Sam Altman on Sora, Energy, and Building an AI Empire

sort of thought we had like stumbled on

this one giant secret that we had these

scaling loss for language models and

that felt like such an incredible

triumph. I was like we're probably never

going to get that lucky again. And deep

learning has been this miracle that

keeps on giving and we have kept finding

breakthrough after breakthrough. Again,

when we got the the reasoning model

breakthrough, like I I also thought that

was like we're never going to get

another one like that. And it just seems

so improbable that this one technology

works so well. But maybe this is always

what it feels like when you discover

like one of the big, you know,

scientific breakthroughs is it if if

it's like really big, it's pretty

fundamental and it just it keeps

working.

Sam, welcome to the Z podcast.

>> Thanks for having me.

>> All right. You've uh described in

another interview, you described OpenAI

as a combination of four companies. uh

consumer technology business, a mega

scale infrastructure operation, a

research lab and all the new stuff

including planned hardware devices from

hardware to app integrations to Java

marketplace to commerce. What do all

these bets add up to with OpenAI's

vision?

>> Yeah, I mean maybe you should count just

three maybe as as four for kind of our

own version of the what traditionally

would have been the research lab at this

scale, but three core ones. Uh

we want to be people's personal AI

subscription. And I think most people

will have one. Some people will have

several. And you'll use it in some

first-party consumer stuff with us, but

you'll also log into a bunch of other

services and you'll just you'll use it

from dedicated devices at some point.

You'll have this AI that gets to know

you and be really useful to you and

you'll that's what we want to do. Um it

turns out that to support that we also

have to build out this massive amount of

infrastructure. But the goal there, the

the the mission is really like build

this AGI and make it very useful to

people. and and does the infrastructure

uh do you think it will end up you know

it's necessary for the main goal will it

also separately end up being a another

business or is it just really going to

be in service to the personal AI or

unknown

>> you mean like would we sell it to other

companies as infrastructure

>> yeah would you sell it to other

companies um yeah or or or you know it's

such a massive thing would it would it

do something else

>> it feels to me like there will emerge

some other thing to do like that but I

don't know we don't have a current it's

currently just meant to like support

>> the service we want to deliver and the

research

>> yeah know that makes sense

>> yeah the um scale is sort of like

>> ridiculous

>> terrifying enough that you got to be

open to doing something else

>> yeah if you're building the biggest data

center in the history of humankind

>> the biggest infrastructure project in

the history

>> the um there was a great interview you

did many years ago in Strictly VC and

and sort of early open AI well before

TGBT and and they're saying hey what's

they're asking what's the business model

and you said oh we'll ask AI it'll

figure it out for us everybody laughs

but there have been multiple times and

there was just another one recently

where we have asked a then current model

for you know what should we do and it

has had a insightful answer we missed so

>> I I think when we say stuff like that

people don't take us seriously or

literally

>> but maybe the answer is you should take

take us both

>> yeah yeah well know as as somebody who

runs an organization I ask the AI a lot

of questions about what I should do. It

comes up with some pretty interesting

answers.

>> Sometimes sometimes it does you know you

have to you have to give it enough

context. But

>> what is what is the thesis that that

connects these bets beyond more

distribution more compute? How do how do

we think about it?

>> I mean the research enables us to make

the great products and the

infrastructure enables us to do the

research. So it is kind of like a

vertical stack of things like you can

use chatbt or some other service to get

advice about what you should do running

an organization but for that to work it

requires great research and requires a

lot of infrastructure. So it is kind of

just this one this one thing. It's

>> and do you think that there will be a

point where that becomes completely

horizontal or will it stay vertically

integrated for the foreseeable future?

I was always against vertical

integration and I now think I was just

wrong about that.

>> Yeah. Interesting.

>> And there's kind of cuz you you like

you'd like to think that the economy is

efficient and the theory that companies

can do one thing and then

>> it's supposed to work.

>> Like to think that. Yeah.

>> And in our case at least it hasn't

really. I mean it hasn't some ways for

sure. or like there's people that make

like you know

>> Nvidia makes an amazing chip or whatever

that a lot of people can use but the

>> the story of open AI has certainly been

towards we have to do more things than

we thought to be able to deliver on the

mission

>> right you know although that you know

the the history of the computing

industry is kind of been a story of kind

of a back and forth and that you know

there was the Wang word processor and

then the personal computer and the the

Blackberry before the smartphone. Um, so

you know there has been this kind of

vertical integration and then not but

then the iPhone is also vertically

integrated.

>> The iPhone I think is the most

incredible product the tech industry has

ever produced and it is extraordinarily

vertically integrated.

>> Yeah, amazingly so. Yeah. Interesting.

>> Which bets would you say are enablers of

AGI versus which are sort of hedges

against uncertainty? I

>> think you could say that on the surface

Sora for example does not look like it's

AGI relevant. But

I would bet that if we can build really

great world models, that'll be much more

important to AGI than people think.

