The following is a conversation with Mark Zuckerberg, his second time on this podcast.
He's the CEO of Meta that owns Facebook, Instagram, and WhatsApp,
all services used by billions of people to connect with each other.
We talk about his vision for the future of Meta and the future of AI in our human world.
This is the Lex Friedman Podcast, and now, dear friends, here's Mark Zuckerberg.
So you competed in your first jiu-jitsu tournament,
and me as a fellow jiu-jitsu practitioner and competitor,
I think that's really inspiring given all the things you have going on.
So I got to ask,
what was that experience like?
Oh, it was fun.
I don't know. Yeah. Well, look,
I'm a pretty competitive person.
Yeah.
Doing sports that basically require your full attention,
I think is really important to
my mental health and the way I just stay focused at doing everything I'm doing.
So I decided to get into martial arts, and it's awesome.
I got a ton of my friends into it.
We all train together.
We have a mini academy in my garage,
and I guess one of my friends was like,
hey, we should go do a tournament.
I was like, okay, yeah, let's do it.
I'm not going to shy away from a challenge like that.
So yeah, but it was awesome.
It was just a lot of fun.
You weren't scared? There was no fear?
I don't know. I was pretty sure that I'd do okay.
I like the confidence.
Well, so for people who don't know,
jiu-jitsu is a martial art where you're trying to break your opponent's limbs or choke
them to sleep and do so with grace and elegance and efficiency and all that kind of stuff.
It's a kind of art form,
I think, that you can do for your whole life,
and it's basically a game,
a sport of human chess you can think of.
There's a lot of strategy.
There's a lot of interesting human dynamics of using leverage and all that kind of stuff.
It's kind of incredible what you could do.
You could do things like a small opponent could defeat a much larger opponent,
and you get to understand the way the mechanics of the human body works because of that.
But you certainly can't be distracted.
No. It's a 100 percent focus.
Yeah.
To compete, I need to get around the fact that I didn't want it to be like this big thing.
So I basically rolled up with a hat and sunglasses,
and I was wearing a COVID mask,
and I registered under my first and middle name, so Mark Elliott.
It wasn't until I actually pulled all that stuff off right
before I got on the map that I think people knew it was me.
So it was pretty low-key.
But you're still a public figure.
Yeah. I didn't want to lose.
Right. The thing you're partially afraid of is not just the losing,
but being almost like embarrassed.
It's so raw, the sport,
and that it's just you and another human being.
There's a primal aspect there.
Oh, yeah. It's great.
For a lot of people, it can be terrifying,
especially the first time you're doing the competing,
and it wasn't for you.
I see the look of excitement in your face.
Yeah.
It wasn't. No fear.
I just think part of learning is failing.
Okay.
Right. So the main thing,
like people who train jiu-jitsu,
it's like you need to not have pride because I mean,
all the stuff that you were talking about before about getting choked or getting joint lock,
you only get into a bad situation if you're not willing to tap once you've already lost.
But obviously, when you're getting started with something,
you're not going to be an expert at it immediately.
So you just need to be willing to go with that.
But I think this is like, I don't know.
I mean, maybe I've just been embarrassed enough times in my life.
Yeah.
I do think that there's a thing where like it has people grow up,
maybe they don't want to be embarrassed or anything.
They've built their adult identity and they kind of have a sense of who they are and what they want to project.
And I don't know.
I think maybe to some degree, your ability to keep doing interesting things is your willingness to be embarrassed again and go back to step one and start as a beginner and get your ass kicked and look stupid doing things.
And yeah, I think so many of the things that we're doing, whether it's this, I mean,
this is just like a kind of a physical part of my life, but running the company,
it's like we just take on new adventures and all the big things that we're doing,
I think of is like 10 plus year missions that we're on where often early on people doubt that we're going to be able to do it.
And the initial work seemed kind of silly.
And our whole ethos is we don't want to wait until something is perfect to put it out there.
We want to get it out quickly and get feedback on it.
And so I don't know.
I mean, there's probably just something about how I approach things in there,
but I just kind of think that the moment that you decide that you're going to be too embarrassed to try something new, then you're not going to learn anything anymore.
But like I mentioned, that fear, that anxiety could be there, could creep up every once in a while.
Do you do you feel that and especially stressful moments sort of outside of did you just met just at work?
Stressful moments, big decision days, big decision moments.
How do you deal with that fear?
How do you deal with that anxiety?
The thing that stresses me out the most is always is always the people challenges.
You know, I kind of think that, you know, strategy questions, you know, I tend to have enough conviction around the values of what we're trying to do and what I think matters and what I want our company to stand for, that those don't really keep me up at night that much.
I mean, I kind of, you know, it's not that I get everything right.
Of course I don't, right?
I mean, we make a lot of mistakes, but I at least have a pretty strong sense of where I want us to go on that.
The thing in running a company for almost 20 years now, one of the things that's been pretty clear is when you have a team that's cohesive, you can get almost anything done.
And, you know, you can run through super hard challenges.
You can make hard decisions and push really hard to do the best work even, you know, and kind of optimize something super well.
But when there's that tension, I mean, that's when things get really tough.
And, you know, when I talk to other friends who run other companies and things like that, I think one of the things that I actually spend a disproportionate amount of time on in running this company is just fostering a pretty tight core group of people who are running the company with me.
And that to me is kind of the thing that both makes it fun, right?
Having, you know, friends and people you've worked with for a while and new people and new perspectives, but like a pretty tight group who you can go work on some of these crazy things with.
But to me, that's also the most stressful thing is when there's tension, you know, that weighs on me.
I think the, you know, just it's maybe not surprising.
I mean, we're like a very people focused company and it's the people is the part of it that, you know, weighs on me the most to make sure that we get right.
But yeah, that I'd say across everything that we do is probably the big thing.
So when there's tension in that inner circle of close folks.
So when you trust those folks to help you make difficult decisions about Facebook, WhatsApp, Instagram, the future of the company and the metaverse with AI, how do you build that close knit group of folks to make those difficult decisions?
Is there people that you have to have critical voices, very different perspectives on focusing on the past versus the future, all that kind of stuff?
Yeah.
I mean, I think for one thing, it's just spending a lot of time with whatever the group is that you want to be that core group grappling with all of the biggest challenges.
And that requires a fair amount of openness.
And, you know, so I mean, a lot of how I run the company is, you know, it's like every Monday morning, we get our, it's about the top 30 people together.
And we, and this is a group that just worked together for a long period of time.
And I mean, people rotate in, I mean, new people join, people leave the company, people go to other roles in the company.
So it's not the same group over time.
But then we spend, you know, a lot of times a couple of hours, a lot of the time it's, you know, can be somewhat unstructured.
Like, I'll come with maybe a few topics that are top of mind for me.
But I'll ask other people to bring things and people, you know, raise questions, whether it's okay, there's an issue happening in some country with some policy issue.
There's like a new technology that's developing here.
We're having an issue with this partner.
You know, there's a design trade off and WhatsApp between two things that end up being values that we care about deeply.
And we need to kind of decide where we want to be on that.
And I just think over time, when, you know, by working through a lot of issues with people and doing it openly, people develop an intuition for each other and a bond and camaraderie.
And to me, developing that is like a lot of the fun part of running a company or doing anything, right?
I think it's like having people who are kind of along on the journey that you feel like you're doing it with, nothing is ever just one person doing it.
Are there people that disagree often within that group?
It's a fairly combative group.
Okay, so combat is part of it.
So this is making decisions on design, engineering, policy, everything.
