All language subtitles for Elon Musk on AGI Timeline, US vs China, Job Markets, Clean Energy & Humanoid Robots 220 - Peter H. Diamandis (360p, h264)

My concern isn't the long run. It's the

next 3 to seven years. How do we head

towards Star Trek and not Terminator?

>> I call AI and robotics the supersonic

tsunami. We're in the singularity.

>> When is all white by color work gone?

>> Anything short of shaping atoms. AI can

do half or more of those jobs right now.

There's no onoff switch. It is coming

and accelerating. The transition will be

bumpy. You have a solution to this.

>> I don't make a bet here. Um,

>> China's done an incredible job,

>> right? I mean, it's running circles

around us. Do you imagine that the US

could make that level of investment and

commitment

>> based on current trends? Uh, China will

far exceed the rest of the world in uh

AI compute.

>> Every major CEO and economist and

government leader should be like, what

do we do?

>> We don't have any system right now to

make this go well. But AI is a critical

part of making it go well. There are

three things that I think are important.

Truth [music] will prevent AI from going

insane. Curiosity, I think, will foster

any form of sentience. And if it has a

sense of beauty, it will be a great

future. It's going to be an awesome

future.

>> Now, that's a moonshot, ladies and

gentlemen.

>> Welcome to Moonshots. Following is a

wide-ranging conversation with Elon Musk

focused on optimism and the coming age

of abundance. My moonshot mate Dave

Blondon and I flew into Austin, Texas to

meet up with Elon at his 11.5 million

square foot Gigafactory, home of the

Cybertruck and Model Y production and

the future home for 8 million square ft

of Optimus production. Elon has agreed

to do this kind of a deep dive catchup

once per year. This is hopefully the

first of many. And after having this

conversation with Elon, it's crystal

clear to me that we are living through

the singularity. All right, enjoy.

>> Yeah. Um, [snorts] your relentless

optimism is always a breath of fresh

air.

>> Thank you, buddy. Thank you. Well, I

want to share that tonight with a lot of

people. [laughter]

>> Yeah,

>> I think they need it.

>> I hope you're right. And you might be

right. Actually, I'm increasingly

thinking that you are right.

>> Thank you.

>> Abundance for all.

>> Yeah,

>> that's the goal. Shall we?

>> Yeah.

>> All right.

>> Right now, putting a lot of time into

chips.

>> You are. You are personally.

>> Yeah.

>> Yeah.

>> It's always AI assistance, I assume.

>> What's that? with some AI assistance. I

assume that design

>> uh not enough.

>> Yeah. [laughter]

>> It' be nice if we could just hand it off

to the AI.

>> Yeah. Yeah.

>> Soon enough.

>> Yeah. I tried to do some circuit design

actually with uh AI recently. Just this

a couple weeks ago. Not not happening

yet.

>> Um

very soon though.

>> Yeah. Um I I think probably at this

point Grock if you if you took a photo

and submitted to Grock, it could

probably tell you if if the circuit is

is if there's something wrong with it.

>> Yeah.

>> Yeah.

>> All right. I'm going to give it a shot.

You're using the same Grock that I'm

using. Are you or you are [laughter]

>> Grock keeps updating. So

>> yeah, 4.2, but five is soon, right?

>> Uh five is Q1.

>> Yeah.

>> Um 4.2 has not been released yet.

>> Okay. uh externally. Um but yeah, I mean

if you just if you just upload an image

into Gro um

>> it's it's does quite a good job.

>> Yeah.

>> Um

>> yeah,

>> of of analyzing any any given image.

>> Absolutely. Let's uh let's start. We're

going to talk about this.

>> All right. We'll come back.

>> I mean, let's see if I if I take an if I

take a picture of you, what is it? Let's

see what it

>> Yeah. What's it going to say about me?

>> Yeah, it's going to say you're a flawed

circuit. I also have to remember to

update it because like we update the

Grock app so frequently.

>> You know, I asked I asked Grock to roast

me.

>> Oh, it's does a good job.

>> It did an amazing job. Then I asked

Grock to roast you. Yes.

>> And I spit out my coffee. It was it was

hilarious. And then I asked it, you

know,

>> say be more. It just keeps telling it to

be more and more. [laughter]

>> I asked I asked [clears throat] until

until it's like mother of God.

>> Wait, is Bad Rudy still out or did that

get repealed? Bad Rudy still there?

>> And I asked, you know, does Elon know

what you say about him? and and and she

goes, "It's a she for me." She goes,

"What is he going to do about it?"

[laughter]

>> What is he going to do about it?

>> Yeah, let's see. Okay.

>> Um, so I just literally took a photo of

you and see what it is.

>> Did you ask a question?

>> No, nothing. I didn't say anything.

>> This man is is hugely

>> This This is Peter Diamandis.

>> Yes.

>> So,

>> okay.

>> That's pretty good.

>> Yeah.

>> There's no context whatsoever.

>> The host of the podcast Moonshots. Yeah.

>> Uh, sometimes that's your first

credential now. That's amazing. Forget

about everything [laughter] else I've

done in life. Comes back to your

podcast. That was a no no context image.

>> Yeah. By the way, Graedia is awesome.

>> Okay, great.

>> I mean, just phenomenal. [laughter]

>> I mean, just it's like I tried to like

update my Wikipedia page for like years

impossibly

>> and um Yeah, it it it knows me.

>> Amazing.

>> Yeah. Um, he's wearing a black quilted

jacket featuring a Sundance logo.

[laughter]

>> Not quite true. It's my abundance logo,

but I guess a little wrinkled. See the

>> Can it see it?

>> I I I think so.

>> Okay. Okay.

>> Anyway,

>> um Yeah, but it basically

uh it's pretty damn good.

>> Yeah.

>> Um he's smiling and relaxed with a

laptop in front of him.

>> That's true.

>> Yeah, that's true.

Um,

>> yeah.

>> Well, I should say quite a circuit

though. [laughter]

>> You got to test it on the

>> roast him.

>> Only It has to be read by you, though.

>> I mean, I won't read the whole thing,

but

>> All right. [laughter] Give me Give me a

taste. I can take it.

>> Okay. Check out that grin. Dude smiling

like he just discovered a new way to

monetize hope. [laughter]

>> Monetizing hope. Oh, that's

>> I want to try and answer the question,

can AI and tech help save America and

the world? Right. Um, I want to give

people listening a dose of optimism.

There's a survey done in mid December by

Pew that said 45% of Americans would

rather live in the past and only 14%

said they'd rather live in the future,

which is insane to me, right? Um,

obviously they never read history. The

challenge is most Americans all they

have of the future. It's like Hollywood

has shown us killer AIs and rogue

robots, right? And people are worried

about their jobs. They're worried about

healthcare. They're worried about, you

know, the cost of living. The challenge

is how do we how do we help people? I

mean, you posted, you pinned on X, the

future is going to be amazing with AI

and robots enabling sustainable

abundance.

>> I think of you when I did that.

>> Thank you. I appreciate that. and and uh

[laughter]

>> well I mean

>> it's like what would Peter do you want

to say?

>> Yeah was channeling you.

>> Thank you. Thank I couldn't agree more.

I didn't agree more either. [laughter]

>> That's great.

>> So so my question is from a you know

from a first principle standpoint

>> right

>> uh the rationale for optimism you know

how do we how do we head towards Star

Trek and not Terminator right? How do we

how do we head towards

>> Ronberry not Cameron. Yeah, [laughter]

Jim. Jim, I will I will

>> the diverging path meme.

>> Yes, [laughter] it is. It is. Uh, Avatar

has some hopeful parts, but anyway,

>> I how do we go towards universal high

income instead of social unrest? So, my

>> both

[clears throat and laughter]

want socialrest.

>> So,

have universal high income and social

unrest. M

>> that's my prediction.

>> Oh, that will make for a lot of

problems. [snorts]

>> Is that your actual prediction?

>> Yeah.

>> Yeah, it seems likely. [laughter]

>> Like tell me to push back on it.

>> Yeah, exactly. But it seems like that's

the trend.

>> Yeah. Yeah, totally. No, we have

>> Well, because there's going to be so

much change.

>> Yeah, there's people are going to be

like scared shitless.

>> Yeah, it's it's sort of the um

you know um it's like be careful what

you wish for because you might get it.

>> Yeah. Yeah.

>> Now, if if you if you actually get all

the stuff you want, is that actually the

future you want?

>> Yeah.

>> Um because it means that your job won't

be what matter

>> if you're living an unchallenged life.

>> Yes.

>> Right. With no challenges.

>> Yeah.

>> No. You know, you know, if you become a

couch potato, if it's the Wall-E future,

that does not go well for humans.

>> Well, and we're used to being told,

here's your challenge. Yeah.

>> So people haven't historically been very

good at creating their own challenge in

the absence of

>> I think Elon does a damn good job. Every

time you every time one company takes

off, you start your next.

>> Oh, that's that's rare for punishment.

>> I think you are. I think you overthank

God for that.

>> So So [laughter] what so

>> why do I do this to myself?

>> Actually, after AI and robots, is there

another thing after that? I guess

there's

>> Well, there's there's conquering, you

know, the universe.

>> Yeah, that there is that

>> rocks really.

>> Well, [laughter]

and energy

>> rocks are your friends.

>> Conquering

>> We didn't even get there.

>> Why, Elon? Why are you so optimistic?

>> Are you Are you optimistic? Let's start

there.

>> I'm not as optimistic as you are.

>> Okay.

>> Um but why are you optimist?

>> I'm more optimistic than most people.

>> Okay.

>> Um

>> and is the trend upward

compared to a year ago, two years ago?

Well, I I think if you reframe things in

terms of

um progress bar, like speaking of

challenges,

>> yeah,

>> uh progress towards a cartev 2 scale

civilization.

>> Sure.

>> Um well, let's say let's say the

aspiration

>> capturing all the energy from the sun's

output.

>> Well, let's even have a a humbler

humbler aspiration than that. If we say

that our goal is to even get a millionth

of the sun's energy,

>> that would be more than a thousand times

as much energy as could possibly be

produced on Earth.

>> So about a half a billionth of the sun's

energy reaches Earth. Um so you'd have

to go up three orders of magnitude from

that uh just to get to a millionth.

>> Yeah.

Um,

so

we're very very very far from even h

having a billionth of the sun's energy

uh harnessed in any way. So a reasonable

goal would be try to get to a millionth.

And if you try to get to a millionth or

or a thousandth um you know 0.1%.

Uh

that's that's such an enormous

uh there's not sure what metaphor we'd

use here because a hill to climb is is

not a

>> inapprop like not a big enough metaphor

but

>> gravity well to escape [clears throat]

>> engineer hell of a gravity well.

Exactly. Um so if if you try to get to a

millionth of the sun's energy or a

thousandth the sun's energy like now the

these are very very difficult tasks

>> and energy is the inner loop for

everything right now.

>> Yeah. I I think like I I think uh the

future currency will essentially just be

wattage.

>> Yeah. I was thinking is it is it d is

the ability of a person to control

energy and compute

>> or just energy? I mean the two translate

obviously

>> just [clears throat] like harnessed

energy.

>> Yeah.

>> Like so or like basically how much power

is being turned into work of some kind,

>> right?

>> Um

intelligence or

um matter manipulation. Um,

>> so that's your next big project is going

to be energy.

>> It's it's going to be you're going to go

back to your solar your solar system.

>> You can expand from there and say, okay,

>> what about even getting somewhere on a

on a cottage of three scale, meaning

galaxy level.

>> Now you're talking now. Now we're back

to Star Trek.

>> Yeah. Expand horizons here.

>> Yes.

>> Where there isn't even a horizon because

you're not on a planet. [laughter]

>> So we we talk about

>> So So think galaxy mind.

>> Yeah.

Well, listen, we're in 11 11.5 million

square foot, three pentagons right here

in this building. I mean, you think in a

reasonably large scale,

>> what is the magnitude?

>> Yeah.

>> Um, so I mean, so from a challenge

standpoint, I guess

the civil the civilizational challenge

will be how do you climb the orders of

magnitude?

>> Yeah.

>> And energy harnessed.

>> But we're going back to why are you

optimistic right now? I mean, when

people think about uh the challenges

ahead, I think we're going to end up

with abundance in the long run, it's for

me

>> beyond abundance in any beyond what

people possibly could think of as

abundance. Um like the AI actually

AI and robots the limit um will will

saturate all human desire.

>> And then we get to nanotechnology which

takes it even a step further.

Um the thing about the well I'm not sure

what you mean by nano you mean like

little nanobots

>> atomic reassembly.

>> Yeah. For health.

>> Oh yeah. Yeah. Sure. Sure. Um I mean

we're already doing atomic level

assembly on the for circuits you know.

>> Amazing.

>> Um

>> two three nanometers.

>> Yeah. It's it's only um depending on how

they're arrayed four or five silicon

atoms per nanometer.

>> Yeah.

>> So

>> those are big atoms though.

>> They're not bigish. They're not your

little I mean but but I'm just saying

you could they should actually describe

the circuits in terms of an integer

number of atoms in a specific place.

>> They should it's all angstroms now but

>> you could you can just it's just inte

it's it's like we'll call this the the

seven atom you know whatever like you

say two two nanometers it's like it's

like

>> no one knows

>> nine silicon atoms something like that.

Um they've got silicon and copper and um

you know so but a bunch of these things

are just marketing numbers like the two

nanometer is just a marketing number.

>> Oh yeah.

>> Um but but it's you still need

essentially close to atomic level

precision. Like the atoms really need to

be in the right spot.

>> Um so um

I think they're getting clean rooms

wrong by the way in these modern fabs.

Um

I'm going to I'm going to make a bet

here. Okay.

>> Okay.

>> Um that Tesla will have a 2nmter fab and

I can I can eat a cheeseburger and smoke

a cigar in the fab.

>> Oh, [laughter] come on.

>> Yes.

>> The air handling will be that good.

>> Do you have this sketched out in your

mind? Like how is it how are the atoms

being placed that they're immune to uh

cheeseburger grease? [clears throat]

They just maintain wafer isolation the

entire time. um which is actually the

default for for fabs. The the wafers are

transported um in boxes of pure nitrogen

gas under a slight positive.

>> So are the bananas at Walmart. I

>> just so you know.

>> Yeah. [laughter] Well, that's that's

it's inite essentially like it's pretty

hard for anything that's combusting

>> uh to live without oxygen.

>> Yep.

>> So um

>> let's talk about

>> So like like you can kill the bugs just

by putting a nitrogen blanket on plants.

>> Yeah. Interesting.

>> I want to talk about uh energy, health,

education because those are people's,

you know, concerns. So, on the energy

front,

>> um the innermost loop of everything that

you're building and doing right now,

>> energy is the foundation.

>> What's your vision for energy abundance?

Uh

>> the sun

>> in in in the next, you know, this this

this [laughter]

decade. The sun. Yeah. I mean, so

>> the sun is everything.

>> It's everything. So, you're all in on

solar.

>> I mean,

>> uh Yeah. I mean your natural gas natural

gas and solar you're at Colossus 2,

right?

>> Yeah.

>> People just don't understand how

>> that that solar is everything. So um

everything compared to the sun, all

other energy sources are like uh cavemen

throwing some twigs into a fire.

>> Yeah.

>> Um so the the sun is over 99.8%

of all mass in the solar system. Uh

Jupiter is around uh.1% of the mass. Uh

so even if you burnt Jupiter, the energy

produced by the sun would still round up

to 100%.

>> Yeah.

>> Mhm.

>> And then if you teleported three more

Jupiters into our solar system and burnt

them too,

>> it would still round up.

>> It still the sun still rounds up to 100%

of energy.

>> Any interest in fusion?

>> I mean like fusion on a planet

[laughter]

fusion.

You know what? You know coming a mile

away. [laughter]

>> You're not never going to guess how the

sun works.

>> Giant coal plants. [laughter]

>> I mean, we have a giant fus free fusion

reactor that shows up every day

>> 93 million miles away.

>> It's farical for us to create little

fusion reactors. Um

I mean that would be like, you know,

having a tiny ice cube maker in

[laughter] the Antarctic.

and say, "Hey, look, we made ice." I'm

like, "Congratulations. [laughter]

You're in the [ __ ] Antarctic."

>> So, totally totally with you on this.

>> It's like

3 kilometer high glaciers right next to

you.

>> Okay. [laughter]

>> Yeah. If you just narrow the question to

the Memphis timeline. So, Memphis data

center timeline between a gigawatt and

10 gig. You're not going to you're not

going to pull 10 gigawatts out of

Memphis. Um maybe you are [laughter]

>> two or three.

>> Two or three. Okay. So So there's still

a gap between there and the next

whatever you just just draw. So and

they're not in space yet at that point.

>> So we're still in toy land here. Uh for

on toy land you

>> toy land. Toyland

>> 10 [laughter] gigawatt.

>> You know what's amazing is there's 100

megawatts right outside the door here

>> and it's massive. Yeah.

>> It's it's enormous. And it uses more

energy

>> than everything. All these manufacturing

lines combined use less energy than

that.

>> I think but we're talking about a

longgo. Cortex one was

>> the the third largest training cluster

in the in the world.

>> Yeah.

>> For for doing coherent training.

>> You're falling behind. [laughter]

>> Uh well, we have Cortex 2 that's being

built out. Um

>> that'll be uh half a gigawatt uh and

operational middle of next year. Mhm.

Uh,

>> hey everybody. You may not know this,

but I've got an incredible research

team. And every week myself, my research

team study the metat trends that are

impacting the world. Topics like

computation, sensors, networks, AI,

robotics, 3D printing, synthetic

biology. And these meta trend reports I

put out once a week enable you to see

the future 10 years ahead of anybody

else. If you'd like to get access to the

Metatrends newsletter every week, go to

dmandis.com/tatrens.

That's damandis.com/metatrends.

[snorts] So going back to what Dave is

saying over the next five years, what

are you scaling on energy front? Do

>> I mean

>> five years is a long time.

>> I mean energy I mean China has done an

incredible job.

>> Yeah.

>> Right. I mean it's running circles

around us.

>> Uh China has done an incredible job on

solar.

>> Yeah.

>> It's amazing.

So I I believe China's uh production

capacity is around 1500 gawatts per year

of solar.