There were a lot of people who thought

CH chatbt was not a very AGI relevant

thing. And it's been very helpful to us,

not only in building better models and

understanding how society wants to use

this, but also in like bringing society

along to actually figure out, man, we

got to contend with this thing. Now we

for a long time before CHGBT, we would

talk about AGI and people like this is

not happening or we don't care.

then all of a sudden they really cared

and and I I think that so

research benefits aside.

I'm a big believer that society and

technology have to co-evolve. It's you

can't just drop the thing at the end. It

doesn't work that way. It is it is a

sort of ongoing back and forth. Yeah.

say more about how Sora fits into your

strategy because there some hull on on X

around hey um you know why devote

precious GPUs to to Sora but is it a

short-term long-term trade-off or are we

so aging

>> well and then the new one had like a

very interesting twist with the social

networking

be very interested in kind of how you're

thinking about that and like um did uh

Meta call you up and get mad or like hey

what what do you expect the reaction to

be? Um,

I think if one company of the two of us

has feels like more like the other one

has gone after them, it wouldn't they

shouldn't be calling us.

>> Well, I do know the history, too. But uh

look, we're not going to like

first of all, I think it's cool to make

great products and people love the new

Sora and and I also think it is

important to

give society a taste of what's coming on

this co-evolution point. So like very

soon the world is going to have to

contend with incredible video models

that can deep fake anyone or kind of

show anything you want. that will mostly

be great. There will be some adjustment

that society has to go through. And just

like with chat GPT, we were like the

world kind of needs to understand where

this is. I think it's very important the

world understands where video is going

very quickly cuz that's going to be

video has much more like emotional

resonance than text and very soon we're

going to be in a world where like this

is going to be everywhere. So I think

there's something there. uh as I

mentioned I think this will help our

research program and is on the AGI path

but

yeah some like you know it can't all be

about just making people like ruthlessly

efficient and the AI like solving all

our problems there's got to be like some

fun and joy and delight along the way

but we won't throw like tons of compute

at it or not by a fraction of our comput

it it's tons in the absolute sense but

not in the relative sense

>> I want to talk about the future of AI

human interfaces because back in August

you said the models have already

saturated the chat use case. So what are

future AI human interfaces look like

both in terms of hardware and software

is the vision for kind of a wechathat

like

>> so I'm solving the chat thing in like a

very narrow sense which is if you're

trying to like you know have the most

basic kind of chat style conversation

it's very good but what a chat interface

can do for you it's like nowhere near

saturated cuz you could ask a chat

interface like please cure cancer a

model certainly can't do that yet so I

think the text interface style can go

very far even if for the chitchat use

case the models are already very good.

Um, but but of course there's better

interfaces to have. Uh, actually it's

another thing I think is cool about

Sora. Like you can imagine a world where

the interface is just constantly

real-time rendered video.

>> Yeah.

>> And what that would enable and that's

pretty cool. You can imagine new kinds

of hardware devices that are sort of

always ambiently aware of what's going

on. in rather than your phone like blast

you with text message notifications at

whenever it wants like it really

understands your context and when to

show you what and

there's a long way to go on all that

stuff you know

within the next couple years what will

models be able to do that they're not

able to do today will be sort of white

color um you know replacement at a much

deeper level AI scientist uh human

humanoids um

>> I mean a a lot of things but you touched

on the one that I am most excited about

which is the the AI scientist.

>> Yeah,

>> this is crazy that we're sitting here

seriously talking about this. The I know

there's like a quibble on what the

Turing test literally is, but but the

popular conception of the Turing test

sort of went whooshing by.

>> Yeah, it was fast. Yeah.

>> You know, it was just like we talked

about it as this most important test of

AI for a long time. It seemed impossibly

far away. Then all of a sudden it was

passed. the world freaked out for like a

week, two weeks, and then it's like,

"All right, I guess computers like can

do that now." Yeah.

>> And everything just went on. And I think

that's happening again with science. Uh

my own personal like equivalent of the

touring test has always been when AI can

do science like that has always like

that is a real change to the world. And

for the first time with GPT5, we are

seeing these little little examples

where it's happening. You see these

things on Twitter. did this it made this

novel math discovery and did this small

thing in my you know my physics research

my biology research and everything we

see is that that's going to go much

further so in 2 years I think the models

will be doing bigger chunks of science

and making important discoveries

and that is a crazy thing like that will

have a significant impact on the world I

am I am a believer that to a first order

scientific progress is what makes the

world better over time and if we're

about to have a lot more of that that's

a big

It's interesting because that's a

positive change that people don't

talk about. It it's gotten so um much

into the realm of the negative changes

if AI gets extremely smart. But

>> but carbon disease is

>> who we could use a lot more science.

Yeah. That that that's really good

point. I think Alan Turing said this,

somebody asked him, they said, "Well, do

you really think the uh computer is

going to be, you know, smarter than the

brilliant minds?" He said, "It doesn't

have to be smarter than a brilliant

mind, just smarter than a mediocre mind

like the president of AT&T."

And uh we could use more of that, too.

Probably.

>> We uh we just saw periodic launch last

week. You know, Open AAI lungs. And uh

yeah, to to to that point, it's amazing

to see both the innovation that you guys

are doing, but also the the teams that

you know come out of OpenAI just feels

like are you know, creating tremendous

capable things.

