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Zuckerberg's Secret Plan To WIN The AI Race | Meta AI Chief Reveals Future

Varun Mayya21:58

Transcription

What's it like working with Mark? What

are some things that you've had a

completely different experience with? I

think one of the things that's really

struck me in working with him is how

quickly he sees the future.

>> Ladies and gentlemen, Mr. Alexander

Wong.

>> Back in 2022, he became the youngest

self-made billionaire in the world.

>> Chief AI officer at Meta.

>> Started a company when he was still a

teenager, went through Y Combinator, and

then built scale AI. Alex Wang is the

most expensive aqua hire yet, $4.3

billion. He's a fascinating character

within the valley

>> and he now leads Meta's super

intelligence labs division.

>> You work very closely with Mark. You're

building a meta super intelligence. What

is meta super intelligence? You know,

the discoveries that we make over the

course of the next 5 years in terms of

AI are going to be some of the most

monumental discoveries of human

civilization has ever made. You know, I

have the Meta Gen 2 Raybands, right? And

I just feel like maybe you guys are

running a very old version of Llama

there. It just doesn't feel like modern

AI yet. Do you have an estimate for when

we'd have modern AI on the glass? uh

very soon.

Ladies and gentlemen, I'm with somebody

um who I think is very special, who I

think um you know is somebody who

spearheads the AI race but is slightly

invisible to the public. Like you're

much less public these days compared to

everybody else in AI. So, thank you so

much for doing this. My last interaction

with you was I think at breakfast. We

did breakfast at MEA uh at the campus.

And you know, one of the questions I had

for you at that time was you had this

fidget spinner

>> and it was a very very different fidget

spinner. I I don't know. I've never seen

anything like it. What was it called?

There's a there's this great I think

it's a British company called Metmo that

makes these uh very uh uh high-end

fidgets. Uh it's a it's a good company.

It's

>> very cool. We're sending Metmo some

sales. Uh but but you know, Alex, I want

I want to start with this question,

right? Like what is it that you do now?

I know you from the scale AI days,

right? Uh but today I know that you work

very closely with Mark. You're building

a meta super intelligence. What is meta

super intelligence? Uh for everybody,

you know, watching. I mean first uh Mark

and and myself we very strongly believe

that this is a very special time in

human history and you know the

discoveries that we make over the course

of the next 5 years in terms of AI are

going to be some of the most monumental

discoveries of you know frankly the

human civilization has ever made. And so

MSL metsumer intelligence labs was

entirely dedicated towards how do we

build and develop the most optimal

organization to be able to both deliver

the breakthroughs and the scientific

advancements necessary to deliver super

intelligence and then also build the

products that will enable this

technology to be deployed to billions

and millions of people worldwide. And

one of the things that makes Meta such a

special place for all of this is the

fact that we have such incredible scale

and reach through our products. You

know, three and a half billion people

utilize our platforms every single day.

That puts us in an incredible position

to actually bring this technology to the

world in a way that's really different,

we think, from many of the other AI labs

out there. And then we also you know um

we had the opportunity to seven months

ago when I joined really kind of design

the org um and design the team from a

blank slate on what is the optimal team

look like for the future of super

intelligence. So you know we really

embraced how do we build the best

possible scientific foundations for this

organization? How do we have the highest

talent density? How do we bring the very

best people together and build the best

possible environment for breakthrough

research to occur?

>> Interesting. um how do you balance

commercializing some of these products

along with research because from my

understanding um and what is available

publicly it seems that you come more

from a products perspective like you've

done scale AI you've helped some of

these product companies really grow uh

how does it feel like going to research

and how do you balance both at the core

we need to be researchled because

fundamentally um we are in such a

special time and and moment when it

comes to frontier AI I technologies and

breakthroughs that um I really think

that that uh you need to be very focused

on the research um and the opportunity

to actually push the frontier to have

very real breakthroughs uh in super

intelligence is just is just magical.

And so we're frontier or we're uh

research driven to be able to push the

frontier, but we actually view it as

like a flywheel internally for all of

meta. So um by building frontier models

and building models that um are uh are

pushing the boundaries of super

intelligence that enables to build

incredible products um and it's kind of

a base material that allows us to build

some of the most interesting and

innovative consumer products in the

world. Those products as they gain scale

then give us the ability to grow our

infrastructure footprint and to build um

you know large scale infrastructure some

of the largest scale infrastructure in

the entire world and then that will

enable us to build even greater models

and continue scaling our research

efforts. So, um, it actually is like one

virtuous flywheel within Meta. And I

think that's a lot of what excites me as

well is that we're not, um, uh, I think

we view this as a very evolving, uh,

and, um, and continuous discipline to

continue advancing the models, products,

and infrastructure all in tandem with

one another.

