How Export Controls Helped Not Hurt China & Power is the Bottleneck to AI | Perplexity CEO

I have nothing to lose.

I came from nothing. I never even

imagined myself to be doing all this.

>> A $20 billion company,

>> $45 million users,

>> over a billion searches a month,

>> built in 3 years by 400 people.

>> These numbers like doesn't motivate me.

It's hard to get motivated by wealth.

You want to get motivated by impact.

>> This is perplexity with co-founder and

CEO Aravven Shrinus.

>> No one's ever in a comfortable position

that no one can relax.

>> They forced Google to redesign their

homepage. then bid $34 billion to buy

Chrome.

>> More than their own valuation.

>> Perplexity changed Google.com more than

any product manager at Google has ever

done. Now you look at AI mode, it looks

exactly like Perplexity.

>> He doesn't do defense. He doesn't do

comfortable. His words, attack, attack,

attack. That's my motto. Go all in and

try your best. Be on the offense all the

time.

>> You know what I hate with podcasts? When

people sit on the fence. Aravind has

really strong opinions in the show

today. He says that Micron will be more

valuable than better. He says that the

resistance to data centers will continue

and get worse. He says the biggest

problem today is a lack of power. He

claims that perplexity has changed

Google more than any Google PM. You want

opinions? This is the show for you.

Ready to go

Ara. Dude, I am so excited that we get

to do this. We've done one remote and

then we did one at Founders Forum last

year. So, thank you so much for joining

me in person.

>> Thanks a lot, Harry.

>> Dude, I It's a weird start, but just

roll with me on it. I asked this of the

best founders that I meet. Are you

motivated more by the fear of failing or

by the thrill of winning?

>> Thrill of winning.

>> Why? Because I have nothing to lose.

I came from nothing.

Like I I I never even imagined myself to

be doing all this. So my life has

already been extraordinary u beyond any

level of imagination. Um I was just in

India like you know doing my undergrad

and you know just just training neural

nets with graphics cards that people in

the labs were using for playing video

games. It was all for fun and um you

know my path led me all the way here. It

was never like a mo my for my mom just

getting a job was success because we

were not we were financially lower

middle class in India which is not even

like lower middle class in UK or the US

and so from there all we wanted to do

was get a job in Google being an

engineer at Google was considered a win

and so I'm I'm already doing remarkably

well compared to that ambition we had as

a family so there's really nothing for

me to lose. That's why anytime I try to

act like I'm trying to avoid failure,

I'm being on the defense. I remind

myself that like that's the stupidest

thing to do. Like you know, you you it's

better go all in and try your best. Be

on the offense all the time. Attack,

attack, attack.

>> When you review then what are you not

being aggressive enough on today? Maybe

in the early days we be very very loud

on social media talking about perplexity

versus Google and I used to do that

myself a lot. So and some people don't

like me for having done that. Today I'm

a lot more measured in how I talk about

our products or competitors and stuff

like that. But it's not a lack of

aggression or anything. Um it's just

that like it's that that is boring.

People already heard that enough from

me.

>> Do you regret the being so bold in your

messaging?

>> No. So it's not a nuance and maturation

of message. It's a that stale and I need

something new.

>> Not just that, I I kind of don't think

it's a relevant framing anymore. We

worked on search. Perplexity started out

as search. We built the first answer

engine in the world that people know

perplexity even today if you mention the

name perplexity people would think oh

that's an answer engine. We built a lot

more things after that. We built a lot

of agents, browser agents, deep

research, computer. We built so many

products after that but we're still

known for that first product and um the

mark has already been made the we

changed the road map of Google. You

could argue that I or the company

Perplexity changed Google.com more than

any product manager at Google has ever

done.

>> Make that argument for me.

>> Well, they never that nobody ever wanted

to ship an answer engine at Google.

Nobody like nobody wanted to tinker

anything on on the interface that made

them $250 billion a year. And uh and

then now you look at AI mode,

it looks exactly like perplexity.

There's there's not even any difference

like the font, the citations, the

specific bolding of inline text, inline

hyperlinks, um suggested follow-ups, the

whole experience is literally looking

like perplexity except it's still not as

good. And so

>> is that bad or good for you that they

learn from you and adapt?

>> It's it's it's it's both good and bad in

the sense, you know, you have to

obviously we I knew this like around end

of 2024 this is going to happen. So, it

never caught me by surprise at all. Um,

it was just a matter of time. I still am

I'm am surprised that the quality is

still not there cuz I I regularly test

every product out there. And u but I'm

I'm happy that honestly uh they they

they changed Google to be what it should

be. And um I believe that the frontier

is where the money is. The frontier in

AI is not about answering questions

anymore. It's about actually going and

doing work for you. We, you know, like

we still have the state-of-the-art deep

research the world will. And that's

actually where people subscribe to pay

for our pro or max products is not for

getting answers in in the in the

traditional way. They're asking for

sophisticated research reports. They're

asking for agents that go and do things

for you. And so we wouldn't have been

able to do all that if we were sitting

in 2024 thinking we have everything

settled here. We're we're good and

comfortable. No, we it the answer engine

was always a lead genen for the frontier

products we build. You need something,

right? Like think about it. Every

company needs to have one successful

product to build the next set of

products. And in AI, nobody can sit

comfortably thinking they have it all

sorted out, including Anthropic. If

Anthropic thinks cloud code is already a

win, in 6 or 12 months from now, they

won't even be around. And so that's the

uncomfortable it it's it's it's it's an

uncomfortable fact about the whole

field. Would you argue today, you just

told me, if you don't mind me quoting

you here, um, you just told me before we

started, that you think OpenAI isn't

ready for an IPO.

Um would you have believed you would be

in a position to say this two years ago

when nobody h wanted to deal with any

product other than chat GPT.

Think about it. So anyone even in such a

massive advantages position can be in a

can be put in a position where they're

no longer the kings. They're fighting

from behind. Right? So that's the state

of the field. That's just it's less

about perplexity or anthropic or open AI

not having modes or having modes.

>> Can I push back on you that I would I I

would stand by two years ago even when

they were a do and they are still a

dominant consumer product but I would

stand by it because I don't think they

are financially ready when you look at

the balance sheet of that that

>> maybe maybe I'll decouple that. I'll

decouple that.

>> Let's decouple that being like financial

readiness for an IPO

>> versus perception of a dominant leader.

Yeah.

>> Do you perceive them as a dominant

leader right now?

>> Yes.

>> In what?

>> Consumer search.

>> Well, except there's no money there,

right? Because it's been commoditized.

So, it's it's always a legion. Like, for

example, why why why are they going all

in on Codeex? Cuz that's where the money

is. And uh we're doing the same on

computer. Anthropic is doing the same on

cloud code. Google doesn't yet have a

product in this category, but I'm sure

they're going to come after that. Meta

is trying to launch Hatch for $200 a

month. You You see that? You see what's

happening, right? So, nobody

>> But there has to be more money than just

code codeex claw.

>> It's not about It's not about code.

That's the main thing. The the money at

least in non-advertising.

I'm not talking about advertising

revenue. In non-advertising subscription

or usage based revenue, the money is in

whatever is the frontier. And today the

frontier is about doing going out there

and doing things for you. And uh

>> do you not think then that there will be

a 100 to20 billion advertising business

for open AI? It's

>> yet to be proven. Let's let's work

through the categories of advertising.

Um who's the number one advertiser on

Google? Amazon. It's a number two.

Booking.com.

Number three or four I think Expedia.

So, um, how much do you think

Booking.com spends on Google? 16

billion, something like that. Something

some some some crazy amount like that.

Um, and, uh,

um, how do you book your hotels or

flights today? Do you book it on chat

GBT or do you book it on Google?

>> Google.

>> Why is that?

>> For me, I actually like discovery. I

would like to see the options.

>> Exactly. Right. So the interface the

interface is less about conversations

and more about exploration.

So when when the decision making is more

subjective and vibes based, you don't

need an objective

answer engine. And and so it's it's it's

and and and you think about the other

category of advertising, direct to

consumer products, fashion. Where is

most of that advertising budget going

into? It's going to meta, Instagram,

because you're just browsing. You're

just like doom scrolling or whatever

they call it, right? And so, uh, the

chat interface doesn't capture that user

intent, that user behavior right now,

which is why it was never a great fit

for advertising. And u, it also

fundamentally corrupts the trust that

people have when they go into a product

and they want the accurate answer, which

is what, you know, perplexity is known

for. Um, and then you're like, "Hey, by

the way, you know, you ask for the most

um highest like like mo best protein

shake, but by the way, these are good

protein shakes you can check out." Like

it it it kind of like hurts the trust

that people have in your platform and

your product. And so, um, that's another

reason why, if you think about it, like

like what Meta or like I think some

other companies in the past have tried

to put ads inside, um, messaging apps

and emails and it's never really worked

out. Um, it it works out in China

in WeChat because there's no other way

for them to fund the whole thing, you

know. So the the the whole economy and

and and user sentime user behavior has

been optimized around gamifying. It's

not how things work in America. So I I'm

I'm I'm bearish on advertising to really

take off in in the chat interface. I I'm

happy to be proven wrong there, but I'm

bearish on that.

