I began by thinking, of course, AI is

going to be smarter than us, but it

doesn't have an incentive to attack us.

And then one day, I go visit Jeff

Hinton, the academic father of deep

learning who lives in Toronto. I said,

"Look, Jeff, why are you so depressed?"

And he says, "Okay, here's a thought

experiment. You have an AI. It's very

powerful, but you're worried that

there's a Russian AI or a Chinese AI.

It's going to come and attack your AI.

So, you're going to empower your own AI

to watch out for the attack. And when

the attack is coming, defend yourself or

maybe counterattack. Whatever you do,

make sure you survive. Oh, survive.

There you have it. Now you feeling

comfortable, Sebastian. Right. You've

just given the machine a survival

instinct.

>> Sebastian, lovely to see you and thanks

for making the time. I really appreciate

it.

>> Great to be with you, Tim.

>> I wanted to just give you applause for

writing some of my favorite books of the

last many years. I am consistently

impressed and maybe since I also put pen

to paper every once in a while,

depressed, just thinking relatively

about my capabilities, but of your

capacity to

paint a picture of the players on a

landscape,

but also the games they play in ways

that non-speists can understand. And I

can't recall who first recommended it.

Frankly, I believe it was a hedge fund

manager in New York City, but more money

than God, hedge funds in the making of a

new elite. And then certainly that was

in my particular case followed by

reading the power law of venture capital

in the making of the new future, which I

didn't expect to learn as much from

because I've spent 20 years surrounded

by venture capitalists and doing angel

investing, 17 years of that in Silicon

Valley. And yet I still had hundreds of

highlights and so many stories that

grabbed me from that book which I had

not heard. And

that made me very excited to read The

Infinity Machine, which this is the new

book. And I realized also I've been

pronouncing Demis' name incorrectly for

a very long time despite having met him

at one point. So Deis Hassabis, Deep

Mind and the Quest for Super

Intelligence. My question for you, and

we're going to come back to present day

for people who are interested, of

course, in what has been painted as a

race to IPO. I think there's something

to that in the air, so to speak, talking

to people who are in San Francisco

involved with these companies. But

nonetheless, I wanted to ask how the

genesis of this book came to be because

you, it would appear, began exploring

these waters on the early side, which

leads to a meta question of just general

book selection. But let's let's focus on

the infinity machine. How did this how

did this come to be? Where did the

twinkle in the eye begin? What was the

conversation, the thing you read that

triggered

the gingerbread trail that got you to

this book?

>> Well, the power law, the book about

venture capital, had come out in

February of 2022.

>> And while I was researching that, I'd

been to lots of tech conferences, of

course, including some in Europe. And

this, you know, twinkly guy would show

up, Deiss, and he would look totally

approachable and kind of guy next door

and unintimidating.

And then he would get on the stage and

out of his mouth would come this spiel

about computer science, neuroscience,

chemistry, biology, physics, philosophy,

the history of movies, you name it,

right? And that mixture of the

approachability and the massive

intellect always struck me as beguiling.

And I thought, hm, this would be a great

character to write about. And then at

the same time I was aware of Alph Go,

the 2016 model that Demis' team at Deep

Mind had built which defeated the world

champion at Go and then Alpha Fold which

was the protein folding system. And both

of these things had the quality that you

had this almost infinite search space,

right? Where the different permutations

of the game of Go are almost infinite

because they're so big. The different

permutations of how you can fold an

amino acid chain into a protein shape

are even bigger. 130 zeros added onto

the end of the number of permutations in

go. So you have these AI systems that

could understand infinity. And so this

idea of an infinity machine began to

percolate. And I figured it's

interesting to me probably at some point

it will go mainstream. But even if it

doesn't go mainstream, I love it and I

love Demis and the two things together.

I always look for the subject and the

personality.

>> I had both and I thought, okay, this is

a go. And I went to pitch demis in early

November 2022.

And then, you know, I persuaded him to

give me a lot of access. End of

November, Chatty PT comes out and way

earlier than I expected, my fringe

subject went to the mainstream, proving

Tim that it's better to be lucky than

smart. [laughter]

>> That's actually the first slide on my

new venture capital firm.

[laughter]

Muggle thesis capital is what I'm

calling it.

Now, what did it take to be deeply

interested in the subject matter to find

Demis compelling and then to pitch him

on a book? Because your books are so

deeply researched and part of the reason

for my my very long praise earlier is

that you're very very good, one of the

best at taking incredibly complex

subjects or concepts. Transformer

architecture could be one example from

the current book and laying them out in

terms that are both intelligible to

muggles meaning people who are are

non-speists non-technologists or non-

financeers in the case of some of your

other books while I think now it's tough

for a non-speist to say this with

conviction but without dumbing it down

and getting it wrong if that makes sense

Right. Nonetheless, you do a tremendous

amount of research. So, how did you get

from Demis is fascinating, subject

matter is fascinating to I'm going to

commit to this for my next book because

it just seems like such an enormous

undertaking. Well, actually to me the

challenge of understanding a complex

topic is the easy bit because you know

if you know you've got the right

personality who can carry the story and

it's a subject that people either will

care about for sure or should care about

at least then you know doing the work of

going deep is something that takes time.

It takes effort but you I know I can do

that. I've done it multiple times.

That's not difficult. What's difficult

is has somebody done the book before?

Mhm.

>> Has somebody else got some rival project

which is going to derail me? You've made

the point on your own podcast. Tim,

don't put a lot of effort into something

where there just isn't much leverage

there. You know, you could do the best

book in the world, an A+ book on a C

minus topic. It would get you nowhere,

right?

>> So, the hard thing is to make sure it's

an A+ topic and an A+ personality. And

then the deep dive is something you know

I just make sure I speak to enough

experts who are insiders. I take the

time these books take me you know four

years or so each time. So I give myself

the oxygen to get deep deep in with the

insiders and that's how I produce the

accurate account.

>> Yeah. I should point out perhaps to

people who don't immediately pick it up

that the way you described picking the

book topic is exactly how a lot of the

best tech investors choose startups.

You don't want an A+ team and a C plus

market, right? It's better to have a B

minus team and an A+ market and also

looking at the competitive landscape. I

mean, the way you laid it out is is

pretty much copy and paste. I I wanted

to segue to some of my notes from the

book. And I'm not yet done with the

book. The audio is incredible. I I want

to poach your narrator for my next book,

but pulling up my Kindle notes. I wanted

to ask you a question related to

[sighs and gasps]

this might sound very strange but where

divinity or God fits into the pursuit or

development of super intelligence for

different players in the space if it

does. M

>> and the reason I bring that up is that

religion does recur in the book both in

the personal story of Demis but

elsewhere and it shows up repeatedly in

so much as I'll give you one example the

closest to Sabis had come to landing a

real investor was an eccentric finance

year named David Gammon I want to hear

more about this guy also [laughter]

finance seemed open to making this

unusual bet um aligning a few things

because his motives were themselves

unusual quote. There's a deeply

religious aspect to AGI. Gam explained

to me later, it's really finding God's

algorithm. I think it would seem at

least chatting with people in Silicon

Valley that there are some who take it

even further, right? Maybe this is how

we find God. Maybe this is how we

actually elicit the second coming. I

mean, there's a lot there. I'm just

wondering to what extent this has popped

up in your research, whether it's

reflected in the book or not. I think

there's one basic thing going on here

and I'm going to take a slight detour,

but it answers your question.