Everything, everything, yeah.
I have to ask, just back to jiu-jitsu for a little bit, what's your favorite submission now that you've been doing it?
What's, how do you like to submit your opponent, Mark Zuckerberg?
I'm in.
Well, first of all, do you prefer no-gi or gi-jiu-jitsu?
So gi is this outfit you wear that maybe mimics clothing so you can choke.
Well, it's like a kimono.
It's like the traditional martial arts, right?
Pajamas.
Pajamas.
That you could choke people with, yes.
Well, it's got the lapels.
Yeah.
So I like jiu-jitsu.
I also really like MMA.
And so I think no-gi more closely approximates MMA.
And I think my style is maybe a little closer to an MMA style.
So like a lot of jiu-jitsu players are fine being on their back, right?
And obviously having a good guard is a critical part of jiu-jitsu.
But in MMA, you don't want to be on your back, right?
Because even if you have control, you're just taking punches while you're on your back.
So that's no good.
Do you like being on top?
My style is I'm probably more pressure and yeah, and I'd probably rather be the top player.
But I'm also smaller, right?
I'm not like a heavyweight guy, right?
So from that perspective, I think, especially because if I'm doing a competition, I'll compete
with people who are my size, but a lot of my friends are bigger than me.
So back takes probably pretty important, right?
Because that's where you have the most leverage advantage, right?
Where people, their arms, your arms are very weak behind you, right?
So being able to get to the back and take that pretty important.
But I don't know, I feel like the right strategy is to not be too committed to any single submission.
That said, I don't like hurting people.
So I always think that chokes are a somewhat more humane way to go than joint locks.
Yeah.
And it's more about control.
It's less dynamic.
So you're basically like a Habib Nurmagomedov type of fighter.
So let's go, yeah, back take to a rear naked choke, I think is like the clean way to go.
Straightforward answer right there.
What advice would you give to people looking to start learning jiu-jitsu?
Given how busy you are, given where you are in life, that you're able to do this, you're
able to train, you're able to compete and get to learn something from this interesting
art.
Why do you think you have to be willing to just get beaten up a lot?
Yeah.
But I mean, over time, I think that there's a flow to all these things.
One of my experiences that I think kind of transcends running a company and the different
activities that I like doing are, I really believe that if you're going to accomplish
whatever, anything, a lot of it is just being willing to push through and having the grit
and determination to push through difficult situations.
And I think for a lot of people that ends up being sort of a difference maker between
the people who kind of get the most done and not.
I mean, there's all these questions about how many days people want to work and things
like that.
I think almost all the people who start successful companies or things like that are just working
extremely hard.
But I think one of the things that you learn both by doing this over time or very acutely
with things like jujitsu or surfing is you can't push through everything.
And I think that you learn this stuff very acutely doing sports compared to running a
company because running a company, the cycle times are so long where it's like you start
a project and then it's like months later or if you're building hardware, it could be
years later before you're actually getting feedback and able to make the next set of
decisions for the next version of the thing that you're doing.
Whereas one of the things that I just think is mentally so nice about these very high
turnaround conditioning sports, things like that is you get feedback very quickly, right?
It's like, okay, like I don't counter something correctly, you get punched in the face, right?
So not in jujitsu, you don't get punched in jujitsu, but in MMA, there are all these
analogies between all these things that I think actually hold that are like important
life lessons, right?
It's like, okay, you're surfing a wave.
It's like, sometimes you can't go in the other direction on it, right?
It's like there are limits to kind of what, it's like foil, you can pump the foil and
push pretty hard in a bunch of directions, but yeah, at some level, the momentum against
you is strong enough, that's not going to work.
And I do think that that's sort of a humbling, but also an important lesson for I think people
who are running things or building things, it's like, yeah, a lot of the game is just
being able to kind of push and work through complicated things, but you also need to kind
of have enough of an understanding of like which things you just can't push through and
where the finesse is more important.
What are your jujitsu life lessons?
Well, I think you did it, you made it sound so simple and were so eloquent that it's easy
to miss, but basically being okay and accepting the wisdom and the joy in the getting your
ass kicked in the full range of what that means, I think that's a big gift of the being
humbled.
Somehow being humbled, especially physically opens your mind to the full process of learning
what it means to learn, which is being willing to suck at something and I think jujitsu just
very repetitively, efficiently humbles you over and over and over and over to where you
can carry that lessons to places where you don't get humbled as much, whether it's research
or running a company or building stuff, the cycle is longer and jujitsu, you can just
get humbled in this period of an hour over and over and over and over, especially when
you're a beginner, you'll have a little person, just somebody much smarter than you just kick
your ass repeatedly, definitively where there's no argument and then you literally tap.
Because if you don't tap, you're going to die.
So this is an agreement, you could have killed me just now, but we're friends, so we're going
to agree that you're not going to and that kind of humbling process, it just does something
to your psyche, to your ego that puts it in its proper context to realize that everything
in this life is like a journey from sucking through a hard process of improving rigorously
day after day after day after day, any kind of success requires hard work.
Yeah, jujitsu more than a lot of sports, I would say, because I've done a lot of them,
really teaches you that.
And you made it sound so simple, it's okay, it's part of the process, you just get humbled,
get your ass kicked.
I've just failed and been embarrassed so many times in my life that it's a core competence
at this point.
It's a core competence.
Well, yes, and there's a deep truth to that, being able to, and you said it in the very
beginning, which is that's the thing that stops us, especially as you get older, especially
as you develop expertise in certain areas, the not being willing to be a beginner in
a new area.
Because that's where the growth happens, is being willing to be a beginner, being willing
to be embarrassed, saying something stupid, doing something stupid.
A lot of us that get good at one thing, you want to show that off.
And it sucks being a beginner, but it's where growth happens.
Well, speaking of which, let me ask you about AI.
It seems like this year, for the entirety of the human civilization, is an interesting
year for the development of artificial intelligence.
A lot of interesting stuff is happening.
So meta is a big part of that.
Meta has developed Llama, which is a 65 billion parameter model.
There's a lot of interesting questions I can ask here, one of which has to do with open
source.
But first, can you tell the story of developing of this model and making the complicated decision
of how to release it?
Yeah, sure.
I think you're right, first of all, that in the last year, there have been a bunch of
advances on scaling up these large transformer models.
So there's the language equivalent of it with large language models, there's sort of the
image generation equivalent with these large diffusion models.
There's a lot of fundamental research that's gone into this and meta has taken the approach
of being quite open and academic in our development of AI.
Part of this is we want to have the best people in the world researching this and a lot of
the best people want to know that they're going to be able to share their work.
So that's part of the deal that we that we have is that, you know, we can get, you know,
if you're one of the top AI researchers in the world and come here, you can get access
to kind of industry scale infrastructure.
And part of our ethos is that we want to share what's invented broadly.
We do that with a lot of the different AI tools that we create.
And llama is the language model that our research team made.
And you know, we did a limited open source release for it, which was intended for researchers
to be able to use it.
But you know, responsibility and getting safety right on these is very important.
So we didn't think that for the first one, there were a bunch of questions around whether
we should be releasing this commercially.
So we kind of punted on that for V1 of llama, and just released it from research.
Now, obviously, by releasing it for research, you know, it's out there, but companies know
that they're not supposed to kind of put it into commercial releases.
And we're working on the follow up models for this and thinking through how exactly
this should work for follow on now that we've had time to work on a lot more of the safety
and the pieces around that.