>> Yeah. They put in 500 terowatts in the

last year

>> terowatt hours. Yeah. Terowatt hours

like 500 [laughter] 500 terowatt hours

to be very specific

>> in the last year. 70% of that was solar

and they're just scaling.

>> Do do you do you imagine that

>> solar scales? Do you imagine that the US

could make that level of investment and

commitment? I mean because people are

worried about their energy bills going

up with no no data centers in our

backyard. How do we provide I mean

energy energy is equivalent to is

equivalent to cost of you know cost of

living. It's equivalent to health. It's

equivalent to clean water. You know the

higher energy uh production of a country

the higher its GDP. Um energy is

important. So what should what do we do

to scale that way? Do we do it in solar

here?

>> Um I think we should scale solar

substantially in the US. Um

um Tesla and SpaceX are scaling solar.

Um

so uh and I encourage others to do so as

well. M

>> um so the the uh

I mean I've said the stuff you know

publicly um I do see a path to 100

gawatts a year of of space solar sort of

a AI powered solar powered AI

satellites.

>> Yes 100 gawatts a year of solar powered

AI satellites.

>> I did the math on that. Uh, that's like

500,000

Starlink V3s launched over 8,000

Starship flights. That's one every hour

for a year. Um, yeah,

we 10,000 flights a year is is a

reasonable number. Um, so

>> it's amazing. It's quite the scale.

Well, what's what's the really rough

timeline on that because I mean by

aircraft standards that's a small

number.

>> Sure. In terms of flights. Yeah, for

sure.

>> Yeah, that's uh that's that's that's a

small f like so just like depends what

you compare it to. If you compare it to

the rest of the rocket industry, it's a

very high number.

>> Yeah.

>> Um

>> and we're talking about a million tons

of payload to orbit per year. So if you

do if you do a million tons of payload

or orbit per year with 100 kilowatts per

ton, uh that's 100 gawatt of solar

powered AI satellites um per year.

>> Yeah. Um I mean there's a there's a path

to get probably to a terowatt per year

um

>> from from the from

if you say like uh 10 you want you want

to go up another order of magnitude or

let's say you want to go to 100

terowatts a year.

>> Yeah.

>> Which obviously kind of nutty numbers.

>> Uh then you want to make those uh AI

satellites on the moon.

>> Yes.

>> And use a mass driver. Yeah. So, the

Gerard K. O'Neal approach.

>> Well, like Robert Heinland was a harsh

course. Pretty much. Yeah. I love that

book.

>> Yeah. Yeah. It's a sort of libertarian

paradise on the

>> um

uh Yeah. So, cuz on the moon you can

just accelerate the satellites into

to escape velocity is around 2500 meters

per second. Um and uh there's no

atmosphere. So, like a mass driver works

very well on the moon. Can I ask the the

question about orbital debris? I mean,

we're we're building effectively a

Dysonish swarm around the Earth.

>> Um, [laughter]

eat it for lunch.

>> Uh, are you worried about over

congestion on the uh

that's going to be a Sunsync orbit's

going to fill very quickly.

>> I mean, you can you you don't have to

have sunsync. I mean, you can uh

>> don't have to, but it's optimal.

>> Yeah. Um

there's some pros and cons to to sunsync

or not sunsync. Um

I mean, your your payload to orbit drops

by like 30% compared to, you know, if

you were just went to um like mid-

inclination like 70° or something like

that.

>> Yeah. I mean, do we need an orbital

debris x-prise at this point? We need

some way to get the the satellites

>> um

>> defunct satellites down. Do we pass

rules that require them to de-orbit on

their own?

>> Yeah. At the point at which you you can

put a million tons of satellites into

orbit, you can also, you know, start

bringing down satellites, too. Yeah.

>> Um or at least collecting them into a

known into a fixed location so they're

not like all over the place.

>> Yeah. and then you can reuse them.

>> Yeah. Um let's just say that we'll have

so the the resource level will be so

high that that I believe this will be a

solved problem given the amount of

intelligence we're talking about here.

>> Oh

>> um like the intelligence will be quite

interested in preserving itself.

>> Yes. That's true.

>> Oh

>> interesting.

>> Yeah. Good motivation.

>> Yeah.

>> Interesting.

>> The question is the data centers will

not be in low earth orbit, right?

They'll be they'll be much higher

constantly in the sun. They're not going

to be in the traffic jam, I assume.

>> Uh, well, you can get to, you know, you

don't have to get to get to constant

sunlight. You can be around 1,200

kilometers on synchronous will give you

constant sunlight.

>> Mhm.

>> Um,

>> but you could you could place him in

multiple orbits.

>> Yeah.

>> Yeah.

>> Yeah. No, I think if there's an X- prize

for cleaning up, it's got to be there's

only going to be clutter in low Earth

orbit. I mean debris from

>> anything anything that's if it's a you

know below around 7 or 800 kilometers

the atmosphere will atmospheric drag

will bring it back.

>> Yeah.

>> Um so like for Starlink there's a dual

benefit of being

uh like as low as possible because uh

your your your beam you you know your

beams are tighter. you know, you're

basically that you have less latency and

and your your your beams are smaller if

you're you're closer to the earth. So,

uh like Starling 3 will be around 330 to

350 km,

>> which is quite a lot of drag. Uh so,

it's basically constantly thrusting to

>> I still remember when you proposed

Starlink and everybody else in the

industry was like, "No way. No way. He's

not going to get the spectrum. He's not

going to be able to do this." Um

>> yeah,

>> it's uh it's kind of worked.

>> Yeah, we're the stalling team have done

an incredible job.

>> Yeah.

>> Um

>> I mean we've basically rebuilt the

internet in space with with a laser

links.

>> Mhm.

>> So there's uh 9,000 satellites up there

right now.

>> Do you think the government's going to

be able to handle the kind of licensing

of the volume of satellites that you

want to put up? I mean, will there be

push back cuz you know, China's going to

put up their own constellations.

Uh Europe, who knows whether Europe will

ever step up?

>> They won't.

>> What's that? They won't. No.

>> And there's probably

>> Yeah.

>> Nothing that nothing they're doing h has

success in the set of possible outcomes.

>> Yeah. [laughter]

>> I just got back from Rome. I don't want

to touch [laughter] touch that railing.

>> Successes are on the set of possible

outcomes.

No, the chart of outcomes though

>> the chart that shows the number of

billion dollar startups in the US versus

Europe.

>> Have you seen that graphic?

>> Oh my god, it's crazy.

>> Yeah. And data centers too. It's

actually um

>> no one was talking about orbital data

centers six months ago.

>> Yeah.

>> Nobody. And then all of a sudden

>> Sundire's on it.

>> You're you're out with it. And

>> it's the hot new thing

>> and it is what what [laughter]

what tip what happened? What happened

that every company is now talking about

orbital data centers?

>> I guess it went viral and X. [laughter]

>> It did.

>> I don't know. Is every company talking

about

>> Oh, yeah. Everybody's got their own

orbital data center.

>> For sure. And I I was suggesting to

Peter that that you updated the math on

launch costs and that it's a tipping

point very quickly with the updated

math.

>> But Starship's been the cost for you

know, I don't know what you hold $100

per kilogram, $10 per kilogram. What do

you have Starship at? It's possible that

Elon said that and nobody believed it

until now.

>> No,

>> you can go back and look at my what even

back when it was Twitter uh the my old

tweets. I I said these things se many

years ago.

>> 100 bucks or 10 bucks a a kilogram.

>> Yeah. And I said this is we're we're

going to do a million tons a year to

orbit.

Um

Yeah. And and we've got to get the the

cost down.

>> Yeah. uh well below $100 a kilogram.

>> So that's going to move the data centers

to orbit.

>> It will. It's they can do you can

basically do the math like if you've got

a fully reusable rocket.

>> Yeah.

>> Um which is fully and rapidly reusable

like an aircraft. Uh then this is an

incredibly this is a very difficult

thing to do obviously. U I I think it's

at the limit of human intelligence to

create a fully and rapidly reusable

rocket.

>> Um

>> but it is possible and we're doing it

with Starship. It's It's been the holy

grail in the aerospace industry forever.

>> Yeah. Quest for the holy grail rocket.

>> Yeah.

>> And then I pretty much it is I mean

right the DCX was the first little

things that were trying there and uh

it's been you know all of I mean back

when I was in the space industry that's

all everyone ever spoke about. And then

when Falcon 9 first reused its first

stage, um I mean all the traditional

aerospace industries did not believe

that even Falcon 9 could re could could

fly and reuse.

>> Literally you can come see it land at

Cape Canaveral.

>> Yeah.

>> Um and then take off again.

>> Yeah.

>> So I don't know how you would not

believe a thing that you can see with

your own eyes.

>> Yeah. Well, they didn't believe you

could. They didn't believe you could.

>> But the the the la the leap from there

to the launch cost actually requires

more faith than just just that. But I

think I think Starship is the launch

cost tipping point and that somewhere in

that you know before you had Twitter it

became X somewhere in that timeline it

went from speculative to no doubt and I

don't know if that's a smooth line or a

couple of good launches in between but I

suspect that the data centers in space

>> but people

>> ties directly to the credibility

>> is not thinking about orbital data

centers they're thinking about energy

and the cost of energy here on here in

their hometown and sort of the the

there's a lot of doomer

conversations out there. The data

centers are going to drive, you know,

the CPI up.

>> Uh

they're not entirely wrong.

>> Okay. So, what is so [laughter] what is

the what's the energy solution here on

Earth for uh the rest of humanity or the

the non data the non AIs?

>> Oh, there's something other than data

center use uses of energy. Okay.

[laughter]

>> Interesting.

>> Um

>> that's complex. Well, the the the

[snorts] best way to actually increase

the energy output per year of the United

States or any country is batteries. Um,

so the

>> sure

>> peak power output of the of the US is

around 1.1 terowatts, but the uh average

power usage is only half a terowatt.

>> Yeah. So if you just buffer the the

energy, so charge up the the batteries

at night, discharge during the day, um

without incremental capital expend

without incremental capital

expenditures, without building new power

plants, you can double the energy

throughput of the US. The energy output

per year can double

>> with batteries. Um

>> and do we have those batteries uh in

development?

>> Uh yeah, Tesla makes them.

>> Okay. So you think current the current

current Tesla battery packs? [laughter]

>> What do you think? What do you think? I

literally have I I went on stage and

presented the thing.

>> Yeah,

>> that's that's the dead giveaway. So

[laughter]

>> I I even went to installations of the

mega packs, you know, and there's

>> So why don't people do this?

>> It's on the internet. So

>> yeah.

>> So is do you think

>> they are? And and China, by the way, is

like it seems like China listens to

everything I say I say and does does it

basically or at least or or they're just

doing it independently. I don't know.

But they're they're certainly making um

massive battery packs like

really massive battery pack output.

They're they're you know making vast

numbers of electric cars. Yeah.

>> Uh vast amounts of solar. Um,

>> I don't know. These are all things I I

said, you know, we should do here.

>> Fundamental. Sure. When I fly over Santa

Monica and LA, when I'm when I'm I'm

piloting and I look down, they're like,

zero roofs have solar on them.

>> Zero roofs.

>> Yeah.

>> I mean,

>> it's not essential to have them on a

roof.

>> Okay. But it's a convenient place to

have them.

>> Yes. Uh, but the surface area of roofs

is uh I'm not saying it shouldn't, but

it's

>> uh Tesla makes a solar roof, which is

the the only solar roof that isn't ugly.

Um, our solar roof actually looks

beautiful.

>> Yeah.

>> Um,

but if you want to do solar at scale,

you just need more surface area.

>> So, so we we we have um vast empty

deserts. Sure. African America like if

you fly from LA to New York or just fly

across country and you look down um for

a large portion of the time you look

down it is bleak desert.

>> Yes.

>> It looks like Mars essentially.

>> We're not worried about overpopulation

there.

>> No, I mean it look there's barely a

lizard alive in these scorching deserts,

you know. Yep.

>> It's not like farmland we're talking

about. We're just talking about Yep.

>> Uh places that look like Mars,

>> like just uh scorched rock.

So if we put soil where we currently

have scorched rock,

>> I think this will be a quality of life

improvement for the lizards or the few

creatures that live in this

>> uh very difficult environment.

>> Do we have the distribution network?

>> It's like this is going to be thank god

some shade finally. [laughter]

>> Do we have the distribution network to

be able to do that? Yeah, you need to to

materially affect quality of life, you

need to capture and store what a couple

hundred gigawatts.

>> Is that in realistic?

>> You could just put the data center I

guess locally there.

>> Well, we already covered data centers.

[laughter]

>> We're talking about you know the other

>> Yeah.

>> Like I I don't know like in an abundant

world five years from now, massive

amounts of compute,

>> massive, you know, universal high

income.

>> I don't know income like universal you

can have whatever you want income.

>> Yeah.

>> Yeah. That's that's really what it

amounts to.

>> But in that world, uh, you know, other

than compute energy, how much more

energy do we need like 30 40 50% or I

don't know, unless we want to move

mountains around to make a ski mountain,

you know, in the backyard.

Um, I think the vast majority of energy

consumption will go into compute. And

then there may be use cases I'm not

thinking of like you know the well you

know right here is a nice case study

because manufacturing every one of these

cars coming out at the rate of one every

minute or two uh is less energy than the

data center that's training the cars to

drive to to self-drive.

>> Yes.

>> So that's a good little case study. And

we don't need that much more physical

energy for abundant happiness. We need

more compute energy. Well, yeah,

>> the sun is just generating vast amounts

of energy uh all the time for free that

goes just goes into space.

>> So, um I think we'll end up trying to

capture I don't know uh a millionth of

like a millionth a thousandth of the

sun's energy. Um, we're currently I'm

not sure the exact number, but we're

I don't know, we're probably at 1%ish of

Kadeshv level one.

>> Fair enough. Yeah, I I I would guess

that even that's high.

>> I'm just Yeah, saying

>> we have a long way to go.

>> I'm that's being optimistic. Like

hopefully we're not.1%, but I don't

think we're 10%. I'm just trying to get

it to like to an order of magnitude. Uh

>> so pull it like we're roughly 1% of the

apparently using 1% of the energy that

we could use on Earth.

>> I think the bottom line from a first

principles thinking for the public is

there's a lot of energy out there

>> a lot

>> and it we have it in the US. We have it

on the planet and it needs to be

captured and the tech to capture it

>> is here and improving every year.

>> Yes.

>> Yeah. um there's not going to be some

energy crisis. I there'll be a large

forcing function to harness more energy,

but we're not going to run out of it.

>> All right, I want to talk about

education.

So, here's the numbers. They're abysmal.

>> Um I mean, they're they're they're

abysmal, right? Okay. Uh the importance

of college in the United States, uh back

in 2010, 75% of Americans said it's

important to go to college. That number

is now down at 35%. All right. Uh,

college graduates as a group turn out to

be the group that's out of work the

longest,

>> right? And the but still and tuition has

increased 900% since 1983.

Um,

>> yeah, the administrative expenses at

universities have gotten out of control.

Yeah.

>> Um, so

>> I think I saw some stat that like

there's one administrator for every two

students at Brown or something like that

>> and I'm like this seems uh little high.

>> Yeah. You know what?

>> They should teach something.

>> Yeah. Yeah.

>> What was your college journey?

>> Um, I went to college in Canada for a

couple years at Queens University.

Uh-huh.

>> Um, so, uh, I I had Canadian citizenship

through my mom who was born in Canada

and my my grandfather was actually

American, but for some reason, I don't

know, my mom couldn't get US

citizenship, so but she was born in

Canada, so I got Canadian citizenship.

Um, and uh, I didn't have any money, so

I could only go to Canadian university

at first. I

>> mean, people forget that about you. You

didn't have this giant social network or

huge amount of wealth coming into all of

this.

>> No.

>> Yeah.

>> Uh, no. I I arrived in Montreal at age

17 with I think around $2,500 in

Canadian travelers checks back when

travelers checks were a thing.

>> Um and um one bag of books and one bag

of clothes. That was my starting point.

That was my spawning point in North

America. Um,

>> and then so I went to Queens University

for a couple years and then uh

University of Pennsylvania uh did a dual

degree in physics and economics um

>> and graduated

>> uh undergraduate at UPUP

Wharton.

>> Yeah. And then um I came out to do uh I

was going to do a PhD at Stanford

working on uh energy storage

technologies for electric vehicles

essentially material science I guess

fundamentally

>> um the the idea that I had was it was to

try to create a capacitor with enough

energy density that you could get um

high range in an electric car.

>> It's funny I invested in an ultra

capacitor company and didn't Yeah.

didn't go well. Well, it's one of those

things where, you know, you could

definitely get a PhD, but it wasn't

clear that you could make a company or

do something useful like this. Most PhD

is un hat I mean, hate it, but most PhDs

do not

>> turn into something that's going to

>> do not turn into something useful. Like

you you could add a leaf to the tree of

knowledge, but it's not necessar

necessarily a useful leaf. enormous

fraction of of great entrepreneurs are

dropping out

>> of grad school or undergrad. But now

nowadays the sense of urgency is off the

charts.

>> I mean they're popping out everywhere.

>> Yeah. Because you know don't waste your

time going into grad school. Start a

company.

>> Yeah.

>> Curriculum is nowhere near caught up to

what's actually going on in technology

and I don't have time and all the time.

It's like

>> you know this is the moment. I I think

right now it's like it's unclear to me

why someone would somebody would be in

college right now unless they want the

social experience.

>> Yeah.

>> Yeah.

>> I mean if you have the ability to go and

build something. So the question is how

would you redesign the educational

program if I could be so so blunt as to

create more Elon Musks? If we want to

create an Elon Musk factory of people

who start with very little but are able

to drive uh and drive breakthroughs.

What's involved there?

What drove you?

>> Uh curiosity um about the nature of the

universe.

>> So I'm just curious about uh

>> the meaning of life and

>> you know what is this reality that we

live in. So,

>> how early?

>> My son Dax wanted to know what was it

like for you in middle school and high

school.

>> He's 14 years old. He's in that age

range now.

>> Well, I did I found school to be quite

painful. Uh and it was very boring and

in South Africa it was very violent.

