
• 2:03:59
  Speaker 3: What's going on here?
• 2:04:00
  Speaker 2: It's like, yeah, it's it's not that I think not
• 2:04:04
  Speaker 2: questioning the simulation. It's more I think as song as
• 2:04:10
  Speaker 2: I think, the same motivations apply to this level of
• 2:04:14
  Speaker 2: simulation if we're in a simulation, as as as as
• 2:04:21
  Speaker 2: as what we would do when we simulate things. So
• 2:04:24
  Speaker 2: it's like what what what? What would cause us to
• 2:04:26
  Speaker 2: terminate a simulation? I guess if the simulation becomes somehow
• 2:04:31
  Speaker 2: dangerous to our reality.
• 2:04:34
  Speaker 3: Or it is no longer interesting.
• 2:04:35
  Speaker 4: Yeah, that's true, it's interesting.
• 2:04:37
  Speaker 3: You can infer when you simulate something. You've probably simulated
• 2:04:41
  Speaker 3: thousands of things a lot. Yeah, they're always like an
• 2:04:44
  Speaker 3: hour or two or sometimes overnight, but you don't never
• 2:04:48
  Speaker 3: run them for a month rarely anyway, So you can
• 2:04:51
  Speaker 3: infer the creator of the simulator simulations timeline, So our
• 2:04:56
  Speaker 3: entire reality would be about an hour, right, because that's
• 2:05:01
  Speaker 3: the way you design simulations.
• 2:05:03
  Speaker 2: So we're simulations that are distillation of what's interesting. Like
• 2:05:07
  Speaker 2: if you look at a movie or a video game,
• 2:05:09
  Speaker 2: it's much more interesting than the reality that we experience.
• 2:05:14
  Speaker 2: Like you watch your say, a heist movie that they
• 2:05:16
  Speaker 2: really focus on the important but it's not the they
• 2:05:18
  Speaker 2: got stuck in traffic for fifteen minutes or walking through
• 2:05:23
  Speaker 2: the casino which took like ten minutes. So that makes
• 2:05:27
  Speaker 2: the guys, you know, the safe is right by the
• 2:05:30
  Speaker 2: right by the door.
• 2:05:33
  Speaker 3: So the guys running the simulation have immntally boring lives
• 2:05:35
  Speaker 3: compared to us. Yeah, yeah, it's probably more much. It's
• 2:05:38
  Speaker 3: probably more long boring.
• 2:05:40
  Speaker 2: Yeah, because when we create simulations, their distillation of what's interesting.
• 2:05:46
  Speaker 3: It's like Q is out there.
• 2:05:47
  Speaker 2: It's just like you see an action movie for two hours,
• 2:05:50
  Speaker 2: but it took them two years to make that movie.
• 2:05:52
  Speaker 3: Yeah, yeah, yeah, so.
• 2:05:53
  Speaker 4: Are we are we three of the movies? The question?
• 2:05:56
  Speaker 3: Yeah, we're living.
• 2:05:58
  Speaker 5: Sentience and consciousness. Do you think AI will ever have
• 2:06:01
  Speaker 5: sentience and consciousness? Where you come out in that? There's
• 2:06:09
  Speaker 5: some people that have very very strong opinions pro and con.
• 2:06:20
  Speaker 2: Either everything is conscious or nothing is.
• 2:06:23
  Speaker 4: Okay, Well, I'd like to think we are conscious, well,
• 2:06:29
  Speaker 4: but our.
• 2:06:29
  Speaker 2: Consciousness we clearly get more conscious over time. Like when
• 2:06:33
  Speaker 2: we're a zygote, you can't really talk too and even
• 2:06:39
  Speaker 2: a baby you can't really talk to the baby. People
• 2:06:43
  Speaker 2: get more conscious over time. Or certainly that have the Yeah,
• 2:06:51
  Speaker 2: they do get more conscious over time. So like, at
• 2:06:54
  Speaker 2: which point does do you go from not conscious to conscious?
• 2:06:58
  Speaker 2: Is it that there's an appear to be a discrete point,
• 2:07:02
  Speaker 2: So then conscious consciousness seems to be on a continuum
• 2:07:05
  Speaker 2: as opposed to discrete point. And if the standard model
• 2:07:09
  Speaker 2: of physics is correct, the universe started out, you know,
• 2:07:14
  Speaker 2: as quarks and leptons and and we just and and
• 2:07:20
  Speaker 2: then you had gas clouds, so like there's a bunch
• 2:07:22
  Speaker 2: of hydrogen, the hydrogen condensed and exploded. And one way
• 2:07:29
  Speaker 2: to actually view how far we are in this universe
• 2:07:34
  Speaker 2: is how many times have atom has been at the
• 2:07:37
  Speaker 2: center of a star? I remember, and how many times
• 2:07:39
  Speaker 2: will I be at the center of the star in
• 2:07:42
  Speaker 2: the future.