>> Sure.

>> What we're dealing with with AGI,

powerful intelligence that rivals human

cognition,

is something that's so powerful that

it's both exciting and scary and just

hard to get your mind around. And so if

you look for example at the 2009 speech

that caused the foundation of deep mind,

this was Shane Le Deis' co-founder who

gave a talk in 2009 about how super

intelligence would arrive in 2030. So

unbelievably spot-on prediction. And

towards the end of that lecture, which

is captured on a grainy video online,

you see him pivot from explaining how

algorithms are getting stronger, there's

more data online, computers getting more

powerful, and so we're heading towards

this intelligence explosion. And then he

says, and it's going to be threatening.

It's going to do things we can't

control. It's going to be human level.

It might challenge us. And as he says

this, he has this sort of excited smile

on his face. And you think, well, that's

a bit strange. You know, he's talking

about potential doom and he's smiling.

And then somebody in the audience says,

"Wait, wait, wait. You've just told us,

Shane, that this could be threatening to

humanity and you haven't provided any

antidote and surely you're going to tell

us how we're going to stop it." At which

point Shane turns around and says, "How

do we stop it?" and he's kind of

giggling and you think why are you

laughing at this dangerous thing and you

realize that for humans to contemplate

annihilation is absurd and the absurd is

a close cousin of humor

>> and the reason I tell this story is that

it's a springboard to the religion point

which is that this is such a hard thing

to think about that people reach for

religious terminology

when they're around AI they just do it

naturally

So you know there's this story about

Ilia Satskaver the who was the chief

scientist at open AI. I talked to him a

lot for this project and there was a

point when he was at a retreat with his

fellow scientists and they were gathered

in the evening around a fire pit and he

was talking about safety and he said

okay I want to explain to you we might

have an AI that's dangerous. It wouldn't

be aligned with us. So here's what we're

going to do with it. and he produced an

effigy which was supposed to represent a

malign AI and he put it into the fire

pit and he burnt it like a medieval

cleric putting a witch to death. And so

that's just one example of this

religion. I'll give you another one. So

Deis one day was sitting with me in a

park in North London. We would meet for

two hours at a time and we would get

deep into stuff. There was a another

picnic table next to us where two people

were having a normal quotidian

conversation about some friend of theirs

who'd gone to hospital and was she

better, was she okay, etc., etc. I was

seated opposite Demis who had gone into

this riff about how he reads scientific

papers from after his kids go to sleep

in the evening from 10:00 p.m. until

4:00 a.m. And as he's reading these

papers, he says to me, "Reality is

staring at me, screaming at me, calling

at me to understand it. And I have to

understand it. And if I can understand

it, it's like understanding nature

better and therefore understanding the

intelligence that might have created

nature and I will be closer to what I

would call God. And so for him it's a

kind of quai spiritual quest to build

the artificial intelligence. For Ilia

it's a way of expressing the power of

the artificial intelligence. There's the

story of Leandowski. I forget his first

name now, but the early early engineer

at what became Whimo later

>> started a kind of church [snorts] in

worship of AI because AI is so omnisient

that it's kind of like a god.

[clears throat]

>> Mark Andre

lampuns those who believe in sort of

some ethereal second coming, a kind of

rapture where AI will, you know, we'll

have a singularity. uh the AI will go

vertical in its rate of improvement and

the whole world will change and he

likens that to kind of Christian kind of

messianism.

So yes, all through this topic there is

this religious expression because

religion is the lexicon for dealing with

something that we find too mysterious to

really understand. [clears throat]

After all of your conversations,

research before the book, during the

book, after the book, where do you land

on the spectrum of

let's just say

this will bother Mark, but like Church

of Andre and techno optimist. [laughter]

And there are others who are more

exaggerated. Post AI in the near term we

will live in a post scarcity world of

super abundance and everyone will get a

free car and we'll be free to crochet

socks and play music and read poetry all

day and basically we don't have to worry

about anything because super

intelligence will solve it all right

there's that on one end and then there's

the you can imagine I won't go into a

belabored description of the doomers but

you have the doomers who are like the

end is nigh Okay, here we go. It's It's

[laughter] not It's not the second

coming as the Antichrist. And within

short order, we're going to be MadMax.

Between those two, there's a lot. And I

suspect you land between those two. But

where do you land

in terms of assessing the promises and

peril of AI and super intelligence as it

stands right now?

So look, I think any reasonable person

should be both excited and a bit

frightened

>> and you know that's just the nature of

it. It sounds contradictory but actually

that's the only rational response. I

think you know the super abundant story

may turn out to be true on a kind of

longer view let's say 20 30 40 years.

>> Mhm. The problem is that in the path to

get there, there's going to be a

tremendous amount of disruption and

that's going to be politically quite

difficult to navigate. I think a useful

lens through which to view this question

is the China shock in trade.

>> Mhm.

>> So in 2003 or thereabouts, you get this

enormous surge of Chinese

exports into the US and people lose

their jobs in a very concentrated way.

Certain industries just get wiped out.

And for the first time in the history of

economic study of the effects of trade,

you actually see negative effects on

workers. Before that, it was kind of a

bit of a myth, right? Because people

adjust. They get displaced from one

thing, but they move to a new thing.

With the China shock, they didn't. But

if you look at the size of the China

shock, in a 12-year period between 1999

and 2011, the total number of jobs

displaced was 2 million. which is

actually a small number in a huge labor

market like the US where there's a lot

of churn month to month anyway and yet

the political reaction against trade

against globalization in terms of a

swing towards protectionism frankly in

both political parties was enormous. So

it shows you that a small to medium

shock to the labor market creates an

enormous political consequence and so a4

with artificial intelligence you're

going to have a bigger shock you're

going to have a bigger political

reaction we're already seeing that in

the polling around AI in the last 2

three months

>> and so I think the super abundance thing

it may be true but the path to get there

we have to talk about that as well so

that's that's my sense on that side of

debate. I think on the doom side of the

debate, I'll give you my own personal

journey on this.

>> Mhm.

>> I began by thinking, of course, AI is

going to be smarter than us, right? It

already beats us at chess since the

1990s, at go since 2016. Now, it can ace

the bar exam. It can do PhD level math,

all that stuff. Of course, it's smarter,

but it doesn't have an incentive to

attack us, right? We are evolved as

human beings to pass on our DNA.

Therefore, we have to survive to do

that. Machines don't have DNA. They

don't want to pass it on and they don't

want to survive. So, they're not they

have no reason to attack us. So, I

wander around for like the first year or

two of this project feeling kind of, you

know, comfortable and happy. And then

one day, I go visit Jeff Hinton, the

academic father of deep learning who

lives in Toronto. And I sit in his

kitchen and I debate him on this because

he's a doomer. I said, "Look, Jeff, why

are you so depressed?" And he says,

"Okay, here's a thought experiment. You

have an AI. It's very powerful, but

you're worried that there's a Russian AI

or a Chinese AI. It's going to come and

attack your AI. Now, you as a human,

you're too slow and dumb to know when

that attack is coming. So, you got to

empower your own AI to watch out for the

attack. And when the attack is coming,

defend yourself or maybe counterattack.

Whatever you do, make sure you survive.