But overall, I mean, I just kind of think that it would be good if there were a lot
of different folks who had the ability to build state of the art technology here.
It's not just a small number of big companies, but to train one of these AI models, the state
of the art models just takes, you know, hundreds of millions of dollars of infrastructure,
right?
So there are not that many organizations in the world that can do that at the biggest
scale today.
And now it gets more efficient every day.
So I do think that that will be available to more folks over time.
But I just think like, there's all this innovation out there that people can create.
And I just think that we'll also learn a lot by seeing what the whole community of
students and hackers and startups and different folks build with this.
And that's kind of been how we've approached this.
And it's also how we've done a lot of our infrastructure.
And we took our whole data center design and our server design, and we built this open
compute project where we just made that public.
And part of the theory was like, all right, if we make it so that more people can use
the server design, then that'll enable more innovation.
It'll also make the server design more efficient, and that'll make our business more efficient
too.
So that's worked.
And we've just done this with a lot of our infrastructure.
So for people who don't know, you did the limited release, I think in February of this
year, of Llama.
And it got, quote unquote, leaked, meaning it escaped the limited release aspect.
But it was something you probably anticipated, given that it's just released to researchers.
We shared it with researchers.
You're right.
So it's just trying to make sure that there's a slow release.
But from there, I just would love to get your comment on what happened next, which is there's
a very vibrant open source community that just builds stuff on top of it.
There's Llama CPP, basically stuff that makes it more efficient to run on smaller computers.
There's combining with reinforcement learning with human feedback, so some of the different
interesting fine-tuning mechanisms.
There's then also fine-tuning in our GPT-3 generations.
There's a lot of GPT4ALL, Alpaca, Colossal AI, all these kinds of models just spring
up, run on top of it.
What do you think about that?
No, I think it's been really neat to see.
There's been folks who are getting it to run on local devices.
So if you're an individual who wants to experiment with this at home, you probably don't have
a large budget to get access to a large amount of cloud compute, so getting it to run on
your local laptop is pretty good and pretty relevant.
And then there were things like Llama CPP re-implemented it more efficiently, so now
even when we run our own versions of it, we can do it on way less compute and it's just
way more efficient, saves a lot of money for everyone who uses this, so that is good.
I do think it's worth calling out that because this was a relatively early release, Llama
isn't quite as on the frontier as, for example, the biggest OpenAI models or the biggest Google
models.
You mentioned that the largest Llama model that we released had 65 billion parameters
and no one knows, I guess outside of OpenAI, exactly what the specs are for GPT-4, but
I think my understanding is it's like 10 times bigger and I think Google's Palm model
is also I think has about 10 times as many parameters.
Now the Llama models are very efficient, so they perform well for something that's around
65 billion parameters, so for me that was also part of this because there's this whole
debate around, you know, is it good for everyone in the world to have access to the most frontier
AI models?
And I think as the AI models start approaching something that's like a super human intelligence,
that's a bigger question that we'll have to grapple with, but right now I mean these
are still very basic tools.
They're powerful in the sense that a lot of open source software like databases or web
servers can enable a lot of pretty important things, but I don't think anyone looks at
the current generation of Llama and thinks it's anywhere near a super intelligence.
So I think that a bunch of those questions around like is it good to kind of get out
there, I think at this stage surely you want more researchers working on it for all the
reasons that open source software has a lot of advantages and we talked about efficiency
before, but another one is just open source software tends to be more secure because you
have more people looking at it openly and scrutinizing it and finding holes in it and
that makes it more safe.
So I think at this point it's more, I think it's generally agreed upon that open source
software is generally more secure and safer than things that are kind of developed in
a silo where people try to get through security through obscurity.
So I think that for the scale of what we're seeing now with AI, I think we're more likely
to get to good alignment and good understanding of kind of what needs to do to make this work
well by having it be open source.
And that's something that I think is quite good to have out there and happening publicly
at this point.
Medha released a lot of models as open source.
So the masculine multilingual speech model, the image buying model, I'll ask you questions
about those, but the point is you've open sourced quite a lot, you've been spearheading
the open source movement, that's really positive and inspiring to see from one angle, from
the research angle.
Of course, there's folks who are really terrified about the existential threat of artificial
intelligence and those folks will say that you have to be careful about the open sourcing
step, but where do you see the future of open source here as part of Medha?
The tension here is, do you want to release the magic sauce?
That's one tension.
The other one is, do you want to put a powerful tool in the hands of bad actors, even though
it probably has a huge amount of positive impact also?
Yeah.
I mean, again, I think for the stage that we're at in the development of AI, I don't
think anyone looks at the current state of things and thinks that this is super intelligence.
And the models that we're talking about, the llama models here are generally an order
of magnitude smaller than what open AI or Google are doing.
So I think that at least for the stage that we're in now, the equity is balanced strongly
in my view towards doing this more openly.
I think if you got something that was closer to super intelligence, then I think you'd
have to discuss that more and think through that a lot more.
And we haven't made a decision yet as to what we would do if we were in that position, but
I think there's a good chance that we're pretty far off from that position.
So I'm certainly not saying that the position that we're taking on this now applies to
every single thing that we would ever do.
And certainly inside the company, we probably do more open source work than most of the
other big tech companies, but we also don't open source everything.
A lot of the core kind of app code for WhatsApp or Instagram or something, I mean, we're
not open sourcing that it's not like a general enough piece of software that would be useful
for a lot of people to do different things.
Whereas the software that we do, whether it's like an open source server design or basically
things like memcache, right, like a good, it was probably our earliest project that
I worked on.
It was probably one of the last things that I coded and led directly for the company.
But basically this caching tool for quick data retrieval, these are things that are
just broadly useful across anything that you want to build.
And I think that some of the language models now have that feel, as well as some of the
other things that we're building, like the translation tool that you just referenced.
So text to speech and speech to text, you've expanded it from around 100 languages to more
than 1,100 languages.
And you can identify more than, the model can identify more than 4,000 spoken languages,
which is 40 times more than any known previous technology.
To me, that's really, really, really exciting in terms of connecting the world, breaking
down barriers that language creates.
Yeah.
I think being able to translate between all of these different pieces in real time, this
has been a kind of common sci-fi idea that we'd all have, whether it's an earbud or glasses
or something that can help translate in real time between all these different languages.
And that's one that I think technology is basically delivering now.
So I think that's pretty exciting.
You mentioned the next version of Llama.
What can you say about the next version of Llama?
What can you say about what were you working on in terms of release, in terms of the vision
for that?
Well, a lot of what we're doing is taking the first version, which was primarily this
research version, and trying to now build a version that has all of the latest state-of-the-art
safety precautions built in.
And we're using some more data to train it from across our services.
But a lot of the work that we're doing internally is really just focused on making sure that
this is as aligned and responsible as possible.
And we're building a lot of our own, we're talking about kind of the open source infrastructure.
But the main thing that we focus on building here, a lot of product experience is to help
people connect and express themselves.
So I've talked about a bunch of this stuff, but then you'll have an assistant that you
can talk to in WhatsApp.
I think in the future, every creator will have kind of an AI agent that can kind of
act on their behalf, that their fans can talk to.
I want to get to the point where every small business basically has an AI agent that people
can talk to to do commerce and customer support and things like that.
So there are going to be all these different things.
And Llama, or the language model underlying this, is basically going to be the engine
that powers that.
The reason to open source it is that, as we did with the first version, is that basically
it unlocks a lot of innovation in the ecosystem, will make our products better as well, and
also gives us a lot of valuable feedback on security and safety, which is important for
making this good.