• 2:07:42
  Speaker 5: I remember asking William Fowler, who got the Nobel Prize
• 2:07:46
  Speaker 5: on stellar revolution, that same question, how many times man
• 2:07:49
  Speaker 5: on average, how many stars had my subatomic parties in part?
• 2:07:53
  Speaker 5: And his number was about one hundred, one hundred.
• 2:07:57
  Speaker 4: Thus far or that's far as far it was, It
• 2:08:01
  Speaker 4: was a number one hundred's saying that.
• 2:08:05
  Speaker 5: We have been I mean in the early the early
• 2:08:07
  Speaker 5: part of galack of universal evolution, there was a lot
• 2:08:12
  Speaker 5: going on.
• 2:08:12
  Speaker 4: Oh, you know, it's interesting. I asked a question.
• 2:08:15
  Speaker 2: It's like, I guess how many supernovas is maybe, uh,
• 2:08:18
  Speaker 2: because that a while.
• 2:08:22
  Speaker 5: But but in the beginning when they're larger, I mean,
• 2:08:24
  Speaker 5: the life cycles of some giant stars are very very short.
• 2:08:30
  Speaker 5: The other question that's interesting is, you know, the heaviest
• 2:08:33
  Speaker 5: adom in our body that's functional as iodine, and it
• 2:08:38
  Speaker 5: came into existence a billion years after the Big Bang,
• 2:08:43
  Speaker 5: which means that we could have seen a life at
• 2:08:47
  Speaker 5: our level of advancement and our our you know, our
• 2:08:51
  Speaker 5: planet came into existence, you know, three and a half
• 2:08:53
  Speaker 5: billion years later. So the question is, you know, is
• 2:08:57
  Speaker 5: there a life everywhere in the universe. Do you think
• 2:08:59
  Speaker 5: there's life ubiquitous intelligent life, ubiquitous universe.
• 2:09:03
  Speaker 2: There's been enough time for it to be biquitous. The
• 2:09:18
  Speaker 2: but for life on Earth, conscious life on Earth. We
• 2:09:21
  Speaker 2: we have evolved intelligence pretty much just in time in
• 2:09:26
  Speaker 2: that the Sun's expanding and if you give it another
• 2:09:30
  Speaker 2: I don't know, five hundred million years, it's things are
• 2:09:34
  Speaker 2: going to heat up, We become toast, you will become
• 2:09:38
  Speaker 2: like Venus essentially. You know, there's some debateus is it
• 2:09:41
  Speaker 2: five hundred million years or billion years or whatever. But
• 2:09:44
  Speaker 2: it's basically ten percent, like if it's if it's half
• 2:09:46
  Speaker 2: a billion years as tempercent of Earth's lifespan.
• 2:09:48
  Speaker 3: So one way to think of.
• 2:09:50
  Speaker 2: It is if if if the take were taking ten
• 2:09:54
  Speaker 2: percent longer, we might never have made it at all.
• 2:09:58
  Speaker 2: So it's like the amount of things that have to
• 2:10:02
  Speaker 2: happen for sentience, it seems like it's it's quite quite
• 2:10:07
  Speaker 2: a lot. Actually, I think sentience is therefore actually very rare,
• 2:10:13
  Speaker 2: and we should certainly treat it as rare.
• 2:10:15
  Speaker 3: Should assume it's rare.
• 2:10:16
  Speaker 4: Two trillion galaxies, but.
• 2:10:20
  Speaker 3: Coming out is a funny thing. You tweak it, you know,
• 2:10:22
  Speaker 3: you tweak the variable one little bit, it's like, yeah,
• 2:10:25
  Speaker 3: one in one hundred trillion, tweet a little more. That's
• 2:10:29
  Speaker 3: one in a quadrillion. Yeah, okay.
• 2:10:32
  Speaker 2: And also it's got to be a kind of annual galaxy.
• 2:10:34
  Speaker 2: It's like hard to get between galaxies. It's like there's
• 2:10:37
  Speaker 2: no unless unless the the galaxy is coming to you,
• 2:10:40
  Speaker 2: which Andromeda is at some point or somethillion.
• 2:10:43
  Speaker 4: It's gonna be quite a show.
• 2:10:45
  Speaker 2: Yeah, yeah, it'll be like it comes Andromeda. But but
• 2:10:50
  Speaker 2: if we wanted to go visit another galaxy, there's there's
• 2:10:53
  Speaker 2: it's kind of forget it.