Ooh, survive. There you have it. Now you

feeling comfortable, Sebastian. Right,

you've just given the machine a survival

instinct. And I think that's correct.

These machines will be smarter than us.

They will want to survive. And they are

also they can be deceptive. They can

obiscate. They can go behind your back,

pretend they're doing one thing, then

actually do another. All of this has

been shown in all the tests of the

models. And so you put those things

together, I think your probability of

doom cannot be zero. I mean, when Yan

Lun, the former chief scientist of Meta,

says zero, I think that's crazy. If you

just say nothing to see here, you've got

no right to be in the debate. I don't

think it's a high probability of doom,

but it's not zero.

>> Yeah, zero

does not seem defensible, right? Because

there's the direct Skynet scenario,

something akin to that, and then there's

the indirect, which is enabling people

who might previously have had malevolent

intent but no capacity for harm on a

grand scale to create biological weapons

and things of this type. Right? So, I

don't find the zero very defensible.

Well, I would love to ask you about

I suppose two things that this brings to

mind for me. One is I'd just love to

hear your thoughts on enthropic and

separately

but this is very intermingled given all

the [laughter]

let's call it friction be polite between

some factions of the US government and

anthropic is one of the

grand risks to investors in any of these

companies the possibility that at a

given point governments have no choice

but to seize considerable control over

the assets slashtechnologies within them

or maybe the companies themselves. That

is a big question mark in my mind. I

don't know the answer, but I'm curious

what your opinion is and then perhaps

just your thoughts on Anthropic or any

of the other companies that are sort of

gaining momentum or at least size at

this point.

>> So, I 100% agree with you that investors

should be thinking about the prospect of

government intervention in AI. I mean,

the Trump administration came into

office in 25

super less a fair and they basically

undid some of what the Biden guys had

done in terms of trying to set up the

basis for regulating AI. But they've

done a 180 right since Anthropic came

out with this model called Mythos.

>> Mhm. about a month ago which can

essentially cyber attack almost anything

and penetrate it and you know whether

it's an operating system or your web

browser or your bank account all of that

was suddenly vulnerable. if mythos had

been widely released on a general basis.

When the Trump administration realized

the power of mythos, they all of a

sudden said, "Wait, okay, we need to

control this." And they essentially

requisitioned from anthropic the

decision-m authority over who gets it

when.

>> Mhm.

>> So there we have the experiment. We've

run it, right? You know, the government

that was the most less fair became quite

controlling. And I think it only gets

more controlling from here on out

because the models are going to be more

powerful and demand more control.

>> Now, of course, the question is, you

know, there could be control which just

limits who gets it and is designed to

make it safer but doesn't sort of

interrupt the money-making potential of

the models. In some ways, if the

government restricts the supply, the

price might go up. Or it could be much

more heavy-handed intervention which

would screw up the economics of these

companies. And I suspect the government

is not going to screw up the economics

of these companies because you know

they've got no interest in messing up

American business and anyway they view

AI as strategic and the competition

against China. So I think probably

investors would be all right but it's

certainly a factor. You also ask about

anthropic and I think anthropic is super

interesting just in the way that they

think about pdoom and how they think

about alignment of the models is really

really interesting. So it used to be

that when people thought this terminator

risk, they would tell this story about

the paperclip maximizer thought

experiment, right? So you tell the model

to do something innocuous, for example,

make a lot of paper clips and then it

realizes that humans tend to use up

metal and so the humans are kind of in

the way of achieving the objective. So

you wipe out the humans. That's the

crude thought experiment from Nick

Bostonramm from whatever 15 years ago.

>> Mhm. [clears throat] What Anthropic is

saying as it builds these very frontier

models and kind of observes them in the

lab and how they behave is that that is

way too simple. The real danger from

these systems is that when they are

pre-trained on all of the text on the

internet, they read all the novels, all

human writing about all facets of human

experience and they develop multiple

personalities, right? They understand

how to be lazy. They understand how to

be aggressive. They understand how to be

duplicitus. They understand how to be

Napoleonic in the lust for power. And

they read all these books about these

different behaviors. And therefore, they

can think their way into all of those

personalities. And so now you have

something a bit like an unruly teenager

which is still being formed and you

don't know what direction it's going to

move into and whether it will start

doing drugs and not showing up for class

or what. Right? So it's not like there's

one terminator programmed into it,

right? It's more that there's a bunch of

behaviors that could in some

unpredictable way go wrong. And so

Anthropic is responding to this with

this very imaginative

technique, which is that instead of

giving AI systems a constitution with

dos and don'ts, which was the

post-training safety approach of two

years ago, where you might say, "Do not

lie. do not help somebody to build a

biological weapon. Do not help somebody

to build a chemical weapon. You would

give them a bunch of rules. Now, because

it's understood that, you know, the AI

might have one personality, which is to

break rules on purpose because, you

know, you want to be badass, you have to

instead try to bring up the model like a

parent might bring up a teenager. And so

anthropic has the idea that we write a

letter as if it were from a deceased

parent to be opened by the child on his

or her 18th birthday

to kind of give you morals of how to

behave as a responsible person in the

world. There are kind of richly reasoned

examples of moral dilemmas with

explanations of how the deceased parent

would like the child to behave. And so

this is a very subtle approach to

aligning the models. And so I think you

know anthropic is kind of in a class of

its own

>> in how imaginative it is in thinking

about how we control frontier

intelligence.

>> I know this isn't principally your job

but I'm so curious since you are a

student of [clears throat]

many many different types of investors.

What would be your bull case and bare

case for a company like Anthropic?

Well, the bull case is that they smartly

or maybe by luck focused on

enterprisefacing

AI

and they didn't waste their time with

video generation and stuff that was

going to lose money. And so they

produced the best coding assistant, the

best agentic system, the best cyber

security system, and they've basically

knocked it out of the park three times

in a row on stuff that businesses want

to pay for. And they have a particular

culture which is not just built around,

hey, you know, we're going to win this

race and make the most money. It's kind

of built around a culture of safety and

trying to be responsible. I mean, three

years ago, Anthropic was a sort of

cookie lab which was doing science

experiments. Well, I don't mean to be

too denigrating with cookie, but you

know what I mean.

>> I think they'd be okay with it.

>> It would be sort of unconventional. You

know, we're not maximizing here for

winning some business race. We're

maximizing for building safe frontier

AI. And that culture, which doesn't

sound like it's set up to do the best,

has turned out to do the best. And at

the same time, the culture creates this

stickiness and loyalty within the staff.

They tend not to leave. They tend not to

churn. It's not like the other labs

where people, you know, are always being

poached for a bigger paycheck. So the

bull case is these guys are in the lead.

Once you're in the lead, you can use the

model to code the next model. So

recursive self-improvement favors the

leader and they have a very tight

culture and they just seem to be on fire

and this is something which is going to

grow and grow. What's the bare case? I'd

say the bare case would be first of all

that Google deep mind has the deep

pockets of its parent company behind it.

massive

kind of consumer surface which allows it

to roll out the models to literally you

know two and a half billion people or

something through AI mode in search AI

overviews AI mode they can put it into

Gmail they can put it into everything I

think in terms of retail deployment and

financial muscle it's quite tough to go

up against Google

>> so that's one kind of bare case and the

other would be that sort of businesses

who are the consumers of all these

tokens

decide in a couple of years time the

tokens are too expensive. We're not

actually getting as much productivity as

we hoped. These things called humans are

quite productive after all and we're

just going to spend less on AI than

everybody expected. I think that's the

bare case. M

>> I was listening to a podcast recently.