But yeah, I mean, the work that we're doing to advance the infrastructure, it's basically
at this point taking it beyond a research project into something which is ready to be
kind of core infrastructure, not only for our own products, but hopefully for a lot
of other things out there too.
Do you think the Llama or the language model underlying that version two will be open sourced?
Do you have internal debate around that, the pros and cons and so on?
This is, I mean, we were talking about the debates that we have internally, and I think
the question is how to do it, right?
I mean, I think we did the research license for V1, and I think the big thing that we're
thinking about is basically like, what's the right way?
So there was a leak that happened, I don't know if you can comment on it for V1.
We released it as a research project for researchers to be able to use, but in doing
so we put it out there.
So we were very clear that anyone who uses the code and the weights doesn't have a commercial
license to put into products, and we've generally seen people respect that, right?
It's like you don't have any reputable companies that are basically trying to put this into
their commercial products.
But yeah, but by sharing it with so many researchers, it did leave the building.
But what have you learned from that process that you might be able to apply to V2 about
how to release it safely, effectively, if you release it?
Yeah, well, I mean, I think a lot of the feedback, like I said, is just around different things
around how do you fine tune models to make them more aligned and safer, and you see all
the different data recipes that, you mentioned a lot of different projects that are based
on this.
I mean, there's one at Berkeley, there's, you know, it was just like all over.
And people have tried a lot of different things, and we've tried a bunch of stuff internally,
so kind of where we're making progress here, but also we're able to learn from some of
the best ideas in the community, and I think we want to just continue pushing that forward.
But I don't have any news to announce on this, if that's what you're asking.
This is a thing that we're still kind of, you know, actively working through the right
way to move forward here.
The details of the secret sauce are still being developed, I see.
Can you comment on what do you think of the thing that worked for GPT, which is the reinforcement
learning with human feedback?
So doing this alignment process, do you find it interesting?
And as part of that, let me ask, because I talked to Yann LeCun before talking to you
today, he asked me to ask, or suggested that I ask, do you think LLM fine-tuning will need
to be crowdsourced Wikipedia style, so crowdsourcing.
So this kind of idea of how to integrate the human in the fine-tuning of these foundation
models.
I think that's a really interesting idea that I've talked to Yann about a bunch.
And you were talking about how do you basically train these models to be as safe and aligned
and responsible as possible.
And, you know, different groups out there who are doing development test different data
recipes in fine-tuning.
But this idea that you just mentioned is that at the end of the day, instead of having
kind of one group fine-tune some stuff and another group produce a different fine-tuning
recipe and then us trying to figure out which one we think works best to produce the most
aligned model, I do think that it would be nice if you could get to a point where you
had a Wikipedia style collaborative way for a kind of a broader community to fine-tune
it as well.
Now, there's a lot of challenges in that both from an infrastructure and like a community
management and product perspective about how you do that.
So I haven't worked that out yet.
But as an idea, I think it's quite compelling and I think it goes well with the ethos of
open-sourcing the technology is also finding a way to have a kind of community-driven training
of it.
But I think that there are a lot of questions on this.
In general, these questions around what's the best way to produce aligned AI models,
it's very much a research area and it's one that I think we will need to make as much
progress on as the kind of core intelligence capability of the models themselves.
Well, I just did a conversation with Jimmy Wales, the founder of Wikipedia.
And to me, Wikipedia is one of the greatest websites ever created and is a kind of a miracle
that it works.
And I think it has to do with something that you mentioned, which is community.
You have a small community of editors that somehow work together well.
And they handle very controversial topics and they handle it with balance and with grace,
despite sort of the attacks that will often happen.
A lot of the time.
I mean, it has issues just like any other human system.
But yes, I mean, the balance is, I mean, it's amazing what they've been able to achieve.
But it's also not perfect.
And I think that there's still a lot of challenges.
Right.
The more controversial the topic, the more difficult the journey towards quote-unquote
truth or knowledge or wisdom that Wikipedia tries to capture.
In the same way AI models, we need to be able to generate those same things, truth, knowledge
and wisdom.
And how do you align those models that they generate something that is closest to truth.
There's these concerns about misinformation, all this kind of stuff that nobody can define.
And it's something that we together as a human species have to define, like what is truth
and how to help AI systems generate that.
And one of the things language models do really well is generate convincing sounding things
that can be completely wrong.
And so how do you align it to be less wrong?
And part of that is the training and part of that is the alignment and however you do
the alignment stage.
And just like you said, it's a very new and a very open research problem.
Yeah.
And I think that there's also a lot of questions about whether the current architecture for
LLMs, as you continue scaling it, what happens?
I mean, a lot of what's been exciting in the last year is that there's clearly a qualitative
breakthrough where, you know, with some of the GPT models that OpenAI put out and that
others have been able to do as well, I think it reached a kind of level of quality where
people are like, wow, this feels different and like it's going to be able to be the foundation
for building a lot of awesome products and experiences and value.
But I think the other realization that people have is, wow, we just made a breakthrough.
If there are other breakthroughs quickly, then I think that there's the sense that maybe
where we're closer to general intelligence.
But I think that idea is predicated on the idea that I think people believe that there's
still generally a bunch of additional breakthroughs to make and that it's, we just don't know
how long it's going to take to get there.
And, you know, one view that some people have, this doesn't tend to be my view as much, is
that simply scaling the current LLMs and, you know, getting to higher parameter count
models by itself will get to something that is closer to general intelligence.
But I don't know, I tend to think that there's probably more fundamental steps that need
to be taken along the way there.
But still the leaves taken with this extra alignment step is quite incredible, quite
surprising to a lot of folks.
And on top of that, when you start to have hundreds of millions of people potentially
using a product that integrates that, you can start to see civilization transforming
effects before you achieve super, quote unquote, super intelligence.
It could be super transformative without being a super intelligence.
Oh, yeah.
I mean, I think that there are going to be a lot of amazing products and value that can
be created with the current level of technology.
To some degree, you know, I'm excited to work on a lot of those products over the next few
years.
And I think it would just create a tremendous amount of whiplash if the number of breakthroughs
keeps like if they're keep on being stacked breakthroughs, because I think to some degree,
industry in the world needs some time to kind of build these breakthroughs into the products
and experiences that we all use that we can actually benefit from them.
But I don't know, I think that there's just a like an awesome amount of stuff to do.
I mean, I think about like all of the small businesses or individual entrepreneurs out
there who now we're going to be able to get help coding the things that they need to go
build things or designing the things that they need, or we'll be able to use these models
to be able to do customer support for the people that they're serving over WhatsApp
without having to, you know, I think that that's just going to be, I just think that
this is all going to be super exciting, it's going to create better, better experiences
for people and just unlock a ton of innovation and value.
So I don't know if you know, but you know, what is it over 3 billion people use WhatsApp,
Facebook and Instagram.
So any kind of AI fueled products that go into that, like we're talking about anything
with LLMs will have a tremendous amount of impact.
Do you have ideas and thoughts about possible products that might start being integrated
into these platforms used by so many people?
Yeah, I think there's three main categories of things that we're working on.
The first that I think is probably the most interesting is, you know, there's this notion
of like, you're going to have an assistant or an agent who you can talk to.
And I think probably the biggest thing that's different about my view of how this plays
out from what I see with open AI and Google and others is, you know, everyone else is
building like the one singular AI, right?
It's like, okay, you talk to chat GPT or you talk to Bard or you talk to Bing.