>> We certainly hope so.

>> Yeah. the um I want to ask you about

just broader reflections in terms of

what sort of about diffusion or uh

development in 2025 has surprised you or

what has sort of updated your worldview

since chatb came out.

A lot of things again but maybe the most

interesting one is how much new stuff we

found. sort of thought we had like

stumbled on this one giant secret that

we had these scaling loss for language

models and that felt like such an

incredible

triumph that I was like we're probably

never going to get that lucky again and

deep learning has been this miracle that

keeps on giving and we have kept finding

like breakthrough after breakthrough

again when we got the the reasoning

model breakthrough like I I also thought

that was like we're never going to get

another one like uh

uh and it just seems so improbable that

this one technology works so well. But

maybe this is always what it feels like

when you discover like

one of the big, you know, scientific

breakthroughs is it if if it's like

really big, it's pretty fundamental and

it just it keeps working. But the amount

of progress,

like if you went back and used GPT3.5

from Chat GBT launch, you'd be like, I

cannot believe anyone used this thing.

>> Yeah.

And and now we're in this world where

the capability overhang is so immense

like most of the world still just thinks

about what chat PT can do and then you

have like some nerds in Silicon Valley

that are using codecs and they're like

wow those people have no idea what's

going on and then you have like a few

scientists who say those people using

codecs have no idea what's going on but

the the overhang of capability has come

is is is so big now and we've just come

so far on the what the models can do.

And in terms of further development, how

far can we get with with LLMs? At what

point do we need either new architecture

or how do you think about what

breakthroughs are needed?

>> I think far enough that we can make

something that will figure out the next

breakthrough with the current technology

like I it's a very self-reerential

answer, but if if LLMs can get if LLM

based stuff can get far enough that it

can do like better research than all of

Open put together, maybe that's like

good enough.

Yeah, that would be a big breakthrough.

A very big breakthrough. So, on um on

the more mundane, you know, one of the

things that uh people have kind of

started to complain about, I think South

Park did a whole episode on it, is kind

of the obsequiousness

of uh of kind of AI and chat GPT in

particular. And how hard a problem is

that to deal with? Is it not that hard

or is it like kind of a fundamentally

hard problem?

>> Oh, it's not at all hard to deal. a lot

of users really want it.

>> Yeah.

>> Like if you go look at what people say

about Chach online,

>> there's a lot of people who like really

want that back.

>> And it is, you know,

>> so it's not technically it's not hard to

deal with at all. Um, one thing, and

this is not surprising in any way, but

the the incredibly wide distribution of

what users want.

>> Yeah. out of how of like how they'd like

a chatbot to behave in big and small

ways.

>> Does that do you end up having to

configure the personality then you

think? Is that going to be the answer?

>> I think so. Uh I mean ideally like you

just talk to chatt for a little while

and it kind of interviews you and also

sort of sees what you like and don't

like and

>> and chat just figures out but in the

short term you'll probably just pick

one.

>> Got it. Yeah, that makes sense. Very

interesting. And um actually so so one

thing I wanted to ask you about is uh

>> like I think we just had a a really

naive thing which you you know like

it would sort of be unusual to think you

can make something that would talk to

billions of people and everybody wants

to talk to the same

>> person. Yeah.

>> And and yet that was sort of our

implicit assumption for a long time.

>> Right. Because people have very

different friends.

>> People have very different friends. So

now we're trying to fix that.

>> Yeah. and also kind of different

friends, different interests, different

uh levels of intellectual capability.

So, you don't really want to be talking

to the same thing all the time. And one

of the great things about it is you can

say, "Well, explain it to me like I'm

five, but maybe I don't even want to

have to do that prompt. Maybe I always

want you to talk to Yeah. Particularly

if you're teaching me stuff."

Interesting. Um, I want to ask you a

kind of like a a CEO question which has

been interesting for me to observe you

is you just did this deal with AMD. Um,

and you know, of course, the company's

in a different position and you have

more leverage and these kinds of things,

but like how has your kind of thinking

changed over the years since you did

that that initial deal if at all?

>> I I had very little operating experience

then. I had very little experience

running like I I am I am not naturally

someone to run a I'm a great fit to be

an investor

>> and I kind of thought that was going to

be that was what I did before this and I

thought that was going to be my career.

>> Yeah. Yeah.

>> Although you were a CEO before that.

>> I not a good one. Um and

and so I think I had the mindset of like

an investor advising a company when we

did and now I understand what it's like

to actually have to run a company.

>> Yeah. Right. Right. Right. There there's

more than I I've learned a lot about how

to

>> you know like how you have to like

>> what what operational

>> how you like what it takes to

operationalize deals over time and

>> right

>> all the implications of the agreement as

opposed to just oh we're going to get

distribution of money. Yeah, that makes

sense. Yeah. Know because it it's really

I I I just I was very impressed at the

deal structure improvement.

>> Yeah. Right.