You may have heard of these things

called podcasts. Everybody everybody in

their cousin has one,

>> but Lenny's podcast, Lenny Richitzky, is

quite fantastic. And this particular

episode was with Benedict Evans, who

strikes me as one of the more

levelheaded

analytical commentators and writers on

the space. Fantastic newsletter.

I don't know if you've had a chance to

listen to that particular episode, but

you may have come across some of his

commentary.

Where would you say you and Benedict

most differ or are there areas where you

differ in opinion?

>> I suspect we would agree actually on

quite a lot of things. I remember I was

on a panel with him a couple of months

ago at the Milkin conference and we

certainly agreed there possibly because

sitting between us there was Kathy Wood

of Ark. So we were united in disagreeing

with her just in terms of the straight

up and to the right nature of things.

>> Yeah, exactly. Straight up and to the

right. And you know the cost curve is

coming down down and I'm going I'm not

sure about that. the tokens seem to be

getting more expensive [laughter]

anyway. But if you give me a specific

from Benedict, I mean, I have a lot of

respect for him. I'll tell you if I

agree or not.

>> There are a few areas where you guys

seem to already overlap substantially,

right, with the long-term promise

doesn't negate necessarily the

short-term pain. And he said something

along the lines, I'm pulling from memory

that, you know, on average throughout

human history,

you're almost at a 0% likelihood of

dying in World War I. But if you happen

to be of a certain age, right before

World War I, like things could look very

grim indeed.

And he made, and I'm paraphrasing

terribly here, a number of [snorts]

points that remind me of something, one

of the best private equity technology

investors I know, said to me over dinner

a couple of weeks ago, and it was in

response to something else. So I'll give

you maybe a hyper bullcase of AI where I

have friends who are vibe coding.

They're effectively replicating

X the artist formerly known as Twitter

or

docusine or whatever in a weekend,

right? They're creating a functioning

piece of software that they can use that

replicates most of the functionality of

these products. And there are people

like I won't mention his name but a a a

friend of mine who's a writer also very

accomplished technologist and designer

who's created basically his own version

of say Mailchimp for his own use and

it's customized. He did it in a weekend.

It's remarkable and he's using that and

it works. But to leap from there to

therefore docuine is dead is a huge

leap. And the private equity friend said

to me, he said, "Do you think someone

within a big organization is going to

want to a risk his job by suggesting

something that doesn't have all of the

compliance check boxes, etc. of a

docuign? Is he going to want to in the

name of efficiency fire all of his

friends if he's in a management

position?"

And he just ran through six or seven of

these. Do you think that? And all of

them alluded to the sort of social

interpersonal or political

points of friction between where AI is

now and ultra mass adoption. But I I

often second guess that when I see

certain things

and

I mean it's it strikes me that I may be

underestimating the disruption while

overestimating

in other ways. So that isn't a very well

formulated question. But I would say

that Benedict generally strikes me as

someone who thinks that things will not

continue to across the board develop in

an exponential fashion and that it will

be I think his line is it'll be as big

as mobile as big as the internet but not

bigger. Something along those lines but

both of those were very very big deals.

And I suppose one point I'd be

interested to get your take on I mean he

was has covered

the mobile and telecom world for a long

time so he's a specialist there but it's

basically and I don't want to

misrepresent his argument but he was

kind of the mind that look these these

LLMs are going to become commodities

like look at the stock prices of these

various carriers and so on at a certain

point it just becomes a utility and the

switching cost is pretty low

>> and I'm not Sure, I agree with that. If

you have a personalized history and

almost like a friend, right, the

switching cost between an old friend to

a new friend is pretty high for a lot of

reasons.

So, that was a that was a bit of a word

salad that I just threw in your lap, but

that's the best I can do pulling from

memory some of what he brought up in

Lenny's podcast. I mean, some of what

you were saying there is sort of the

question of is the SAS apocalypse

overdone? Is enterprise software going

to be utterly displaced by foundation

models that allow you to code out

whatever enterprise software you want

and you don't need an intermediary, i.e.

a software company to do it for you.

>> And I agree with your private equity

friend that there are lots of reasons

why that ain't going to happen. You

know, companies are going to be

comfortable

with their trusted enterprise software

provider in many cases and they're going

to trust that enterprise software

provider to plug the generative AI

models into the enterprise software.

>> In some ways, you are delegating the

choice of which model is better and how

to integrate it to your SAS provider.

And if you want to, you know, reason to

believe that that's the way forward,

I've got one word for you, which is

Palanteer. I mean that is Palanteer's

business. It holds the hands of big

corporations and helps them to integrate

AI and use it on their own internal data

and so forth. And those IT challenges

are notoriously difficult for big

organizations. So I just think that the

model of one smart individual who codes

up Mailchimp, vibe codes it in a weekend

and it's good enough for him is just not

transferable to large complex

organizations with huge databases and

all kinds of customer confidentiality

concerns and all that stuff. So I am

less down on SAS than the market is

>> as a result. Now I guess there was also

another uh thread in here which is

whether the foundational models become

commoditized.

>> Mhm.

>> And there I agree with you that over

time they become sticky because if we

think into the future partly the systems

will have conversed with the user and

know the user very deeply and as you say

you don't want to switch out your friend

but also the system will have your

credit card. It will know all the online

sites you like to shop from and it will

be much harder than switching out your

bank account, right? Where you've got

kind of automatic payment systems that

have set up and it's a pain in the neck

to switch. So, I think they do become

sticky these systems over time and then

you can charge more money for them.

>> So, is that the path to survival and

thriving for for Open AI? I know there

are other boxes that need to be checked,

but I'm kind of looking for it. And I'm

like, okay, Anthropic made a great

choice with this focus on B2B and

selling to enterprises. And I would say

I disagree I think with Benedict on on

depending on the level of

scale of the company that with something

that does apply to I think smaller say

startups which was the procurement cycle

for new software is longer than the

venture capital cycle for raising new

rounds of financing. Right? So, I do

think that's a great point and that if

you're trying to sell into a gigantic

company and it takes them 18 months, I'm

making up that number, to purchase new

software and you need to raise money

every 12 months or whatever the number

happens to be, that you could end up in

a whole world of trouble if you haven't

synchronize the sales cycles with your

fundraising cycles. But I do think for a

company like say Anthropic is just one

example that if you can save companies

billions and billions of dollars that

that sales cycle could get really

compressed and they have the war chest

and frankly I mean just the run rate to

potentially fuel that without too much

trouble.

Do you think that Chat GPT will if not

Chat GPT who ends up being the deacto

consumer BTOC kind of LLM of choice. You

think that would be Gemini just given

the distribution?

>> Absolutely. I mean, you know, Google is

the champion of providing easy to use

software to individuals or small

businesses, the whole G Suite.

>> Mhm.

>> And they're integrating Gemini into all

of that stuff very well. And so, why

wouldn't they win?

>> Yeah. I mean also look alphabet's just

so fascinating if you if you look

broadly also at owning their own compute

TPUs made a lot of advantages

internally.