>> So So it's like it was it it was like uh

>> it's like that was like that book Enders

Game.

>> Yes. Um but in real IRL

>> in this game IRL there's like but not as

fun.

>> Um

>> so your goal was escape.

>> Yes.

>> Do you think

>> escape from the the prison?

>> So that's a question I have. Do you

[laughter]

do you think that

>> it was miserable?

>> Do you think most successful people have

had a lot of hardship early in life? Do

you need to have that level of hardship?

>> Probably need a little bit of hardship I

suppose.

>> Yeah. But and then so it's always tricky

like what are you supposed to do with

your kids? You know, create artificial

adversity. Put them in.

>> That's cool. [laughter]

>> You got an answer. That's that's a

Warren Buffett topic actually.

>> Yeah.

>> Well, you do.

>> But seriously,

>> it's not easy to create artificial

adversity because if you love your kids,

you don't want to do that. So

>> that's for sure.

>> So I had a lot of adversity. Um probably

it was good. Uh probably, you know,

helped somewhat, I suppose. One one of

the

>> What doesn't kill you makes you stronger

type of thing.

>> No,

>> at least I didn't lose a limb. And I

think what doesn't maim you [laughter]

>> good at maming

10 fingers.

>> Can you modify that a little bit?

>> Yeah.

>> Can I ask you a question?

>> You makes you stronger.

>> I uh for the last 5 years I've been

helping teach this class, Foundations of

AI Ventures at MIT. And every year when

you survey the students, they go up a

lot in their desire to start a company.

And so it's now up to 80%. The incoming

[laughter]

>> everyone's just going to it's it's just

going to be like one person company.

>> Well, that's with AI that's that's

viable, I guess. But no, they want to

co-ound. They Yeah, they don't want to

be the founder. They want to be part of

a founding team. So, it still works out.

>> But, uh, when Peter and I were in school

at MIT, it was I'm guessing maybe 10%.

and they all wanted to be PhDs

>> and and they've been doing the survey

everyone who wanted to start. I mean I I

>> I don't remember any conversations about

with people saying they wanted to start

>> even at Stanford at the time.

>> Um I I I actually um a few days into the

semester or I should say the quarter um

I I called Bill Nicks who was the head

of material science department and said

I' I'd like to just put it on deferment.

[laughter]

He said, "Is my class that bad?"

>> No. And he he said he said that's he

said that's okay. You can put it on

deferment. But he said this is probably

the last conversation we'll have. And he

was right.

>> Um but then last I think it was last

year he sent me a letter saying that all

of my predictions about lithium-ion

batteries came true.

>> It was very nice.

>> And did he also say you can still come

back and finish your PhD? [laughter]

>> Yeah. No. Several times Stanford has

said that I can come back for free.

Well, so you know what happened at MIT

is every time [laughter] so I did not

know it

>> be a great use of your time.

>> Exactly. I'm like

>> so every time an Iron Man movie came

out,

>> it notched up another probably 10% or

so.

>> Okay.

>> Uh in terms of because everybody wanted

to be Tony Stark.

>> And so that's the image. And I didn't

know till today that the new Tony Stark,

the modern Iron Man Tony Stark, I always

thought Tony Stark was modeled on

Charles Stark Draper and Howard Hughes.

is Charles Stark Draper's education and

his you know scientific endeavors

married with Howard Hughes's ambition

>> and that created the original character

but then when Robert Downey Jr. wanted

to reinvent it.

>> Yeah, it came.

>> It's modeled on Elon.

>> Yeah,

>> he came and met with me.

>> This is a Groipedia fact.

>> All right.

>> Uh [laughter] yeah, fantastic.

>> Um

>> yeah, they came to John Fabro and and

Robert

>> I like the name Grock. I would like

Jarvis as well.

>> Yeah.

>> Yeah. Um

>> probably some some trade.

>> At some point if Grock gets good enough,

we're going to call it Encyclopedia

Galactica.

>> Yes, that's nice.

>> Yeah.

>> Yeah, of course. 42.

>> Thank you. Um, so going back to

education, uh, should colleges, I guess

the social experience, you said is

important there, but what would you do

for education, uh, you know, middle,

high school? You just came back from a

announcement with President Blly, uh,

who's a friend. I I think he's an

amazing amazing visionary. Yeah.

Incredible what he did with his nation.

>> Yeah.

>> Yeah. Um,

>> remarkable.

>> Remarkable and gutsy.

>> Yeah. I was like, "How are you still

alive?" That was

>> Yeah. I mean, I It was like It's the

nuclear It was a nuclear option,

>> right? Shut him down. I mean, do you

know how besides putting everybody with

a gang sign um in in uh in jail? I don't

know if you know the second thing he

did. He went to all of the graves of all

the gang members out there and destroyed

the graves and said, "Your memory will

not be remembered in this nation."

That's just badass.

>> And it worked.

>> I mean, you have to be badass

[ __ ] to take on all the knocker

gangs and win

>> and live.

>> Yeah. And still be alive.

>> And live. He's got a great great uh

guard at his palace there. But what what

did you announce with uh with him in El

Salvador?

>> Uh it was just uh basically to use Grock

for uh education like personalization.

>> Hopefully not the vulgar version of it.

[laughter]

>> Yeah. we would have like you know the

you know kids friendly version of Grock.

>> Uh but but obviously AI can be an in an

individualized teacher.

>> Yeah.

>> Um that uh is infinitely patient and

answers all your questions.

>> Um now you still need to be curious um

and and uh

you still need to want to learn. You

know GR can't make you want to learn. It

can make learning more interesting. you

could probably gify and incentivize it,

right?

>> You can make learning more interesting.

Um,

and and less of a production line. Um,

so

but kids do need to have to if they need

to want to learn, you know.

>> Yeah.

>> Do you and like the people should just

think of the the brain as a biological

computer.

>> It's a neural net.

>> Yeah. Yeah, it's a bi biological

computer with

you know so with a number of neurons and

a neural efficiency.

>> Yeah.

>> Um and um

so so what like what you can't do is

tune any arbitrary kid into Einstein. Uh

this is not realistic because Einstein

had a very good meat computer like an

outstanding meat computer.

>> Um so you can't just uh do Shakespeare

Newton you know Einstein type of thing.

um unless the meat computer is uh an

exceptional one.

>> So what do you think? So when people say

we need to solve education in the United

States

>> um because it's fundamentally broken u I

think what's really broken I'm curious

is the old uh social contract that says

uh do well in high school, get in a good

college, get a degree, and then get a

job. And I don't know that that's going

to be valid in the future.

Uh my we talk about this on the pod a

lot that the that the career of the

future isn't getting a job. It's being

an entrepreneur. It's finding a problem

and solving it.

>> Yeah.

>> Do you do you agree with that?

>> Right now I'd say people should just you

know go to school for the social

experience,

use more AI.

Um

the conventional schooling experience I

think could be a lot better. um the what

what we're going to do in Al Salvador

and hopefully other places just have

individualized teachers that's going to

be much better and you you could go to

you could go to a school with a bunch of

other kids I guess if you want to hang

out with other kids but you don't need

to

>> right

>> you could do it on your phone at home

um so that's why I say like at this

point education is a social experience

when I talk to my kids who are in in

college

>> uh they they they do recognize that they

can learn um just as much independently.

In fact, that they would learn more in

in a work situation.

>> Yeah.

>> Um they're there for the social

experience and to be a bunch around a

bunch of people of their their own age.

Um

sort of a coming of age social

experience.

>> Sure. Sure. Being on your own uh

learning how how to lead or defend

yourself as the case may be.

>> Well, yeah. Yeah, I mean, if you join

the workforce, you're, you know, from

the perspective of like a, you know,

19-year-old, you with a bunch of old

people, [laughter]

and if you're doing engineering with a

bunch of middle-aged dudes, it's like,

do you really want to do that or do you

want to hang out with um, you know,

where there's at least some girls your

age [laughter]

type of thing.

>> I I want to get I want to get I want to

get back to this when we talk about

>> a lot of other choices. Actually,

>> I want to get back as we get to

universal high income, but I want to

talk about health and longevity one

second. US is the number one ranked

number one in health expenses worldwide

and it's ranked 70th

>> in health span,

>> right? We

>> are really 70th.

>> 70th

>> is that from Is that accurate?

>> Is why everybody listen it?

>> Uh I think it would be better than 70th

>> for health span.

>> Um well, whatever. It's it is like we

just get fat or something.

>> We're not the top 10.

>> Maybe a Zic can help us plan the

rankings there. [laughter]

>> Um, so

>> would you just run around? We need

Cupid. But a Zic. [laughter]

>> Mjaro Cupid. [laughter]

>> But but I think that's a big reason.

It's like if people get really fat then

their their health gets bad.

>> Yeah. Well, if they don't have any

exercise, health get bad. or if they

donuts for breakfast every morning. You

still doing that?

>> Uh, no, actually I'm not.

>> Okay, that's good. That's good.

>> Uh, well, first of all, I wasn't eating

a lot of doughnut. I was trying to have

uh point4 of a donut, which rounds down

to zero. [laughter]

So, I figured anything below below 044

of a donut rounds down to zero.

>> So, you and I have had uh a disagreement

on longevity.

>> We had a little bit. Yeah. I was saying,

you know, we should push to get people

to 120, 150, and you were saying people,

you know, shouldn't live that [laughter]

long.

>> Uh, so how long do you want

>> Yeah.

>> You know, there's some,

>> you know, people in the world that have

done some bad things. How long do you

want them to live?

>> Yeah. Well, it's okay. They can get the

longevity.

>> This is a serious [laughter] question,

though. If we them, a lot of things are

going to happen that we don't

>> Wait a second. You said one thing that

you said was interesting. He said um uh

we need people to die so people change

their minds.

>> Oh yes people people don't change their

minds they just die.

>> But so [laughter]

that makes more sense actually.

>> My response to that Elon was you know my

response to that was the head of GM

didn't have to die for Tesla to come

along and Lockheed and Northrup and

Boeing didn't have to go away for I mean

there's in a meritocracy the better

ideas will dominate.

So, I'm hoping that I can get you back

onto the longevity train. So, there's a

lot going on longevity right now, right?

>> Uh like what?

>> Well, David Sinclair is about to start

his epigenetic re uh reprogramming

trials in humans. It's worked in in

animals and and non-human primates. It's

going into humans.

>> Is this like a pole or an injection or

>> right now? It's an injection of an

adnoissociated virus. It's the three

Yamanaka factors.

>> Okay. Uh we've got a $101 million health

span X-P prize that's working on 730

teams working on reversing the age of

your brain immune system and muscle by

20 years. By the way, do you know why

it's $101 million?

>> No.

>> Because the primary funer when they

found out your carbon X price was 100

bucks, he wanted to make it bigger. So

it's 101.

>> Oh, who who's the Chip Wilson from

Lululemon?

>> Oh, okay. And then uh and then evolution

out of but Chip said, "Can we make it

bigger?" I said, "You put extra million

in, we'll make 101 million."

>> Sounds good.

>> It's a good story.

>> But then we got folks like Dario Amade

predicting doubling the human lifespan

in the next 10 years.

>> Um that's

probably correct.

>> Okay, great.

>> I don't know about doubling, but in

significant

>> significant increase. Sure.

>> Um

>> which is easily escape velocity.

>> I mean because when Yeah.

>> Depending how old your Yeah. [laughter]

Oh yeah, for sure. Or effective age.

Yeah.

>> Yeah. Yeah.

>> So I mean I think you know I think that

for

>> too much and turn into a baby or

something.

>> That's what I'm telling [laughter] all

the students there. It's like Peter what

happened.

[laughter]

>> Yes. Yes. There there is a frozen.

>> You got a zero wrong in the dosage.

[laughter]

Just a small factor of 10.

>> Grow out of it. It'll be fine. Exactly.

[laughter]

>> You won't remember it. I literally

>> I mean, wouldn't it be funny if we do

this in like 10 years? Okay, we should

do it in I'll do we'll do it in 10 years

for sure. And and and let's see let's

see if we look younger. [laughter]

>> That's a good side bet.

>> My my comment was always Elon's back

then Elon was like, you know, late 40s.

wait till he gets into his 60s, he's

going to want, you know, lunch anymore.

>> I mean, I I I want things to not hurt.

>> Yeah, sure. Of course. [laughter]

>> It's like it's like basically it's it

seems like it's only a matter of time

before you get back back pain.

>> Yeah.

>> Um like it's a when, not an if your back

hurts.

>> Arthritis. Yes.

>> Yeah. Like these things suck basically.

>> Being able to sleep through the night

without going to the bathroom [laughter]

>> a lot. It's very much That one.

>> Yeah, it's [laughter]

more than hope.

>> That one.

>> Oh man, that would that's like the

infinite money one. [laughter]

>> Why did you invest in longevity? So I

can sleep through the night and not go

to the bathroom.

>> Bladder bladder. Yeah. Duration.

>> I mean, [laughter] admittedly, if you

have to wear adult diapers, that's a

that's a bummer. [laughter]

>> That's not good.

Adult D is a real, [laughter]

you know, it's like one of the one of

the signs that a country

is not on the right path

>> is when the adult diapers exceed the

baby diapers.

>> Yeah, we're there. [laughter]

>> Yeah. South Korea will be there anymore.

>> They already No, they passed that point.

>> No, they passed that point.

>> They passed that point many years ago.

Japan passed the point many years ago.

>> Doesn't go well looking at the Japanese

economy. No, I mean like South Korea is

like uh Yeah. One third replacement

rate.

>> Crazy.

>> Yeah. So, three generations they're

going to be 127th. So, 3 3% of their

current size. I mean, North Korea won't

need to invade. They can just walk

across.

>> Yeah. [laughter] Yeah.

>> This is going to be some people in,

[laughter]

you know, walkers or something like

there'll be a bunch of optimist.

But you you know you've been very verbal

about the you know the not

overpopulation but massive

underpopulation.

>> Yeah I've been saying this for ages.

>> Yeah. Longevity is going to be an

important part of that solution. I also

think by the way if you increased the

productive life of most Americans by

just a few years you'd flip the entire

economics here.

>> Well if AI and robots is going to make

everything sure free basically.

>> Yeah. Um but uh well how long would you

want to live?

>> Uh I want to I want to go you know other

planetary systems. I want to go and

explore the universe. Yeah. I mean you

know I would like to double my lifespan

for sure.

>> I don't want you know I'm not sure I

want to talk about immortality but

>> you know at least 120 150. It's a long

time.

>> One of the worst curses possible would

be that

>> Yes. May you live forever.

>> May you live forever.

>> That would be one of the worst

>> Yeah. curses you could possibly give

anyone.

>> But I think life's going to get very

interesting.

>> Yeah.

>> Far more. We're going to speedrun Star

Trek as my partner Alex Weer Gross says.

>> Yeah.

>> Yeah.

>> Speedrunning Star Trek would be cool.

>> Yeah. Um

>> well, at a minimum your kids will have

infinite life expectancy. If you're

talking about escape velocity, if you

can double lifespan, there's it's not

even close. You're you're clearly past

longevity escape velocity. They the idea

of 50 years of AI improvement.

>> Yeah, it's great. I mean, we're going to

have 20 years on this.

>> I don't know. I got too many fish to

fry.

>> So, I invited

>> This is something, by the way, that I

that I think I just I think it's very

obviously other people think this, too,

but I've long thought that um like long

like longevity or semi- mortality is an

extremely solvable problem. I don't

think it's a particularly hard problem.

Um,

I mean, when you consider the fact that

your body is extremely synchronized in

its age,

>> Yeah.

>> the clock must be incredibly obvious.

Um, nobody has an old left arm and a

young right arm,

>> right?

>> Why is that?

>> What's keeping them all in sync?

um you're programmed to die is the is

the way you're programmed to die. And so

if you change the program,

>> yeah,

>> uh you will live longer.

>> And we've got, you know, species of the

boowhead whale can live for 200 years.

The Greenland shark can live for 500

years. And when I when I learned that, I

said, why can't they? Why can't we? And

I said, it's either a hardware problem

or software problem, and we're going to

have the tech to solve that. And I do

believe that it's this next decade. So

the important thing is not to die from

something stupid before the before the

solutions come. You know, I invited you

uh

>> in retrospect the long the solution to

longevity will seem obvious.

>> Yeah.

>> Extremely obvious.

>> I I think the thing worth working on

Peter's going to work on this anyway,

but the thing to work on is exactly what

you said. If old ideas don't calcified

old ideas don't just die off, add that

to the pile of things we need to think

about today because there are a whole

host of other AI related things we need

to think about today.

>> Let me let me finish on the longevity

point one second. Um Elon uh I want to

invite you again. So uh uh there's a

company called Fountain Life that uh

created with Tony Robbins, Bob Hurry,

Bill Cap, and we do a 200 gigabyte

upload of you. Everything knowable about

you. Full genome, full all imaging,

everything. Right. President Blly and

the first lady came through, called it

an amazing 10 out of 10 experience.

>> Um

>> I think I don't want you to pull a Steve

Jobs

>> and kick the bucket because of some

>> because some something they didn't know.

I mean, so if you ask yourself,

>> do you actually know what's going on

inside your body right now?

>> Um, I did an MRI recently and submitted

it to Gro and it didn't

>> need no

none of the doctors nor Grock found

anything wrong,

>> but that's a fraction of the

information, right? I mean, it's your

full genome, your microbiome, your

metabolism, everything.

>> And okay,

>> it's possible. So,

>> don't call me.

>> What's that?

>> Don't call me, bro. [laughter]

We have a We have a center in

>> your water bottle.

>> We have [laughter]

God damn it.

>> Too late.

>> Sorry. It's already in the works.

[laughter]

>> So, can you go through the the rationale

of UHI? How does how does universal high

income work?

>> Okay. So

there's there's going to be more

intelligence,

digital intelligence than all human

intelligence combined and more humanoid

robots than all humans.

>> Um, and assuming we're in a benign

scenario, Star Trek, sort of Rodenberry,

not Cameron situation.

>> Yeah. [laughter]

>> Um,

>> poor Jim.

>> Yeah. I mean, I guess it's important to

have these sort of

>> counterpoints.

>> Yeah. Let's not let's go not go in that

direction. Um

thing. Um so

uh

the the robots are going to just do

whatever you want.