>> There there are two areas that I want to

unpack there. The first and just taking

them kind of chronologically and how you

said them, money's in the frontier. The

more I hear this kind of the more I

question it because I think that we

dramatically overestimate

how important frontier models are to do

quite basic work.

>> Yeah. So frontier doesn't mean a

frontier model. Frontier just means

whatever is the frontier outcome you can

have right now with AI.

The Greg Brockman recently tweeted the

model is no longer the product, right?

Um, and it's funny because you you know

that as as a leader of a frontier lab,

he has all incentive to say the model is

the product and and that's what Google

people tell. I think one of the Google

people keeps tweeting that model is the

product. I forgot who. Um,

and so the reason Greg is right is

because um, if you take codeex or

perplexity computer clot code, what is

that? It's it's an orchestration system,

right? It it takes a model, pairs it

with an agent harness.

And what is an agent harness? Think of

it the simplest way of describing it is

like rules for how the agent loop should

run. What are all the skills and sub

agents and connectors and tools it

accesses? And uh without the harness you

don't necessarily capture and convert

the intrinsic intelligence in the model

into valuable output tokens.

The output tokens if you're if you're

literally just a reseller of model

tokens you have no business because the

model will get commoditized. So even if

you're a model builder, you don't have a

business. As an infra layer, you have

some business on serving those output

tokens. But as an application layer or a

model builder, you don't really have a

business. If you're just a reseller of

tokens that come directly out of the

model, you have business if you know how

to take the model ground it in valuable

context, orchestrated with a really good

agent harness

um connected to the right set of tools

and connectors whether it's personal

connectors or business connectors and

provide the experience to people in one

single unified system.

And uh the way we differentiate

ourselves at perplexity is we don't just

orchestrate across tools and files and

connectors. We also orchestrate across

models.

That is the differentiation that

anthropic and open AAI cannot claim

because you wouldn't find GPT5I

inside the cloud code harness. You

wouldn't find claw opus 47 or 8 inside

the codeex harness. These are competing

with each other, right? Whereas you

would find both these models inside

perplexity computer and that way we can

bring down the we can increase the token

value per watt per user. If you assume

that

if you assume that whatever decides the

dollar like the price the dollars is the

power watts fundamentally that's that's

the thing that nobody else can subsidize

other than the government. Um you know

that whoever pro you know provides the

most valuable output tokens with the

least amount of power expended to

produce them generates the greatest

value to the end user and has the most

pricing power has the most value and so

that that that is the orchestration

problem to solve who the one single the

most important metric in AI is token

value per what per user. What does it

mean for the value of open AI and

anthropic? If model is not the product

and it becomes a utility, something you

can switch into and switch out

>> interface.

Everyone thinks we're all building the

model layer or the race. We're not

actually. Um, I would even argue that

building models is a way to stay at the

frontier, but you have to own an

interface

in which valuable AI output tokens are

generated, the most valuable tokens. It

doesn't have to be the product. This is

the single most important thing to like

you know unlearn for most founders and I

had to do it too which is to be

successful in AI product layer whether

you're a model builder or not it's not

about building something that gets a

billion users that mentality has to

completely shift

there are a few power users who are

propelling this token economy right now

if you look at like all these um crazy

stories of how there's this one engineer

who got Amazon to spend like half a

billion dollars in a month because of

some stupid way they set up like agent

loop inside cloud code. Okay, maybe

that's a mistake, but there are real

engineers in meta in in other companies

spending like 10 million a year per

engineer on on on these, you know,

coding tools. There are users in

Perplexity Computer. Um, there's one

user, I think, who spends upwards of

like $10,000 a month, something like

that. Crazy. And and and not like

wasting it. They're not wasting money.

Their business runs using agent loops

that are running inside these harnesses.

And they use these products in

sophisticated ways that I I I couldn't

even conceive when we were building the

product ourselves. Even internally

inside our own company, there are some

people who have set up these kind of

like multi- aent hierarchy and agent

loops that looks like its own software

architecture.

And I often just ask these guys to come

explain to the rest of the company, hey,

like what are you doing with these

tools? Like you clearly are consuming it

way over, you know, what we thought the

average person in the company would do.

And the single biggest differentiation

between those who use agents a lot and

those who don't is whether they run

repetitive cron jobs

like whether you use AIS as one-off

tasks. You just delegate a task and then

it gets done. That's like kind of using

it for like deep research or like

whatever, right? Like one single task

versus the AI is like continuously

monitoring something for you. The AI is

continuously like triggering based on

certain events and going and doing

certain things, giving you alerts like

you set up workflows that keep running

for all the time. Every time you get an

inbound email like it triages or every

time there's a latency spike, it has to

identify which part of the codebase

caused that, it has to go and do the

root cause analysis and then identify

the right engineer. all these things the

this is where the frontier is and and so

uh going back to my main point.

These products are not going to be used

by uh you know 100 million people but

they will generate revenue that's going

to be higher than the advertising

revenue of Google or Meta. It's going to

happen.

>> Completely understand what you say

there. I do just want to focus in on a

specific element there when you were

saying like the power users because I

think one of the core numbers is

actually Mark Benov said they spend 300

million on anthropic which works out to

be about

>> it'll be interesting to know from him if

that 300 million came from you know what

is the distribution across employees

>> so it works out to be that was on

developers within Salesforce so it's

about 3.8% 8% of developer salaries.

What percent of developer salaries do

you think will be spent on tokens in 24

months time? Cuz that fundamentally

changes the value of open air and

anthropic. If it stays at 3.8%.

They will not be $5 trillion companies.

But if it's 100% like Brandon at Mccor

said it will be in a year, they they'll

be 10 trillion companies. Well, um I

think they can certainly beat $10

million companies whether it's going to

be um a full percent of the developer

payroll today or not because there's a

lot of non-developer

work that'll also be done with a agents.

Um and that's actually what we focus on

for Perplexity Computer. We're not going

after the developer market. We're going

after anything that developers don't

non-developers do. basically um your

your finance department or your corp dev

or your like um sales reps or your data

science teams um your your research

analysts I think that's actually even

bigger market that it's it's it's not

even like like think of it as like clot

code multiplied by 10 that that's the

size of that market

>> if I push you on developer salary spend

what percent of token spend as a portion

of salary do you think We'll see in 24

months.

>> It's hard to say.

I think the costs are going to go down.

That's why it's hard to say.

>> You think the cost will go down? Cuz

this is the kind of the challenge that

we've had. We thought when we went from

chat to agent that costs would go down

and token costs would go down. They've

gone up.

>> Yeah. For now.

>> Help me understand that and how that

changes.

>> I think in software um you kind you kind

of want to pay for the frontier. Um it's

kind of like if you know some engineer

is awesome. If you know you have like

the next Jeff Dean,

would you rather hire that person and

not hire five five people who are medium

engineers but not Jeff Dean level with

the same amount of budget you have? Yes.

Right. Let's say you had a million

dollars. You could hire five people

worth 200K or you could hire one Jeff

and pay them a million. What would you

do?

>> One Jeff.

>> Yeah. So I think you would pay for the

frontier. Um but what stays frontier

keeps changing. Um in in 12 months from

now let's say thought experiment there

is an open source model as good as Opus

48.

>> Mhm.

>> And um you still have to pay for

inference. You know nothing is truly

free but it's going to be like let's say

10 times cheaper than Opus 48. And when

you pair it with the right agent

harness,

you know, and all the connectors,

GitHub, everything, all your developer

workflows work fine, why would you um

assume that the token spend is going to

be still high? It's not going to be for

the same things you're doing today. It's

not going to be. But there might be a

different set of things you might do

with the frontier that you're not

conceiving today. Uh my prediction would

be soft a agents that are like

completely autonomous software

engineers. Today I think we we're all

using tools like cloud code or codeex to

write code but not as literal software

engineers. There is a large sway of

people that is now bearish on your

frontier models who open eyes and your

anthropics because they're realizing

that you can actually do a lot with open

models for a fraction of the price. What

you're saying is actually that is true

but

>> we will still pay for the frontier and

so they will still ac

and and I think this distinction

it feels like a contradiction. It's not

though. It feels like two things cannot

be true simultaneously.

But that that's not quite the case. In

fact, I would argue that the frontier is

increasingly going to be a thing that um

very few individuals might even want.

Like you could argue that after a point

like it's not even interesting that AI

can write software. You you we've

normalized it, right? Let's say let's

say that that's going to be the case.