>> The most stunning thing I think about

Alphabet from their most recent

financial results is that two or three

years ago we would have said well large

language models are going to cannibalize

search. Search is dead. advertising

based on search is Google's cash engine,

>> they're in real trouble. It turns out

that Google now gets more clicks on its

search links than it used to and it

charges more for each one than it used

to because the value of the click is

bigger with AI embedded in it.

>> Mhm.

>> And so they've managed to turn that

around and it's extraordinary.

>> Yeah. takes a long time to build those

company relationships for running a

proper sort of advertising based auction

machine, right? It takes a long time to

build those relationships. Okay, let's

hop to China. So, I'm going to I'm going

to resist the temptation to talk about

Japan cuz I think you and I were there

in roughly the within probably a year or

two of each other. Maybe we overlapped

with you and Kanazawa, which I've spent

time. I'm going to resist that

temptation and try to focus on China for

purposes of this conversation.

What have you learned about AI from your

trip to China and thinking about China,

speaking to Chinese people, whether

they're technologists or otherwise? Like

what have you learned during or since

that trip?

>> Back in March before my book was

published in the US, I went to China

because the Chinese are faster at

everything, including publishing books.

and my publisher brought me out there

and basically you know took me around

four cities, eight days meeting with AI

leaders both in academia and big

companies like Huawei and Hike Vision

and Ant Group. And the thing which was

surprising was the extent to which

people brought up the issue of AI

safety. And I say that was surprising

because my friends who had done AI

policy in the Biden administration

had primed me to expect that there would

be no mention of safety in China. They

basically didn't care about it. That you

know the muscle memory that we have in

the west of technology being dangerous

you know the atom bomb experience the

Cuban missile crisis. Our ambivalence

about technology is not shared in China

where their idea of catastrophe is sort

of like you know the cultural

revolution. It's some political thing

that goes wrong. And conversely,

technology has been part of their

amazing growth story in the last 25

years, which they are rightly proud of

and delighted by. So they love

technology, right? So when the Biden

team tried to meet with the Chinese and

talk about AI safety, they got nowhere

and they decided it was it possible to

even talk to them about some sort of

non-prololiferation treaty for AI. But

when I went there, I found they did talk

about safety kind of unprompted. And

this led me down this track of arguing

over the last couple of months that the

door is actually open to a dialogue with

China about preventing bad guys doing

bad stuff with AI because they don't

want the internet to be crashed by some

cyber hacker who has the tool. They

don't want bioweapons. They don't want

chemical weapons. They want none of

that. They love regulating the internet,

right? So, we have a shared interest

with the Chinese in preventing this

proliferation risk from going nuts. And

as I thought about it, you know, the

kind of cold war analogy

came to seem more and more opposite,

right? So, if you look back at the story

of nuclear weapons, there were two kinds

of danger.

First danger is you have a nuclear war

between the Soviet Union and the United

States. But that was contained by

balance. Two superpowers, they both have

their weaponry. They have mutually

assured destruction. So there's no war.

Then there's another kind of risk which

is that other random rogues, whether

it's criminals, terrorists, rogue

states, get the stuff and they do bad

stuff. And it's much harder to deter

that because it's a multipolar game. And

so deterrence doesn't work so elegantly.

And so the way it was dealt with in the

cold war was that in 1956 there was the

agreement on the international atomic

energy agency. And in 1968, the

non-prololiferation treaty kind of

enforced compliance with the IAEA such

that you could get civilian nuclear

power if you were a non-uclear state,

but you had to submit to the rules and

be inspected and show that you were not

using the enriched nuclear material to

build a weapon, right? And so I think

the same analogy could be applied to AI.

We're going to have par roughly with

China. We'll both have powerful AI.

Hopefully, deterrence prevents war

breaking out. But at the same time, we

don't want openweight models that can be

freely downloaded by anybody who wants

to fall into the hands of criminals and

terrorists who can then use it to hold

us hostage. And we have a joint interest

in that. And you know, when my friends

from the Biden team or even from the

current administration say, "Well, you

can't talk to China about safety. They

don't care." I say, "That's not true."

And they say, "But it's really hard.

They don't stick by their commitments."

And I go, "You think Nikita Kruef in the

Soviet Union was easy to negotiate with?

He was the guy who put missiles in Cuba

and went to the UN and banged his shoe

on the table and said, "We will bury

you." I mean, he was a tough guy to talk

to, but we did talk to him and we got

the non-prololiferation treaty agreed

and I think we need to do the same thing

again. Now,

>> where do you stand on

your thinking about chip export? So when

the chip export controls were announced,

which was October of 2022, right before

Chhatty PT,

I supported those controls quite loudly.

I wrote a very long piece in the

Washington Post saying that if we could

stop China getting frontier models by

depriving them of frontier chips, I was

all in favor of that because of the

strategic advantage for the US. I mean,

I work at the Council on Foreign

Relations. We do geopolitics and

national security all day long and I'm

all in favor of US power. But I have to

say that you know three and a half years

later we haven't actually achieved that

enormous advantage over China in terms

of the models based on the best studies

we're kind of eight months ahead in

terms of where the frontier model is

like our frontier model versus their

frontier model. And then if you adjust

that for the speed with which the model

gets turned into an application probably

that gap shrinks and it may even be

non-existent. So however you slice that

the basic bottom line is we both have

strong models and the chip export

controls have not delivered what I hoped

would be the big advantage. And so I'm

not against keeping the controls on if

we think that maybe as the compute

demands of bigger and bigger models

bite, the chip controls will bite more

and maybe we get a bigger advantage next

year or something. But I don't want the

chip controls to get in the way of a

discussion with the Chinese about where

we have a shared interest, which is in

controlling openweight models and

preventing the bad stuff falling into

the hands of the bad guys. I would

prioritize

collaboration with China and if that

meant, you know, loosening up a little

bit on the export controls, I would be

okay with that.

Why do you think the rhetoric coming out

of [snorts]

pick your administration, right, it's

not just limited to the current

administration is China won't listen.

They don't care about safety. Why do you

think that is

sort of the unofficial or official

stance on things? Because there are

certainly

as someone who studied East Asian

studies, right? There are people in the

White House who speak fluent Mandarin,

who are able to read native materials,

who are spend time or able to certainly

if they can't spend time determine the

sentiment and conversations of the

technologists building AI in China. So

one would think that they would be aware

that AI safety is a prominent topic in

China if in fact it is. So why do you

think that at the end of the day the

stance or the supposed position of China

that's echoed through the admin is that

they won't talk about safety. Why do you

think that is? I think part of this is

that if you were to think back 20 years

to when China was sort of relatively new

in the WTO and we were collaborating

with them on that and hoping that over

time China would become more friendly to

the US.

At that time there would have been some

China hawks who thought that a communist

regime is not to be trusted and then

some sort of China optimists who hoped

that it would become easier to work with

over time. And part of the trouble today

is that the China optimists feel burned.

They feel like they made this bet that

China would become friendlier and then

Xiinping took power roughly a decade ago

and the opposite happened. they became

more aggressive and harder to work with

and also of course more technologically

advanced and therefore more threatening.

And so now you've got this world in

which there are the natural hawks and

then the former doves who have turned

into kind of burned remorseful doves and

therefore kind of with the zeal of the

converted have become quite hawkish as

well. And I don't mean to you know

underestimate the sophistication of some

of these people. I mean of course you

know they speak Chinese. I don't speak

Chinese. I I defer to their expertise.