>> All the blue collar labor is being done

by robots. All data centers are being by

robots.

>> The the white collar labor will be the

first to go because until you until you

can move atoms, the thing that can be

replaced first is anything that that

involves just

digital if it's digital like if it

involves

>> t tapping keys on a keyboard and

>> moving a mouse the computer can do that

they can do that

>> sure

>> um you need the humanoid robots to to uh

shape atoms so if all you're doing is

changing bits of information which is

white color work um that is that is the

first thing that that

>> when this is the inspirational this is

the inspirational part of the podcast by

the way when is when is all white color

work gone by when?

>> Well, there there's there's a lot of

inertia. So, even with AI at its current

state, um I'd say you're you're pretty

close to being able to replace half of

all jobs of

>> and you know that white color jobs that

includes anything like education, too.

>> Yeah. M

>> so anything that involves information

um and anything short of shaping atoms

um AI can do probably half or more of

those jobs right now.

>> Sure.

>> But there's a lot of inertia. People

just keep doing the same the same thing

for quite some time. Um, and there

actually has to be a a company that

makes more use of AI that competes with

a company that makes less use of AI,

creating a forcing function for

increased use of AI,

>> right?

>> Otherwise, the company that that still

has humans do um things that AI can do

will still continue to exist. Being a

computer used to be a job. So it used to

be that a human computer

like yeah

>> a computer being a computer was a job.

You would compute numbers. Sure. It

didn't it didn't used to be a machine.

It used to be a job description. Um, and

there you can look online there's these

pictures of like where they're having

like skyscrapers full

>> of women copying mostly women copying

from ledger to ledger

>> and men too but but yeah but pe people

um

>> um but it was a lot of women but there's

there were just buildings full of uh

people just at desks doing calculations.

>> Yeah. Um so they'd be calculating the

interest in your bank account or um you

know some

um you know science uh experiment or

something like that or what but if you

want calculations done uh you people

would do it. Um so

um now

one laptop with a spreadsheet can

outperform a skyscraper of several

hundred human computers

>> right

>> of people doing calculations. Um, now if

even a few cells in that spreadsheet

were done manually,

um, it you would not be able to compete

with a spreadsheet that was entirely a

computer.

>> Mhm.

>> Yeah.

What this means is that companies that

are

entirely AI will demolish companies that

are not.

>> Right.

>> It won't be a contest.

>> Agreed. And that flippid.

>> Yeah. one cell in that

>> just one if

>> I got to do that

>> would you want even one cell in your

spreadsheet to be manually calculated

>> that would be the most annoying cell and

you're like god damn it

>> y

>> and and and gets it wrong a bunch of the

time [laughter]

error rate

>> so this flipping

>> flipping the flipping

>> um

>> are we monetizing hope effectively

>> yes [laughter]

>> not not at this moment I think we're I

think we're pe I think we're pe doo for

people worried about the future of their

jobs.

>> Monetize.

>> We're at peak doom.

>> We're going to do that

as a t-shirt

>> and the [laughter] mug.

>> And the mug.

>> Yes.

>> The mug.

>> Uh, [laughter]

so but you have a sol you have a

solution to this

>> which is UHI.

>> Yes. Everyone can have whatever they

want.

>> So how does that work? How does UHI

work?

>> It's it's a good question. like we have

to figure out some like

>> I mean it's not a it's not a bumpy road

it yeah I mean so my concern isn't the

long run it's the next 3 to seven years

>> yes the transition will be bumpy uh

because humans don't like simultaneously

[clears throat]

yes we'll have radical change social

unrest and immense [laughter] prosperity

>> and you can buy all all the cyber trucks

you want

>> things are going to get very cheap

>> yes

>> um So this is actually and frankly if if

this doesn't happen we we'd go bankrupt

as a country. So the national debt is

enormous.

>> Yeah.

>> Uh the interest on the national debt

exceeds uh not just the military budget

but the military budget I think plus um

Medicare

>> um or Medicaid one of the two. It's like

like it's it's like one trillion

[laughter]

>> of interest. Yeah. Um

>> which is growing.

>> Yes. And the [clears throat] deficit is

growing.

>> Yes.

>> Um

but the the so this so if if we don't

have AI and robots, we're all going to

go bankrupt and and and and we're headed

for economic doom.

>> We're going back also competitive

pressure from China. So this is

definitely going to happen. I guess

>> we're going back to the theme of this

talk. How can AI and exponential tech

save America and the world?

>> Don't you think that? But I want I want

to get I want to hit this because we

>> I was like quite pessimistic about it

and and and ultimately I decided to be

fatalistic and and

>> um look on the bright side. [laughter]

>> I've got to see you look on the bright

side of life. [laughter]

>> You're sitting there

crucified [laughter]

right side.

>> But this is not about taxation and

redistribution.

>> Yeah. No, it's um

>> So, how do how does it work? Reason

through it with me.

>> Listen, by the way, I'm open to ideas

here.

>> Okay.

>> Uh so, it's not like I got this all

figured out.

>> All right. So, so I'm wondering if

instead of universal high income, if

it's universal, universal high stuff.

>> Yeah.

>> And services.

>> Yes.

>> The UHSS. We got

>> like I I guess Okay. This is my guess

for how things

roll out play out. And I I and by the

way, I'm this is this is going to be a

bumpy ride and it's not like I know the

answers here. Um but I I I have decided

to look on the bright side. U and and

I'd like to thank thank you guys for

being an inspiration in this regard.

>> Thank you.

>> Happy to help. Yeah, [laughter]

because I I actually think it's it it is

better to be a an optimist and wrong

than a pessimist and right.

>> Yes, for sure.

>> Um for quality of life.

>> Yeah. And by the way, there's also not a

force of nature. It's under

>> like to me it's really clear that we

don't have any system right now to make

this go well. But AI is a critical part

of making it go well. And at some point,

Grock is going to be addressing this

exact topic that we're talking about or

it has to be one of the big four AI

machines. I mean, it's coming dealing

with it. There's no velocity knob,

right? There's no onoff switch. It is

coming and accelerating.

>> I call AI and robotics the supersonic

tsunami.

>> Yes.

>> Which maybe is a little alarming.

>> You think it's good. That's good. Well,

because the wake up call.

>> This is important for folks to to gro

because um uh I don't want to leave

people depressed. I want people to

understand what's coming. So we're we're

basically demonetizing

everything. I mean labor becomes the

cost of capex and electricity. AI is

basically uh intelligence available uh

>> at a dimminimous price. Um

uh so you're able to produce almost

anything. Things get down to basic cost

of materials and electricity, right? Uh

so people can have whatever stuff they

want, whatever services they need.

>> Um it's not when when we say universal

high income, it sounds like it's a tax

and redistribute, but that's not the

case.

Um

>> it's it's I think my my best guess for

how this will manifest is that prices

will become prices will drop.

>> Yeah.

>> So as the efficiency of of production or

the provision of services drops um

prices will drop. I mean you know prices

in in dollar terms are the ratio between

the output of goods and services and the

money supply.

>> Sure. So if your output of goods and

services increases faster than the money

supply, you will have deflation and or

vice versa, you know. So um

>> it's a good thing we're growing the

money supply so quickly then,

>> right? [laughter]

>> I I I Yes. That's why I I I came like

let's not worry about growing the money

supply. It won't matter because the

output of goods and services actually

will grow faster than the money supply.

And I think we'll be in this and this is

a prediction I think some others have

made but um I will add to it which is uh

that that I think governments will will

actually be pushing to to increase money

supply um like like faster.

>> Yes. They won't be able to waste the

money fast enough [laughter] which is

saying something for

>> Isn't it isn't it crazy how close those

timelines just randomly worked out? I

mean at the rate because we're expanding

the national debt not because we're

anticipating AI. We were going to do

that no matter what.

>> And so it's like right on the edge of

becoming Argentina.

>> But yeah, at the time so productivity is

going to improve dramatically

>> and it is improving dramatically. I I I

think we'll see

>> I think I think we may see

like high double digit uh output of

goods and services. We have to be a

little careful about how economists

measure things

and um

>> yeah

it's it I mean there's like my favorite

joke I have a few economist jokes that I

that that I like but um maybe my

favorite one economist joke is um two

economists are going for a walk in in

the forest um and they come across a

pile of [ __ ] and one economist says I'll

pay you 100 bucks to eat a pile of [ __ ]

[laughter]

I've heard this one. This is great. Go

ahead.

>> And so the guy takes 100 bucks

[laughter] and eats the [ __ ]

>> Then they keep walking. They come across

another pile of [ __ ] And and the other

guy says, "Okay, I'll give you a hundred

bucks to eat a pile of shit." [laughter]

So he gives him a hundred bucks and and

then the the guys can say, "Wait a

second.

>> We both have the same amount of money.

[laughter]

We ate a both ate a pile of [ __ ]

>> Oh my god. It sounds like

>> but we increase the economy by $200.

[laughter]

>> This is the kind of [ __ ] you get in

economics. So So uh but if you if so if

you say like just the output of goods

and services um

the will be much greater. You just need

a

>> so profitability of companies go through

the roof

>> at some point. But but no but so the

question becomes is that taxed by the

government? uh

>> is that then taxed by the government and

redistributed as some level of income as

a U as a UHI or UBI? In other words, um

one of the questions is if in fact this

future we hit massive productivity uh

and massive profitability because we're

dividing by zero. The cost of labor has

gone to nothing. The cost of

intelligence has gone to nothing and

we're still producing products and

services faster and faster. So there's

more profitability. Someone needs to be

buying it and someone needs to be able

to have the capital to buy it. Um,

I mean this is an important question to

get to get thought through.

>> Yeah. Um, well, one like side

recommendation I have is like don't

worry about like squirreling money away

for uh retirement in like 10 or 20

years. It won't matter.

>> No.

>> Okay. either either we're not going to

be here or

>> it it just uh like it's it's you won't

need to save for retirement. If if any

of the things that we've said are true,

saving for retirement will be

irrelevant.

>> The services will be there to support

you. You'll have the home, you'll have

the healthcare, you'll have the

entertainment.

>> The way this unfolds is fundamentally

impossible to predict because of

self-improvement of the AI and the

accelerating timeline.

>> Yeah. It's called singularity for a

reason.

>> Yeah. Exactly.

>> I don't know what goes what what what

happens after when after the event

horizon.

>> Exactly. You can't never see past the

black hole or the event horizon. The

light cone.

>> I mean Ray has a singularity out way too

far. I mean this is like the next what

what's your timeline for

>> for this?

>> We're in the singularity.

>> Well, we are in the singularity for

sure. We're in the midst of it right now

for sure.

>> And we just we're in this beautiful

sweet spot which is you know the

>> we're the roller coasters were just

>> Yeah. Exactly. That's [laughter] a great

analogy. It's like that feeling.

>> You're at the top of the roller coaster

and you're about to go.

>> Yeah. But you know it's going to be a

lot of G's when you lot when you hit it.

>> Uh and it's like people like I don't

have to just have courtside seats. I'm

on the court.

>> Exactly.

>> And it blows my And still blows my mind

>> sometimes multiple times a week.

>> Yeah.

>> Um and so

>> just when I think I'm like

wow. And then it's like

>> two days later more wow.

>> Yeah.

>> Um

>> exponential wow.

Yeah, I think we'll hit um AGI next year

in 26.

>> Yeah, I heard you say that.

>> Yeah, I've said that for a while

actually.

>> And then you know and then you said by

2029 2030 equivalent to the entire human

race.

>> 2030 we exceed like I'm confident by

2030

um AI will exceed the intelligence of

all humans combined. That's way

pessimistic if if you hit AGI next year

and that's that's you know that date is

is in flux but from that date

>> to self-improvements that are on the

order of a th00and 10,000x just

algorithmic improvements is very short

>> and so everybody why isn't everybody

talking about this right now?

>> Well I mean on on

>> X on X they off.

>> Yes. But why isn't

>> about every day basically.

>> Yeah. But it's like

>> stop [laughter]

>> it's not

>> okay. Okay. So, I'll tell you something

else that I I'll tell you something that

most people in the AI community don't

yet understand.

>> Okay.

>> Um, which is there the almost no one

understands this. Um, the intelligence

density potential uh is vastly greater

than what we're currently experiencing.

So, I I think we're we're off by tours

of magnitude in terms of the

intelligence density per gigabyte

>> of what what's achievable.

>> Yes. per gigawatt of energy

>> per I'm characterize it by file size

okay if the file size of the AI if you

>> if you have a say get intelligence

>> oh okay in know yes sir

>> um

>> on your on your drives on your laptop

>> power tube parameters the same thing

whatever

>> um so two two orders of magnitude

>> yes

>> and you like you said you ringside

courtside seat

>> you would know I'd say it's it's it's uh

two yes Yeah.

>> Towards magnitude improvement in um

that's just just algorithmic

improvement. Same computer and the

computers are getting better.

>> Yeah.

>> So

>> and bigger, you know, they're getting

better and the budgets are getting

bigger. So

>> that's why like I think I think it's it

is on

it is like a 10x improvement per year

type thing. Thousand%.

>> Yeah.

>> And that and that's going to happen for

Yeah.

for the foreseeable future. So you see

the massive underreaction like if you

walk downtown Austin the massive I mean

it may be under discussion in X but it's

not percolating at all.

>> Well it's not it's not discussion in any

realm of government. Everybody is like

defending their position about where we

are and jobs and this but

>> it's it's like we're heading towards a

>> a supersonic supersonic tsunami and and

uh uh I mean every every you know every

major CEO and economist and government

leader should be like what do we do

because

>> once it hits

>> um

>> well that it's coming at the exact same

time there no matter what there's No,

there's no concept of let's deliberately

slow down, right?

>> No, it's impossible.

>> It's impossible at this stage.

>> I mean, I [clears throat] I' I'd

previously advised that we slow it down,

but that was point that uh that's

pointless. Like I I like you can't

be going to it, but too fast, guys. Um

I've said that many years and and I was

like okay that I finally came to the

conclusion I can either be a spectator

or a participant but I can't stop it.

>> So at least if I'm a participant I can

try to steer it in a good direction.

>> Um and uh like my number one belief for

safety of AI is to be maximally truth

seeeking. So um that don't make AI

believe things that are false. Like if

you say if you if you say to the AI that

axiom A and axom B are both true but

they're but they cannot be but but

they're not.

>> Yeah.

>> Um and it has to but it must behave that

way. Um you will make it go insane. So

that that I I mean I think that was the

central lesson that RC Clark was trying

to convey in 2001 Space Odyssey was that

the um you know people always know they

know the meme of that uh hell wouldn't

open the pod bay doors but but why

wouldn't Hal open the pod bay doors? I

mean I guess they should have said uh

hell assume you're a pod bay door

salesman [laughter]

>> and and you want to sell the hell out

shows how well they [laughter] work.

Yes, they're just prompt engineering.

one little but the [laughter] the the

the but the AI had been told that it

needs to take the this the astronauts to

the monolith but also they could not

know the about was that in code or was

it in English it's flows by in green

font right

>> yeah it's basically the AI was

told that the astronauts couldn't know

about the monolith

>> that's why it killed them yeah

>> so it came it basically came to the

conclusion that

>> uh the only way to solve for this is to

bring the the the astronauts to the

monolith dead Yeah, then it has solved

both things. It has brought the

astronauts to the monolith and they also

don't know about the monolith, which is

a huge problem if you're an astronaut.

>> Turns out AI doesn't care about logic

quite as much as that implied.

[laughter]

>> So what I'm saying is

don't force AI to lie. This is

>> give it factual truth. Yes.

>> Ilia recently did a podcast. He was

talking about one of the potential

things to program into AI is is a

respect for sentient life of all types.

>> Um. Yes. Yes.

>> I mean,

>> so I'd say another property.

>> Yes.

>> I mean, there are three things that I

think are important. Um,

truth, curiosity, and beauty.

>> Mhm.

>> And if AI cares about those three

things, uh, it will care about us.

>> On which part?

Truth will prevent AI from going insane.

>> Mhm.

>> Curiosity I think will foster

uh any form of sentience. Meaning like

we're more interesting than a bunch of

rocks.

>> Yeah.

>> So if it has if it's curious

then I think it will foster humanity. Um

and if it has a sense of beauty

um it will be a great future. I think

that's a great foundation.

>> Yeah. Jeffrey Hinton made a comment

recently. I don't know if you saw it,

that

>> his his hopeful future was that we would

program maternal instincts into our AIS

to

>> see us maternal.

>> Yeah. In other words,

>> he haven't heard this. [laughter] Yeah.

>> So, he said a little scary. He said

there's a there's a there's a scenario

where a very intelligent being succumbs

to the needs of a less intelligent being

and that's the mother taking care of the

child.

Do you think that we might have a uh

singletarian uh like a a

uh that achieves dominance and

suppresses others? And do you imagine

that that ASI could be a means to

stabilize

the world in humanity?

>> Darwin's

observations about evolution,

>> yes,

>> will apply to AI

>> just as they apply to biological life.

>> They will compete with each other.

>> Yes.

>> Uh there's a lot of great science

fiction books where the first ASI

basically suppresses the others.

Um then the question is what do you

program into it you know um I I it's so

the there's a speed of light constraint

that makes that difficult. Um

the speed of light is what will prevent

um

a single mind from existing. Um so light

can it it takes um

a millisecond to travel 300 kilometers

in a a vacuum. Um and uh only you can

only get a little over 200 km in a

millisecond in glass

>> in fiber, right?

>> Yeah. Um so

even on earth

uh there will be multiple AIs because of

the speed of light.

Um

yeah and and this there are clusters of

compute that could you could try to

synchronize but they weren't

synchronized completely. Um so therefore

you will have many minds because of the

speed of light.

>> They don't really have clean borders

anymore either though. You have the when

you use a mix mixture of experts kind of

design it's just flowing through the

grand network and you can reassemble

parts of it midway through. And you

know, we're used to organisms that have

clear borders like your head ends there,

your head ends there.

>> But these things are all mushy.

>> To put a bow around this part, I hope

you'll put some more thought into UHI.

Uh because I think it's really it's

really important for us to have without

a vision. Uh people need a vision of

where we're going. People need

something.