And my view is that there are going to be a lot of different AIs that people are going
to want to engage with, just like you want to use a number of different apps for different
things and you have relationships with different people in your life who fill different emotional
roles for you.
And so I think that they're going to be, people have a reason that I think you don't just
want like a singular AI.
And that I think is probably the biggest distinction in terms of how I think about this.
And a bunch of these things, I think you'll want an assistant.
I mean, I mentioned a couple of these before, I think like every creator who you interact
with will ultimately want some kind of AI that can proxy them and be something that
their fans can interact with, or that allows them to interact with their fans.
This is like the common creator promise, everyone's trying to build a community and engage with
people and they want tools to be able to amplify themselves more and be able to do that.
But you only have 24 hours in a day.
So I think having the ability to basically like bottle up your personality or, you know,
give your fans information about when you're performing a concert or something like that.
I mean, that's, that I think is going to be something that's super valuable, but it's
not just that, you know, again, it's not this idea that I think people are going to want
just one singular AI.
I think you're going to, you know, you're going to want to interact with a lot of different
entities.
And then I think there's the business version of this too, which we've touched on a couple
of times, which is, I think every business in the world is going to want basically an
AI that, um, that, you know, it's like you have your page on Instagram or Facebook or
WhatsApp or whatever.
And you want to, you want to point people to an AI that people can interact with, but
you want to know that that AI is only going to sell your products.
You don't want it, you know, recommending your competitors stuff, right?
So it's not like there can be like just a, you know, one singular AI that, that can answer
all the questions for a person because, you know, that like that AI might not actually
be aligned with you as a business to, um, to, to really just do the best job providing
support for, for your product.
So I think that there's going to be a clear need, um, in the market and in people's lives
for there to be a bunch of these.
Part of that is figuring out the research, the technology that enables the personalization
that you're talking about.
So not one centralized godlike LLM, but one, just a huge diversity of them that's fine
tuned to particular needs, particular styles, particular businesses, particular brands,
all that kind of stuff.
And also enabling, just enabling people to create them really easily for the, you know,
for to, for your own business, or if you're a creator to, to be able to help you engage
with your fans.
Um, so yeah, I think that there, there's a clear kind of interesting product direction
here that I think is fairly unique from, from what, you know, any of the other big companies
are taking.
Um, it also aligns well with this sort of open source approach, because again, we sort
of believe in this more community oriented, uh, more democratic approach to building out
the products and technology around this.
We don't think that there's gonna be the one true thing.
We think that there, there should be kind of a lot of development.
So that part of things I think is going to be really interesting and we could, we could
go probably spend a lot of time talking about that and the, the kind of implications of,
um, of that approach being different from what others are taking.
Um, but then there's a bunch of other simpler things that I think we're also going to do.
Just going back to your, your question around how this finds its way into like, what do
we build?
Um, there are going to be a lot of simpler things around, um, okay, you, you post photos
on Instagram and Facebook and, you know, and WhatsApp and messenger and like, you want
the photos to look as good as possible.
So like having an AI that you can just like take a photo and then just tell it like, okay,
I want to edit this thing or describe this.
It's like, I think we're, we're going to have tools that are just way better than, than
what we've historically had on this.
Um, and that's more in the image and media generation side than the large language model
side, but, but it's, it all kind of, you know, plays off of advances in the same space.
Um, so there are a lot of tools that I think are just going to get built into every one
of our products.
I think every single thing that we do is going to basically get evolved in this direction,
right?
It's like in the future, if you're advertising on our services, like, do you need to make
your own kind of ad creative?
No, you'll just, you know, you just tell us, okay, I'm, I'm a dog walker and I am willing
to walk people's dogs and help me find the right people and like create the ad unit that
will perform the best and like give an objective to, to the system.
And it just kind of like connects you with the right people.
Well, that's a super powerful idea of generating the language, almost like a rigorous AB testing
for you that works to find the best customer for your thing.
I mean, to me, advertisement when done well, just finds a good match between a human being
and a thing that will make that human being happy.
Yeah, totally.
And do that as efficiently as possible.
When it's done well, people actually like it.
You know, it's, I think that there's a lot of examples where it's not done well and it's
annoying and I think that that's what kind of gives it a bad rap, but, but yeah, I don't
know.
And a lot of the stuff is possible today.
I mean, obviously AB testing stuff is built into a lot of these frameworks.
The thing that's new is having technology that can generate the ideas for you about
what to AB test something that that's exciting.
So this will just be across like everything that we're doing, right?
All the metaverse stuff that we're doing, right?
It's like you want to create worlds in the future.
And then it'll just describe them and then it'll create the code for you.
So natural language becomes the interface we use for all the ways we interact with the
computer, with the digital.
More of them.
Yeah, yeah, totally.
Yeah, which is what everyone can do using natural language and with translation, you
can do it in any kind of language.
I mean, for the personalization is really, really, really interesting.
Yeah.
It unlocks so many possible things.
I mean, I, for one, look forward to creating a copy of myself.
I know we talked about this last time.
But this has, since the last time, this becomes –
Now we're closer.
Much closer.
Like I could literally just having interacted with some of these language models, I could
see the absurd situation where I'll have a large or a lex language model and I'll
have to have a conversation with him about like, hey, listen, like you're just getting
out of line and having a conversation where you fine tune that thing to be a little bit
more respectful or something like this.
I mean, that's going to be the, that seems like an amazing product for businesses, for
humans, just not just the assistant that's facing the individual, but the assistant that
represents the individual to the public, both directions.
There's basically a layer that is the AI system through which you interact with the outside
world, with the outside world that has humans in it.
That's really interesting.
And you that have social networks that connect billions of people, it seems like a heck of
a large scale place to test some of this stuff out.
Yeah.
I mean, I think part of the reason why creators will want to do this is because they already
have the communities on our services.
Yeah.
And a lot of the interface for this stuff today are chat type interfaces and between
WhatsApp and Messenger, I think that those are just great ways to interact with people.
So some of this is philosophy, but do you see a near term future where you have some
of the people you're friends with are AI systems on these social networks?
On Facebook, on Instagram, even on WhatsApp, having conversations where some heterogeneous,
some is human, some is AI.
I think we'll get to that.
And if only just empirically looking at, Microsoft released this thing called Shao Ice several
years ago in China, it was a pre-LLM chatbot technology that was a lot simpler than what's
possible today.
And I think it was like tens of millions of people were using this and just really became
quite attached and built relationships with it.
And I think that there's services today like Replica where people are doing things like
that.
But I think that there's certainly needs for companionship that people have, older people.
I think most people probably don't have as many friends as they would like to have.
If you look at, there's some interesting demographic studies around that the average person has,
the number of close friends that they have is fewer today than it was 15 years ago.
And I mean, that gets to like, this is like the core thing that I think about in terms
of building services that help connect people.
So I think you'll get tools that help people connect with each other are going to be the
primary thing that we want to do.
So you can imagine AI assistants that just do a better job of reminding you when it's
your friend's birthday and how you could celebrate them.
It's like right now we have like the little box in the corner of the website that tells
you whose birthday it is and stuff like that.
But at some level you don't just want to like send everyone a note that says the same note
saying happy birthday with an emoji.
So having something that's more of a social assistant in that sense and that can update
you on what's going on in their life and how you can reach out to them effectively, help
you be a better friend.
I think that that's something that's super powerful too.
But yeah, beyond that, and there are all these different flavors of kind of personal
AIs that I think could exist.