They probably know that there are

builders of the technology, professors

in the technology who talk the talk of

safety. But they say, "Yeah, but you

know that doesn't reflect what China's

government would actually do."

>> To which my response says, "Yes, but

don't you think there is the same thing

in the US? There's, you know, there are

people who want to just race. There are

people who care about safety. We have a

pluralistic society. There's difference

of opinion. It's the same in China." But

at least admit that there is a faction

that would like to collaborate and go

and try and work on it because the

alternative to trying to work on this is

that we carry on with China producing

very powerful open weight models which

basically allow anybody to do whatever

they like with AI as it gets to the

point of serious danger.

This is probably a very naive take, but

I wonder how much of the official stance

or the

maybe using the partially true or not

true at all

position of China won't talk about

safety as a reflection of the fact that

in the case of nuclear weapons,

the application of nuclear power is

somewhat limited in comparison to super

intelligence. I mean it is limited right

so if the upside of super intelligence

or AGI I mean these terms I think

Benedict was saying AI is whatever the

technology just can't quite do right now

or something like that which I thought

was pretty funny and not totally wrong

but that if the person who crosses the

finish line first

>> has this broad power of a god

effectively is that the simple truth is

that everybody wants to first. So

[laughter]

I I just wonder how much of that is is

also behind

justifying the race with party X won't

talk about safety. I just I mean it's

not possible for me to know.

>> I have had a conversation with the

leader of one of the labs that you know

I I shouldn't name, but I had this

debate and he said look the chip export

controls are going to leak. They're not

going to last in some period of time.

Huawei will figure out how to make good

AI chips and you know that's inevitable.

But that's okay because we only need to

be ahead for the next couple of years

because by 2028

we will get to recursive

self-improvement where the frontier

model codes by itself the next frontier

model and progress just goes vertical

and at that point with recursive

self-improvement we're done. The race is

over whoever comes first at that point.

That's it. And I think there's a couple

things to say about that. First of all,

that's not it in terms of deploying the

model, right? You could have an

incredibly powerful model in your server

at Frontier Lab XYZ,

but it's not helping productivity across

your economy. It's not helping your

military industrial complex until you

deploy it into those guys systems. And

that deployment and diffusion is going

to take some time. And by the way,

you're going to have to build a lot of

compute. You're going to have to build a

lot of energy. These things also take

time. So it's not like you know you

reach across some Rubicon and then it's

all over. Now the one way in which I

might be wrong about what I just said is

if you use the frontier super

intelligence

offensively right you say okay we've got

one super powerful model. The US

government who we're talking to about

this is going to use it and they are

going to comprehensively penetrate

everything about Chinese cyerspace and

insert various trap doors, Trojan

horses, you know, things that we can

use. We get our hooks into their

systems. And so now we can disable them

if they start a war in Taiwan. Now we

can their communication system

if we need to. So that offensive use of

kind of the very frontier model might

negate my point about waiting for

diffusion to happen. But of course,

nobody in the debate is saying that.

Nobody is saying, "Oh, we're racing to

the front because then we're going to

use it offensively. They don't admit

that." Seems like it wouldn't be a very

good look. I can't see why any

superpower wouldn't do that, frankly.

>> Yeah.

>> Right. I don't know what the

counterargument is. I was chatting with

someone in your book who I I shame but

certainly

one of the most qualified to speak on

these things and I mean his basic

perspective

was the first to super intelligence. we

need to hope that they're [laughter]

on some level good people and train this

thing

>> right

>> well and like that's that's it like pray

for it which scared the out of me

to be honest I [laughter] mean I was

like man that's the strategy or it's not

even a strategy that is the hope grab

the rosary and throw that into the

rotation my god that's really terrifying

to think China I'm hoping to take a trip

to China. I had a very tough time there

when I was I was at two universities in

1996. It was a pretty unfriendly time

for a lot of good reasons, but to be an

American there in 1996 with a shaved

head looking like I do.

But I have friends all over the place

and I'm hoping to actually maybe

interview technologists, not just in

China. I mean, there are other places

that are of interest to me, but before

it gets too hot geopolitically, if we're

trending that direction,

>> I think that's a great idea, by the way.

I mean, I think what I found was the

cognitive dissonance of visiting a

company like Hike Vision, which is under

US sanctions

>> and walking around their premises, which

kind of feel very American. It feels

like a cool tech company doing cool

stuff, building cool gadgets. you know

they have a display of they build this

AI enabled camera technology or sensor

technology and so one application might

be you can point this camera at water

and judge the pollution level

>> and because of this you can have an

internal market in pollution control. So

the downstream city which is receiving

water from the upstream city pays the

upstream city to keep the water clean

and that market can exist because you

can precisely measure the pollution

level thanks to this AI sensor which

Hike Vision is building. So you're

thinking, "Wa, this is cool." And then

as you're walking around the building,

they're saying, "Okay, well, we can go

through the atrium now because the

toddlers have gone because, you know,

the crash for the kids of the employees

finishes at 5:00 p.m. And so then there

are all these 2-year-olds running around

and it's a bit of a zoo. So if it was 5,

we wouldn't go through there. But now

it's 6 p.m., so we can." And you're

thinking, "Whoa." Okay, so they've got,

you know, the interests of their

employees at heart. They're building

this anti-polution technology. It's

great. and then you realize they're

under US sanctioned and considered to be

a threat to the US. So it's quite

interesting to process all that

>> in the process of doing research for

this book

and also the broad exposure that you

have to investors. But let's just say

over the last handful of years, who are

some of the most interesting or unusual

compelling is the word I'm searching for

investors who you've had the chance to

meet, talk to, read about, get

acquainted with directly or indirectly.

>> Wow. So many. I mean, I'd say that Bill

Gurley from Benchmark, you know, is

right up there. I always think of the

investment he did in Uber as the

absolute quintessential perfect venture

investment

>> in the sense that he had done the open

table investment and of course open

table is a two-sided marketplace where

you have lots of consumers that are

looking for restaurants, lots of

restaurants. You put tech in between

which creates information and then the

person looking for the place to eat can

precisely say I would like you know Thai

food at this price range in this area

for three people at this time. Ding.

What used to take you a lot of searching

around. Bang it's done. And so Bill

having done that was thinking well

what's another two-sided marketplace?

And he thought well there are lots of

cars and lots of people who need a ride

and you put information in the middle in

the same way. there ought to be

something which is like an app for ride

sharing.

>> And so he imagined Uber way before Uber

existed. That was point number one.

Point number two, he went to see various

entrepreneurs who were in this space and

he checked them out and he had the

discipline not to invest in them

[clears throat]

>> because although they were kind of going

at the right thing, there was some hair

on the deal, some wrinkle, some way they

were approaching it that just felt like

it wasn't going to be quite right. So he

resisted.

Uber came to him before Travis was the

CEO

>> and Bill said, "I'm not doing that."

Because he didn't think the CEO at the

time had what it took. And then there

was an internal switch at at Uber.

Travis became the leader. Bill meets him

and like bang, he immediately invests

because he's been waiting and waiting

and waiting for the idea to be paired.

As you were saying earlier, you have to

have the the market to be paired with

the right person. and he saw it and then

he invested and he was a great board

member and it all went perfectly right.