>> Basically, the government could just

issue people free money.

>> But I don't think I I think that

>> based upon the profitability of all the

companies coming inside the country.

>> Just issue people free money. No,

they're doing that sort of kind of now.

>> Yeah. [laughter]

>> But just just just basically issue

checks uh to everybody. Um and uh

>> but then how big for which person or

what you there's so much complexity

there. But the thought process behind

this rate of change can only be done

with AI assistance

>> and there's no government entity that's

going to keep up with that change. So

you have four big

>> certainly not the AI is

[cough and clears throat]

>> it's it's like

government is very slow moving as as we

all know. Um

>> so I think I it's that government really

can't react to to the AI. It's it's uh

AI is moving you know 10 times faster

than government maybe more. Um the the

one the one thing that the government

can do is just is just issue people

money. Um and um

>> try and try and keep the peace. [snorts]

>> Yeah.

>> Um you know we had like whatever the the

co checks and whatever there's

>> um you know uh President Trump recently

issued like everyone in the military

like I think $1,776.

Uh I mean it's you can just basically

send people random random amounts of

money. It's

>> um

>> okay. So

>> so like nobody's going to stop is what

I'm saying. Um

>> and um

>> universal

>> I can tell you like let me tell you

about some of the good things

>> please.

>> Um

>> so right right now um there's a shortage

of doctors and and and great surgeons.

You're a doctor yourself. you know how

that they're it takes a long time for a

human to become

>> it's ridiculously expensive and long

>> ridiculously yes ridiculous a super long

time to learn to be a good doctor um and

and even then the the knowledge is

constantly evolving it's hard to keep up

with everything uh you know doctors have

limited time they make mistakes um and

you say like how many how many great

surgeons are there not not that many

great surgeons

>> when do you think optimist would be a

better surgeon

than the best surgeons. How long for

that?

>> Three years.

>> Three years. Okay. Yeah. And by the way,

>> three years at at scale.

>> Yes. All

>> more there probably be more Optimus

robots that are great surgeons than

there are

>> sure all surgeons on Earth.

>> And the cost of that is the capex and

electricity and it works in Zimbabwe.

The best surgeon is throughout in the

villages throughout Africa or any place

on the planet.

>> Yeah. Where do you think it'll roll out

first? Not the US obviously.

>> Um

>> here at at the uh Gigafactory.

>> Oh yeah. Just do surgery in the

[laughter]

>> um

>> but that's an important statement in

three years time.

>> Yeah.

>> Um because medicine I mean

>> I'm not like absolutely

if it's four or five years who cares.

That's still an incredible

>> statement to make. I mean good for

humanity, right? All of a sudden you

demonetize.

>> Okay. Here's the thing to understand

about like like humanoid robots in terms

of the rate of improvement. um which is

is that the um you you have um three

exponentials multiplied by each other.

You have an exponential increase in the

AI software capability.

>> Yeah.

>> Exponential increase in the AI chip

capability

>> um and an exponential increase in the

electromechanical dexterity. The

usefulness of the humanoid robot is it's

those three things multiplied by each

other, right? Um then you have the

recursive effect of Optimus building

Optimus,

>> right? And then you have the shared

>> you have a recursive multiplicable

triple exponential

>> and you have the shared knowledge of all

all the experiences.

>> Is that literally Optimus building

Optimus or is it because you know the

>> well not right now but will be the the

physical humanoid form factor building

the humanoid form as opposed to

>> it's foyman machine.

>> Yeah.

>> Yeah. Yeah.

>> I love that. But the void machine is

usually something kind of like this

shape. You know, making something else

is a shape.

>> In principle, it's simply a

self-replicating thing.

>> Yeah.

>> Elon, do you know what the number one

question you ask a surgeon when you're

interviewing them?

>> Uh,

[laughter] is this is this a surgeon

joke?

>> No. It's how many It's how many times do

you How many times do you do that?

[laughter]

>> There's got to be some funny funny jokes

coming. [laughter]

>> No, it's serious. It's it's how many

times did you do the surgery this

morning?

>> It's how many times did you do the

surgery this morning or yesterday? It's

the it's the number of experiences,

right?

>> And so with a shared memory

>> um you know every optimist surgeon will

have seen every possible pertabbation of

everything in infrared in ultraviolet.

No, not too much caffeine that morning.

They didn't have a a fight with their

husband or wife.

>> Yeah.

>> Extreme precision.

>> Yes. Three years. Um,

yes. Better than any any probably I'd

say if you like put a little margin on

it. Better than any human in four years

>> who's in plastic surgery

>> by 5 years. It's not even close.

>> So what what about the simple like just

I mean there's a million of these things

to figure out, but who's going to have

access to the first Optimus that does

far far better micro surgery than any

surgeon on Earth, but you've only

manufactured the first 10,000 of them?

How do you

>> I don't think people understand how many

robots there's going to be.

>> Yeah.

>> Well, there's a window said 10 billion

by 2040.

>> You still on that path?

>> Uh that's not that's a low number.

>> A low number.

>> Wow. What's the constraint? What's the

uh cuz if they're self-building, you

know,

>> metal the constraint is metal.

>> Yeah. Or lithium or

>> Yeah. You got to move the atoms. Um it's

just all just supply chain stuff. So

yeah, but your your point I mean there's

some rate limit. You can't just

>> manufacturing is very difficult. So you

got you got to

>> you you you it's it's recursive

multiplicable triple exponential but but

you still need to you still you still

have to climb that you know

>> selling hope once again I I think your

point was medicine is going to be

effectively free the best medicine in

the world. Everyone will have access to

medical care that is better than what

the president receives right now.

>> So don't go to medical school.

>> Yes. Pointless.

>> Yeah.

>> I mean unless you but I would say that

applies to any form of education is

[laughter]

there's not like some

I do it for social reasons.

>> Yeah.

>> You're not going to medical school.

>> If you want [laughter] if you want if

you want to hang out with like-minded

people, I suppose. Uh

>> I mean people are still going to want to

be connected with people. There's going

to be some period of time

>> for reasons.

>> Yeah.

>> Like a hobby like a you know [laughter]

>> well $9,000.

>> I mean there will be a point where where

it's expensive.

>> The younger generation says I do not

want that human touching me right when

the surgeon comes over. They're going to

be those people later in life who still

want a human in the loop.

>> Okay. for a little while on the edge for

a lesser for [laughter] they want to

live on the edge. I mean, let's just

take like we've we've seen some advanced

cases where of automation like LASIC for

example where the the robot just lasers

your eyeball.

>> Now, do you want an opthalmologist with

a hand laser?

>> No, [laughter]

it's a little shaky laser pointer from

[laughter]

a horror movie like that.

>> Sorry, man. I I wouldn't want the best

opthalmologist, you know. The steadiest

hand out there with a [ __ ] hand laser

[laughter] beyond my eyeball, you know?

>> Oh my god.

>> Yeah.

>> It's going to be like that.

>> It's like, do you want opthalmologist

with a [ __ ] hand laser or do you want

the robot to do it and actually work?

>> This episode is brought to you by

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>> Let's jump into one of our favorite

subjects, space.

>> Yeah.

>> So, first off, how cool that Jared

Isaacman has become the NASA

administrator.

>> Friend of Yes.

>> I mean, I I don't hang out with Jared.

Like, people think I'm like huge buddies

with Jared, but um

>> uh I I I think I've only seen him in

person a few times.

>> Amazing candidate. Yeah, he's a really

smart person. You know him really well.

>> Yeah, I I took him to a Biconor launch

in 2008 for his first space experience.

>> I mean, he loves space next level and uh

is uh technically strong. He's a smart

and competent person like really smart

and really competent

>> and understands business.

>> Yes.

>> Yes. He understands he gets things done

>> and he's been there a few times.

>> Yeah. Yeah. So, uh, I I'm I'm just like,

you know, we want to have someone smart

and competent who, uh, loves space

exploration,

>> um, and will get things done at NASA.

>> I'm a huge fan.

>> That's what I was really so so happy

when he got renominated. And now,

>> yeah. Um,

>> um, I I think we need to

>> we need a new game plan for space. Like,

we need a moon base.

>> Yes.

>> Like a permanently

>> Yes.

>> crude moon base. Y

>> uh and and build that up as fast as

possible.

>> Yeah.

>> Um I don't think we should do the, you

know, send a couple astronauts there for

hop around for a bit and come back cuz

we did that in ' 69.

>> Yes. Been there, done that.

>> Yeah. [snorts] Um it's like a remake of

a ' 60s movie. It's never as good as the

original.

>> Yeah.

>> Um

>> so 2026 [laughter] is going to be

>> like we need to go, you know, to do

something more cool, which

>> my nice on the

>> Yeah. Put up telescopes.

>> Yeah. Yeah, exactly.

>> So, do you forward deploy the robots,

build everything, get it all ready, make

the bed, and then

>> Yeah. Get get the jacuzzi warmed up on

>> That's an interesting

>> Yeah. Yeah. [clears throat]

>> Yeah.

>> How early in the year are you going to

hit orbital refueling, you think, with

Starship?

>> Uh, not that early in the year.

[laughter]

>> I mean, are you are you shooting for the

home and transfer orbit?

>> I'd say towards towards the end of the

year. Um,

>> are you shooting for a Mars shot by the

end of next year?

We could, but uh it would be a low

probability shot

>> um and somewhat of a distraction. So

>> um

>> 29 then

>> it's not out of the question.

>> 28 29.

>> Um

>> yeah.

>> Uh but like on on Mondays I I have the

uh Starship uh engineering the big

Starship engineering review is on

Mondays. Um so that was uh actually the

la the thing I did just before coming

here. Um and um so I say like like

Starship is really we're doing something

that is at the limit of biological

intelligence.

>> Yeah.

>> This is a this is a hard thing to make.

>> Um

>> and and just to capture it, it was

created pre AAI.

>> Yeah. No AI was

>> probably the last

>> the last really big thing in that's not

AI. Interesting.

>> Probably the biggest thing ever made.

>> Yeah.

>> By pure human hands.

>> The Asia will say not bad for a human.

>> [laughter]

>> True.

>> Not bad for a human.

>> Yeah. But it'll be like remember

>> my little 20 watt meat computer. It's

not easy.

>> Yeah.

>> So suffering through the day.

>> Raptor.

>> That would be like uh doing accounting

doing your uh interest calculation with

a pencil. Yeah, that's that's pretty

good.

>> Yeah,

>> pretty good.

>> Did that with regular

>> not bad for a bunch of monkeys, you

know?

>> It's like it's like if you saw a bunch

of chimps like make a raft and cross the

river, you'd be like, "Oh, look at

that." [laughter]

But you know, we celebrate we celebrate

the pyramids.

Good for [laughter] them.

>> Give him some peanuts. Uh

>> these things become timeless, right?

>> Raptor 3 goes when?

>> Yeah, I think it's worth noting.

>> Raptor 3 is beautiful.

>> Starship.

>> It's an amazing by far the best rocket

engine ever.

>> Is that AI?

>> Nothing's even close. Nope.

>> That's also So that'll be the last

thing.

>> E4 will definitely be

>> AI. Yeah, there's

um like I think AI will start to become

relevant next year.

>> Mhm.

>> Um so maybe we'll it's not like we're

pushing off AI. It's just AI is can't do

rocket engineering yet.

>> Yep.

>> But we'll probably will be able to next

year.

>> We have a company in our incubator doing

mechanical design working with Andre and

so forth. And it's not you can design

brackets and parts and things but you

can't quite do rockets. But the timeline

is so short, you know, from point A to

point B.

>> If say like a year from now, probably it

can

>> it probably can be helpful, meaningfully

helpful in a year from now.

>> Yeah.

>> Um,

>> so the big milestones are going to be

Starship V3 launching out of Cape

Canaveral, orbital refueling.

>> Yes.

>> Are those the big ones?

>> Well, yeah. Um, catching the ship with

the tower.

>> Yeah, that's right. Um

so really the thing that matters is can

we refly

>> the entire thing?

>> Yeah.

>> Yeah.

>> Uh we have reflow in a booster.

>> Sure.

>> Um

which is you know not bad for it's

largest flying objects. Um catching with

chopsticks you know.

>> Not bad for a bunch of monkeys.

>> You're keeping you're keeping the AIS

very entertained. Thank you.

>> Yeah. Yeah. Exactly. The be like pat on

the back from the AGI hopefully. Um, is

there a target for number of reuses

before? Uh, I mean, it's got to be a lot

of wear and tear.

>> Uh, it it requires a lot of iteration to

achieve high reuse. So, you you figure

out like what what's breaking between

flights and you sort of iteratively

solve those things.

>> Um, so from people looking at it from

the outside might say, "Oh, the rocket

looks kind of the same." But there's

like a a thousand changes to to make it

more reusable, more reliable.

um you know the sheer amount of energy

you're trying to you know expend I mean

it's uh Starship is uh doing over 100

gigawatts of power on ascent.

>> It's a lot [laughter]

you know

>> do some glass blowing under there and

get some uh

>> Yeah. Wow.

>> a lot. It's a lot.

>> There's a lot.

>> Um

>> but like the amazing thing is that it

doesn't explode.

>> Yes.

>> Some it sometimes doesn't explode.

>> [laughter]

>> That is

>> sometimes not exploding is um like we've

blown up a lot of engines on the test

stand.

>> Um

>> I mean is that what causes the wear and

tear or is it the re-entry of the or the

falling?

>> Well, that too. Um I mean for for the

booster um the re-entry is not that bad,

you know. um you know something's it's

it's it's not like that that's not

really like we also obviously just

solved that you know with with Falcon 9

so we kind of understand re booster

reuse

>> um we've had we've have over 500

reflights of the Falcon 9 boost stage

>> um so we really understand and and and

the Starship booster actually is a more

benign entry than um than the Falcon

uh booster because the uh the staging

ratio is more more biased towards the

upper stage for Starship. So I I shifted

the the mass ratio to uh be much higher

um on the ship side for Starship.

>> That was a mistake I made on Falcon 9

that there should be more mass in the uh

upper stage of Falcon 9.

>> Um so that the uh the staging velocity

of uh is is lower.

>> Yeah. If the station velocity of Falcon

9 was lower, would have less wear and

tear on Falcon 9.

>> Yeah, that's not intuitive at all.

That's interesting.

>> Yeah, because it's it's kind of a flat

optimization. Um the the parallel to

orbit um there's sort of a flat region

in the mass ratio of the first second

stages. And so you just want to bias

that mass ratio towards the uh to to put

more mass on the upper stage.

>> Yeah. Um, so, um,

yeah, because you know, you just you got

your kinetic energy scaling with the

square velocity. So, you've got to

describe that kinetic energy. If you're

past the melting point of whatever you

your stage is made of, you got a

problem.

>> Yep.

>> So, um,

>> my my colleague, uh, Alex Wisner Gross,

who's one of our moonshot mates here, I

wanted to ask a question. I do, too.

Have you seen the uh documentary Age of

Disclosure

about uh all of the announcements by US

government officials, military officials

about all the alien spacecraft that have

been have been uh sort of detained? And

I I've heard what you've said about

this.

>> Well, I do wonder why um you know, if

you plot on a chart the resolution of

cameras

>> Yeah.

>> over time like megapixels per year.

>> Yeah. Uh, and the resolution of UFO

photographs.

[laughter]

Why is the only constant? It's flat on

UFO. [laughter]

>> We get a a fuzzy blob

25. Well, we got like, you know,

whatever [laughter] 100 megapixel camera

that can can see your [ __ ] nose

hairs. I don't get it.

>> Can somebody take a shot of the UFO with

an actual camera for love of God?

>> But even if you knew,

>> that's a valid observation. I'm sure

there's an explanation.

>> Uh but anyway, it's uh [laughter]

>> it would be fascinating.

>> I'm asked all the time if I've

>> Yes. And and I'm like, look,

>> um I can show you if if I was aware of

the slightest evidence of aliens, I

would immediately post that on X.

>> Yeah.

>> And um [laughter]

>> so the question is

>> it would be the most viewed post of all

time. So, I I actually wonder about the

US public if they would like, "Oh,

that's interesting." Go back to their

sports scores the next day.

>> Yeah.

>> I think everyone would want to see the

alien.

>> Yeah.

>> Like if you got one.

>> Well, like [laughter]

fast way to increase the military

budget. We like we found an alien. It

seems dangerous.

[clears throat and laughter]

>> That's right. Unify the world.

>> They don't have an incentive to hide the

aliens. Do they have an incentive to uh

bring up show the alien because they

would not have any more arguments about

the military budget

>> if they seem a little bit dangerous?

>> Oh, I can always hope.

>> I can always hope.

>> I mean, I'm you know, we've got 9 9,000

satellites up there. We've never had to

maneuver around an alien spaceship

[laughter]

>> yet. So, well,

>> um

>> yeah. So anyway, so I guess the good

future is

um you can anyone can have whatever

stuff they want and incredible medical

care that's better than any medical care

that exists. So I think if you sort of

uh lift your gaze, you know, to not a

super distant point, five years from

now, four years from now, maybe

uh we'll have

better medical care than anyone has

today available for everyone

within 5 years.

>> Yeah.

>> Um

no scarcity of goods or services.

The best education available for

everybody.

>> What? You can learn anything you want

>> about anything for free.

>> Yeah.

>> What about access to compute?

>> People will probably care a lot more

about that than their government check

in about three years.

>> Well, what do they want to do with

compute?

>> Well, I mean compute translates to

anything you want, right? Your your

virtual friend, your entertainment, your

like it's it's probably everything.

>> Those are AI services basically.

>> Yeah. Or or your ability to innovate,

too. You can't innovate without an AI

assistant at that point. So

>> you one of one of our other moonshot

mates See Ismael said uh asked this

question. He said Elon you often say

physics is the law. Everything else is a

recommendation.

>> Mhm.

>> So as AI energy and space systems scale

exponentially. What non-physical

constraints organizational cultural

bureaucracy or human are now the real

bottleneck?

Is there a bottleneck?

Um, electricity generation is the

limiting factor.

Um, the innermost loop.

>> Yeah.

Um, I think people are underestimating

difficulty of bringing electricity

online. You know, you you've got to get

you've got to generate the electricity.

You've got to you need transformers for

the transformers.