Instead of companies being built with

like tens of thousands of software

engineers unlike the past, there'll be a

lot more companies with smaller software

teams and each of us will be using a lot

of AIS. So um that's actually good for

the world. We'll be seeing a lot of

different businesses. We'll be seeing

allocation of software labor in places

that was never even possible. and and uh

whatever is a frontier is going to be

things that kind of like AI is going and

designing chips, AI is designing drugs,

AI is figuring out how to build robots,

AI is figuring out how to cure cancer.

These are applications where you don't

have like 10 million users. It's like a

few companies, but the effect of that

work will touch a lot of human lives. I

think to me that that's where the

frontier is headed. Um you could also

see that from the moves that Frontier

Labs are making. Anthropic bought um a

wet lab could be for the talent could be

for the infrastructure to run like wet

lab experiments but imagine taking all

those tokens and putting it in the mid

training instead of just tokens from

GitHub right um so then that's going to

produce something interesting.

>> Don't laugh. Is there an asimtope to

frontier problems to be solved? I know

that sounds ridiculous, but if you are

continuously on the chase for the next

frontier problem, you get to cancer, you

get to climate change. And my word, I

hope they solve both in like heaven,

that's a huge amount to solve.

But if you're on the treadmill of

continuously, is there an asmtope to

that? Do you see?

>> There's no there's no mathematical

argument

to there being a cap on the amount of

economic value

one can create with with with um AGI or

ASI like systems. Um and Elon Elon has a

good argument for this like like where

he says money loses all meaning in a

post AGI economy

because you'll be producing

an abundance of energy and labor

and fundamentally the economy is

grounded to energy and labor. If you can

produce an abundance of them,

well what what meaning does money have?

Um and um and so I I don't think we run

out of things to solve at the frontier.

I think we're always going to be creat

like like why why would why did people

even want to understand the universe?

Like like why did we want to understand

subatomic particles, quantum physics,

black hole theory, um you know the

origins of the universe like what what

what is the purpose? But we still went

ahead and did it because that's kind of

what the purpose of humanity has always

been to understand the unknown. You

know, David Deutsch is famous for saying

this, right? Like we are the only

species capable of being curious about

what is already familiar. Like you can

stare at a fruit and you know that it's

a mango and like you know exactly like

how it tastes, you know how it looks,

you know the shape, you know what

seasons it grows and and and stuff, but

you can still look at it and ask one

more question about it that you haven't

asked before. Other animal species

cannot. Once they kind of once they have

it in their mental model, what it looks

like and touches and feels like, they're

going to ignore it. It's not it's no

longer interesting to them. Kashi, you

mentioned about agent usage and you said

if you do repetitive tasks versus one

off say chron jobs, you know, I think

Sam said it's we're going to have 24/7

AI and um yeah, they've talked about a

hardware product that's going to come

out.

>> Do you think we will have continuous

agents running?

>> Yeah. In so

>> and I think that's kind of why I believe

>> the orchestration problem I I talked

about maximizing the token value.

>> Can you just help me? Sorry. when you

say the orchestration problem.

>> Yeah. So, so okay. So there are like

four objectives

um accuracy, intelligence and accuracy

and then privacy and cost.

You know these are all competing with

each other. So you can you could argue

that um you could max out on

intelligence and accuracy by building

giant giant data centers and spending a

lot of power to uh you know run them and

u you could miss out on privacy and

costs cuz everything will be centralized

and and and you're going to be paying a

lot. Um, you could argue that everything

can run locally and so that'll be good

for privacy and cost but may not be

frontier intelligence, may not be

frontier accuracy. So the solution is to

figure out a sweet spot. You know, use

local models when necessary, use server

side models when necessary and

orchestrate across local models and

serverside models. Uh, grounded in

valuable personal context. Sometimes the

intelligence might already be there but

the system might not work that because

the harness isn't grounded in the right

set of tools right so build a worldass

harness that can even make an okayish

model appear great and be able to use

the right model for the right task and

the right part of the task sub aents and

and even like utilize the compute we all

have in our own devices all that that

you know doesn't need to be always on a

server that is an orchestration from a

router, an awesome router, a master

orchestrator router. Now, um, if you do

that, you can realize the vision of a

24/7 AI without people freaking out

about going bankrupt

because no one's going to be able to

afford a 24/7 AI, Frontier AI, running

on the server. Imagine you turned it on

and you you could never switch it off

unless something crazy happened. Um,

you're the the the the the thing that

most people worry about those AI is

like, "Oh, what if it does something

crazy?" But the real concern actually is

the cost. Um nobody's going to be able

to afford it a cron job at the fidelity

of few seconds, you know, um that that

runs all the time. And so, um the

bottleneck there is actually

orchestration and local compute. And so

I believe like like um one needs to

build a continuously learning

local model um that can save you on like

compaction

context windows. So you and and and try

to preserve as much compute locally and

rely on the server side frontier only

when necessary and keeps learning, keeps

adapting, keeps evolving. And that model

um is not just a model. It's a model

plus the harness plus the local chip and

the compute and the ecosystem of devices

it controls. That system um is going to

be your own intelligence. Essentially

the data center moved to your local

device and you you get to control it.

You get to own it. You don't get to

worry about somebody like you know

spying on you or looking at all your

tokens. Very valuable personal tokens.

Imagine you have like very sensitive

deal materials. Let's say you're doing a

deal um and then um a Frontier Lab has

all your tokens that you use to like

write a memo.

Imagine somebody could hack into that

server and steal your deal from you. You

wouldn't want that, right?

>> I'm going to be honest. I think there's

much more valuable things for people to

steal from

London based VC.

>> But yes, I can figure you're not just

yet another London VC. You have like a

$400 million fund last time read it. So

>> imagine like you know you're

>> already making your moves for the $4

billion fund right so so everyone has

certain levels of like you know

sensitive stuff and and so I think

that's where I believe that the 247

always on agent is going to be realized

by the company that wants to play the

role of the orchestrator not the model

builder not the frontier model builder

but the orchestrator and uh and I think

that's what that's what we want to do um

computers has been positioned explicitly

as the agent orchestrator. The the

musicians in the orchestra are these sub

agents that utilize these different

models. Think of them as the instruments

and uh the tools, the connectors, the

models. These are all the instruments

and the musicians are the sub aents and

the symphony is the work and the system

is the orchestra and and computer is the

orchestra conductor. that that that's

how it's been positioned. So what it

orchestrates

keeps evolving, right? It it changes. It

changes from,

you know, models to files to tools to

chips to devices. But but it doesn't

even matter like you don't care as long

as it orchestrates things correctly and

and and and maximizes the token value

for what per user. If you can solve this

problem, you will capture the most

economic value in AI long term.

Shortterm it might look like oh like

this other lab's revenue is growing you

know exponentially this that but long

term this is the one objective that

truly matters.

>> Who is best positioned to do that?

>> I believe it's us cuz you have the

incentive of not token maxing you have

the incentive of delivering the most

value to the user like we we every time

any part of the AI stack improves

our product improves. Um since the

beginning of the year, Anthropics models

have made tremendous progress. But

what's also true is that our revenue has

more than tripled since the beginning of

the year. Tripled since this beginning

of the year and uh we and a lot of

thanks to model progress made by

anthropic and we also brought our

burndown thanks to OpenAI competing with

them and bringing down the cost of the

same capability. And now with progress

in open source and local models and

local chips, we're going to move some of

the inference back to the local devices

and bring down the cost even more. So

every time any part of the AI stack,

whether it's chips, models, harnesses,

any of these gets better, our system

improves tremendously. And if our system

improves tremendously, our users love it

and they pay more. They spend more and

so our business grows. So I think to

your question of who's best positioned

to win in that world for that objective

of being an orchestrator is the one

whose product or business

benefits from other people's progress at

any layer of the stack. And so if Jensen

produces a better chip, it's great for

us. If Dario produces a better model,

it's great for us. If Apple produces a

better device, it's great for us. And

like I I love the fact that we are able

to be a very positive player at every

layer of the stack and not have to rely

on any one person to win. When we look

at the different providers that we said

kind of server side versus you on device

when we look at server side a lot of

people talk about an AI infrastructure

bubble which I think is funny stupid and

moronic. To what extent do we have a

data center supply problem today from

what you see? I think the biggest

problem is actually in power. So what

let's break down what is a data center.

Is it like that you just buy like a

bunch of chips from Dell or Super Micro

and No, that that's just one part of it.