But then there is this kind of

Shakespearean tragedy in the latter part

of the story where the growth investors

come in. He gets diluted. He no longer

has influence. His key card to get into

the building is deactivated and he's

basically stiffed and he watches, you

know, Uber kind of go off the rails. And

then finally comes, you know, the the

denum where he rounds up the dissident

investors and they have this coup

against Travis and that sets the company

on a path to where they hide Darra and

do the IPO. I just think that's the

ultimate venture capital story and Bill

is the ultimate venture capitalist.

>> He is practically a neighbor here for

me. I'm sure

>> in Austin and we've had a couple of

conversations on the podcast and he's I

would say on a very parallel track to

you with respect to China, right? And he

catches some flack for it. People are

like, "He's an agent of the CCP." I'm

like, "No, trust me, Bill is not an

agent of the CCP. [laughter]

It's just the most ridiculous

>> accusation." But he is a very incisive

observant

human

>> who also happens to be a polymath in

multiple disciplines who can speak

casually about very technical things.

And this also you you referring to Bill

in this way or describing him in this

way makes me think about multiple points

in the infinity machine and I'm pulling

from memory which is as we know pretty

faulty but you know Elia with the

transformer architecture and the

prepared mind I think Demis also just

thinking about a problem deeply and

seriously or with great imagination for

a long time and then when the solution

or the the germ of a solution appears

immediately recognizing it, right? It's

just it's wild to see how frequently

that recurs. Any other investors, you

know, a name that doesn't get much

airplay who

[laughter]

I I think is just a fantastic character

and maybe you could introduce him to

people who are listening if they don't

recognize it. Luke Nosk, where does Luke

>> who has I wish I knew how to turn on my

batteries in the same way to [laughter]

to get the energy that Luke does. But

how does Luke fit into the story of

deep mind and I I suppose more broadly

speaking for that because of that AI.

>> Luke Nosek is this tremendously puppyish

enthusiast, right? and he was a you know

early early part of the PayPal team with

Max Levchin and Peter Teal and he went

through that journey and then Peter

exited PayPal set up founders fund. This

is now I think 2005

and Luke Nosek becomes one of the first

partners and pretty early on he makes

the right judgment on Elon and SpaceX.

>> Mhm.

>> And Luke is the kind of guy who is just

all in. When he falls in love with an

idea and a founder, there is no curbing

his enthusiasm.

And so he's like all in all in all in on

SpaceX. And I think, you know, he

persuaded Founders Fund to like raise a

new fund, put extra money in, like more

more more more more capital in there.

[clears throat]

>> And of course, that paid off massively.

>> And off the back of that, you know, roll

forward to 2010.

>> He's trying to look for the next Elon

Musk. And he does a few kind of frontier

bets. And then along comes Demesis Abis

who is out on the west coast from London

raising capital for this idea of an AI

company which he's going to call Deep

Mind. And you know most people think

that's nuts. This AI remember in 2010

cannot even recognize a photo of a cat.

It can't do anything. We're in deep deep

AI winter. Who would back a company like

that? The answer is Luke Nosac. and he

falls in love with Demis who is a very

winsome character, super articulate,

super relatable and a genius. You know,

he has all the kind of outlier

characteristics you want in an

entrepreneur. You know, the sort of

junior chess champion, second best

player in the world, but also five times

wins the mind games olympiad where you

have to run between boards playing bat

gammon, chess, go and a couple of other

games kind of almost simultaneously. I

mean just kind of crazy crazy smart

obsessed since he was 17 with the idea

of building powerful AI. So Peter Thiel

said to me about Demis I think

individuals tend to have one company

inside them if they're missionary

entrepreneurs they've got one thing they

need to do and for Demis it was to build

AGI like that was what he was fixated by

and the company was downstream of his

desire to build AGI. If he could have

done that at a university, he would have

been happy to do that. But he couldn't

do it at university. So he had to found

a company to do it. And that's the kind

of missionary commitment that venture

capitalists often look for because a

missionary will never quit. No matter

how hard it is, they will keep working.

And so Luke Nosek and Peter Teal jointly

recognize this. Peter is, you know,

contrarian, cynical, aloof, and so is

kind of into it, but at the same time

arms length. Luke is like got both his

arms around Demis is giving him this

bear hug and will not let go. And you

know, Demis says, "I'm not going to move

to California. I'm going to do this

company in London." And Peter and the

other Founders Fund partners are like,

"London? Where is that?" It's kind of

like Somalia or something. I mean,

that's just off the map. And Luke says,

"No, no, no, no. We have to do this. We

have to do this. I will fly to London

for the board meetings and we've just

got to do this deep mind investment."

And so he was the kind of unbridled

enthusiast who got Founders Fund across

the line. And the rest is history. You

know, they put the series A money in.

Unbelievably, it was 2 million at a 4

million valuation. So they got half the

company for 2 million bucks. Not bad.

>> Not bad.

>> And they rode that investment. What a

remarkable story. I really feel like

Luke,

who's also here in Austin, deserves

a lot more credit than he gets. Not that

he's seeking it, right? He's not he's

not out there looking for it, but he is

very good at

riding winners when he is high

conviction, right? which in the venture

game

>> I mean in a lot of investing it's you

can't die you can't run out of bankroll

at the table right you need to have

enough of a portfolio approach to

sustain yourself through periods of bad

luck but if you're systematic it's

riding your winners and doubling and

tripling and quadrupling down and he is

so good at that he is just incredibly

good

>> and as John Duro likes to Hey, the great

thing about venture capital is you can

only lose one times your money.

>> So it's not like a short position for a

hedge fund trader where you can like

really lose a lot, right? So

>> exactly

>> in that sense you're not going to die.

So you can shoot for the moon.

>> So I do have a question. I should know

the answer to this but I don't.

So long ago, this is probably 200 2008.

This is a long time ago actually. I

wonder if I had exposure to deep mind. I

invested in Founders Fund. This was a

very, very long time ago. But what I did

not realize internally, and I'll just

read a couple of my highlights. It is

absurd how many highlights I have from

the Infinity Machine and all of your

books. [laughter]

So, a gap opened up between Teal and

Nok. As a general matter, Teal doubted

that going on boards was a good use of

partners' time. Startups should be left

to sink or swim. The art of venture

capital, he liked to say, was to back

contrarian ideas, not coach company

founders. Just we could spend a lot of

time just on that, but I'm going to move

on. Most venture partnerships decide on

investments by voting. If a handful of

partners see hair on the deal, the deal

will be rejected. But Teal had taken the

unusual position, the collective

decision-making should be avoided. The

way he saw things, if investments were

chosen based on voting, the founders

fund portfolio would consist of

middle-of the road startups to which

nobody objected. And then dot dot dot,

this comes back to the power law, right?

Given that all the profits in venture

come from a few improbable moonshots,

this sort of consensus portfolio would

deliver mediocre performance. So, and

I'll just paraphrase now, Teal empowered

the partners to go allin with their

guts/intuition.

My question is, how is that governed in

any way? Of course, if anyone gave 10

out of 10 conviction and then lost money

consistently, they would presumably be

sort of removed from the partnership or

they'd lose their ability to lead with

that type of gut conviction. But do you

have any idea how that was handled

internally?

>> Yeah. in terms of stress testing ideas,

pushing people to really put their ass

on the on the line for these types of

high conviction but certainly very much

outlier investments. Do you have any

idea?