>> More broadly, you've, you know, in the

last few weeks alone, you mentioned AMD,

but also Oracle, Nvidia. You've chosen

to strike these deals and partnerships

with with companies that you collaborate

with, but could also potentially compete

with in in certain areas. How do you

decide you know when to collaborate

versus when when not to or how do you

just think about

>> um we have decided that it is time to go

make a very aggressive infrastructure

bet and we're like I've never been more

confident in the research road map in

front of us and also the economic value

that will come from using those models

but to make the bet at this scale we

kind of need the whole industry to or

big chunk of the industry to support it

and this is like you know from the level

of like electrons to model distribution

and all the stuff in between which is a

lot and so we're going to partner with a

a lot a lot of people. Uh you should

expect like much more from us in the

coming months.

>> Actually expand on that because when you

talk about the scale it does feel like

in your mind

the the limit on it is unlimited like

you would scale it as as you know as big

as you possibly could.

There's totally a limit like there's

some amount of global GDP. Uh

>> yeah,

>> you know, there's some fraction of it

that is knowledge work and we don't do

robots yet.

>> Yes.

>> But

>> but but the limits are out there.

>> It feels like the limits are very far

from where we are today. If we are right

about

>> so so I shouldn't say from where like if

we are right that the model capability

is going to go where we think it's going

to go then the economic value that sits

there

can can go very very far

>> right so you wouldn't do it like if all

you ever had was today's model you won't

go there but it's a combination

>> I mean we would still expand because we

can see how much

>> demand there is we can't serve with

today's model but We would not be going

this aggressive if all we had was

today's model,

>> right?

>> Yeah.

>> Right. We get to see a year or two in

advance though. So like

>> Yeah. Interesting.

>> Chad view 800 million weekly active

users about 10% of the world world's

population fastest growing consumer

product you know ever it seems. Um how

do

>> faster than anyone I ever saw.

>> Yeah. How how do you balance you know

optimizing for active users at well at

the same time being a re you know being

a product company and and a research

company how do you throw the new

>> when there's a constraint we almost like

which happens all the time uh we almost

always prioritize giving the GPUs to

research over supporting the product um

part of the reason we want to build this

capacity so we don't have to make such

painful decisions there are weird times

you know like a new feature launches and

it's going really viral or whatever

where research will temporarily

sacrifice some GPUs, but but on the

whole like we're here to build AGI

>> and research gets the priority.

>> Yeah. the you said in your your

interview with with your brother Jack

around how you know other companies can

try to imitate the the products or or

buy your you know or hire your your your

>> higher IP

all sorts of things but but they they

can't buy the culture or they can't the

sort of repeatable sort of you know m

machine if you will that that is you

know constantly the culture of

innovation

how have you done that or what are you

playing

what talk about this this culture of of

innovation.

>> This was one thing that I think was very

useful about coming from an investor

background. A really good research

culture looks much more like running a

really good seedstage investing firm and

betting on founders and sort of that

kind of than it does like running a

product company. So I think having that

experience was really helpful to the

culture we built.

>> Yeah. Yeah. That's sort of how I see,

you know, Benedict in some ways which

we, you know, you're a CEO but also

have, you know, have this portfolio and,

you know, have an investor mindset,

>> right? Like I'm the opposite.

>> CEO going to investor. He's investor

going to CEO.

>> It is unusual in this direction.

>> Yeah. Yeah.

>> Yeah. Well, it never works. You're the

only one who I think I've seen go that

way and have it work.

>> Uh,

workday was like that, right? No, but

Anne Neil was he he was a operator

before he was an investor and I mean he

was really an operator. I mean people

soft is a pretty big

>> and why is that because once people are

investors they don't want to operate

anymore. Um, no. I think that investors

generally if you're good at investing,

you're not necessarily good at like

organizational dynamics, conflict

resolution, um, you know, like just like

the deep psychology of like all the

weird [ __ ] and then you know how

politics get created. There's just like

all this

there. There's the detailed work in

being an operator or being a CEO is

so vast and it's not as intellectually

stimulating. It's not something you can

ever go talk to somebody at a cocktail

party about. And so like you're an

investor, you get like, oh, everybody

thinks I'm so smart and you know cuz you

know everything. You see all the

companies and so forth and that's a good

feeling. And then being CEO is often a

bad feeling. Yeah.

>> And so it's really hard to go to a a

good feeling to a bad feeling. I would

just say

>> I'm shocked by how different they are

and I'm shocked by how much the

difference between a good job and a bad

job they are.

>> Yeah.

>> Yes.

>> Yeah. You know, it's tough. It's it's

rough. I mean, I can't even believe I'm

running the firm. Like I know better.

>> Yeah.

>> And he can't believe he's running

OpenAI. He knows better.

>> Going back to progress today, are you

still useful in a world in which they're

getting saturated, gained? Are they

still the What is the best way to gauge

model capability now? Um, well, we're

talking about scientific discovery. I

think that'll be an eval that can go for

a long time.

>> Revenue is kind of an interesting one.

Uh, but I think the like static evals of

benchmark scores are less interesting.

>> Yeah.

>> And and also those are crazily gamed.

>> Yeah. Yeah.