So I think an assistant is sort of the kind of simplest one to wrap your head around,
but I think a mentor or a life coach, someone who can give you advice, who's maybe like
a bit of a cheerleader who can help pick you up through all the challenges that inevitably
all go through on a daily basis and that there's probably some role for something like
that.
And then all the way, you can probably just go through a lot of the different type of
kind of functional relationships that people have in their life and I would bet that there
will be companies out there that take a crack at a lot of these things.
So I don't know, I think it's part of the interesting innovation that's going to exist
is that there are certainly a lot like education tutors, right?
It's like I just look at my kids learning to code and they love it, but it's like they
get stuck on a question and they have to wait till I can help answer it or someone else
who they know can help answer the question in the future, there will be like a coding
assistant that they have that is designed to be perfect for teaching a five and a seven
year old how to code and they'll just be able to ask questions all the time and it'll be
extremely patient.
It's never going to get annoyed at them, right?
I think that there are all these different kind of relationships or functional relationships
that we have in our lives that are really interesting and I think one of the big questions
is like, okay, is this all going to just get bucketed into one singular AI?
I just don't think so.
Do you think about, this is actually a question from Reddit, what the long-term effects of
human communication when people can talk with, in quotes, talk with others through
a chatbot that augments their language automatically rather than developing social skills by making
mistakes and learning?
Will people just communicate by grunts in a generation?
Do you think about long-term effects at scale, the integration of AI in our social interaction?
Yeah, I mean, I think it's mostly good.
That question was sort of framed in a negative way, but I mean, we were talking before about
language models helping you communicate with, it was like language translation helping you
communicate with people who don't speak your language.
At some level, what all the social technology is doing is helping people express themselves
better to people in situations where they would otherwise have a hard time doing that.
So part of it might be okay because you speak a language that I don't know, that's a pretty
basic one that I don't think people are going to look at that and say, it's sad that do
we have the capacity to do that because I should have just learned your language, right?
I mean, that's pretty high bar, but overall, I'd say there are all these impediments and
language is an imperfect way for people to express thoughts and ideas.
It's one of the best that we have.
We have that, we have art, we have code.
Well, language is also a mapping of the way you think, the way you see the world, who you are.
And one of the applications, I've recently talked to a person who's actually a jiu-jitsu
instructor, he said that when he emails parents about their son and daughter that they can
improve their discipline in class and so on, he often finds that he comes off a bit of
more of an asshole than he would like, so he uses GPT to translate his original email
into a nicer email, the more polite one.
We hear this all the time.
A lot of creators on our services tell us that one of the most stressful things is basically
negotiating deals with brands and stuff like the business side of it because they do their
thing and the creators, they're excellent at what they do and they just want to connect
with their community, but then they get really stressed.
They go into their DMs and they see some brand wants to do something with them and they don't
quite know how to negotiate or how to push back respectfully.
So I think building a tool that can actually allow them to do that well is one simple thing
that I think is just an interesting thing that we've heard from a bunch of people that
they'd be interested in.
But I'm going back to the broader idea.
I don't know.
Priscilla and I just had our third daughter a couple of months ago, and it's like one
of the saddest things in the world is seeing your baby cry, right?
But it's like, why is that?
Well, because babies don't generally have much capacity to tell you what they care about
otherwise, right?
It's not actually just babies, right?
My five-year-old daughter cries too because she sometimes has a hard time expressing what
matters to her.
And then I was thinking about that and I was like, well, actually a lot of adults get very
frustrated too because they have a hard time expressing things in a way that, going back
to some of the early themes, that maybe is something that is a mistake or maybe they
have pride or something like all these things get in the way.
So I don't know.
I think that all these different technologies that can help us navigate the social complexity
and actually be able to better express what we're feeling and thinking, I think that's
generally all good.
And there are all these concerns like, okay, are people going to have worse memories because
you have Google to look things up?
And I think in general, a generation later, you don't look back and lament that.
I think it's just like, wow, we have so much more capacity to do so much more now.
And I think that that'll be the case here too.
You can allocate those cognitive capabilities to deeper, more nuanced thought.
But it's change.
So just like with Google search, the addition of language models, large language models,
you basically don't have to remember nearly as much.
Just like with Stack Overflow for programming, now that these language models can generate
code right there.
I mean, I find that I write like maybe 80%, 90% of the code I write is now generated first
and then edited.
I mean, so you don't have to remember how to write specifics of different functions.
That's great.
And it's also, it's not just the specific coding.
I mean, in the context of a large company like this, I think before an engineer can
sit down to code, they first need to figure out all of the libraries and dependencies
that tens of thousands of people have written before them.
And one of the things that I'm excited about that we're working on is it's not just tools
that help engineers code, it's tools that can help summarize the whole knowledge base
and help people be able to navigate all the internal information.
And I think that that's, in the experiments that I've done with this stuff, I mean, that's
on the public stuff, you just ask one of these models to build you a script that does anything
and it basically already understands what the best libraries are to do that thing and
pulls them in automatically.
I mean, I think that's super powerful.
That was always the most annoying part of coding was that you had to spend all this
time actually figuring out what the resources were that you were supposed to import before
you could actually start building the thing.
Yeah.
I mean, there's, of course, the flip side of that, I think for the most part is positive,
but the flip side is if you outsource that thinking to an AI model, you might miss nuanced
mistakes and bugs.
You lose the skill to find those bugs and those bugs might be, the code looks very convincingly
right, but it's actually wrong in a very subtle way.
But that's the trade-off that we face as human civilization when we build more and more powerful
tools.
When we stand on the shoulders of taller and taller giants, we could do more, but then
we forget how to do all the stuff that they did.
It's a weird trade-off.
Yeah.
I agree.
I mean, I think it is very valuable in your life to be able to do basic things too.
Do you worry about some of the concerns of bots being present on social networks?
More and more human-like bots that are not necessarily trying to do a good thing or they
might be explicitly trying to do a bad thing like phishing scams, like social engineering,
all that kind of stuff, which has always been a very difficult problem for social networks,
but now it's becoming almost a more and more difficult problem.
Well, there's a few different parts of this.
So one is there are all these harms that we need to basically fight against and prevent.
And that's been a lot of our focus over the last five or seven years is basically ramping
up very sophisticated AI systems, not generative AI systems, more kind of classical AI systems
to be able to categorize and classify and identify, okay, this post looks like it's
promoting terrorism.
This one is exploiting children.
This one looks like it might be trying to incite violence.
This one's an intellectual property violation.
So there's 18 different categories of violating harmful content that we've had to build
specific systems to be able to track.
And I think it's certainly the case that advances in generative AI will test those,
but at least so far it's been the case, and I'm optimistic that it will continue
to be the case, that we will be able to bring more computing power to bear to have even
stronger AIs that can help defend against those things.
So we've had to deal with some adversarial issues before, right?
I mean, for some things like hate speech, it's like people aren't generally getting
a lot more sophisticated, like the average person who let's say, you know, if someone's
saying some kind of racist thing, right, it's like, they're not necessarily getting more
sophisticated at being racist, right?
It just, it's okay.
So that the system can just find, but then there's other adversaries who actually are
very sophisticated, like nation states doing things, and we find, whether it's Russia
or just different countries that are basically standing up these networks of bots or inauthentic
accounts is what we call them, because they're not necessarily bots, that some of them could
actually be real people who are kind of masquerading as other people, but they're acting in a coordinated
way.
And some of that behaviour has gotten very sophisticated and it's very adversarial.
So they, you know, each iteration, every time we find something and stop them, they kind
of evolve their behaviour.