>> So, what's the team like? Like how do

you structure the research team and

where where is handoff to to products?

like how does it like if you can give me

like for example an example of something

you're working on what's the team

structure for that like and then when is

handoff to product that would be very

useful yeah so so actually one of the

things that has really struck me has

been um if you look at a lot of the most

successful AI products and a lot of the

most successful AI developments that

have happened they come from a um a

tandem effort between research and

product so um we're we're I think past

the phase where it's just about research

in you know a corner and then that hands

off to product people and then they

deploy that. I think if you look at a

lot of the biggest breakthroughs like

chatbt or cloud code or a lot of the

things that we're working on it comes

from um you know researchers who are

thinking about the product and product

people are thinking about research and

then working handinhand with one another

to sort of co-develop the best possible

products. Some of the things that we're

really excited about are personal

agents. you know, recently, um, Manis

released, uh, agents that are working

247 on behalf of our users, um, and are

constantly working to, uh, you know,

accomplish your goals or make your life

better. And we really see that as, um,

this is the first of, uh, a a whole

series of of, um, products that we're

excited to release around personal

agents. It's one of the areas where we

think there's some of the greatest

opportunity to actually give a more

powerful version of AI to every single

person in the world and I think will be

one of the things that we'll we'll look

back on a decade from now and view as

one of the big breakthroughs in AI

productization. Yeah, I I really like

Manis. I remember using it, you know, a

few months ago. I keep going back to it

again and again. It's a cool product.

Um, do you have a sense of what Meta's

identity is in the AI battle? I feel

like, you know, Anthropic has one. It

feels a very It feels like it feels very

um, you know, machines of love and grace

style. Open AI has one. It's very

consumer pop friendly one. But like

Meta's identity is still very much on

device. It at least to me as a consumer,

it feels like ondevice. It's there, but

the device is like up front and center.

But is there an identity you're building

for for Meta Super Intelligence Play?

Yeah, I think um I think what we really

believe in are personal agents deployed

globally. So, one of the things that

makes us unique is that we are a global

company and uh we have half of the world

using our products every single day. I

mean that is just um an incredible

amount of reach and it means that as we

deploy powerful personal agents to

everybody in the world. It creates

totally new opportunities I think um are

very hard for any other lab to actually

fully accomplish in terms of what does

that mean for entire communities? What

does that mean for countries? What does

that mean for um you know the whole

world as we all on board onto this

technology together. Um the other thing

that we're really excited about uh is

the sort of continued um what does the

hardware vision look like, right? And uh

this is an area that we've been

investing in for many many years are

wearables and sort of the the next form

factors for consumer hardware. And we

think that with personal agents um that

vision has never been more real where I

think you're going to want your personal

agent to be on a constellation of

peripherals uh in the future and you're

going to um we're going to expand beyond

the phone into a world where you're

going to want your personal agent to be

with you in a bunch of different ways.

uh that that um that will always be on

be, you know, see what you see, hear

what you hear, uh and will be able to

just help you in a way that's much

deeper than and then than even the

devices today are able to help them.

>> Cool. Like a like an always on friend

who's with you on all your devices.

That's why cool. I think there's a lot

of other companies trying to do that,

but I think you have the step ahead

because I've already worn the meta

hardware products and I'm already

comfortable with it. So it's very easy

to to say well here's an update which

which allows you to to have you know

this god tier intelligence on which

actually brings me to a an aside point

which is you know I have the meta gen 2

ray bands right um and I just feel like

maybe you guys are running a very old

version of llama there um it just

doesn't feel like modern AI yet.

>> Yeah. Yeah.

>> Do you have an estimate for when we'd

have modern AI on the glass?

>> Uh very soon. Um you know I think I

think uh we've been you know when I got

when I got to Meta something like 7

months ago um the entire focus was let's

set up this organization

uh in the right way for the long term so

that we're not we're not just setting us

setting ourselves up to cut a corner

here or to optimize for some short-term

outcome but but mortgage the long-term

opportunity. We're going to set up it

with the right set it up with the right

scientific foundations. We're going to

set up with the incredible talent

density and the focus on long-term

science. We're going to remove

artificial deadlines so that we're

actually building the technology at the

best pace. And what we've seen from that

is actually over the past 7 months,

we've built the foundations incredibly

quickly. And now we're at a moment where

I think over the coming months, you're

going to see incredible velocity coming

from us. And that'll continue throughout

the course of the year. We think that um

over the course of the full year, we

will really be pushing the frontier in a

very exciting way across many dimensions

of the technology. Um so uh so stay

tuned. I know it's been a long wait for

many people, but uh we're really excited

about what's coming.