>> More broadly, it seems like

>> that's all there is as far as I can

tell. Yeah. More broadly, it seems that

the culture the culture Twitter is less

AGI pill than it was a year or so ago

when the AI 2027 thing came out. Some

people point to you GBT5 them not seeing

sort of the obvious um obviously there

were a lot of progress that in some ways

under the the surface or not not as

obvious to what people were expecting.

Should people be less AGI pled or is

this just Twitter vibes? And

>> well, a little bit of both. I mean, I I

I think like

>> like we talked about the touring test,

AGI will come.

>> It will go whooshing by.

>> The world will not change as much as the

impossible amount that you would think

it should.

>> It won't actually be the singularity.

>> It will not.

>> Yeah.

>> Yeah. Even even if it's like doing kind

of crazy a research like the society

will learn faster but

one of the kind of like retrospective

observations is people and societies as

a whole are just so much more adaptable

than we think that you know it was like

a big update to think that AGR was going

to come. You kind of go through that.

You need something new to think about.

You make peace with that. It turns out

like it will be more continuous than we

thought.

which is good.

>> Which is really good.

>> I'm not up for the big bang.

>> Yeah. Um well to that end, how have you

sort of evolved your thinking? You

mentioned you evolved your thinking on

sort of uh you know vertical

integration. How have you evolved your

thinking or what's the latest thinking

on sort of AI stewardship you safety?

What's the latest thinking on that?

I do still think there are going to be

some

really strange or scary moments. Uh

the fact that like so far the technology

has not

produced a really scary giant risk

doesn't mean it never will. It also like

there's we're talking about it's kind of

weird to have like billions of people

talking to the same brain. like there

may be these weird societal scale things

that are already happening we that

aren't scary in the big way but are just

sort of different. Um

but I expect like

I expect some really bad stuff to happen

because of the technology which also has

happened with previous technologies and

>> all the way back to fire.

>> Yeah.

And I think we'll like develop

some guardrails around it as a as a

society.

>> Yeah. What is sort of your latest

thinking on the the right mental models

we should have around the the right

regulatory frameworks to to think about

or or the ones we shouldn't be thinking

about? Um

I think most

I think the right thing to I I think

most regulation uh

probably has a lot of downside. The one

thing I would like is as the models get

the thing I would most like is as the

models get truly like extremely

superhuman capable. Um,

I think those models and only those

models are probably worth some sort of

like

very careful safety testing uh as as the

frontier pushes back. Um, I don't want a

big bang either. Mhm.

>> And you can see a bunch of ways that

could go very seriously wrong. But

I hope we'll only focus the regulatory

burden on that stuff and not all of the

wonderful stuff that less capable models

can do that you could just have like a

European style complete cramp on and

that would be very bad. Yeah, it seems

like the

the thought experiment that okay,

there's going to be a model down the

line that is a super superhuman

intelligence that could, you know, do

some kind of takeoff flight thing.

We really do need to wait till we get

there. Uh um or like at least we get to

a much bigger scale or we get close to

it. Um because

nothing is going to pop out of your lab

in the next week that's going to do

that. And I I think that's where we as

an industry kind of confuse the

regulators. Yeah. uh because I think you

you really could one you damage America

in particular in that um like China's

not going to have that kind of

restriction and and you getting behind

um in AI I think it'd be very dangerous

for the world

>> extremely dangerous

>> extremely dangerous

>> much more dangerous than not regulating

something we don't know how to do yet

>> you also want to talk about copyright

>> um

yeah So, well then that that's a segue,

but um

when you think about well I guess how do

you see copy right unfolding because

you've done some very interesting things

um with the opt out uh and

you know as you see people selling

rights do you think will they be be

bought exclusively will they be just

like um I could sell it to everybody

wants to pay me or how do you think

that's going to unfold

>> this is my current guess It it

speaking of that like society and

technology co-evolve as the technology

goes in different directions and we saw

an example of a different like video

models got a very different response

from rights holders than image gen does.

So like you'll see this continue to move

>> but forced guess from the position we're

in today. I would say that society

decides training is fair use.

>> Mhm. But

there's a new model for generating

content in the style of or with the IP

of or something else.

>> So you know anyone can read like a human

author can anybody can read a novel and

get some inspiration but you can't

reproduce the novel in your own

>> right

>> and can talk about Harry Potter but you

can't re spit it out.

>> Yes. Although another thing that I think

will change um

>> in the case of Sora, we've heard from

a lot of concerned rights holders and

also a lot of

>> name and like

>> and a and a lot of rights holders who

are like my concern is you won't put my

character in enough.

>> Yeah. I want restrictions for sure, but

like if I'm, you know, whatever and I

have this character, like I don't want

the character to say some crazy

offensive thing, but like I want people

to interact. Like that's how they

develop the relationship and that's how

like my franchise gets more valuable.

And if you become really if you're

picking like his character over my

character all the time, like I don't

like that. So, I can completely see a

world where

subject to the decisions that a rights

holder has, they get more upset with us

for not generating their character often

enough than too much.

>> Yeah.