They don't just pack up their bags and go home and say, okay, we're not going to try.
You know, at some point they might decide doing it on meta services is not worth it.
They'll go do it on someone else if it's easier to do it in another place.
But we have a fair amount of experience dealing with even those kinds of adversarial attacks
where they just keep on getting better and better.
And I do think that as long as we can keep on putting more compute power against it,
and if we're kind of one of the leaders in developing some of these AI models, I'm quite
optimistic that we're going to be able to keep on pushing against the kind of normal
categories of harm that you talk about, fraud, scams, spam, IP violations, things like that.
What about like creating narratives and controversy?
To me, it's kind of amazing how a small collection of, what did you say, inauthentic accounts.
So it could be bots, but it could be humans.
Yeah, I mean, we have sort of this funny name for it, but we call it coordinated inauthentic
behaviour.
Yeah.
It's kind of incredible how a small collection of folks can create narratives, create stories,
especially if they're viral, especially if they have an element that can catalyze the
virality of the narrative.
Yeah.
And I think there, the question is you have to be, I'm very specific about what is bad
about it, right?
Because I think a set of people coming together or organically bouncing ideas off each other
and a narrative comes out of that is not necessarily a bad thing by itself.
If it's kind of authentic and organic, that's like a lot of what happens and how culture
gets created and how art gets created and a lot of good stuff.
So that's why we've kind of focused on this sense of coordinated inauthentic behaviour.
So it's like if you have a network of, you know, whether it's bots, some people masquerading
as different accounts, but you have kind of someone pulling the strings behind it and
trying to kind of act as if this is a more organic set of behaviour, but really it's
not.
It's just like one coordinated thing.
That seems problematic to me, right?
But I mean, I don't think people should be able to have coordinated networks and not
disclose it as such.
But that again, you know, we've been able to deploy pretty sophisticated AI and, you
know, counter-terrorism groups and things like that to be able to identify a fair number
of these coordinated and authentic networks of accounts and take them down.
We continue to do that and I think we're, we've, you know, it's one thing that if you'd
told me 20 years ago, it's like, all right, you're starting this website to help people
connect at a college and, you know, in the future, you're going to be, you know, part
of your organisation is going to be a counter-terrorism organisation with AI to find coordinated and
authentic.
I would have thought that was pretty wild, but no, I think that's part of where we are.
But look, I think that these questions that you're pushing on now, this is actually where
I'd guess most of the challenge around AI will be for the foreseeable future.
I think that there's a lot of debate around things like, is this going to create existential
risk to humanity?
And I think that those are very hard things to disprove one way or another.
My own intuition is that the point at which we become close to superintelligent, superintelligence
is it's just really unclear to me that the current technology is going to get there without
another set of significant advances, but that doesn't mean that there's no danger.
I think the danger is basically amplifying the kind of known set of harms that people
or sets of accounts can do, and we just need to make sure that we really focus on basically
doing that as well as possible.
So that's definitely a big focus for me.
Well, you can basically use large language models as an assistant of how to cause harm
on social networks.
You can ask it a question.
You know, Meta has very impressive coordinated inauthentic account fighting capabilities.
How do I do the coordinating authentic account creation where Meta doesn't detect it?
Like literally ask that question.
And basically there's this kind of part of it, I mean, that's what OpenAI showed that
they're concerned with those questions.
And I'm just curious, you can comment on your approach to it, how to do a kind of moderation
on the output of those models that it can't be used to help you coordinate harm in all
the full definition of what the harm means.
Yeah.
And that's a lot of the fine tuning and the alignment training that we do is basically,
you know, when we ship AIs across our products, a lot of what we're trying to make sure is
that you can't ask it to help you commit a crime, right?
So I think training it to kind of understand that and it's not like any of these systems
are ever gonna be 100% perfect, but you know, just making it so that this isn't an easier
way to go about doing something bad than the next best alternative, right?
I mean, people still have Google, right?
You know, you still have search engines, so the information is out there.
And for these, you know, what we see is like for nation states or, you know, these actors
that are trying to pull off these large, you know, coordinated and authentic networks to
kind of influence different things.
At some point when we would just make it very difficult, they do just, you know, try to
use other services instead, right?
It's just like if you can make it more expensive for them to do it on your service, then kind
of people go elsewhere.
And I think that that's the bar, right?
It's like, it's not like, okay, are you ever gonna be perfect at finding, you know, every
adversary who tries to attack you?
It's, I mean, you try to get as close to that as possible, but I think really kind of economically
what we were just trying to do is make it so it's just inefficient for them to go after that.
But there's also complicated questions of what is and isn't harm, what is and isn't misinformation.
So this is one of the things that Wikipedia has also tried to face.
I remember asking GPT about whether the virus leaked from a lab or not, and the answer provided
was a very nuanced one and a well cited one, almost dare I say, well thought out one, balanced.
I would hate for that nuance to be lost through the process of moderation.
Wikipedia does a good job on that particular thing too, but from pressures from governments
and institutions, it's, you could see some of that nuance and depth of information, facts
and wisdom be lost.
Absolutely.
And that's a scary thing.
Some of the magic, some of the edges, the rough edges might be lost to the process of
moderation of AI systems.
So how do you get that right?
I really agree with what you're pushing on.
I mean, the core, I think the core shape of the problem is that there are some harms that
I think everyone agrees are bad, right?
So sexual exploitation of children, right?
Like you're not going to get many people who think that that type of thing should be allowed
on any service, right?
And that's something that we face and try to push off as much as possible today.
Terrorism, inciting violence, right?
It's like we went through a bunch of these types of harms before.
But then I do think that you get to a set of harms where there is more social debate
around it.
So misinformation I think has been a really tricky one because there are things that are
kind of obviously false, right?
That are maybe factual, but may not be harmful.
So it's like, all right, are you going to censor someone for just being wrong if there's
no kind of harm implication of what they're doing?
I think that there's a bunch of real kind of issues and challenges there.
But then I think that there are other places where it is, just take some of the stuff around
COVID earlier on in the pandemic where there were real health implications, but there hadn't
been time to fully vet a bunch of the scientific assumptions.
And unfortunately, I think a lot of the establishment on that kind of waffled on a bunch of facts
and asked for a bunch of things to be censored that in retrospect ended up being more debatable
or true.
And that stuff is really tough and really undermines trust in that.
So I do think that the questions around how to manage that are very nuanced.
The way that I try to think about it is that I think it's best to generally boil things
down to the harms that people agree on.
So when you think about is something misinformation or not, I think often the more salient bit
is, is this going to potentially lead to physical harm for someone and kind of think about it
in that sense.
Beyond that, I think people just have different preferences on how they want things to be
flagged for them.
I think a bunch of people would prefer to kind of have a flag on something that says,
hey, a fact checker thinks that this might be false.
Or I think Twitter's community notes implementation is quite good on this.
But again, it's the same type of thing.
It's like just kind of discretionarily adding a flag because it makes the user experience
better.
But it's not trying to take down the information or not.
I think that you want to reserve the kind of censorship of content to things that are
of known categories that people generally agree are bad.
Yeah, but there's so many things, especially with the pandemic, but there's other topics
where there's just deep disagreement fueled by politics about what is and isn't harmful.
There's even just the degree to which the virus is harmful, the degree to which the
vaccines that respond to the virus are harmful.
There's just almost like a political divider on that.
And so how do you make decisions about that, where half the country in the United States
or some large fraction of the world has very different views from another part of the world?
Is there a way for meta to stay out of the moderation of this?