>> Yeah, because I I just feel like that's

a very easy, you know, sort of upgrade

for me, right? Or everybody else, which

is just have those glasses be super

because I I just feel like they're being

artificially restrained by a very old AI

on it. And I just know what modern AI

can do. and you already have access to

the camera, you already have access to

audio, uh you can do wonders, right? Uh

but

>> to your point, we've already sold

millions of of units and it's already a

ubiquitous technology and and so I I

think the opportunity is just immense.

>> Yeah, I think it's one software update

away from superpowers. So, I'm very very

excited about that. But I think it's

incredibly mature of you to come in and

first build out the AUG. And it's

something that I've learned like this

year uh compared to you know five or 10

years ago to build out the AG for

velocity a year later. Um how do you

learn all this? Like what's the

difference between you as an 18-year-old

entrepreneur you know starting scale AI

versus today building you know what

you're building today? Like what's the

difference between you as an as as an

entrepreneur?

>> Yeah. I mean I' I feel like I've learned

just so many different things. Um I

think I think one thing when you're when

you're young you're very impatient,

right? And uh and I think you know this

as as well as I do. Um you know I

started my company uh right out of

college, dropped out of college and um

you know you you're so impatient to make

things happen that and that's both a

great strength and a great weakness.

Like I think on the one hand you do you

can make things happen faster than than

other people would expect but you're

also um uh not necessarily setting

things up to be long-term sustainable

and to be um to create long-term

advantages. And one of the things that

um I've thought a lot about, you know,

if you sort of study the history of uh

of great businesses in Silicon Valley or

even just broadly in the in the sort of

like history of business, the ones with

true staying power have built some sort

of foundation that is actually very

difficult to replicate. And it's

something that is it's almost like a

seed that is planted and grows over the

course of of of you know, in many cases

decades. And so I think a lot of um a

lot of how we think about how we thought

about building MSL and how we think

about building teams and um you know

accomplishing big things going forward

is how do you set something up such that

uh it has durability and it has a um it

has a differential point of view all the

way down to the organization and that

enables it to grow and expand and

develop in a way that is um that will be

continue to be differentiated long into

the future. So I I think this sort of

mix of you know I think I think you know

to put it pithily I think you can't let

your impatience drive you um too far and

you need to um it's important to always

be thinking about what foundations are

you building and what does the long-term

story look like.

>> Yeah. You know if I had to summarize the

last 10 years of my you know

entrepreneurial career I would come up

with the same insights. slow

intentionally slow down build build for

the long term and then eventually and

also put the right people together right

because you know and and they need like

three or four years to bloom so I I

totally get you hey what was the scale

exit like like I mean I don't even know

if you can call it an exit right so

>> they're still going

>> yeah they're still going right like I

would say what is the what was the

relationship why do you go decide to

work at you know Meta super intelligence

like how did that conversation with Mark

happen give us some some insider your

information.

>> Yeah. Yeah. Well, um I mean it was

incredibly non-standard. Um and I think

the way it happened was even um was very

surprising because it took you know Mark

is obviously quite a bold and visionary

leader and I think it really took um you

know uh that level of vision for for the

whole thing to come together. Um, and I

mean it was an incredible I think

milestone for scale and everything that

we've done. Um, and scale continues on

and I think that that team is continuing

to execute and deliver uh on really

incredible um outcomes for enterprises

and governments and um continues to uh

crush it. But you know the the

opportunity that we saw really was um

you know there's it was an incredible

milestone for scale and it was a way to

kind of give back to all the people who

have uh supported scales um you know

success to date including the investors

and the employees and and everybody

involved while also um setting scale up

for the future and and frankly the

opportunity that I saw with with Meta

was was just astronomical. I think that

um you know sometimes in the middle of

these AI races everything just feels so

um pressurized so you can sort of lose

sight of things and and um I think at

that time

you know a lot of people were weren't

giving meta the credit it deserved in

terms of I mean it has all the

ingredients for incredible success in

AI. It has the distribution. It has the

billions and billions of users. It has

the scale, it has the business model, it

has um the incredible talent, has the

infrastructure. And so all the pieces

were were really there. And I think the

opportunity to really um kind of lock

everything in in a way that allows us to

allows Meta to to really um succeed and

thrive in the long term was very

exciting.