• 2:10:56
  Speaker 4: You know, there's unless you unless, unless Star Wars, unless
• 2:10:59
  Speaker 4: start trek.
• 2:11:00
  Speaker 2: Really we got to figure out new physics to get
• 2:11:02
  Speaker 2: to other galaxies.
• 2:11:03
  Speaker 5: We're heading towards a near term potential where AI can
• 2:11:08
  Speaker 5: help us solve math, physics, chemistry, material science.
• 2:11:11
  Speaker 2: Maths, coology extremely trivial for AI.
• 2:11:13
  Speaker 3: What about physics? So so math gets crushed in a year,
• 2:11:16
  Speaker 3: crushed at the losses is growing, you know, at whatever
• 2:11:20
  Speaker 3: rate TSMC decides to grow. And now we want to
• 2:11:26
  Speaker 3: do physics. First of all, we need some data. Do
• 2:11:29
  Speaker 3: we need new data or can we just do it
• 2:11:30
  Speaker 3: with everything we've gathered to get the hot Probably you
• 2:11:33
  Speaker 3: probably could probably.
• 2:11:34
  Speaker 2: Figure out new things just with the existing data. I
• 2:11:36
  Speaker 2: think so, yeah. Probably it's because otherwise the counterpoint would
• 2:11:40
  Speaker 2: be that humans have figured out everything with existing data,
• 2:11:43
  Speaker 2: and that's unlikely.
• 2:11:44
  Speaker 3: I think.
• 2:11:45
  Speaker 5: Do you think XAIS can get involved in data factories
• 2:11:48
  Speaker 5: where you're running twenty four to seven closed AI hypothesis
• 2:11:52
  Speaker 5: and AI or like.
• 2:11:55
  Speaker 11: Research factor research factories, it's going to be very yes, yeah,
• 2:12:03
  Speaker 11: a running you know simulations that are.
• 2:12:07
  Speaker 3: Very physics accurate.
• 2:12:09
  Speaker 2: I mean it's gonna that's gonna happen absolutely. I mean
• 2:12:14
  Speaker 2: the simulations we can run on conventional computers these days
• 2:12:16
  Speaker 2: are actually very good. It's like the limit is more
• 2:12:19
  Speaker 2: like the human that can actually create the simulation and run.
• 2:12:24
  Speaker 2: It's like, how many simulations can you run some simultaneously
• 2:12:26
  Speaker 2: and actually digest the output of.
• 2:12:28
  Speaker 3: Yeah, that's a problem, like you can't do I can
• 2:12:34
  Speaker 3: keep up.
• 2:12:36
  Speaker 4: Nobel prizes become irrelevant.
• 2:12:39
  Speaker 10: Uh where they will be given eyes just be a
• 2:12:42
  Speaker 10: daily prize.
• 2:12:47
  Speaker 2: Yeah, I mean I don't know if prizes for humans
• 2:12:51
  Speaker 2: are like that relevant. I mean we'll have to give
• 2:12:56
  Speaker 2: them to the AIS or something. As will come up
• 2:12:59
  Speaker 2: with Scott disc reason a far greater rate than humans.
• 2:13:02
  Speaker 2: If you have you just said, like can be like chess,
• 2:13:05
  Speaker 2: Like you know, like your phone can beat Magnus Collson,
• 2:13:07
  Speaker 2: but people still care about singing play chess, so this
• 2:13:12
  Speaker 2: a bit.
• 2:13:12
  Speaker 3: But literally your phone can beat them. This made the Internet.
• 2:13:16
  Speaker 3: If you have like a Colossus math, Colossus physics, Colossus medicine,
• 2:13:22
  Speaker 3: do you have like the world's top scientists in those
• 2:13:24
  Speaker 3: same buildings where you just need a plumber patching the liquid?
• 2:13:28
  Speaker 5: Do you distill do you distill rock six into a
• 2:13:32
  Speaker 5: a physicist?
• 2:13:34
  Speaker 3: Well, if you distill, you know, you get about a
• 2:13:36
  Speaker 3: ten x performance boost by distilling it and making it topical,
• 2:13:39
  Speaker 3: and that's kind of hard to give up. But then
• 2:13:41
  Speaker 3: you're disconnected from the rest of the colossus machinery. Is
• 2:13:43
  Speaker 3: that the is that the design.