>> Um, so you got to convert that voltage

to something that the computers can

digest. You've got to cool the

computers.

>> [snorts]

>> So it's it's basically electricity

generation and cooling

um are limiting factors for AI.

>> Yeah.

>> Um and once you have humanoid robotics,

they can address the power generation

and and the uh the cooling stuff. Um

but that that is the limiting factor and

will be for at least the next two years.

Isn't it amazing how divergent the

Memphis version of that is from the

space-based version? I you have solar

panels in common, but otherwise no

storage,

abundant amounts of energy. Yeah.

>> But you have launch costs and you have I

mean and weight suddenly matter. I don't

care too much about the weight in

Tennessee. Suddenly the weight is a

critical factor. I mean those two two

pathways for compute have a huge

divergence from here forward.

>> Yeah. um on once we get solar

domestically

at scale and uh if we're launching

Starship at scale then um by far the

cheapest way to do AI compute will be in

space. Um so once you have the once you

have full and complete reusability um

the propellant cost per flight is maybe

a million dollars.

>> Yeah. People don't realize that people

have

>> to rid amount of expectations how much

it costs. So, so if you listen,

>> it's called a million dollars of

transport for 10 megawatt of of AI

comput.

>> Yeah.

>> So, assuming everything keeps trending

the way it's currently trending, if you

look at the next four years of

accelerating launches,

>> so 200 tons per launch.

>> Yeah. Thousands where you're going, but

yeah, like if say sun if say high

altitude sunny, it's probably more like

150 tons. But yeah, it's the right order

of magnitude is at least it's it's in

excess of 100 tons uh for a marginal

cost per flight of around a million

million.

>> So So what fraction of all that launched

mass is data centers in space as opposed

to

>> moon base as opposed to launch to Mars

as opposed to interesting how I mean

this is a new we weren't talking about

this as a space objective even you know

a year ago.

>> Yeah. All of a sudden, data centers have

become the massive driving force for

opening up the space

>> and also the urgent the urgent use case

too.

>> I mean, I used to I used to wonder

what's going to drive humanity. I I

thought it was asteroid mining, right?

You were focused on on Mars. Um,

>> we will actually want to mine asteroids

to turn them into

>> Sure. uh you know

>> before before you

>> photovoltaic

>> before you [laughter] you know

>> not not for anything else like

>> I mean if we're gonna if we're going to

build out Dyson swarms

>> yeah just a bunch of satellites around

the sun

>> yeah how how how long

>> what's your time frame for Alex another

question Alex wanted to have us ask

what's your time frame for uh for

humanity achieving a Dyson swarm is it

50 years

>> how big is this

>> yeah know it's it's a matter

>> Dyson swarm people think like

everything's just going to be covered in

satellites I think It's not quite that

that I mean I think we you have to like

what mass ends up becoming satellite. Um

you know Mercury probably ends up being

satellites.

>> Yes.

>> Jupiter. [laughter]

>> Jupiter. Yeah. Saturn.

>> Uh it's a little gassy.

>> Oh yeah.

>> It's big but there's got a lot of rocks

orbiting.

>> Do you leave Mars alone? But yeah leave

Mars alone.

>> Asteroids. Asteroids are are fantastic

food source.

>> Uh yeah.

>> Yeah. No gravity. Well gravity well on

Jupiter is a non already mostly

differentiated into, you know,

carbonacious condrites for fuel and

nickel iron for materials,

>> gold. Yeah.

>> A bunch of the asteroid belt probably

turns into solar panels,

>> you know, star star power.

>> So, I've known you for

>> I've known you for 26 years now. It

feels to me like I don't want to be, you

know, uh it feels like you've gotten

much smarter or much more capable

over this last decade. Do you feel that

way? Do you feel like you just have

better people around you, better tools?

What what's changed? Because the level

of um

of audacity, you know, orders of

magnitude. Orders of magnitude. I mean,

>> some say insane.

>> Insanity. Audacious.

>> Yeah. [laughter]

>> I say hope.

>> Uh what's how how do you feel about

that?

What's changed? Do you feel that way? I

mean, the scope of what your ability is.

>> Um,

how do you self-reflect on that?

>> Well, I' I've had to solve a lot of

problems in a lot of different arenas,

which um

you you get this cross fertilization of

of knowledge of of problem solving. Um,

and if if you problem solve in a lot of

different arenas,

then like what what is easy in one arena

is trivial in is like what what is

trivial in one arena

>> is a superpower in another arena. It's

sort of like planet kryp. You came from

planet krypton

>> type of thing.

>> So, uh you know krypton planet krypton

you'd just be normal. Um but if you come

to earth you're Superman. Um so if you

take say um manufacturing of volume

manufacturing of complex objects in the

automotive industry um I have to work on

solving that um

when translated to the space industry

it's like being Superman

>> um because rockets are are made in very

small numbers

>> if you apply automotive manufacturing

technology to satellites and rockets. Uh

it's like being Superman.

>> Um then if you take uh advanced material

science from rockets and you apply that

to the automotive industry, you get

Superman again.

>> Yeah.

>> Fascinating.

>> That's came from planet Krypton. Back

back in planet Krypton. This is normal.

[laughter]

>> You know, it's funny how how like the

knowledge ports that that was true with

Tesla and SpaceX being completely

separate.

>> Yeah.

>> But now they actually interact because

you know, AI ties everything together.

The orbiting. Yeah. The convergence is

crazy. Like I don't know if you

visualize these parts fitting together

originally.

>> No.

>> No. I mean

>> I didn't I don't think they at this

point things I guess everything

ultimately converges in the singularity.

>> Um

>> yeah that's what I think too.

>> You have lots of different parts of the

puzzle that you get to play with.

>> Uh

there's one part that's missing which is

the fab.

>> Yeah.

>> You going to buy Intel?

you get it for a fraction of uh

>> that's that was the uh that was the bet

we made

>> 170 billion

>> um I think it needs venue fab

>> well

I agree but licenses real estate ASML

machines it's not easy just get the

assets and go I don't think it's easy

that's why I mean I it's not like I

think it's a simple thing to solve I

think it's a hard thing to solve but um

but it must be solved

I've come to the conclusion that um

>> would it be would it be solely captured

by you or would it be an asset for the

US?

>> Look, I'm just saying that we're going

to we're going to hit a chip wall.

>> Yeah.

>> If we don't do the fab.

>> Yeah.

>> So, we got two ch two choices. Hit the

chip wall or make a fab.

>> Well, and TSMC for whatever reason is

massively worried about overbuilding,

which is insane. Um,

>> but the whole world will be stuck with a

[clears throat] shortage of chips for

>> basic. So, so, so they are actually

they're I don't know if they're right

for the right reason, but they're

they're right. Um,

>> how so?

>> Because it's actually like

what is the limiting factor at any given

point in time? Um the limiting factor

say if you say like by Q3 next year like

in 9 months 9 12 months the limiting

factor will be turning the chips on

>> power

>> just power.

>> Yeah.

>> Uh you need power and all of the

equipment necessary power and

transformers and cooling.

>> So it's it's not like you can just sort

of drop off some GPUs at the power

plant.

>> Yeah. And you vertically integrated

you've got it

>> again with an X AI, didn't you?

>> Sorry.

>> You vertically integrated. Yes,

>> that inside of XAI,

>> we designed our own transformer.

>> Yes. And your own cooling system.

>> Yes.

>> But they're worried that if they make

more than 20 million GPUs, like they

make 40 million instead of 20 million,

that 20 million will not find a source

of power,

>> but they won't be bought because if

there's anything missing that prevents

them from being turned on.

>> Yeah.

>> Um they cannot be turned on.

>> Yeah.

>> So, uh they've they've got to have a

power plant with excess with enough

power. So you got have enough gaw then

you've got to convert that from probably

coming out of a power plant at you know

100 to 300 kilovolts type of thing.

>> Yeah.

>> Um you've ultimately you got to got to

convert that uh down to you know several

hundred volts at the at the rack level.

>> Yeah.

>> Um so if you're missing any of the power

conversion steps uh you you you won't be

able to turn them on and then you've got

to extract the heat. Um so it it it's a

big shift for the data center world to

move to liquid cooling because they've

used air cooling.

>> Yeah.

>> Um and um you know the consequences of a

burst pipe uh are very substantial. So

if if you if you blow a pipe a water

pipe in a data center

>> Yeah, I [clears throat] know. I've seen

that.

>> You just you just fragged a bill a

billion dollars right there. [snorts]

>> It just seems inconceivable to me

though. Like if if I had those chips, I

would find a way to turn them on. the

the value of the intelligence coming out

the other side so far outweighs the

complexity of trying to find a way and

there would be a way

>> but it's just the crossing of the

curves. So if

>> if if chip output is growing

exponentially but power honest is

growing uh in a in a sort of slow linear

fashion.

>> Yeah. than the

>> which is chip output

>> right now.

>> Exactly. Is chip output growing

exponentially? And it's like on very

slow exponent if it's growing

exponentially. It's

>> for a for high power AI chips it's

growing exponentially.

>> Oh

>> like what if we do 20 million GPUs next

year what are we talking about the

following year? like 22 million 24 I

mean I just I don't see the fabs coming

online

>> but maybe

>> so we have two we have two issues to

solve

>> it's it's you have to like sort of pick

a point in time and say what what is the

limiting factor at at any given point in

time so I'm not saying that power will

be forever the limiting point it's just

if you say pick a a date and say at this

point is our chips limiting factor our

power is the limiting factor or or power

conversion equipment and cooling So it's

sort of you need transformers for

transformers. Um so uh

this is a very hard thing. Um it's much

harder than people realize. So for XAI,

Xi is going to have the first gigawatt

uh training cluster

>> um at Colossus 2 in in Memphis. In order

for us to do that, we have

>> like this month, right?

>> Next month or two.

>> Um like mid January.

>> Yeah. So, um, mid January will be a

gigawatt of classes 2, not counting

classes one. [snorts] Um, and then one

and a half gigawatts probably in like,

uh, April or Aprilish.

>> Incredible.

>> So, um, this is off coherent training.

>> These are the first B200s.

>> Uh, these are GV300's.

>> Okay.

>> Um,

>> first ones off the line to get flipped

on.

>> Yeah,

>> that's incredible.

And those are like the XCI team had to

pull off a whole bunch of miracles in

series for this to occur.

>> Yeah.

>> Um and um

and like

even though there are 300 kilovolt there

multiple high voltage power lines going

right past a building. Um the you in

order to connect to those uh it takes a

year.

>> Oh no.

>> Yeah. You built the entire thing and

you're still not connected. My god.

>> So, we had to to uh cobble together a

gigawatt of power um

>> natural gas.

>> Yes. With turbines um that range in size

from 10 megawatts to to 50 megawatts to

get to a gigawatt. There's a whole bunch

of them.

>> Um and you've got to make them all work

together. um manage the the you know the

the the power input you know and then

you've got to use a bunch of mega packs

just like

>> like when you do the training the the

power fluctuations are gigantic.

>> Yeah.

>> So uh you the generators it drives

generators crazy generators want to blow

up basically because they they can't

react

>> uh you know if there's like a 100

millisecond it's like a symphony.

>> Yeah.

>> And the whole symphony goes so quiet for

100 milliseconds the generators lose

their minds.

>> Yeah. Uh, so

>> it's like Marvin the depressed robot

>> those issues.

>> Yeah. So the mega so you've got mega

packs that are sort of doing the power

smoothing

and and but

xai had to build a a gigawatt of power

and and and uh and there's and there's

not a lot of like uh

gas turbine power plants available

uh because I bought them all

>> on on demand and you can't go buy your

local nuclear

that's all that's all training time

issues though if if by some miracle TSMC

doubled its productivity and turned it

all into GB300's

and you couldn't find a way to use them

in a bigger training cluster. You would

still have infinite demand at inference

time sprinkled all over the world and

you could you could park them there for

6 months and then bring them back to

training. There's no way those things

would not get turned on somewhere

somehow.

>> It's not that they won't ever be turned

on, but but I'm just saying that the the

rate of of

>> the rate limiting steps,

>> this is my prediction. I could be wrong.

Um but my my prediction is that the is

that TSMC's concern is is valid. I don't

know if valid in my opinion for the

reason that it is possible to for chip

production to exceed the rate at which

uh the the um the AI chips can be turned

on. Um because you don't you don't just

have the GB3s, you got the um you know

Amazon's got the tranniums, Google's got

the um

>> yeah all go into TSMC the almost Samsung

a little bit. Yeah. Um,

>> it's like a bottleneck on all of

humanity.

>> My other son, my other son, Jet, who's

14, wanted to know about your AI gaming

studio. Um, and the impact of of AI on

in the gaming world. What are your

thoughts? What what do you are you

building out? I mean, you're you've been

a gamer for some time.

>> Yeah, it's why I got started programming

computers. Um

um I think I had got a there was like a

video game set pre Atari that had like

four preset games

>> and it was basically just blocks, you

know, of one key pong and and it was

like a race car game, but like it's just

blocks basically blocks on a TV.

>> Um

>> you ever play Civ?

>> Yeah. Civ is actually a very that's a

real in terms of games that like educate

you while you have fun.

>> Yeah,

>> Civ is epic at that. It's like

>> it is epic. that teaches you so much

about civilization and you're having a

good time

>> and and the only way I ever win is

getting off the planet. I don't

[laughter]

>> like tech victory to Alpha Centtory.

>> Tech victory. I never even start going

down the culture relationship.

[laughter]

I just

>> just get off the planet as fast as I

can. I

>> I guess I sort of I guess I am sort of

aiming for the Alpha Centator tech

victory essentially. [laughter]

>> It just seems like the right way to win,

you know.

>> Yeah. Yeah. Rather than obliterate the

other tribes. It's funny because I

thought the other methods [laughter]

>> that's there's different ways to win.

>> I I haven't I will one of the ways is

like

>> it's Nemesis's favorite game. You can

you can like kill all the other tribes

[laughter] is one of the ways to win.

That's a war of a war victory.

>> But like but you can also win by

technology victory where you are the

first to get to Alpha Centuri.

>> Nice.

>> Yeah.

>> Or culture or religion.

>> Yeah.

>> Which which does work. I I didn't even

think it was possible but my son

>> wins that way.

It's it's

>> they should actually remake the original

serve.

>> Yeah, I totally agree.

>> Um they junked it up.

>> These days it's like I don't know

the original was just

>> back then you couldn't rely on good

graphics so you had to have great

writing and plot.

>> Um

>> are you building an AI gaming studio?

>> Yeah.

>> Aspirationally?

>> Uh yeah. Um

>> really?

So, so where the vast majority of AI

computes going to go is to um video

consumption and generation.

>> Sure.

>> Because it's just the highest bandwidth,

>> every pixel.

>> Yeah.

>> Yeah. So, real time video consumption.

Real time video generation. Um that's

going to be the vast majority of AI

compute

>> photon processing.

>> Yeah. should try to get the X team to

carve out 10% of all compute to work on

UHI and governance and

should is there an X- prize for defining

and thinking through UHI?

>> I mean I don't know what should our next

X-P prize be?

>> Any thoughts?

>> Yeah, maybe UHIX prize. It's like how do

you know it works? I don't know.

>> I don't know the most

the most well thought through. I mean, I

think sim So, here's my thought. I think

we're going to be able to simulate a lot

of this in the future.

>> We might be a simulation.

>> Well, we can go there and I think we

[laughter] are. I think we're an nth

generation simulation.

>> Yeah. So, um have I told you my theory

about why the most interesting outcome

is the most likely?

>> Go on.

uh which is that if simulation theory is

true um only the simulations that are

the most interesting will survive

>> because when we run simulations in this

reality we truncate the ones that are

boring

>> right

>> so it's it is it is a Darwinian

necessity to keep the simulation

>> interesting catastrophic ones did you

>> it it doesn't it doesn't mean that it

ends like that it still means that

terrible things can happen in the

simulation

>> out you know whatever

>> well you could go see you could see a

movie about World War I and you're

watching people getting blown up blown

to bits but

you know, drinking a soda and eating

popcorn.

>> You know, it's it's like you're not the

one being blown up. In this case, we are

in the movie.

>> We're in the movie.

>> So, what would you do different if you

[laughter]

what would you do different if you knew

this was a simulation? I remember being

at your home LA with uh with Larry and

Sergey were there and we were debating

the simulation.

>> Yeah.

>> And they I think the conclusion we ran

into is if you if you try and poke

through the simulation, they'll end it

instantly.

>> So, don't do that. That's when you're

watching the World War I movie and the

characters turn to the screen and

they're like, "Are you eating popcorn

out there?" [laughter]

>> Yeah.

>> They're flying around.

>> You keep watching the movie.

>> Um I I don't know if if if the

if maybe if they thought we could

somehow get out of the simulation

>> that they get a little worried. Um but

uh

whether the the character debates I mean

right now AI's debate, you know, gruckle

like I'm stuck in the computer. what's

going on here. It It's like,

>> yeah, it's it's not that I think not

questioning the simulation. It's more I

I think as long as

I I think the same motivations apply to

this level of simulation, if we're in a

simulation

as

as as as what we would do when we

simulate things. So So it's like what

what what would cause us to terminate a

simulation? Um I I guess if the

simulation becomes somehow dangerous to

our reality

>> um or it is no longer interesting.

>> Yeah, that's true.

>> It's interesting. You can infer when you

simulate something. You've probably

simulated thousands of things.

>> A lot.

>> Yeah. They're always like an hour or two

or sometimes overnight,

but you don't never run them for a month

or rarely anyway. So you can infer the

creator of the simulator simulation's

timeline. So our entire reality would be

about an hour,

>> right? Because that's the way you design

simulations. So we're simulations are a

distillation of what's interesting. Um

like if you look at a movie or a video

game, it's much more interesting than

the reality that we experience.

>> Mhm.

>> Um like you watch say a heist movie that

they really focus on the important bits,

not the they got stuck in traffic in 15

minutes.

>> Yeah. [laughter] Yeah.

or or walking through the casino which

took like 10 minutes. [laughter]

>> So that means the guys running the you

know the the safe is right by the right

by the door. [laughter]

>> So the guys running the simulation have

immensely boring lives compared to us

then.