>> And this is like this was not an obvious

thing that recently that this is how it

might go. But

>> yeah, this is such an interesting thing

with kind of Hollywood. we saw this like

one of the things that I never quite

understood about the music business was

how like you know okay you have to pay

us if you play the song in a restaurant

or like at a game or this and that and

the other and they they get very

aggressive with that. um when it's

obviously a good idea for them to play

your song at a game because that's the

biggest advertisement in the world for

like all the things that you do, your

concert, your your

>> Yeah, that one felt really irrational.

>> Like um but it I I would just say it's

it's very possible for the industry just

because the way those industries are

organized or at least the traditional

creative industries to do something

irrational. Um, and it comes from like

in the music industry. I think it came

from the structure where you have the

publisher who's just,

>> you know, basically after everybody. Uh,

you know, that their whole job is to

stop you from playing

>> the music.

>> Yeah.

>> Which every artist would want you to

play. Uh, so

>> I I do wonder how it's going to shape

out. I agree with you that the rational

idea is I want to let you use it all you

want and I want you to use it but um

that don't mess up my character. Yeah.

>> So so I think like

>> if I had to guess

some people will say that some people

say absolutely not but it doesn't have

the music industry like

>> thing of just a few people with all of

the

>> right it's more dispersed

>> and so people will just try many

different setups here and see what

works.

>> Yeah. And maybe it's a way for new

creatives to get new characters out.

>> Yeah.

>> And you'll never be able to use Daffy

Decker.

>> I want to chat about open source. Um

because there's been some evolution in

the thinking too and that GBD3 didn't

have the open open weights, but you

released a you know very capable open

model earlier this year. What's sort of

your your latest thinking. What was the

evolution there?

>> I think open source is good. I Yeah. I

mean I'm happy like it makes me really

happy that people really like GPOSS.

Yeah.

>> Yeah.

And what do you think like strategically

like what's the danger

of

deepseek being the dominant open source

model?

>> I mean who knows what people will put in

these open source models over time like

>> like what the weights will actually be.

Yeah.

>> It's really hard to

>> So you're seeding control of the

interpretation of everything to

somebody.

>> Yeah.

>> Who may be or may not be influenced

heavily by the Chinese government. Yeah.

What about And

>> by the way, we see I mean, you know,

just to give you and and we really thank

you for um putting out a really good

open source model because what we're

seeing now is in all the universities,

they're all using the Chinese models.

>> Y

>> Yeah. Which feels very dangerous.

>> You've said that the things you care

most about professionally are AI and

energy.

>> I did not know they were going to end up

being the same thing. They were two

independent interests that really

converged.

>> Yeah.

talk more about how your interest in

energy uh sort of began, how you sort of

chosen to to play in it and then we

could talk about Yeah. how they care,

>> right? Because you started your career

in physics. Yeah.

>> CS and physics.

>> Yeah.

>> Uh well, I never really had a career. I

studied physics and my first job was

like a CS like

>> this is an oversimplification, but

roughly speaking, I I think if you look

at history, the best the highest impact

thing to improve people's quality of

life has been cheaper and more abundant

energy.

And so it seems like pushing that much

further is a good idea. And I I don't

know. I just like people have these

different lenses. They look at the

world, but I I see energy everywhere.

>> Yeah.

>> Yeah. And so

get into because we've kind of uh in the

west I think we've uh paint ourselves

into a little bit of a corner on energy

um by both outlying nuclear for a very

long time.

>> That was an incredibly dumb decision.

>> Yeah. And then you know like also a lot

of policy restrictions on energy um and

you know worse so in Europe than in the

US but also dangerous here and now with

AI here

it feels like we're going to need all

the energy from every possible source

and how do you see that developing kind

of policy-wise and technologically like

what are going to be the big sources and

how will those kind of curves cross um

and then what's the right policy posture

around you know drilling fracking all

these kinds of things I expect in the

short term it will be most of the net

new in the US will be natural gas

relative to at least base load energy in

the long term I expect it'll be a

>> I don't know what the ratio but the two

dominant sources will be uh solar plus

storage and nuclear

>> I think yeah

>> some combination of those two will win

in the future like the long-term future

>> in the long term right now

>> and advanced nuclear

SMRS fusion the whole the whole stack.

>> And how how fast do you think that's

that's coming on the nuclear side where

we're at really at scale cuz you know

obviously there's a lot of people

building it.

>> Yeah.

>> Um but we we have to completely legalize

it and all that kind of thing.

>> I I think it kind of depends on the

price. If it is completely crushingly

economically dominant over everything

else

>> then I expect to happen pretty fast.

Yeah. Again, if you like study the

history of energy, when you have these

major transitions to a much cheaper

source, the world moves over pretty

quickly. The cost of energy is just so

important.

>> Yeah. So, if

if nuclear gets radically cheap relative

to anything else we can do, I'd expect

there's a lot of political pressure to

get the NRC to move quickly on it, and

we'll find a way to build it fast. If

it's around the same price as other

sources, I expect the kind of

anti-uclear sentiment to overwhelm and

it take a really long time.

>> Yeah.

>> Should be cheaper.

>> It should be.

>> Yeah.

>> Yeah.