You actually have to go secure land or

you have to lease something, lease a

property and uh you have to buy a bunch

of turbines to generate power or you

have to work with like power suppliers,

grid suppliers and uh you also have to

work on cooling. So there's a lot of

other work you got to put in that is far

far slower. you have to get permits to

do all these things and uh and so

usually what's happening is um there's a

lot of lead time to doing this and um

the models that are um already in use

today these have been trained in the

hopper generation so the blackwell

generation model I think the first model

that's blackwell generation category is

um mitos

and it's already scary like people are

already like freaking out about it So

imagine that um everyone pre-trains a

model um on like a million or like you

know hundreds of thousands of black

wells now those models are going to be

far more powerful than what exists today

and then the ver rubins are coming next

year in full capacity like like all the

data centers of wear rubons will be in

next uh you know used next year that

model will be even more powerful. So I

think we there is a certain physical

buildout time

that always bottlenecks frontier

capabilities. That's why there's a value

in that layer. Whoever knows how to do

this puts it puts together a bunch of

GPUs and chips and networking and power

and cooling and actually like

orchestrating all this software layer on

top and you know is able to convert that

into frontier output tokens. that that

that vertical integration has a lot of

value. So that's why the markets are

pricing infrastructure companies with a

higher uh PE ratio

>> than companies like Meta for example.

Even though Meta builds a lot of infra

is valued as a software company. When we

see like you know Meta's capex spend and

it wanting to increase in the last few

days and thinking about raising more and

more money to increase capex spend I get

it with a lot of the AI providers like

your open eyes or Anthropase because

they are making money from their AI

products. For Meta, the capex spend

correlates to increasing accuracy on

ads, which is like a six to eight% bump

in revenue. I get it. But for the capex

spend, it doesn't make sense.

>> Well, um I I I believe like they they

are understanding

what the market's saying. You know, I

don't think they're

dumb to not see what what what's being

said. I think they're introducing a lot

of subscription products um from what

I'm reading. So they're definitely going

to like basically the company needs to

not just be a social platform maximizing

engagement and turning that into ad

revenue, right? And I think um that

requires them to launch a lot of like

agents subscription based products and

maybe even a cloud meta cloud that that

rents out servers like what Elon's doing

at SpaceX and and maybe once they do

that

the the narrative might change, right?

But um to go back to my point, it might

not be inconceivable that

um

Micron, the supplier of HPMs, might be

more valuable than Meta in the next 6 to

12 months. It's already at like a

trillion and Meta is like 1.3 to 1.4

trillion.

>> Can you help me understand that? Because

memory is already a massive bottleneck.

It's increased 5x in price in terms of

the cogs, right? Um, but people are

going, "Wow, Micron is fully priced at

this point." Why is it not fully priced?

>> Because it's still the bottleneck.

Whatever is the bottleneck

will command the price.

Um, AMD is doing really well because

CPUs became a bottleneck again. Agent

loops, agent harnesses are all running

on CPUs. The tokens are produced by the

frontier models on GPUs. But whatever

work like let's say like claude

generates a coding script that decides

to download 500 files from different

websites and then you know munches a lot

of data and transforms it in certain

ways and generates a plot and then hosts

it on a website that you can you can

share with your people. All that

computers is running on CPUs.

Agents are using CPUs more than humans,

right? And so suddenly there's a rise in

enterprise CPUs and the beneficiaries of

these are like Intel and AMD. So then

they get to be the bottleneck like like

whoever's going to be the bottleneck

will win and and so infra is the

bottleneck right now because there's a

lot of demand and we just don't have the

supply and so whoever supplies memory

SSDs for storage CPU compute suddenly

these are all like interesting like um

they're more important than companies

that are just building data centers and

not knowing how to turn that into a

valuable outputs. Do you believe your

Nebius and your Core Weaves will be a

sustainable

multiund billion company in the future

or is it solving a short-term supply

problem?

>> Um I certainly think they can be

sustainable.

>> Yeah.

>> Um I think there are some I don't like

look I don't know particularly which of

those is going to win and there's also

other players like Cruso and um Firebird

and a bunch of companies. It's all about

being resourceful. You got to take power

from areas where there's a lot of

natural resources

and the cost to bring up the data center

is pretty cheap and the time to bring up

the data center is cheap and your

service is reliable. Like if somebody

commits to buying 100,000 GPUs from you,

um the service should be pretty good. Um

and uh you should be able to secure the

supply ahead of time. Plan well. Um and

I think some companies are even

innovating at the power layer. You know,

um generating their own power is one way

to bring down the margins. Uh and so I

think there's certainly like value in

that layer because um it's hard to

replicate work. That's how I see it. You

could argue that OpenAI can do all the

work that Core V was doing and that's

kind of what they wanted to do with

Stargate. But why is Corev more

successful at building data centers than

OpenAI? It's

>> hard to do. It's operationally

intensive.

>> Yeah, operationally intensive. You got

to focus. You got to like spend most of

your time um securing permits like

figuring out power, figuring out like

bottlenecks in the supply chain here and

there um and constantly plan ahead and

like test all these systems carefully.

deal with like random physical issues

that you know arise in like you know

running a data center there's something

called TCO you know cost of operations

>> you got to factor that in so uh that

said I I I don't think there's value um

if you're just like a server renter if

you're just a GPU server rack renter if

you're just leasing it to different

companies on certain hourly pricing

rates there's not a lot of value you

have to actually build some software on

top kind of like how AWS did. It's

called Amazon Web Services, not Amazon

servers, right? So, um you have to have

some software orchestration on top that

allows you to get software margins on

top of what you're doing. And I think

that's why you're seeing moves like NBS

um

like like going for the AI model

inference like you know taking open-

source models or hosting your models and

and and um that's a business model of

certain other companies like fireworks

and you know um ben and all that but you

could imagine neocloud just going for

that business.

>> That was exacting me my question. So, I

just had the co-founder of Nebius on the

show and the really clear takeaway was

the the challenge that he has, which is

there's a huge amount of money that

wants just capacity and compute.

>> Yeah.

>> With the awareness that he needs to

build a full stack product if he wants

to have a long-term sustainable

business. That was the core realization

for me. When I look at the inference

layer, like you said, fireworks or base

10, how do you think that plays out? Do

we have standalone hundred billion

dollar companies in inference alone or

do we see that commodity?

I mean you it's just it's all about

working backwards like what does it take

to build a hundred billion company

assume like

>> 10 billion in revenue

>> exactly 10 billion in revenue 30 to 40%

gross margins good amount of net income

good cash flow okay 10 billion in

revenue

um is not that inconceivable for for a

company that can both do AI hosted

inference and server capacity and data

center buildouts

very operationally well. It's all about

like you know there there are some

factors beyond their control like open

source models continuing to be awesome.

If open source models stop to actually

be good where the gap between them and

the frontier is like more than 12 months

or like 15 months 18 months then I don't

think these companies really have a

business model because um they're not

going to be able to host they're only

going to be able to

rent capacity to open Athropic and so um

that's exactly what Roman and Nebia said

he said if consolidation happens and

there's anthropic and open AAI or two or

three dominant providers that is the

biggest threat.

>> That's correct. Yeah. And so um but you

got to make a leap of faith assumption

that you know like the the models from

China or Nvidia is making good progress

on their models in Limatron. Um you got

so there's going to be enough factors in

the market to keep u consolidation

as an outcome from from like stopping

from happening. But you don't control

your own destiny if you're those

companies. That that that's basically

the problem. Totally get that. Okay. So,

we can have standalone companies that

are hundred billion dollars in inference

alone. So, I'm just pillaging you for

your knowledge. When we look at the

model selection companies like an open

router or like factory AI just released

that kind of model selection or model

rooting product which did very well on

launch, is there hundred billion dollar

companies in the model selection and

routting business?

>> Probably not.

Um I think you can't just be a

provider of router. You have to use the

router to produce something meaningful.

Um actually most of the business value

of open router is less than the router

even though the product is called open

router. It's not routing across models

there. It's actually just routing across

different endpoints of the same model.

So um why okay so maybe let let's let's

let's ask this question. If you wanted

to use claude opus or

um I don't know like GBD55 developer why

would you not want to just use it with

your own API key versus using it inside

open router? Number one argument. The

single simplest argument as to why you

would want to do that is

model fallbacks. Sometimes your API keys

might not have the rate limits or even

if you have the rate limits it might

there might be an error on open AI

servers that you know don't guarantee

you the response time you need to run

your application and uh open router

would go and earn the uh you know they

would pay for capacity for like one year

ahead uh with the funding they have and

secure the rate limits and multiple

endpoints across multiple different

providers of openi models be it Bedrock

or Azure or OpenAI themselves. And so

that routing is valuable. It's

essentially an infra problem they're

solving which is reliable token supply.