>> Very cool. You know, I have I have this

question that I ask almost everybody,

you know, in the AI race, right? which

is uh you know I'm sure you have some

ideas and thoughts about AI that your

peers don't agree with right some way

it's going to go in the future or some

you know method of training or whatever

it could be right uh do you have an

insight that you feel your peers might

not agree with I'm talking about your

peers in AI I think some some people in

the industry agree with me on this but

um one of the things I think is is of

paramount importance is developing the

technology with extreme responsibility

And I think a lot of the concerns around

safety um you know both the traditional

concerns around AI safety as well as new

concerns around how do you ensure that

this technology is is used safely by the

billions and billions of people who are

going to use it every day. I think those

are incredibly incredibly important and

I think we're seeing this with as with

any new technology as it gets deployed

um you know they raise novel safety

concerns and the responsibility really

is on us to develop to develop the

technology um in in in a responsible

way. You know, the the other piece

that's very important for this is the

vision of the future that we see where

where it is a personal agent, something

that is sort of with you all the time

that you really trust with your goals

and your hopes and your fears and sort

of everything in your life. To build

that technology effectively requires

just a huge amount of trust from our

users, from the public, from

governments, from um from every

stakeholder that you could possibly

imagine. And so um we really take the

sort of the need to build safely and and

thoughtfully extremely highly and I

think this is shared by some in the the

um AI community. I think some people are

have you know moved away from some of

these commitments but it's something

that we're we're uh I at least take

extremely seriously. Would you have like

a chief philosopher to to set the tone

for your AI? I think Anthropic has

somebody like this now. Um, Gemini is

very like, you know, rate of refusals is

very high. It's very bland. Uh, would

you have as meta have a chief

philosopher to to set the tone for how

that AI behaves? Yeah, we we actually we

collaborate with uh a number of both

philosophers and psychologists to help

us develop and build the behavior of the

model in a way that we think will be

most conducive for um being helpful and

and empowering our users to accomplish

their goals. And and you know, it's

funny. One of the things that we've

spent a lot of time thinking about is

how do you develop kind of like a um uh

a mutual

uh you know, in some ways like a um uh

like a mutual relationship between the

between the humans and the agents where

the humans obviously um want the agents

to be successful and the agents want the

humans to be successful. um and and

figuring out how to engineer then

design. That is something that's I think

very important for all of this to work

out effectively. Very cool. I have one

last question for you because I've I've

taken a lot of your time. What's it like

working with Mark? What's his working

style like? Uh what are some of the

things that the public says that are

true in terms of working style? What are

some things that you've had a completely

different experience with? What's it

like working with Mark? Well, I think

first Mark is um I mean Mark is one of

the most you know notable individuals in

technology for you know the past few

decades and I think he um I think

there's a lot out there about him that

that is not fair from having worked with

him very closely. I mean first he is

just like in many ways a very regular

guy. He's a total family man. Um he uh

is very devoted to his children and his

family and his wife and um I think uh

he's his personal values I think are are

quite commendable. But what's more than

that, I think as a leader, he is um

incredibly bold and ambitious and um and

I think one of the things that's really

struck me in working with him is how um

uh how quickly he sees the future is

maybe one of the one of the terms I

would use. I think he is able to take a

technological advancement or something

that's happening um all the way at the

technology level and then really play

that forward in terms of what does that

mean for our users, what does that mean

for consumers, what does it mean for

businesses, what does that mean for our

entire ecosystem and then um work with

everybody on the team to make that

happen as quickly as possible through

Meta. So um I think he's been a very uh

uh I've I've feel very lucky to be able

to work with him. one of the sort of

like great entrepreneurs of our time.

Um, and uh, yeah, I think it's a real

it's a real pleasure. He enables me and

I think the whole team to dream bigger

than uh, than we would otherwise.

>> Very cool. Thank you so much, Alex. This

was very enlightening. I learned so much

about, you know, Meta Super

Intelligence. I can't wait for, you

know, superpowers to be on my glasses. I

also can't wait for the new ones, right?

Um, I saw the displays at at Meta

Connect, but uh, you know, I I don't

think they're available in India yet.

So, at some point I want to get my hands

on one and just, you know, use all of

the AI you put in there. I can't I can't

wait to see all the cool stuff you do

with the neural band as well. Um, so

good luck and uh yeah, I'm I'm I'm going

to continue buying and using your

products.

>> Yeah, it's going to be the um the future

will be here faster than we think.

>> Yeah, this year.

>> Yeah,

>> this year. Awesome. Thank you so much

and make sure you subscribe. Bye.