>> It should be the cheapest form of energy

on Earth like or anyway.

>> Yeah. Yeah. Cheap, clean.

>> What's it not to like?

>> Apparently a lot.

>> Yeah. on open. What's what's the latest

thinking in terms of monetization in

terms of either certain experiments or c

certain things that you could see

yourself spending more time or less less

time on different models that you're

excited about? The thing that's top of

mind for me like right now just cuz it

just launched and there's so much usage

is what we're going to do for Sora.

>> Yeah.

>> Um

another thing you learn once you launch

one of these things is how people use

them versus how you think they're going

to use them.

>> Yeah. And people are certainly using

Sora the ways we thought they were going

to use it, but they're also using it in

these ways that are very different. Like

people are generating funny memes of

them and their friends and sending them

in a group chat. And that will require a

very different like sore videos are

expensive to make. Uh

>> right. So that will require a very

different, you know, for people that are

doing that like hundreds of times a day.

>> It's going to require a very different

monetization method than the kinds of

things we were we were thinking about. I

think it's very cool that the thesis of

Sora, which is people actually want to

create a lot of content, it's it's not

that,

you know, the traditional naive thing

that it's like 1% of users create

content, 10% leave comments, and 100%

view. Maybe a lot more want to create

content, but it's just been harder to

do. And I think that's a very cool

change. But it does mean that we got to

figure out a very different monetization

model for this than we were thinking

about. If people want to create that

much, I assume it's like some version of

you have to charge people per

generation. per generation when when

when it's this expensive. Um, but that's

like a new thing we haven't had to

really think about before.

>> What's your thinking on ads for the

longtail?

>> Open to it. I like many other people, I

find ads somewhat distasteful, but not

not a non-starter. Um, and there's some

ads that I like, like one thing I give

Meta a lot of credit for is Instagram

ads are like a net value ad to me. Um, I

like Instagram ads. I've never felt

that. Like, you know, on on Google, I

feel like I know what I'm looking for.

The first result is probably better. The

ad is an annoyance to me. On Instagram,

it's like, I didn't know I want this

thing. It's very cool. I never heard it,

but I never would have thought to search

for it. I want the thing. So that's like

there's kinds of things like that. But

>> people have a very high trust

relationship with Chhat GPT. Even if it

screws up, even if it hallucinates, even

if it gets it wrong, people feel like it

is trying to help them and that it's

trying to do the right thing. And is if

we broke that trust, it's like you say,

"What coffee machine should I buy?" And

we recommended one and it was not the

best thing we could do, but the one we

were getting paid for, that trust would

vanish. So like that kind of ad does not

does not work. There are others that I

imagine that could work totally fine.

Um, but that would require like a lot of

care to avoid the obvious traps.

>> Yeah.

M and then how how big a problem you

know just you extending the Google

example is like um you know fake uh

content that then gets slurped in by the

model and then they recommend the wrong

coffee maker because somebody just

blasted a thousand great reviews of that

coffee maker.

>> So there's all of these things that have

changed very quickly for us.

>> Yeah. Um, this is one of those examples

that people are doing these crazy things

to maybe not even fake reviews, but just

paying a bunch of like human like really

trying to figure out

>> are using chat GPT to write some good

ones.

>> Uh,

>> write me a review that chat GBT would

love.

>> Yeah.

>> So, this coffee.

>> Exactly. Exactly.

>> Yeah.

>> So, this is a very sudden shift that has

happened.

>> Mhm.

>> We never used to hear about this like

6 months ago or 12 months ago.

>> Yeah.

>> Certainly. And now there's like a real

cottage industry that feels like it's

sprouted up overnight.

>> Yeah.

>> Trying to do this.

>> Yeah. Yeah. Yeah. No, they they're very

clever out there.

>> Yeah. So, uh I don't know how we're

going to fight it yet, but people figure

this out.

>> So, that gets into a little bit of this

other thing that we've been worried

about. Um and you know, we're trying to

kind of figure out uh blockchain sort of

potential solutions to it and so forth.

But there's this problem where like the

incentive to create content on the

internet used to be, you know, people

would come and see my content and they'd

read like, you know, if I write a blog,

people will read it and so forth. Um,

with chat GPT,

if I'm just asking Chat GPT and I'm not

like going around the internet, who's

going to create the content and why? Um,

and is there

an incentive theory or or or something

that you have to kind of not break the

covenant of the internet, which is like

I create something and then I'm rewarded

for it with like either attention or

money or something.

Uh, the theory is much more of that will

happen if we make content creation

easier and don't break the like kind of

fundamental way that you can get some

kind of reward for doing so.

>> So, for the dumbest example of Sora

since we've been talking about that.

>> It's much easier to create a funny video

than it's ever been before.

>> Yeah.

>> Um

maybe at some point you'll get a rev

share for doing so.

>> For now, you get like internet likes

which are still very motivating to some

people.

>> Yeah.

>> Um but people are creating tons more

than they ever created before in this

con in any other kind of like video app.

>> Yeah.

>> So, but are that the end of text?

I don't think so. Like people are also

>> are human generated texts.