It's not actually oh like they're

lowering the cost by deciding if this

prompt should go to like GPT or clot or

something like that. That's not what

they're actually selling to the

developer. That's not actually the

business model. And uh and then for a

lot of these Chinese open source models,

there's not you probably don't want um

your API tokens from going to like let's

say you don't want your API tokens going

to China. Um and so you and and let's

say you don't have the bandwidth to work

with like different inference providers

or verify who's good and you know who's

not. You're just thrusting open router

to take care of all that and then you

know they're going to like supply the

tokens to you. So it it's it's routing

not at the level of like oh like

deciding which model is cheap for what

task. It's more like um a reliable token

supply and I think there's some value in

that layer definitely uh otherwise they

wouldn't have these many um users and

these many trillions of tokens being

routed a month but it's um it's not like

you know high gross margins business

it's the way the business model works

for them is actually um they would

secure a discount from the model

providers by guaranteeing a lot of

supply but they would still charge the

user their listing price on the API and

that difference is their margins. Do you

understand?

>> I I I totally get you. We spoke about

bottlenecks and you said about HPM, high

performance memory and micron and the

value that you know they have to say and

what it can be. What bottleneck will we

have in 3 years that we're not

discussing today?

>> I think power will remain the

bottleneck. Yeah,

>> I think it's it feels like that to me.

Unless something dramatically changes in

the way data center buildouts happen. Uh

I actually believe that there will be a

lot of resistance to building data

centers. It's because people incorrectly

think that data centers consume a lot of

water or eat up a lot of power which is

both both are untrue. Satya even made

the statement that it it's like a can of

water or something uh in terms of how

efficient these companies are.

>> Do you think that's why they're putting

up resistance to them? I don't. I think

it's cuz it's a symbol of job losses. Uh

increasing wealth in

>> it's a lot of things. It's a lot of

things. Um it's a lot of apprehensions

um fear about like what's going to

happen channelizing in so many different

ways. Um, sometimes it's channelizing

through hatred for wealth inequality and

like wanting to tax people. Sometimes

it's channeling through like concerns

for the environment and like climate

change. Um, sometimes it's uh

channelizing in a way where um you're

all like oh like the price of the grid

is going up because you guys are

building all these data centers and then

or like I'm paying more for my phones

and laptops now because the RAM prices

have gone up because you guys went and

bought all of it. So I think there's a

lot of different ways in which it's

getting channelized but the common

sentiment is um like like a pretty bad

sentiment about AI.

>> Do you think it will be meaningful

to the development of those data

centers? I think right now 40 out of 100

are not being developed because of

public resistance.

>> Yeah. So um that that's where the power

bottleneck is and um you could see maybe

certain countries sees the opportunity

for this and um

um allow these model builders to go

build data centers there. Um Elon's

going to space to do that. Um so that's

going to be an interesting experiment.

Um because there's a lot of energy from

the sun that can be harnessed there. and

uh there's a lot of natural resources in

other countries. Regulations might be

more friendly.

So, we're still going to see data center

buildouts. It might not happen in the

US. And um but but the fact that you

have to solve physical problems like you

actually have to deal with the supply

chain, the permits, securing power, like

making sure like things work and getting

the lead times lower and lower. You're

not solving problems like cloning some

SAS apps here, right? You're or like

you're building a go to market team or

like um doing better marketing against

the competitor's products. Like yes,

those are also hard problems, but these

are like much harder problems where like

you're not in full control of your

destiny and you need a lot of capital

and connections and like the right

people uh sometimes even like political

help to unlock progress. And so that's

why this will continue to remain the

bottleneck in my opinion. And there's a

lot of risk as well because if you do

encounter another Deep Seek moment here

where there's a vastly more efficient

model that's been built with a very

different vertically integrated

architecture

and you built out all this capacity and

you're like, damn, that's I overbuilt.

there's something far more efficient

that can run on on on people's local

devices, their MacBooks, their Windows

PCs.

Yeah. Like you're probably freaking out

then. And so you hope that

>> How likely do you think that is though?

>> It's probably like 20% 30% chance. The

reason I think there's some possibility

is that because of the export controls

um you are so the deepseek is not

building with the Nvidia stack. they're

building with the Huawei stack

and because there are export controls on

not just the Nvidia GPUs but also on

HPMs

these um architectures that that DeepS

building are far more like memory

efficient they made innovations on the

KV cache to be really small enough that

you can host it on the SSDs

and you don't need high bandwidth memory

for inference time and they're going to

have a completely different architecture

for inference, completely different

architecture for storage cuz they're not

allowed to use the 3D nans. So their

architecture is going to look it's not

just the model architecture. The model

architecture is already pretty

different. They've made innovations on

the attention layer. They made

innovations on like the the training

algorithm so that it doesn't consume a

lot of interconnect capacity. So they

they've made a lot of they basically

their whole stack is getting vertically

integrated to their hardware and their

chips and their fabs and so on and so

that's a very different bet from what

America's making.

>> Do you think the export controls have

helped or hurt us? jury still a lot

shortterm it's helping because the only

reason I my belief the only reason where

why there's even like a 12 month gap

between open source and frontier is

export controls it's definitely helped

and and and definitely like companies

like anthropic lobbyed very hard for it

but um there is a chance that because of

that they now get really good at the

physical layer and One advantage they

have is they can actually build data

centers

a lot a lot a lot faster. Power is not a

problem. Permits are not a problem.

People are not a problem. Labor is not a

problem. Expertise is not a problem. And

so by forcing them to go out there and

build all this, you're converting them

into a far more

like potent competitor.

>> Do you think we still dramatically

underestimate China's capabilities?

>> I think so. Because if AI is like not

just digital, that's also physical AI.

You got to build fabs, robots, chips and

harness the energy really well and um

package it into local devices.

I think they have a lot more advantages

than America.

>> How important is it that we have our own

TSMC in the US? So TSMC is actually

there is a fab of TSMC in Arizona. Like

not a lot of people talk about this but

TSMC is investing like $150 billion into

that into into building American fabs

and um they've already invested $40

billion or something like that. 60

billion last time I checked. So there is

a TSMC in Arizona that's coming up.

There's also um Intel and that's why you

know American government owns 10% of

Intel. U Nvidia and SoftPank own 5%

each. So there is a lot of investment

going into an American fab as well as

TSMC is investing into its American

fabs. Elon's building terra fab like I

think it people have woken up to the

importance of building fabs but um this

is also why China is particularly very

very competent because given the

capabilities of China that we just

mentioned there really articulately I

know it's a ridiculous question but sort

it um if I were to say to you your job

is to make sure America stays

competitive

what would you do to ensure that you

retained competitiveness in an

increasingly strong China.

>> I think I think take physical

infrastructure a lot more seriously and

continue funding it um and not like have

all these

you know I I wouldn't say meaningless.

It's more like not propagate fake news

around data centers

um about how data centers are polluting

and contaminating water or like they're

sucking up all the water um and and and

actually be fact driven and so you know

I hope our product helps there like you

you can you can go to perplexity and ask

any question and get fact checked on

your assumptions but yeah like it's very

important that we educate the public

um about what's actually going on in in

a language they easily understand and

not fear-monger, okay? Like not be like,

oh, like all their jobs are going to go

away like this, that like there's going

to be lots of amazing companies that are

going to get built with far fewer people

getting multi-billion dollar, multiund

million valuations with like 20, 30

people and propelling like trillions of

dollars of new GDP. Like let's talk

about how to enable that. let's talk

about how to build that and create a

more positive future together, right? Uh

instead of, oh, like 90% of the jobs are

going to be gone. Like you're all going

to get screwed over by our models and

like and and it's it's our it's our

moral duty to tell you all this like

blah blah blah. Like that doesn't make

any sense to me. Like you can't win by

saying that and also like complaining

about not being able to build data

centers fast. Do you think we've done a

complete disservice by having the

marketing message that Dario has had

that all jobs are going and it's all

doom and gloom?

>> Yeah,

I think so. I mean I think you know they

have contradictory messages in their own

like

uh different social

engagement so far where the most recent

one I heard was there is no evidence

that AI is taking over jobs.

But so I I I think there there needs to

be a consistent communication around

this. And

I also think that um very little is

being spoken about how AIs can help you

build companies in a very very different

way like the current AIS AI.

It it's already true that so many things

you would hire people for you can do it

with agents. But one way of looking at

it is like oh like what happens to all

the jobs. But the other way of looking

at it is like, hey, like I can I never

had the chance to go build out a company

on this idea that I've been having all

this all this while and maybe me and a

group of friends can come together and

build this and can you guys figure out a

way to give us compute credits or you

know Amazon gave a lot of compute

credits to a lot of startups like when

we started Perplexity

we had like around $200,000 worth of

Amazon credits and GCP credits and Azure

credits.

um that almost like together

cumulatively this was worth like a

million dollars in computer credits. Now

in today's world it's going to be like a

million dollars of computer credits. And

we're doing that like we we're funding

this thing called a billion dollar build

where we're giving a million dollars of

computer credits to any group of people

who have a credible path to building a

billion dollar company and I want like

thousand such companies to be built.