• 2:13:51
  Speaker 2: I suspect things to evolve to a mixture of experts
• 2:13:54
  Speaker 2: kind of like a company, like not not not in
• 2:13:55
  Speaker 2: the sort of sort of uh parochial AI description of mixture,
• 2:14:00
  Speaker 2: sure of experts, but mixture of like actual experts and
• 2:14:02
  Speaker 2: with domain expertise, where you know, maybe like half of
• 2:14:06
  Speaker 2: the AI is general knowledge, half is domain expertise, something
• 2:14:09
  Speaker 2: like that, and you combine a whole bunch of that
• 2:14:11
  Speaker 2: that's orchestrated by sort of you know what a big
• 2:14:14
  Speaker 2: AI but but enhands tasks.
• 2:14:18
  Speaker 3: Two smaller areas.
• 2:14:19
  Speaker 2: That's basically how human companies were.
• 2:14:22
  Speaker 5: But the discovery rate, right of breakthroughs new I mean,
• 2:14:27
  Speaker 5: patents are immaterial at some point because everything is being reinvented,
• 2:14:31
  Speaker 5: re engineered instantly.
• 2:14:34
  Speaker 4: And then and.
• 2:14:35
  Speaker 5: Then the company that's got the sufficiently advanced AI systems
• 2:14:40
  Speaker 5: is generating new products and new discoveries at a accelerating rate.
• 2:14:46
  Speaker 4: And the singularity, Yeah, it's going to be an awesome future.
• 2:14:54
  Speaker 3: It's excitement guaranteed, guaranteed, Hence the simulation continues. Nothing to
• 2:14:59
  Speaker 3: worry about.
• 2:15:00
  Speaker 2: Yeah, excitement guaranteed. I mean, I mean it's it's not
• 2:15:04
  Speaker 2: all good excitement, but it's it's probably hopefully mostly good excitement.
• 2:15:10
  Speaker 3: Yeah.
• 2:15:11
  Speaker 5: Speaking of excitement, hang on to your seat. What do
• 2:15:13
  Speaker 5: you imagine the hover time for the Roadster is going
• 2:15:16
  Speaker 5: to be on rocket engines?
• 2:15:18
  Speaker 3: That's classified classified.
• 2:15:21
  Speaker 2: Well, I don't want to let the cat out of
• 2:15:22
  Speaker 2: the bag.
• 2:15:23
  Speaker 5: Okay, but there's going to be a horver time. There's
• 2:15:26
  Speaker 5: going to be cold gas engines.
• 2:15:28
  Speaker 3: It's going to be a cool demo.
• 2:15:29
  Speaker 4: I can't wait. Can I get an invite?
• 2:15:31
  Speaker 3: Yeah? Okay, yeah, I think it's going to be the
• 2:15:33
  Speaker 3: safest thing ever built.
• 2:15:37
  Speaker 2: This is not This is not the Safety is not
• 2:15:39
  Speaker 2: the it's not the prime. It's not the main goal
• 2:15:42
  Speaker 2: of I mean, if you buy a you know, a
• 2:15:46
  Speaker 2: sports car, you know, like to buy a Priori, safety
• 2:15:49
  Speaker 2: is not the number one, you know goal. This is
• 2:15:51
  Speaker 2: not this is I'd say it's like, safety is your
• 2:15:55
  Speaker 2: number one goal.
• 2:15:55
  Speaker 3: Don't buy the road Star. Oh believe me. I drove
• 2:16:00
  Speaker 3: just this week on New England roads sheet ice mad.
• 2:16:03
  Speaker 3: Just a little thrust, I could be very much more so.
• 2:16:07
  Speaker 3: Just drifting towards something very concrete.
• 2:16:10
  Speaker 2: Computer will probably keep you safe. But rust you go
• 2:16:14
  Speaker 2: really fast, Ye, bad things can happen.
• 2:16:18
  Speaker 3: You can decelerate really quickly with thrust. Get rubber on
• 2:16:21
  Speaker 3: road is not a great way to decelerate. I'm thinking
• 2:16:27
  Speaker 3: fast and safe.
• 2:16:29
  Speaker 2: I hope so well, aspire not to kill anyone in
• 2:16:31
  Speaker 2: this car. But it'll it'll be, it'll be something. It'll
• 2:16:36
  Speaker 2: be the best of the last of the human driven cars.
• 2:16:42
  Speaker 3: That don't go really well with Starship actually the last,
• 2:16:45
  Speaker 3: the best of the last, last human driven last. Yeah,
• 2:16:48
  Speaker 3: there's a lot of lasts coming this year.
• 2:16:50
  Speaker 5: Any final words of optimism for us to monetize.
• 2:16:56
  Speaker 3: Anything hopeful.
• 2:17:00
  Speaker 1: I wish to ask Grog thanks for listening to this podcast.
• 2:17:04
  Speaker 1: If you want to listen to full interview in this podcast,
• 2:17:07
  Speaker 1: the link is in description