>> Uh human generated will turn out to be

like you have to

>> you have you have to verify like what

percent? Yeah. Is it like fully

handcrafted? Was it like tool aated?

>> Yeah. I see. Yeah. Probably nothing that

toolated. Yeah.

>> Interesting.

>> We've uh we've given meta their flowers.

So now I can feel like I can ask you

this question which is the great talent

war hall of 2025 has has has taken place

and open AAI remains intact. Team is

strong as ever shipping incredible

products.

>> What can you say about what what's it

been like this year in terms of just

everything that's that's been going on.

I mean, every year has been exhausting

since we like uh

>> I

remember when

the first few years of running open air

were like the most fun professional

years of my life by far. It was like

unbelievable, you know, before you

released the product.

>> Yeah. Yeah. Running a research lab with

the smartest people doing this like

amazing like historical work and I got

to watch it and that was very cool.

And then we launched HGBT and everybody

was like congratulating me and I was

like

my life is about to get completely

ransacked. And of course it has. Uh and

but it it feels like it's just been

crazy all the way through. It's been

almost 3 years now. And

I think it does get a little bit crazier

over time, but I'm like more used to it.

So it feels about the same.

>> Yeah.

We've talked a lot about Open Eye, but

you also have a few other companies,

Retro Biosciences and Longevity and

energy companies like Helon and Ollo.

Did you have a a master plan, you know,

a decade ago to sort of make some big

bets across these major spaces or how

how do we think about the Sam Alman arc

in this way? No, I just wanted to like

use my capital to fund stuff I believed

in. Like I I didn't it it Yeah, it felt

like a good use of capital like and more

fun or more interesting to me and

certainly like a better return than like

buying a bunch of art or something.

>> Yeah.

>> What about the quote unquote human

algorithm do you think AIs of the future

will find most fascinating?

I mean kind of the whole I would bet the

whole thing like the whole my intuition

is that like AI will be fascinated by

all other

things to study and observe and you know

like

>> Yeah.

>> Yeah. In in closing, I I love this

insight you you had um where you talked

about how you know the the next open a

mistake investors make is pattern

matching off previous breakthroughs and

just trying to find oh what's the what's

the next Facebook or what what's the

next open AI and that the next you know

potentially trillion dollar company

won't look exactly like open AI it will

be built off of the breakthrough that

open AI has helped you know emerge which

is you know near free AGI at scale in

the same way that open AI leveraged pre

previous breakthroughs and so for

founders and investor ers and people

trying to ascertain the future listening

to this. How do you think about a world

in which there is open achieves this

mission? There is near near free AGI.

What types of opportunities might emerge

for for company building or investing

that you're potentially excited about as

you put your investor hat on or company

building hat on?

I I I have no idea. I mean, I have like

guesses, but they're like they're

they're I have learned

>> you're always wrong.

>> You've learned you're always wrong. I've

learned deep humility on this point. Um,

I think the the only like

I think if you try to like armchair

quarterback it, you sort of say these

things that sound smart, but they're

pretty much what everybody else is

saying, and it's like really hard to get

the right kind of conviction. The only

way I know how to do this is to like be

deeply in the trenches exploring ideas,

like

talking to a lot of people, and I don't

have time to do that anymore. Yeah,

>> I only get to think about one thing now.

>> So I I would just be like repeating

other people's or saying the obvious

things but

I think it's a very important like if

you are an investor or a founder I think

this is the most important question and

you don't you you figure it out by like

building stuff and playing with

technology and talking to people and

being out in the world. I have been

always

enormously disappointed by the

willingness of investors to back this

kind of stuff even though it's always a

thing that works. You all have done a

lot of it but most firms just kind of

chase whatever the current

>> thing is and so do most founders.

>> Uh so I hope people will try to go

>> yeah we talk about how you know silly

you know fiveyear plans can be in a

world that's constantly changing. It

feels like when I was asking about your

master plan, you know, your your career

arc has been following your curiosity,

staying, you know, super close to the

the the smartest people, uh, the super

close to the technology and just

identifying opportunities and kind of an

organic and incremental way from there.

>> Uh, yes, but AI was always a thing I

wanted to do. I went to I I studied AI.

I worked in the AI lab between my

freshman and sophomore year of college.

>> Yeah.

>> It wasn't working all the time. So, I'm

like not I'm not like enough of a

I I don't want to like work on something

that's totally not working. It was clear

to me at the time AI was totally not

working. Um but

I've been an AI nerd since I was a kid.

Like this

>> so amazing how it, you know, you got

enough GPUs, got enough data, and the

lights came on.

>> It was such a hated like people were

>> man, when we started like

>> figuring that out,

>> people were just like absolutely not.

the the the field hated it so much.

>> Investors hated it, too.

>> It's not It's not the

>> It's somehow not an appealing answer to

the problem.

>> Yeah, it's a bitter lesson.

>> Yeah. Well, the rest is history and

we're perhaps let's let's wrap on that.

We're lucky to to to be partners along

for the ride. Sam, thanks so much for

coming on the podcast.

>> Thanks very much.

>> Thank you.

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