>> What did you think of Sam Alman giving

$2 million of tokens to YC companies

initially?

>> I think we should do more of that.

Yeah, that that's the right thing to do.

Like we should do a lot more of this

because you want new companies to be

built. Um and and and even if they're

worth multi00 million, right, it's good.

If there are thousands of them, like

that's a lot of new GDP. I I spoke to an

Betski before the show and she said how

AI pilled the team is for you. How big

is the team today?

>> It's like 400 people.

>> 400 people. How big will it be in two

years time?

>> I don't know. It's hard to say. Maybe

800 or,000.

>> So, will companies follow the same

headcount trajectory that they have

always followed and we will just solve

new problems. Or will they be

dramatically more efficient with a much

fewer number of people?

>> Definitely, they'll be dramatically more

efficient. Right. and and that's why I I

I am a believer in building a lot more

efficient companies

not and being an example for all these

companies ourselves like like people

should look at perplexity and be like oh

like with 400 people um you can build

like a multi like like I don't know like

20 billion $20 billion company um and so

that means with like 40 people I could

probably build a billion dollar or $2

billion

you know, and that that that's totally

doable. Totally doable. And um and and

so for us, maybe that means is with

4,000 people, we could be worth 200

billion. We we could be worth $2

trillion with like 10,000 people.

You know, I think I think that doesn't

mean it's bad for all the um hundred,000

people we did not hire for a typical $2

trillion company.

I would rather have those 100,000 people

be split into groups of like hundred

thousand groups like that and each of

those thousand groups are worth a few

billion dollars. That's awesome. And I

think a lot more people need to be

entrepreneurial.

Um there are people who would be bad

employees in any company because they're

just like difficult to work with. They

they don't listen to like instructions.

So like they don't follow like road maps

or not they're not like easy to

collaborate with. But maybe the the flip

side of that is those those are the kind

of qualities that founders typically

have.

>> Ain there is a population and a very

large population that are not AI native

people that are not using AI to improve

workflows, improve efficiency.

What would you advise them?

>> Get started. First steps get started and

and and channelize your curiosity.

Right. Um, you don't need to use AIS to

do your existing work. If that's if your

existing work is boring to you, you

probably won't enjoy it even if you use

AIs to do it.

>> You got a lot of heat for saying people

don't like their job. So,

>> I I didn't say if you actually listen to

my interview, I did not say that. So,

people want clickbait articles and they

take something I said in one sentence

and out of context and make it into a

headline. What did you say? I I

specifically said this. Hey, like there

are a lot of people who don't enjoy

their jobs. Does any like By the way,

the fact that that that that thing went

viral is not because I was completely

wrong. I think a lot of people resonated

with the fact that I was actually honest

in saying a lot of people don't enjoy

their jobs. And that has nothing to do

with your economic position or standing

in society. You might even be like

really wealthy but doing a job that you

completely don't enjoy and like

destroying like the peak years of your

adult life working on something that is

horrible or like like depressing. So

like my point is that if that's you and

if the reason you could never leave your

job is because you were always worried

if you how would you build a company

from scratch? Like there are all these

things to figure out how you have to

hire a lot of people. Oh, you have to

like set up an office this that. Like

that's changed. For the first time in

history, you can get started on an idea

with like one or two other friends and

and and and maybe have a real genuine

shot at building a billion dollar

company. Totally get that. Everything

that we've discussed today has been on

the back of unprecedented demand up and

to the right. We need more memory. We

need more data center supply. We need on

demand and server side. Everything's

like up and to the right. Seeing some

cracks in and Uber's saying, "I'm not

sure I'm getting the productivity gains

that I thought." Microsoft aligning with

them, putting a $1,500 token budget. Do

you think we will have a continuous up

and to the right acceptance that

productivity gains are unwavering? We

have to do this, or will there be

falterings along the way? I mean, I'm

sure there's going to be falterings

along the way and people are rightfully

freaking out about token maxing, which

is why I think you need some form of

hybrid agenic inference. You need some

amount of inference compute to run

locally that you're not paying for

tokens on um unmetered intelligence

essentially.

>> How will the best companies of the

future structure token budgets? My hope

is that they don't have to understand

that

they will be able to work with an

orchestrator who does it for them. It's

not going to be easy for you to

constantly keep track of like which

models are the best at what things and

how do you allocate oh this is the

budget for coding, this is the budget

for finance or like like how do you even

understand like which models are good at

each of those things and like how much

do you spend on each of these divisions?

You're not going to be able to keep

track.

>> I I had a friend on the show the other

day say that Google will be the token

king. They can produce the lowest cost

tokens out of anyone. They own full

stack TPUs, data centers, networking,

power, procurement.

Do you think that's true that they will

be the lowest cost token producer?

>> They have advantages all all advantages

one needs to have to be that. But they

underestimated the importance of coding

models and so they far behind the

frontier right now. So again, they could

catch up, totally capable, totally

competent team, but today they're not

quite at the frontier.

>> I was shocked the other day. I saw the

Cloudflare announcement that um now

agent traffic has overtaken human

traffic for them.

>> Why? Why are you shocked?

>> It was quicker than I thought.

>> Okay.

>> Personally, I thought that would happen,

but in two years, maybe not now.

How does the world change when agent

traffic far exceeds human traffic?

>> I think people are just going to have a

lot more agency.

That's it.

>> Do websites go away? Does design not

matter? Does the advertising model of

the internet die completely?

>> No, it doesn't. Because my belief is

that

the advertising model around like travel

or shopping or like u fashion are not

getting disrupted by agents because the

judgment is not objective.

Any anything where the judgment is

objective, the transaction is based on

objective judgment that's going to get

disrupted by agents.

anything where the transaction is more

subjective like the decisions are more

subjective like like what is the best

piece of furniture inside this this this

podcast like why this particular table

or like those kind of things

>> probably for the mic you would buy an

objective decision the table

>> you probably are caring about the

aesthetics of the room I think I I think

that's kind of how I I feel the world

will split and subjective things will

still be ad based objective things will

be agent based

I watched your commencement speech on

the back of speaking to Samir at Excel

and he said I had to watch it. So

obviously I watched it. Um and one of

the points you made was the defining

skill of the area is asking better

questions.

>> Yeah.

>> What question is no one asking today

that maybe everyone should be asking?

>> I think people need to ask more about

like okay assuming I have a lot of

agency available to me what do I do?

Imagine like I gave you a headcount of

like 100,000 people or 10,000 people

and and and

you know enough computer credits to run

those agents. What would you do?

Like let's say I ask you Harry like you

know let's say I you have suddenly like

10,000 agents at your disposal. What

would you do? Like I I remember you

telling me or not me but but in some

episode of yours where

>> you said you're only you only did this

podcasting because you felt like you

didn't have an arbitrage to go win deals

>> 100%. Yeah. It's why I still do it. I

mean I love what I do but yeah.

>> Okay. So you've gotten some amount of

distribution. So now assuming that you

can you you have let's say you could

spend $100 million on a genenic

inference and grounded with all the

connectors and stuff and it's all

working. What would you do to to with

with that capability to um further your

goals? Like what what what should your

goals even be then? I I think that's the

question I would ask assuming that in

the next three to five years you're

going to be able to like delegate

whatever digital task you want and and

with the right harness and agents and

like be able to delegate that.

>> Fundamentally it would be to build aic

infrastructure to be able to find,

identify, outreach, set up, win great

investments and have the media sit on

top and power that. that is intensely

difficult to do and would be the holy

grail to investing but like

>> that would power what my end goal

ambition is.

>> Yeah. So your goal is to be the you know

run like a 10 to 100x larger fund right

that that's basically what I'm hearing

from you.

>> So that's like let's assume it's like a

$40 billion fund from 400 million. Um

then all you got to ask is like assuming

I have all the headcount I need to do

this like how much faster can I do it? I

I think that's how I would frame this

question. I think Elon has like a

similar thing he spoke about once where

okay assume that a task somebody tells

you a task is going to take 10 years. Um

ask the question what would it take to

do it in 10 months?

Maybe it's impossible to do it in 10

months, but you'll probably get pretty

far asking those questions

compared to somebody who takes it for

granted that it's it's going to take 10

years.

>> All right, interviewer, we put it on

you. What's your 10year and how does

that look in a 10-month time frame?

>> I think our our mission beyond any level

of capitalism is to make the planet more

curious.

You know the product is always intended

to helping people ask the next question

and uh my goal is to truly realize that

like that level of agency

that needs to exist in this world is

quite not there.

>> I think I think that needs to be

grounded in numbers dude to make it like

possible. It's like me saying oh I want

the best investments

like which is why a $40 billion fund is

helpful.