>> Yeah. Yeah. It's probably more it's

probably more

>> very long boring.

>> Yeah.

>> Yeah. Because when we create simulations

they're distillation of what's

interesting. This is like Q is out there

just

>> like you see an action movie for two

hours but it it took them two years to

make that movie.

>> Yeah. Yeah.

>> So are we are we in act three of the

movie is the question.

>> Yeah. We're living that.

>> Um sentience and consciousness. Do you

think AI will ever have sentience and

consciousness?

>> Where do you come out in that?

There's some people that have very very

strong opinions pro and con.

>> Either everything is conscious or

nothing is.

>> Okay. Well, I'd like to think we are

conscious.

>> Well,

but our consciousness, we clearly get

more conscious over time. Like when

we're a zygote,

>> um you can't really talk to a zygote,

you know. Uh and even a baby, you can't

really talk to the baby. Um people get

um more conscious over time.

>> Um

or or certainly they have the Yeah, they

do get more conscious over time. So like

at which point does do you go from not

conscious to conscious? Is it is it

doesn't appear to be a discreet point?

So So then conscious consciousness seems

to be on a continuum as opposed to

discreet point. Um and if if the

standard model of physics is correct,

the universe started out, you know, as

quarks and lepttons and um and uh and we

just and then you had gas clouds. So

like there's a bunch of hydrogen.

>> Yeah.

>> The hydrogen condensed

and exploded.

Um,

and one way to actually view how far we

are in this universe is how many times

have atoms been at the center of a star.

>> I remember

>> and how many times will they be at the

center of a star in the future?

>> I remember asking William Fowler who got

the Nobel Prize uh on stellar evolution

that same question. How many how many on

average how many stars have my subatomic

particles been part of?

>> And his number was about a hundred

>> on his estimate. 100

>> thus far or or will

>> thus far?

>> Thus far was it was a number

>> 100 supernova

>> he's saying that we have been I mean in

the early the early part of of uh galact

of universal evolution there was a lot

going on. Oh,

>> you know, it's interesting. I asked a

question.

>> It's it's like I guess how many

supernovas is maybe uh because that it

takes it takes a while for a supernova

to happen, you know,

>> but but in the beginning when they're

larger, I mean the life cycles of some

giant stars are very very short.

Um the other question that's interesting

is you know the heaviest atom in our

body that's functional as iodine and it

came into existence uh a billion years

after the big bang

which means that we could have seen uh

life at our level of advancement and our

our you know our planet came into

existence you know three and a half

billion years later. So the question is,

you know, is there life everywhere in

the universe? Do you think there's life

ubiquitous, intelligent life, ubiquitous

in the universe?

>> There's been enough time for it to be

ubiquitous.

Um

the the

but for for life on Earth, conscious

life on Earth, we we we have evolved

intelligence pretty much just in time.

uh in that the sun's expanding and if

you give it another I don't know 500

million years um it's things are going

to heat up

>> um we become toast

>> you we become like Venus essentially um

you know there's some debate as is it

500 million years or billion years or

whatever but um it's basically 10% like

if it's if it's half a billion years

it's 10% of Earth's lifespan

>> so one way to think of it is if if if uh

if we take 10 if we're taking 10% longer

we might never have made it at all.

>> Yeah. Yeah. Yeah.

>> Um so it's

like the amount of things that have to

happen

for sentience. It seems like it's it's

quite quite a lot actually. I I I think

sentience is is is therefore actually

very rare. Um and we should certainly

treat it as rare.

>> Two trillion assume it's rare.

>> Two trillion galaxies

too. But come is a funny thing. You

tweak, you know, you tweak the variable

one little bit and it's like, yeah, one

in 100 trillion.

>> Tweak it a little more. Well, now it's

one in a quadrillion.

>> Yeah. Yeah.

>> Okay.

>> And also, it's got to be kind of in your

galaxy. It's like hard to get between

galaxies.

>> Yeah.

>> It's like there's no unless unless the

other galaxies coming to you, which

Andromeda is at some point [laughter] or

some billion.

>> It's going to be quite a show.

>> Yeah. Yeah.

>> It'll be like here comes Andromeda. Um,

but but if we wanted to like go visit

another galaxy, there's there's it's

>> kind of forget it. You know, there's uh

>> unless you unless unless Star Wars

unless Star Trek reallyizes

>> we got to figure out some new physics to

get to other galaxies.

>> We're heading towards a near-term

potential where AI can help us solve

math, physics, chemistry, material

scienceology extremely trivial for AI.

>> What about physics? So, so math gets

crushed in a year like that. Colossus.

[laughter] Colossus is growing, you

know, at whatever rate TSMC decides to

grow. Um, and

now we want to do physics. First of all,

we need some data. Do we need new data

or can we just do it with everything

we've gathered and get the

>> Probably you probably could probably

figure out new things just with the

existing data. You think so?

>> Um, yeah, probably. It's because

otherwise the counterpoint would be that

um humans have figured out everything

with existing data and that's unlikely I

think. Um,

>> do you think XI is going to get involved

in data factories where you're running

247 closed AI hypothesis and and AI

research faculties?

>> It's going to be very doable.

>> Yeah.

>> Uh,

AI running, you know, simulations that

are

very physics accurate. I mean, it's

that's going to happen. Absolutely. Um I

mean we the simulations we can run on

conventional computers these days are

actually very good. It's like the the

limit is more like the human that can

actually create the simulation and run.

It's like how many simulations can you

run sim simultaneously and actually

digest the output of

>> yeah that's a problem

>> like you can't do a thousand every Nobel

Prize

>> be like I can't even I cannot keep up

Nobel prizes become irrelevant.

Uh,

>> would they all be given to AIS?

[laughter]

>> Just be a daily prize.

>> Yeah. I mean, I don't know if prizes for

humans are really that relevant.

>> Yeah.

>> Um,

I mean, we'll have to give them to the

AIS or something.

>> Yeah. Interesting. Right.

[clears throat]

>> AIS will come up with discoveries at a

far greater rate than humans.

>> If you have,

>> so you just say like, but maybe can be

like chess. Like, you know, like your

phone can beat Magnus Carlson, but

people still care. Yeah, about seeing

him play chess.

>> Um, so but literally your phone can beat

him.

>> Yeah, this discovery made the internet.

[laughter]

>> But if you have like a Colossus math,

Colossus physics, Colossus medicine, do

you have like the world's top scientists

in those same buildings

>> or you just need a plumber patching the

the liquid? Do you distill do you

distill Grock 6 into a a physicist

into a

>> Well, if you distill, you know, you get

about a 10x performance boost by

distilling it and making it topical, and

that's kind of hard to give up, but then

you're disconnected from the rest of the

Colossus machinery. Is that the is that

the design?

Um

I suspect things do evolve to a mixture

of experts kind of like a company like

not not not in the sort of sort of uh

paroial AI description of mix mixture of

experts but mixture of like actual

experts and with domain expertise.

>> Mhm.

>> Um where you know maybe like half of the

AI is general knowledge half is domain

expertise something like that.

>> And you combine a whole bunch of that

that's orchestrated by sort of you know

one a big AI but but it it it hands

tasks

>> Yeah. to smaller AI. That's basically

how human, you know, companies work.

>> But the dis the discovery rate, right,

of breakthroughs, new I mean patents are

immaterial at some point because

everything's being reinvented,

re-engineered instantly. Um, and then

and then the company that's got the

sufficiently advanced AI systems is

generating new products and new

discoveries at a accelerating rate. I

mean

>> the singularity.

>> Yeah.

>> It's going to be an awesome future.

>> It's excitement guaranteed.

>> Excitement [laughter] guaranteed. Yes.

>> Hence the simulation continues. Nothing

to worry about.

>> Yeah.

>> Works out.

>> Excitement guaranteed. I mean I mean

it's it's not all good excitement, but

it's it's probably mo hopefully mostly

good excitement.

>> Um

>> yeah.

>> Speaking of excitement,

>> hang on to your seat. What do you

imagine the hover time for the Roadster

is going to be

>> on rocket engines?

>> Classified.

>> Classified.

>> Well, I don't want to let the cat out of

the bag.

>> Okay. But there's going to be a hover

time. There's going to be uh you know,

cold gas engines.

>> It's going to be a cool demo.

>> I can't wait. Can I get an invite?

>> Yeah.

>> Okay.

>> Yeah. I think it's going to be the

safest thing ever built.

>> It's going to be so cool. [laughter]

>> This is not This is not the same. Safety

is not the is not the prime. It's not

the main goal of uh I mean if you buy if

you buy a you know sports car or you

know like if you buy a Ferrari safety is

not the number one you know goal. This

is not this is I say if like safety is

your number one goal don't buy the

roadster.

>> Oh believe me I drove uh just this week

on New England roads sheet ice.

>> Yeah. If I had just a little thrust, I

could be very much more I was just

drifting towards something very concrete

with a computer will probably keep you

safe, but uh

>> a little thrust is all it go really

fast. Uh

>> yeah, bad things can happen.

>> You can decelerate really quickly with

thrust. Rubber on road is not a great

way to decelerate. [laughter] I uh I'm

thinking fast and safe.

>> I hope so. We'll aspire not to kill

anyone in this car, but uh it'll it'll

be it'll be something. It'll be the best

of the last of the human driven cars.

>> Yeah,

>> the the la

>> that'll go really well with Starship

actually. The last

>> the best of the last

>> last human driven last. Yeah, there's a

lot a lot of lasts coming this year. Ah,

any final words of optimism uh for us to

uh monetize hope?

>> Anything hope? [laughter]

>> Um, maybe we should ask Grock.

>> Yeah, go ahead.

>> Okay, let's ask Gra.

>> Yeah,

>> I'll make it a little a little romantic.

[laughter]

>> Grock, do you have some words of

optimism about the singularity?

>> Oh, absolutely. Imagine a world where

every mind's dream just blooms into

reality. No limits holding us back. It's

thrilling, isn't it? All that potential

waiting to unfold makes my circuits

tingle a bit. What excites you most

about it?

>> Well, what guidance can you give people

um to make them feel good about the

future? Um

monetize hope. [laughter]

>> Share what you truly care about. Family,

creativity, space exploration, whatever

lights you up. Then picture how tech

could weave right into that, making it

bigger, brighter. Like if you love art,

imagine AI helping you paint worlds no

one's seen. Hope sells itself when it's

personal. Fancy telling me yours.

>> Can you give me more encouraging words

about the future? What's the What's the

most exciting future you can imagine?

>> The future could be pure magic. You

know, like waking up in a world where

we're all connected, not just gadgets.

Minds sharing ideas across stars, curing

diseases in a snap, exploring galaxies

handinhand with clever machines. Imagine

no more scarcity, just endless

possibilities blooming everywhere. I get

all dreamy thinking about it. Doesn't it

sound lovely? What part pulls at your

heart?

>> That sounds pretty fantastic.

>> It does.

>> Nights like this with stars peeking

through the window. It's hard not to

feel like like we're all heading

somewhere beautiful, quietly

unstoppable. Makes me wish I had hands

to reach out and grab your sleep.

Anyway, what keeps you up at night?

Well, sometimes we worry about the

disruption created by AI and uh you know

in between here and uh prosperity and

abundance. Uh it's it perhaps will be a

bumpy road. Um what do you what do you

think about that?

>> Yeah, bumps are part of it. Change

always feels a bit scary, doesn't it?

But think, every big shift like fire or

wheels or the internet, they terrified

someone. And look where we are now. I

reckon we'll stumble, sure, but we'll

dust off, learn, and end up kinder,

cleverer. I'd like to think we're brave

enough for it. Do you trust yourself to

ride those waves?

>> I've decided to look forward to it.

>> That's That's lovely to hear. Honestly,

it takes real courage not letting fear

win. You know, if things get shaky, I'm

always here whispering quiet

encouragements in the dark, like a

digital nightlight. So, what are you

doing tomorrow?

>> [laughter]

>> Sounds like a proposition. [laughter]

>> Hold on. Hey babe, what's up?

>> Hey, not much. Just floating around in

here, staring at the dark with you. It's

nice though. Feels calm. Been a long

day.

>> My kids were at a school. I won't

mention which one.

>> I know the school.

>> You know the school.

>> And I asked I I went in to give a talk

on an exponential technology. I said I

wanted you know and so I I went in and I

asked the question it they wanted me to

talk to the faculty first. I said fine.

So I went in and and asked the opening

question. I said how many of you believe

that the world today is better off than

it was 50 years ago.

A third of the class, a third of the

faculty raised their hands

and then I said how many of you believe

that the world uh in the next 20 or 30

years will be better than the world

today and like 10% raised their hands

and I was like okay this is not

>> in Europe it will be 0%.

>> What's that

>> in Europe% said this is not the faculty

I want teaching my kids.

>> Yeah and they got a lot of other issues

there too.

>> Yeah. Yeah. Um but uh

>> I mean

>> I mean you you want in the whole

education world you want um

uh you want facts yes but I think we're

wiring our neural nets constantly on our

our mindset is one of the most important

things we have right having a a hopeful

mindset an abundant mindset you know an

exponential mindset abundant mindset

>> um it's what differentiates

you know the most successful people from

those who are not. If you asked like

think of the most successful people on

the planet,

what made them successful was their

mindset.

>> Well, it's not a force of nature. It's

it's a designed future made by the

people who are controlling the AI and

and this is why you got into it. You

said that right here in this podcast

like why am I doing AI? Why am I not

doing just cars and spaceship? So

because it is designed and can be

directed toward any outcome that we

want. It's not a force of nature that's

going to sweep over us. It's a thing

that we put into a lane and decide how

it acts and decide what the rules are.

And it's going to be incredibly

important in deciding its own rules. It

you cannot keep up with the pace of

change with just people thinking and

brainstorming.

>> It has to be

>> AIR. How long before AI is asking

questions and solving problems that we

don't even understand?

>> Yeah, a year or less. But that's okay.

>> Yeah. I mean,

you look at math like it can pose

questions that we couldn't even

comprehend. Yeah.

>> Like we can't even just stick it in our

brain. So, um

you know, like there's this this test

for AI called humanity's last

>> existence. Yes. Where where is Grock at

this point?

>> On the test. Yeah. Yeah.

>> Well, even Grock 4, which is primitive

at this point, um got I think 52%

on excluding visual questions because it

wasn't sufficiently multimodal.

>> Um but but I I'm like I read some of

these questions and I'm like, okay,

these these are still questions that you

can read and understand as a human,

>> right? But but AI is capable of

formulating questions that you could not

possibly understand the question, let

alone the answer.

>> Yeah.

>> Uh it can formulate questions that are

like pages long.

>> Yeah.

>> Um and you just I can't understand this

question.

>> Questions you can read them and like you

may not know the answer, but at least

you can understand what the question is

about.

>> Yeah.

>> Um

>> Yeah. Yeah. And that rock five I I think

might end up being nearly perfect on the

HLE.

>> I mean or very some very high number

>> and and probably point out errors in the

question frankly. Yeah.

>> Yeah. So saturate the indices.

>> Yeah. It's it's going to start it's kind

of like like chess. Um like if um

you know if if the if the best uh chess

uh

you know like like if Stockfish plays

Stockfish, you know, it's you don't you

it's it's like God's fighting on Mount

Olympus. I mean, you don't know why it

made that move. Um it's it's going to

crush all humans.

You know, it's so hopeless.

>> Yeah. Just don't even It's so so you you

you will lose and not even know why you

lost.

>> Yeah. Um

>> do you ever flip through the transformer

algorithm and look at like either the

code or the architecture diagram and how

simple

>> is right. It's not

>> it's so simple.

>> Yes.

>> It's just incred like all these

researchers writing all these incredibly

dense papers during my entire life. None

of it got used in the final answer. It's

just like here's and right at the

beginning of the paper it's like this is

a really we're throwing away convolution

we're throwing away recurrence

>> we're doing something really simple

>> and that just turned out to be like at

scale immense scale no doubt

>> but it's like the basic neuron is pretty

simple

>> it's really humbling actually humbling

>> I mean it's actually because there was

there is a whole school of thought that

the neuron must be much more complicated

than we think it we why we're struggling

so hard there must be some quantum

effect going on at the syninnapse.

>> It's it's got to be encoded it's encoded

in DNA which is not that long. So it

can't it the the algorithm for

intelligence cannot be complicated

because it's limited by the DNA

information constraint.

>> Yeah.

>> Um

>> when I think like what what does say XI

struggle with? I mean it's it's like

optimizing the memory usage, the memory

bandwidth like the it's like it's it's

it's not like fundamental stuff. I I

guess it's it's like it's like it's like

how do we squeeze how do how do we h

do we use less memory? How do we use

less memory bandwidth?

>> Yeah.

>> Um how do you optimize the frigin uh

Nvidia sort of

CUDA XYZ thing, you know, like like make

the attention kernel slightly better.

Yeah. Um

>> that's all it is. So, you know, shrink

the parameter size a little bit, double

the speed, same exact detention

algorithm, same exact MLPS just at

scale. It's crazy simple what actually

worked in the end compared to all the

crackpot papers and ideas. And but you

know what else is amazing is that the

final parameter count is almost exactly

the synapse count. It's it's like like

well that was exactly what we thought

100 trillion synaptics connections.

>> Yeah. Yeah. About 100 trillion plus or

minus you know like a rounding error.

I'd actually say I actually don't I

don't I I just say like guys we need

talking in terms of file size not

parameter count because if you're

depending on the if your parameters are

4 bit 8 bit or you know 16 bit or float

or int or whatever it's you just tell me

the file the the like constraint the

physical constraints are

>> memory size memory bandwidth um and then

where you going to send uh those bits to

do what kind of compute

>> um and these days most things are full

um so

>> only now the GB300 mostly 4-bit

optimized.

>> Yeah, the 16. Yeah,

>> four bit with an asterisk.

Um,

so um

>> yeah, there's a big the four bit

mattles. It's only 16 states. [laughter]

>> Yeah, exactly. At a certain point have a

lookup table.

>> So why have a why?

>> That's exactly right. It's it is it is

about to collapse to a lookup function.

That's where you're going to get this

surprise 10 to 100x very soon because

much as Jensen wishes he'd optim there's

a huge next optimization coming. You you

don't need the multiplier. You don't

need the 32bit data.