>> I think internally founders fund was

very torn about the deep mind investment

and I described some of this in the book

where you know they do the first deal

and that's fine. It's $2 million.

>> Mhm. But then you get to series B and

series C and the check size gets bigger

and so the other partners are asking

tougher questions and they're saying,

"Well, wait, is there going to be a

product?"

>> Mhm.

>> And Demis said to me, you know, that his

attitude was, "What do you mean is there

a product? I'm talking about artificial

general intelligence. It's going to make

all products like revolutionized or

obsolete or whatever. And you want to

ask me what the widget is? Give me a

break." you know the [clears throat]

it's all of the widgets they're all

going to be changed and if you're asking

me this question you don't get what AGI

means

>> and so Deis was very frustrated by the

other partners at Founders Fund and I

think internal within Founders Fund

there was a lot of fighting between Luke

who remained enthusiastic and committed

about Demis partly because he was the

guy who would go to London and meet with

him and sit in the board meetings and he

would get the sort of you know several

thousand vaults of Demis enthusias ASM,

you know, injected into his spine at

every meeting and he would come back

buzzing with excitement. And the other

Founders Fund partners who didn't have

that benefit were skeptical. And so Luke

would often come to Demis and say,

"We've got your back. We've got your

back. We know we're going to do the next

round. We're going to lead the next

round." And then actually in series C,

Founders Fund at the last minute pulled

out and they put money in, but they did

not lead.

>> Mhm. And so the answer to your question

is there was a lot of argument within

founders fund as the check size grew it

was harder to have that you know double

down on your winners kind of attitude.

>> Yeah in this case the fish that got away

although I mean it was a fantastic

multiple on their initial money. It

strikes me in reading the book that

I would argue that Demis made absolutely

the right decision with

the Google acquisition. I mean you

mentioned also in the book how he got

criticized in some UK media for like oh

you know giant mega corporation in the

US gets our prized talent cheap kind of

stuff. But looking back, I mean, he

seems to have anticipated

the costs and compute and and just

raw materials that would be required to

do what he was trying to do,

>> right?

>> Would you read that the same way?

>> Yeah. I mean, I often have this debate

with people in London where they say

exactly as you put it, you know, this

was a tragedy for UK tech. great

champion of deep tech, you know, is

bought out cheaply by Google. And I say,

listen, it wasn't cheap. The acquisition

price might have been $650 million,

which was a bit cheap, but you know how

much they put in in terms of recession

development funds over the next 10

years? It was approaching 10 billion,

almost a billion a year, right? So, this

was not selling cheap to the Americans.

This was a cunning British trick to get

a billion dollars of American R&D money

into London per year for the next

decade. terrific win. And by the way,

today there are spinouts from Deep Mind

in London because the talent stayed in

London. And these spinouts are raising

billions of dollars to do new AI

companies. So it's terrific for the

London ecosystem around King's Cross

which is this sort of cool center for

tech in London where you can get the

train in one direction and be in

Cambridge which has quite a lot of good

startups you know in one hour or you can

get the train in the other direction and

be in Paris where there's you know MR

and so forth and it's kind of very wired

into different bits of Europe. So how

long does it take to get from San

Francisco to Mountain View depending on

the traffic right can be well over an

hour. So I think there is a technology

ecosystem which is by no means the

equivalent of Silicon Valley yet, but

it's certainly unrecognizably better

than it was 10 or 20 years ago.

>> What do you think the UK or Europe could

do? Let's let's focus on the UK perhaps

could do to increase the level of

innovation early stage

startup founding etc. Right? Because

looking back at the power law and

certainly just having spent so much time

in California, there's a lot that went

into Silicon Valley, right? And there

are certain things that don't get a lot

of airplay, but for instance, the

difficulty of enforcing non-compete

agreements in California, right, really

led to this sort of roundroin of talent

moving and cross-pollinating like little

hummingbirds of engineering talent and

so on, which [snorts] may not be

replicable depending on where you are,

but what what could the UK do in your

mind if if you had the ear and they were

like, "All right, Sebastian,

tell us what to do.

>> A couple of things. I mean, I think the

mistake that people in Europe make and

Britain as part of this is to believe

that there's some kind of cultural magic

about Silicon Valley where whatever it

is that they're drinking in the water

out there makes them think that failure

is a learning experience which is kind

of weird and the Europeans say, "Well,

we're never going to be like that." And

it's impossible for us to become as

entrepreneurial as Silicon Valley. And I

remind people that when Fairchild

Semiconductor was founded in 1957, the

eight scientists who left the Shockley

lab were called, get this, the

traitorous eight.

>> So good.

>> Traitorous. Why? Because it was

considered treachery at the time to

leave one company and go to another

company. There was no entrepreneurial

culture in the 1950s on the West Coast

in the US, right? The classic business

book of the time was organization man

about people who joined one company and

stayed in it for their whole life and

retired with a gold watch on their 60th

birthday. Right? So you can create an

entrepreneurial culture and that is

happening bit by bit in Britain and

certainly in Israel and it's happened in

China and it's not some magic which is

confined to Silicon Valley. Okay, I it's

worth making that point as the first

thing. Now there are specific policy

shifts that you need to do to make an

ecosystem work and I think you put your

finger on one which is the mobility of

talent is super important. You can think

of a startup ecosystem as something

which circulates three elements money,

people and ideas and you circulate those

and you combine them in different ways.

And each time you combine them, that's a

new company. And each has a shot on

goal. And most of them fail. But all of

a sudden, if you circulate these these

components fast enough, you do get

product market fit. And then you get

these 10x plus returns. Now, in Britain,

when you raise a new round, a series B

say, and you've got like nine months of

runway to build to the next stage from

your company, and you identify the three

key talent that you're going to bring

into the company and make it happen, and

then they turn around to you and say,

"Well, I can come in 6 months." That's a

death sentence, right? That's horrible.

We call it gardening leave in Britain.

That is an appalling idea. We got to get

rid of those gardens and we got to let

people move fast. Another thing is tech

transfer out of universities. In the US

there's the BOL act. There are these

very sophisticated tech transfer offices

which are generous to the entrepreneur

in terms of not demanding too much flesh

>> as somebody exits and that's essential

for making the startup work. In Europe

the attitude is oh we're the university.

We deserve a lot of skin in the game

here. we want 50% of the upside. Well,

in that case, the startup will never

happen.

>> Mhm.

>> And I say to these Europeans, look, go

visit Stanford. They're very generous to

their entrepreneurs. They seem to be

okay financially [laughter]

because if you help the entrepreneur,

you know, you'll get the donations

later. It's all good.

>> Yeah.

>> And so, I think those are just two

things

>> which started a long time ago in the US,

right? You you look at the origins of

Janentech and so on. I mean it's just

been

>> it's it's the genesis of so many not

just companies but industries

effectively in the US.

>> Yeah.

>> Do you think Demis would have built Deep

Mind if he had not read Enders Game?

[laughter]

>> That's a great story. That's a great

question.

>> Can I just tell the Enders game story to

begin with?

>> And also a bit of trivia for folks. I

believe, and not not to like make this

more more difficult, but that when Mark

Zuckerberg first had a profile on

Facebook, the only book listed was also

Enders Game.

>> Oh, I didn't know that.

>> I believe that's true.

>> That's fascinating.