>> Sure. I can say the same thing like 2

trillion you know it doesn't matter

right like 100x 10x 1000x these are all

like um motivational milestones

>> do you think will be a trillion dollar

company

>> yeah anyone can be a trillion dollar

company SKH and Samsung are worth a

trillion last last couple of weeks did

you know Samsung started off as a

grocery store did you know that you

didn't know that okay so it's true they

started selling dried

Seriously. Um, Heinix was um SK the SK

group started off as um um textiles

company. So, anyone can be worth a

trillion dollar company and like you

just have to work your way towards that.

I mean, the exact same logic for you

that you laid out for how can a company

be worth um hundred billion. Okay, you

said you need to make a $10 billion in

revenue. Isn't that the same for

trillion? Like you need to make a

hundred billion in revenue.

>> Mhm.

>> And there was actually some very

interesting data that CO2 revealed. I

don't know if you saw it recently, which

basically says about the probability of

reaching the next level of value is much

higher. So when you're at a billion,

it's like much more likely to reach 10

billion. 10 billion much more likely.

>> Yeah, that's true actually for even

people. Like it's way more likely for a

person with $100 million in in liquid

net worth to become a billionaire than

someone with $10 million.

>> Are you not worried about the wealth

inequality? Aaron, if we being blunt, we

both are very lucky now to live in kind

of nice worlds and rarified airs. Are

you not worried by just how much money a

very small number of people have and how

[ __ ] hard it is for everyone else and

that gap is getting bigger?

I think the way to like ensure that

that's not that doesn't remain the case

is to distribute the benefits more

widely. You got you got to let anyone by

the way the people who are using our

tools like I had an Uber driver I'm not

even like making this thing up so um as

honest as it can get. an Uber driver in

San Francisco um once told me that he

watched one of my uh YouTube interviews

where I explain how you can build a

product or a web app with an AI from

scratch, went on to do it and um um used

AIS to add like billing and all that and

that makes more passive income for him

than um driving Ubers and so he actually

reduced the amount of time he's driving

Uber because He he loves wipe coding new

apps and u that that already tells you

that

for the person with agency and a

positive outlook for the future,

anything is possible. And so if you keep

communicating

all the negative things you can about AI

and wealth inequality all the time and

that's the only thing news uh and press

writes about,

I think it'll perpetuate and people will

only think the bad things. And so it's

it's it's very essential that if you

think you're already doing well, it's

very essential that you talk about what

are all the things that can go well and

give hopes to people who were once upon

a time like you like you you were you

didn't you you started this um

podcasting circuit like when you had

nothing, right? So

>> nothing.

>> Exactly. So it's possible. So you got

you got to talk more about that than be

like oh I feel so guilty that I made it

and now I'm like you know what about all

these people who haven't made it like

you can also make it.

>> I I think I have a more pessimistic view

of actual general public which is I

don't think that many people have

agency. I think a lot of people have

victim mentality.

>> You got you got to help them. Like I

think that's that's the most important

thing.

>> I think they got to help themselves.

>> Sure. But people will help themselves

once they see that okay like I kind of

want to be like this guy. let me let me

work hard. You need an example, right?

Um it's not like nobody can become um

get in shape. Like it it takes

discipline.

>> Takes discipline. You got to get rid of

bad habits. And so

>> and now is the best time ever to change

your life in 12 months. Like the ability

to go from nothing to to actually

billionaire in 12 months is now possible

in some respect.

>> Yes. And so I look, I'm not saying

everyone's going to make it and

everyone's going to be worth a billion

dollars.

>> Isn't that the caption from this this

show, Arvin? Everyone's going to make

it.

>> Anyone has the potential to make it.

>> So it's it's it's as likely for

Perplexity to become worth $2 trillion

as as a founder who's yet to secure your

funding to be worth a billion dollars.

So it's it's equally hard. Equally hard.

And um and I think you just have to give

yourself, you know, shots at the goal

and um be curious. That's that's the

message from the commencement speech. Be

curious.

>> We have SpaceX. We have Anthropic. We

have Open AI going public. It feels like

someone's kind of shot the gun and the

race is on. Is there enough money

to fund three such large IP?

>> There will be some reallocation for

sure.

like um there there might be some

holders of like SAS stocks who would put

it into anthropic or something. Let's

say you believe that enterprise AI is

going to take off. You might want to

hedge between having a lot of Microsoft

stock and Salesforce stock versus like

putting some of that into anthropic. So

let's say like Vanguard or Black Rockck

own like you know cumulatively they own

like $200 billion of Microsoft and

Salesforce. They might be like, "Okay,

I'm going to take 30 40 billion of that

and put it into anthropic."

Fine. You know, not a bad bit to make.

>> What happens to all the enterprise SAS

companies that are public growing? Yeah.

Fine.

>> They have to they have to weather the

storm.

>> Is it a storm or is it a continuous

precipitation?

>> I think you have to bring down the costs

and produce new value.

Salesforce has done well because they

always went and bought the next thing.

If you're just selling the same

software, you're probably not going to

be around. IBM is still around because

they went and bought Red Hat and

Hashikarp and now they're buying

Confluent. So, there are ways for these

companies to stay alive and extend their

lifespans and stuff. It's obviously

going to be hard to preserve a brand

that's as relevant

like like I don't think the IBM brand is

that relevant anymore in terms of like

evoking an emotion and people to go use

their products but as a business it's

going to be awesome you know it's going

to be fine.

>> I have to finish on you said IPO in

2028.

I had to ask this. I woke up to this in

my like you know um group. We have a

team WhatsApp and it's like ask IPO

2028. I hope I hope it can be sooner

than that.

>> When do you know when you're ready? Like

is there like a billionaire? Are you at

500 million er now?

>> More than that. Far far more than that

actually.

>> Really?

>> We we're not ready to share it, but um

growing really fast.

>> Revenue growth matters much more to you

than profitability

>> today. I think in general, by the way,

you can look at public markets. Um

people want topline growth.

more than um bottom line efficiency

right now because it's very hard. It's

it's rare.

>> Well, you definitely need one.

>> Of course, sustainable businesses,

>> you need to have a model in place to get

the bottom line efficiency when that

becomes the objective and and you need

to also like have a path to getting

there.

>> Where are you cost inefficient today

where you expect to be significantly

better in 2 to 3 years? We're training

our own models, post- trainining it on

top of amazing open source models, and

that will bring down the cost that we

currently spend on Frontier model

tokens.

We expect to continue to use Frontier

models for designing new experiences and

new capabilities that do not exist today

in our products. But whatever exists

today in our products right now, we

expected to completely re rely on like

models we own and serve ourselves. And

that's

going to be the best way to bring down

the costs and increase our margins.

>> Will the largest enterprises in the

world all be fine-tuning open models to

have tailored models that are much more

specific to them?

>> Absolutely. Because it's in your

incentives to bring down the cost.

>> Does that not provide another bad case

for the large frontier model providers?

>> Frontier model providers will only

remain relevant if they remain at the

frontier. If for 6 months you're not

seeing a new capability,

it's bad for them.

And so that's the uncomfortable nature

of this field. You no one's ever in a

comfortable position. Like I said in the

start, no one's no one can relax. This

is

>> [ __ ] a hard business. It's got

harder.

>> It's going to get even harder. And and

um that's the nature. This is the the

price is too big. Like you've never seen

like like take entropic. I think it's um

worth like one to one and a half

trillion some something in that range.

That's basically the valuation of meta

and and and this all was created in like

6 years.

Meta took like 20 years to build. So the

price is so big and so no one can um no

one can be comfortable

and and and and and anyone who's winning

today can lose tomorrow including

including the mod providers.

Previous this year, there was like a

three-month period where people were

like, "Oh, Py, what's happening with

Pacity?" Do you pay attention? Do you

give a [ __ ]

>> Of course, I pay attention to all that.

>> Do you care? There was one in particular

in San Francisco. Do you remember where

they were like, "Oh, what's the company

you had short?"

>> Yeah, we were voted the most likely to

fail. Cursor was voted the second most

likely to fail. Open AAI was voted the

third or something. Um,

>> you didn't give a [ __ ]

>> I I feel like we're all doing well.

Curser, I think, is getting sold. SpaceX

Open AI

>> is

>> going public soon.

>> We tripled our revenue since that

>> since that uh judgment was made. So

brought down the burn by more than 50%.

So I I don't know like my my my sense is

that um I also feel most of those people

who sit on these like meetups and vote

don't actually build anything useful.

Yeah.

>> Uh, okay. We're going to do a quick fire

around because, uh, I could talk to you

all day. Um, first one, what's one

widely held belief that you think is

completely wrong?

>> I think a lot of people are obsessed

about like, you know, identifying a mode

in the first year or two of their

company. But, um, I think like the only

shot you have is move fast. like veloc

in my mind like moving fast is a way of

expressing humility because you you're

constantly making contact with the world

and trying to question your assumptions

all the time.

>> Where are you still moving too slow

internally today?