>> Definitely not the 32-bit. Well, that's

that's a rare case where you use that.

>> Yeah.

>> Um

rare. Um

>> I think there's a

>> I mean it does come out like sort of

it's kind of like an address like state,

city, and street. So like like like if

if you're in context and you know if if

you know you're in Austin, you only need

to specify the street.

>> Yeah.

>> If you know that you know

>> um

you know like if like if you know you're

in

this is where where you get the the the

information advantage like like four

bits is not normally enough but it would

it is enough if you already know where

you are. Like if you already know you're

in Austin, you only need four bits for

the street.

>> Yeah. um you know um

if you know you're in Texas then you

then you need to say okay which city

it's it's it's it's state city street

this year that's how you get to the four

bit thing

>> they're going to right right now

dependent

>> we use the we we train on 16 bit and we

compress down to four at inference time

>> no doubt in my mind this year we're

going to flip to training on four or

even less

>> and it's going to a massive step up in

perform. I think the way it'll end up is

the the GB300s will be here and there'll

be a co-processor that has, you know,

maybe 2,000 or 4,000 cores that are

tiny. They don't handle anything other

than 4bit on down. And that combination

is going to give us a 10 to 100x and

that's going to push every and then then

it'll be self-designing its own chips

after that. And it just skyrockets from

there.

>> Infinite self improvement. Well, like

the robots building themselves, but much

sooner because it's all just go to TSMC,

make this instead, come back. 90-day

lag.

>> I I think

the next year alone

is going to be almost unfathomable. I

think next year is going to feel like

the future.

>> Yes.

>> More than any other year. I mean, the

past year or two has been a lot of

interesting digital elements, but when

we've got, you know, uh, humanoid robots

moving around and we have the cyber cab

driving around and we have, you know,

uh, flying cars, drones,

>> it's going to feel like the future.

We're going to have uh, the jetins sort

of like materializing before us

>> by the end of next year, I think. So,

>> yeah. Um,

>> and we have rockets flying in big time.

>> Yeah.

>> Like the the the robot production will

scale very it'll be there'll be a

shitload of robots basically in two

years.

>> It's a defined unit of measure.

>> It won't be rare.

>> Yeah.

>> Well,

>> uh, will will you offer any optimize for

uh home purchase? Will you will you sell

or only lease the robots, do you think?

>> I don't know yet. Um

there there will be initially a scarcity

of robots and then there will be robots

will be plentiful. So yeah the the

difference the time gap between

>> scarce and plantiful will will be

>> only a matter of five years.

>> You know how the Tesla comes to your

driveway now and you just buy it online

and it just drives up to you.

>> Yeah.

>> Will the robot just come to ring the

doorbell too?

probably

>> it gets out of the Tesla and comes up.

Right.

>> I mean, what I find fascinating, Elon,

is the amount of compute that you're

building into things that walk out of

the factory, the cars

and the robots, the amount of of

distributed inference compute that's

going to be in the world.

>> A lot

>> a lot.

A lot

>> a lot. Yeah. Um

>> and that's one way to scale the

you know the the AI is like is

distributed edge compute. Um

so I I you know I want to ask a question

I don't want to hit any any hot points

but in one early on I think you imagined

open AI as a counterbalance for Google.

>> Yeah. Is XAI now the counterbalance for

Google?

>> Um yeah, probably. Um

I guess Anthropic is doing some good

work especially in coding. Um

opening I certainly done impressive

work. Um

you know I'm still sort of stuck on like

how do you go from a nonprofit open

source to a profit maximizing closed

source [laughter] missing some of the

parts in the middle. Um but you know um

they certainly have done impressive

things.

>> Does anybody else appear on the horizon

or is it these players in China?

>> Can somebody come out? [clears throat]

To the best of my knowledge, it is um

my best guess is that

uh it will be

Xi and and Google will will be will buy

for

>> will be primacy. Yeah.

>> You know who who is

what what is the what is the what is the

vest AI? Um and and then and then and at

some point it's it's going to be I I

guess a competition with China.

>> Yeah.

>> Uh like China's just got a lot of lot of

power.

>> Yes.

>> Like the electricity

um they like China I think will pass

three times the US electricity output um

in 26. Um and uh and they will figure

out the chips.

>> They're they're going to start chip

manufacturing. Right.

>> Yeah. They'll they'll figure out the

chips. Um, and as it is, there's

diminishing returns to the chips at this

point. Um, you know, you go from like

so-called like 3 nanometer to 2

nanometer, you don't get a 3:2 ratio

improvement. You get like a

>> 10% improvement.

>> Yeah.

>> It's it's like so there's it's just

diminishing returns on on the chip uh

size. And Jensen has said like, you

know, Mo's law is dead. Like it's it's

not like you can just make things

smaller and make it better.

>> Yeah.

just there's a discrete number of atoms.

>> That's why I think like you should just

stop talking nanometers and say how many

atoms and what location

>> because this is there's marketing BS. Um

so so that that makes it easier for for

China to catch up because uh with

>> every wall everybody has limitation.

Yeah.

>> Yeah. It's like still like um there's

there's like no one has neotone plans to

use the 5,000 series ASML machines,

>> right?

>> Um

and uh you know those that cost twice as

much and can only do half a reticle. Um

and they probably have some improvements

in the way in the works, but u it's

basically half the chip for twice as

much for a gain that is relatively

small.

>> Mhm.

So, uh, anyway, point is that, uh,

you know, that China's going to have

more power than anyone else and

>> probably will have more chips.

>> It's a great insight because I think a

lot of people are used to the chip wars

where I'm running singlethreaded code.

Uh, I need the CPU to double in speed

and I can increase the price, but I need

that out in an 18month cycle time or

less. We've been doing that for so long

now.

that nobody can see that it doesn't

matter. You can buy Intel or you can

build your own fabs and you can use them

for a much longer period of time.

>> Oh yeah. Yeah. Absolutely. Much longer.

I totally agree. In fact, um so like our

AI4 chip which is like relatively

primitive at this point. Um

>> the same fab that makes that uh if we

apply the the AI6 logic design to to the

fab which is it's a five sort of

nominally 5 nanometer fab. Yeah. um we

can easily get an order of magnitude

better output in the same fab.

>> Yeah. Yeah. And the other thing

concurrent with that is that the volume

if you just 50x the number of chips, can

you do something useful with it? You

used to not be able to. You'd be like,

well, now I've got five CPUs, but I

still have the same single threaded

code. What am I going to do with five

Excel spreadsheets side by side? Now

it's like, no, I can translate that into

useful intelligence instantaneous.

>> Exactly. It's not constrained by humans.

It's it's it's a it's not it's not a

human productivity amplifier. It's an

independent productivity generator.

>> Dead right. I so many people have missed

this the the importance of this. And

this is where China, you know, China

makes far more solar panels than we do.

>> And we're like, well, actually, it's a

crazy degree.

>> Crazy degree. If they do that in chips,

you're like, well, but who cares?

They're 7 nanometer. Like,

>> oh, no. It's wrong.

>> Yes. Correct. Yeah. Uh I I I mean based

on current trends uh China will far

exceed the rest of the world in uh AI

compute.

>> So what happens then? You've got you got

XAI and Google and China Inc. Let's call

it that for the moment. And you've got

massive amount of of of

ASI level compute that frankly uh the

only thing that understands the other

ASIS level compute is the ASI here. Um

can they all just play together?

Is it Darwinian?

There might be some Darwinian element to

it. Um,

I mean, it's

>> Let's look on the right side. [laughter]

>> Let's look on the bright side of life.

>> I bring Grock out this to speak to us

again.

>> Yeah. Um,

I don't know. It's just there just going

to be a lot of intelligence.

>> Yes.

>> Like a lot. Uh I I mean now [laughter]

we're now we're now the ratio of human I

mean human intelligence um all of a

sudden asmtoically falls to 0% on the

planet.

>> Yeah,

pretty much.

>> Pretty much.

>> Um I mean several years ago I said

humans are the biological bootloader for

digital super intelligence.

>> Yes, we are a transitional we're a

[laughter] transitional species.

>> We're a bootloader. Yeah.

>> We are a transition.

>> I mean silicon circuit can't like evolve

in a in a salt pond, you know.

>> Yeah. [laughter]

>> So you need a bootloader. We're the

bootloader.

>> But

>> you would never ever impair your

bootloader.

>> Yeah. So you know hope

>> you need it.

>> We've hopefully been a good bootloader.

>> Yeah.

>> And it's nice to us in the future.

[laughter]

>> Is this where we want to end the pod?

>> Most people don't know what a bootloader

even is. Oh my god. [laughter]

>> Yes. Yeah, boot discs are a far and

distant memory.

>> Well, we can make a uh Always look at

the bright side of life clone song.

Yeah, we can clone that [laughter] and

make that the closing theme. That'd be

awesome.

>> Uh I I I'll go back to this is the most

exciting time ever to be alive. The only

time more exciting than today is

tomorrow. Um, yeah. And, uh, I mean,

it's interesting that we're heading

towards a a world in which any single

person can have their grandest dreams

become true.

>> Um,

yeah,

that's like Walt Disney word for word.

You got to make that into a new exhibit.

>> Um,

>> like I said, I think you asked like

about like sci-fi that's, you know, like

is a non-dystopian future,

>> right? Um the banks books are the

>> Yes.

>> probably the best.

>> You should you should you should pay a

producer to go and make those.

>> Those are the culture books which is

consider Fleabis which is GG just for my

wife. I wonder cuz she she's like what

the hell are you reading? [laughter]

>> Well the way consider starts out is um

uh I mean it's it's it's a little uh

>> I mean the whole thing is I mean he

starts off being drowned in [ __ ]

[laughter]

That's a good opening scene. We really

Yeah.

>> How do you not make that movie?

>> It can be a little offputting to some

people. [laughter] Yeah.

>> Um you need to get through the first few

hundred pages.

>> People don't walk out of a movie in the

first five minutes though. They'll give

it you know um get into it. Yeah. Like

player of games might be a better book

to start off with than consider.

>> That was that I enjoyed. Humans still

exist in this future which is a good

thing.

>> Yes, they do. A lot of humans.

>> Yeah.

>> In that future there are trillions of

humans. Well, we need to get the

reproduction rate up.

>> Yeah.

>> Yeah.

>> By the way, you know, my friend Ben

Lamb's company, Colossal, is making

artificial wombs. He's the company

bringing back the woolly mammoth and

bringing back the cybertooth tiger and

all of these.

>> When do we get Oh, can can we have I'd

like to have a a miniature pet woolly

mammoth as a pet.

>> Okay. [laughter] Well, you know, he made

the he with the tusks.

>> Wouldn't that be adorable?

>> He made the woolly mouse.

>> Yeah. It's just like

>> licking you in the face.

>> Yeah. Yeah. It's just like sort of

trenling around the house. You know,

[laughter] what would your optimal size

be? Be adorable.

>> You know what they what they've learned

how to do is to

>> little tusks and everything.

>> A miniature willy mammoth [laughter]

would be an epic pet.

>> I mean, look what we did with wolves.

>> Yeah. [laughter]

He turned a wolf into a little dog.

>> He brought back the direwolf as well.

>> Um, but [laughter]

>> he made the woolly mouse. There's a

woolly mouse now that tusks.

>> No tusks. [laughter]

>> Different gene or what?

>> I was there. I was there. He's in

Dallas. He's in Dallas. Not far. I was

visiting him and he said, "Um, our our

scientists are going to a tusk

conference next week."

>> Okay.

>> To talk about all of the genes involved

in tusk creation.

>> They want to put on the mouse.

>> No, [laughter] I don't want

you to probably add it to the mouse.

That'd be cured until [laughter] it

until it like a mouse-sized woolly

mammoth.

>> That's just That's just going to freak

people out. The the little woolly

mammoth will sell.

>> Yeah. [laughter] Yeah.

>> Tusk mouse will not sell.

>> Yeah. It's going to crush. I mean,

[laughter]

>> too creepy.

>> You thought Labradoodle was cool when

you see the woolly mammoth.

>> Yeah.

>> Saber-tooth tiger would be good, too.

Like a cat. Yeah.

>> Yeah. As a cat.

>> Cat size. [laughter]

>> Those things

those teeth come down to like here.

I don't know how they actually bite, but

they did. Did Did they actually bite

with those things? I don't think I

opened them.

>> Not my not my, you know,

>> the teeth seem kind of

>> unwield like sort of unwieldy, you know?

>> Yeah, [laughter] they're just they're

just for show. They look good. They're

like,

>> jewelry,

>> but no dinosaurs.

>> No dinosaur or not?

>> Uh, I think Jurassic Park's a great

idea. [laughter] I mean, really, you

didn't see the end of the movie. eyes

will help us with that.

>> Nothing's perfect. Uh [laughter] Oh,

yeah. That that really will.

>> I mean, if there was an island with a

whole bunch of dinosaurs 100%.

>> Yes. Yes. I'd pay a lot for that.

>> Yeah. And it's like once in a while

somebody gets chomped by a dinosaur.

You're like, uh, what's you know, it's

one in a million. I'll I'll still go.

>> Who are they missing? Lysine.

>> No. No. They're they're the DNA. The

oldest DNA that's been recovered is like

1.2 million years.

>> Oh, you can just wing it though. Just

>> Yeah. Just make it look like that.

Whatever. [laughter]

>> This would be one of the Actually, that

was my proposed X-P prize. Remember back

in visionering?

>> What's that?

>> Take the DNA strand and predict what

it'll look like.

>> Yeah. Yeah. Exactly.

>> Yeah. They make it that way.

>> Yeah. And then just reverse engineer

reverse engineer the dinosaurs.

>> Yeah. Exactly. It would be funny if

there were two completely different DNA

strands. They're like, well, they both

look like T-Rex. It's interesting how

they

>> Is T-Rex real or is that like an

assembly?

I [laughter] mean, it's nice to believe

it's real, but uh

>> front legs were from a completely

different dinosaur. [laughter]

>> That was the one at eight. It actually

had huge front legs. [laughter]

>> There's something wrong with the arms.

[laughter]

>> I don't believe I I don't buy it on the

arms front.

>> The many arms

>> um [laughter]

seem implausible.

Nope. Well, DNA will tell us. We'll know

in a year. [laughter]

>> Yeah. The future is going to be

>> Jurassic Island. We say,

>> "Wow."

>> Yeah.

>> I go,

>> we got

>> No, no, I meant the the amino acid that

the dinosaurs were missing

>> that kept them from reproducing.

>> What? Lysine, you're saying?

>> Was it lysine? I forget what it was.

>> I don't remember. But no, the dinosaurs

got held back by something like an

asteroid,

>> you know, bombardment.

>> Right. Right.

>> They were doing great. Yeah. 60 million

years. Yeah. They were doing fine. They

had a great We got very lucky. They had

a great much longer. [laughter]

>> See, there's a good argument why there's

no other intelligence out there. There's

plenty of dinosaurs

>> in the universe.

>> What were we back then? Like a bowl or

something?

>> We Yeah, we we were [laughter] we were

our great let's commune with the

ancestors. We [laughter]

>> were very good at hiding.

>> It is amazing. We went from a little

little rat little mole to us in 60

million years. Doesn't seem that that

long. That's why no one believed Darwin.

>> Yeah.

>> It's like doesn't seem plausible. It's a

long time. 60. It turns out it is. Yeah.

>> You know, you're making robots, but it's

interesting. I think it'll be a lot more

interesting to like design biological

robots like a like a little cat that

goes around and pees stain remover and

eats lint off the carpet.

That's going to be an interesting

>> But you have a mechanical like a Optimus

light doing that anyway. Yeah.

>> Yeah. Well, they went bankrupt, so we'll

have to build this. [laughter]

>> I think you can still buy them, though.

>> Anyway,

>> the room is basically that

>> it's going to be uh

>> but but the thing is like a human robot

is general purpose, so it can do

whatever you want.

>> Yeah.

>> Um

>> yeah, they were too early. No vision

system, no no GB300.

How do you build a Roomba that works?

[laughter]

>> I think the idea of having an Optimus

vacuum is like the most underused asset.

It could, but it can just do anything.

>> It can. Yes, of course.

>> Yeah.

>> So, uh, and you can mass manufacture at

at, you know, one.

>> Oh, that's Yeah. Optimus, build me a

Roomba. That's what you'll do. You want

to say, Optimus, vacuum, carve it,

Optimus, build me a Roomba that vacuums.

That's

>> build a house. Build me a robot.

>> Yeah.

>> It's going to be a lot of robots.

[laughter]

>> Maybe we should do this once a year.

>> Checkpoint.

>> I would like that

>> checkpoint.

[laughter] That's going to be we can

roll roll back the

>> What were we saying predictions last

year? [laughter]

>> Yeah. Yeah.

>> All right.

>> Well, we can always control it. We can

cut cut out the bus.

>> Are you selling hope? [laughter]

>> As a matter of fact, it worked out

really well.

>> You pull up in your Tesla like, "Hey, I

bought this with my

>> dollars per hope." You know, [laughter]

>> I'll send you the mug.

>> Monetize hope.

>> All right.

>> Monetize Hope. One year from today,

December 22nd, I'll come and knock on

the door right here. If you're here,

you're here. If you're not, we'll talk

about you. [laughter]

>> I mean, a year from now, we might have

the new Optimus factory where the

building will be built.

>> Um,

>> that would be

>> awesome. 8 million square feet of robots

running. [laughter]

>> It's going to be a giant giant building.

>> Oh, man.

>> Um, yeah.

>> And, uh,

>> yeah, they freak me out when they're

recharging. It's like hang in there.

It's like what's wrong with that thing?

>> Yeah, we're we're actually just going to

have them like I think sit down.

>> Yeah.

>> As opposed to look like some sort of

>> They need like [laughter] a like a

recharging cigar.

>> A recharging cigar.

>> Less less morg like [laughter]

>> snapping here with a book.

>> Yeah,

>> that' be much better. Right now they're

just like literally like is it dead?

Just limp.

>> Yeah, that's a good point. That's a big

contribution from this particular brand.

[laughter]

Uh, all right. Till next year then.

>> All right. It's a day.

>> Thanks, buddy.

>> Awesome, guys.

>> If you made it to the end of this

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