>> I think we can be even more AI.

It's insane I'm saying this because we

are building some of the most

interesting AI products and internal

adoption of our own products, our

competitors products can be even higher

and and um this is despite us being

extremely

um agent build internally and trying to

delegate as much to agents. Yeah, that's

where that that's like a big area for my

my hope is that we can turn this company

almost into an AGI and and um have that

doesn't mean no humans work here, but

there will be an AGI that has all the

context it needs to run different

divisions of the company

in a semi-autonomous way with some

scaffolding provided by humans here and

there. And and that's not that's going

to feel that's not going to feel scary

at all. We'll normalize that that

feeling very fast. It's just going to

feel like 10, you know, uh the 10x

engineers running certain aspects of the

company.

>> If I gave you unlimited money, what

would you do today that you're not

doing?

>> I would build data centers.

>> You would?

>> Yeah.

>> In space?

>> I don't have expertise to do that, but I

would I would start with land on Earth.

You know, I think there's a lot of land

and and maybe you can be resourceful in

securing permits and power in different

countries, but I would start there. I

think it's, you know, I like I said,

like I think physical infrastructure

buildouts is like the return of the

industrial age again

like like the the the forefathers who

built the industrial revolution,

um oil pipelines, steel bridges,

factories producing cars, all these

things that we take for

granted today were built by people who,

you know, spend a lot of time thinking

about how to scale these things in a

costefficient way and so um we need to

do that a lot for AI and um yeah that's

what I would do of course you you you

cannot just be building infra you need

to be able to utilize all that infra to

producing valuable output tokens to the

user

but um we're already good at doing that

so infra is the thing I would focus on

you can buy and hold for 10 years SpaceX

anthropic or open AI the three IPOs

coming in the next few months which you

buy and hold for 10 years and why

>> SpaceX

why it's an end of one company

like Enthropic and OpenAI can claim they

do whatever each other does but u um

SpaceX is the only company building

space infrastructure for connectivity.

Have you been on a flight with Starlink?

No,

>> you should.

You will hate being on a flight without

Starlink after that. Imagine we can

record this. I can watch this podcast

while flying on a plane.

Starlink lets you do that. That's just

one aspect of the business. That's just

one aspect of

>> one small aspect of the business.

>> Yeah. Like there's a lot of like I'm

excited about possibilities to travel

from Australia to like uh San Francisco

in like 30 minutes. You know, all this

feels like sci-fi, but I'm excited about

all these possibilities.

>> What job does not exist today that will

be incredibly common in 5 years time?

>> I think it already exists. So, if the

forward deployed engineer is definitely

on the rise, I guess like people with a

really good sense of like um quality

control.

Maybe a better uh way to answer this is

like most jobs that exist like valuable

jobs that exist are usually like

reincarnations of something that already

existed.

Like so I don't think we're going to see

completely new things. It's just going

to reincarnate in different ways.

>> You can advise your little sibling who's

finishing university today and just done

a computer science degree. One thing,

what would you advise them?

>> Stay curious.

Don't don't don't give into like FOMO

and trying to max out on something here

in the short term. Like don't go to

Twitter and feel like a loser that

people on Frontier Labs are getting so

rich and like you everything feels

hopeless to you or something like there

is so much more to build like we are

just getting started like the the the

application layer era or like

infrastructure buildouts there there's

like a lot of opportunities we are

seeing more spinouts from open AI

anthropic you name it every single day

do we have hundreds of these neolabs

in vertical models.

>> No, not not a big believer in too many

of them. I think you got to produce some

differentiation. That's the most

important thing. Um like like I I if

would you call Deep Seek a Neolab?

>> No.

>> Why?

>> I think very stupidly for me I don't

call it a Neolab because I I attribute

Neolabs like spinouts from larger labs.

>> I see. and and kind of verticalized

which is probably wrong on both par like

axes

>> but it's horizontal and it's not a spin

out.

>> Yeah. I mean I kind of like the idea of

labs taking a differentiated bet. Okay.

If somebody really questions the

transformer architecture itself or

somebody really questions needing to

build on Nvidia GPUs or something like

that like like foundational bets makes

or or somebody questions or somebody

goes out and builds for robotics models.

I think I think that's like somewhat

uncorrelated and different and that

makes sense for a lab, but I feel like

they're like just labs for the sake of

being lab and I don't think they're

going to make it.

>> Can you paint for me? I I do like this

one. What's the most plausible story

whereasty becomes a trillion dollar

company? What do you do then? The

orchestration layer.

>> I mean, accuracy and orchestration is is

is like two goals that have been

consistently true since the beginning of

our company. So I think we'll continue

to do that. We'll be orchestrating

across devices, chips, models, tools,

files, connectors, everything. Right. So

what would I do once that happens? I

don't know. We we'll chart our path to

10 trillion.

>> Are you happy now? But are you are you

enjoying this?

>> Of course. I mean, I wouldn't like

there's so many things I could be doing

if not for this. And um I think the

process is is is what motivates you. So

you asked me I think somewhere in

between you need to give me a number of

where you want. I don't I don't work

like that actually. I I like for example

like the these numbers like getting to

two trillion or 20 trillion

are are exciting but like that that

doesn't motivate me. It's it's hard to

get motivated by wealth. You you you

want to get motivated by impact. Who's

the smartest person you've met? Final

one. You've met Jensen Hang. You've met

the best of the best. I've been

fortunate enough to Who's the smartest?

>> People are smart in their own ways. It's

hard to compare. Like I met Jensen,

Elon, all these guys and like Bezos.

>> What was it like meeting Elon?

>> Amazing. I mean Elon's like a very uh

focused person like like that. He might

not appear that way on Twitter but you

know with a lot of like random tweets

but he's extremely laser sharp focused

on whatever he's doing at that moment in

time. Actually the the one skill that as

an entrepreneur that I would really like

to take like build from somebody like

him like take from somebody like him and

have it for myself is that ability to

just zone out of all the other things

that's happening in your business or

other businesses and just focus on that

limiting problem right now like the

bottleneck problem and and and and

ignore everything else. It's very hard

to do like even within perplexity I

cannot just focus on like one part of

the business alone. It's very difficult

like I'm I'm always looking at other

things simultaneously. And um his style

is to just always look at the limiting

problem and just ignore everything else.

And uh that's very hard to do because

you you actually have to be really good

at concentration.

You you have to be really good at

ignoring

even important things which are

distractions to your core objective

right now.

>> Was Jensen hang what you thought he'd

be?

>> Far better.

>> Really?

>> Yeah. Jensen is so truth seeeking. It's

insane.

I think he or somebody else told me or

read in a book that he

um is so intense that he wakes up every

day and tells himself that he sucks

and goes in like like he's so intense

that he tells everybody around him that

they're 30 days away from going out of

business. Think about it, right? $5

trillion

um guaranteed to make $500 billion in

revenue in the next two years. Um

and um has the most advanced chips in

the world and and and he operates with

that mentality that he could be 30 days

away from going out of business. That is

what it takes to be Jensen Huang. And uh

there's so much to learn from these

guys. There's so much to learn. I think

uh there's one aspect of like you know

being comfortable where you are thinking

you made it uh you know that that feels

good to get here so far but these guys

are not stopping like I I don't think

Elon wants to stop at uh if you look at

his pay package for SpaceX it's

structured around um creating a colony

in Mars with a million inhabitants and

uh building enough comput in space so

that's why it's not like motivating to

be

worth a 10 trillion in net worth or

something. you know, if if he does these

things, I'm sure he's going to get

there, but um it's more motivated around

like making the impossible things happen

and and and having like that long-term

outlook like you um I think that has

been the biggest thing to learn from

maybe these two individuals in

particular is um

a lot of people view this like

entrepreneurship as like oh if it wins

if if I win and I have a great outcome

and I sell my company. I would have like

generational money. I don't have to work

ever again. And then what you end up

like like just staying at home and like

your your your kids will obviously have

like trust funds and they're not going

to get inspired watching their dad play

paddle.

>> Yeah. You know, you're not going to set

the right example for them. and they're

not going to be able to take your wealth

and multiply it cuz they they didn't

watch somebody who actually did that.

You they you did it before

they they they were like adults. And so

um I think you always need to be doing

something. Um like like Jensen said some

recently that he hopes to die on the job

or something like that. Like that's the

attitude you need to have. Like you got

you you need to work forever. I was so

upset though when Jensen said, "If I'd

known how hard it was going to be, I

wouldn't have done it." When he did, I

don't know if you saw that into I was

like, "Oh,

>> yeah. I think it's pretty hard, but you

you don't do it because you do it

despite that." I think I think that's

how it works.

>> Arvin, listen, this has been so

fantastic to do. I so appreciate you

taking the time while you're in London.

So, thank you so much for joining me.

>> Appreciate it.