It's very difficult to just abstain, but I think we should be clear about which of these
things are actual safety concerns and which ones are a matter of preference in terms of
how people want information flagged.
We did recently introduce something that allows people to have fact checking not affect the
distribution of what shows them their product.
So, okay, a bunch of people don't trust who the fact checkers are.
All right, well, you can turn that off if you want.
But if the content violates some policy like it's inciting violence or something like that,
it's still not going to be allowed.
So I think that you want to honor people's preferences on that as much as possible.
But look, I mean, this is really difficult stuff.
I think it's really hard to know where to draw the line on what is fact and what is
opinion because the nature of science is that nothing is ever 100% known for certain.
You can disprove certain things, but you're constantly testing new hypotheses and scrutinizing
frameworks that have been long held and every once in a while you throw out something that
was working for a very long period of time and it's very difficult.
But I think that just because it's very hard and just because they're edge cases doesn't
mean that you should not try to give people what they're looking for as well.
Let me ask about something you've faced in terms of moderation is pressure from different
sources, pressure from governments.
I want to ask a question how to withstand that pressure for a world where AI moderation
starts becoming a thing too.
So what's Meta's approach to resist the pressure from governments and other interest
groups in terms of what to moderate and not?
I don't know that there's like a one-size-fits-all answer to that.
I think we basically have the principles around we want to allow people to express as much
as possible, but we have developed clear categories of things that we think are wrong that we
don't want on our services and we build tools to try to moderate those.
So then the question is, okay, what do you do when a government says that they don't
want something on the service?
And we have a bunch of principles around how we deal with that because on the one hand,
if there's a democratically elected government and people around the world just have different
values and different places, then should we as a California-based company tell them that
something that they have decided is unacceptable, actually that we need to be able to express
that?
I mean, I think there's a certain amount of hubris in that.
But then I think there are other cases where it's like a little more autocratic and you
have the dictator leader who's just trying to crack down on dissent and the people in
a country are really not aligned with that and it's not necessarily against their culture,
but the person who's leading it is just trying to push in a certain direction.
These are very complex questions, but I think it's difficult to have a one-size-fits-all
approach to it.
But in general, we're pretty active in advocating and pushing back on requests to take things
down.
But honestly, I think a request to censor things is one thing, and that's obviously
bad, but where we draw a much harder line is on requests for access to information.
Because if you get told that you can't say something, I mean, that's bad.
Obviously, it violates your sense and freedom of expression at some level, but a government
getting access to data in a way that seems like it would be unlawful in our country exposes
people to real physical harm, and that's something that in general we take very seriously.
That flows through all of our policies in a lot of ways.
By the time you're actually litigating with a government or pushing back on them, that's
pretty late in the funnel.
I'd say a bunch of this stuff starts a lot higher up in the decision of where do we put
data centers, then there are a lot of countries where we may have a lot of people using the
service in a place, it might be good for the service in some ways, good for those people
if we could reduce the latency by having a data center nearby them.
But for whatever reason, we just feel like, hey, this government does not have a good
track record on basically not trying to get access to people's data.
And at the end of the day, if you put a data center in a country and the government wants
to get access to people's data, then they do at the end of the day have the option of
having people show up with guns and taking it by force.
So I think that there's a lot of decisions that go into how you architect the systems
years in advance of these actual confrontations that end up being really important.
So you put the protection of people's data as a very, very high priority.
That I think there are more harms that I think can be associated with that.
And I think that that ends up being a more critical thing to defend against governments.
Whereas if another government has a different view of what should be acceptable speech in
their country, especially if it's a democratically elected government, then I think that there's
a certain amount of deference that you should have to that.
So that's speaking more to the direct harm that's possible when you give governments
access to data.
But if you look at the United States to the more nuanced kind of pressure to censor, not
even order to censor, but pressure to censor from political entities, which has kind of
received quite a bit of attention in the United States.
Maybe one way to ask that question is if you've seen the Twitter files, what have you learned
from the kind of pressure from U.S. government agencies that was seen in Twitter files?
And what do you do with that kind of pressure?
You know, I've seen it.
It's really hard from the outside to know exactly what happened in each of these cases.
We've obviously been in a bunch of our own cases where agencies or different folks will
just say, hey, here's a threat that we're aware of.
You should be aware of this too.
It's not really pressure as much as it is just flagging something that our security
systems should be on alert about.
I get how some people could think of it as that.
But at the end of the day, it's our call on how to handle that.
But I mean, in terms of running these services, we won't have access to as much information
about what people think that adversaries might be trying to do as possible.
Boy, so you don't feel like there would be consequences if anybody, the CIA, the FBI,
a political party, the Democrats or the Republicans of high powerful political figures,
write emails.
You don't feel pressure from a suggestion.
I guess what I say is there's so much pressure from all sides that I'm not sure that any
specific thing that someone says is really adding that much more to the mix.
There are obviously a lot of people who think that we should be censoring more content.
There are a lot of people who think we should be censoring less content.
There are, as you say, all kinds of different groups that are involved in these debates.
So there's the elected officials and politicians themselves.
There's the agencies, but there's the media.
There's activist groups.
This is not a US-specific thing.
There are groups all over the world in every country that bring different values.
So it's a very active debate.
And I understand it, right?
I mean, these kind of questions get to really some of the most important social debates
that are being had.
So it gets back to the question of truth, because for a lot of these things, they haven't
yet been hardened into a single truth.
And society is sort of trying to hash out what we think on certain issues.
Maybe in a few hundred years, everyone will look back and say, hey, no, it wasn't it obvious
that it should have been this, but no, we're kind of in that meat grinder now and working
through that.
So these are all very complicated.
And some people raise concerns in good faith and just say, hey, this is something that
I want to flag for you to think about.
Certain people, I certainly think, come at things with somewhat of a more kind of punitive
or vengeful view of, I want you to do this thing.
If you don't, then I'm going to try to make your life difficult in a lot of other ways.
But I don't know, this is one of the most pressurized debates, I think, in society.
So I just think that there are so many people in different forces that are trying to apply
pressure from different sides.
I don't think you can make decisions based on trying to make people happy.
I think you just have to do what you think is the right balance and accept that people
are going to be upset no matter where you come out on that.
Yeah, I like that pressurized debate.
So how has your view of the freedom of speech evolved over the years?
And now with AI, where the freedom might apply to them, not just to the humans, but
to the personalized agents as you've spoken about them.
So yeah, I mean, I've probably gotten a somewhat more nuanced view just because I think that
there are, you know, I come at this, I'm obviously very pro freedom of expression, right?
I don't think you build a service like this that gives people tools to express themselves
unless you think that people expressing themselves at scale is a good thing, right?
So I didn't get into this to try to prevent people from expressing anything.
I want to give people tools so they can express as much as possible.
And then I think it's become clear that there are certain categories of things that we've
talked about that I think almost everyone accepts are bad and that no one wants and
that are illegal, even in countries like the US where, you know, you have the First Amendment
that's very protective of enabling speech, it's like you're still not allowed to do things that
are going to immediately incite violence or, you know, violate people's intellectual property or
things like that.
So there are those, but then there's also a very active core of just active disagreements
in society where some people may think that something is true or false, the other side
might think it's the opposite or just unsettled, right?
And those are some of the most difficult to kind of handle, like we've talked about.
But one of the lessons that I feel like I've learned is that a lot of times when you can,
the best way to handle this stuff more practically is not in terms of answering the question
of should this be allowed, but just like what is the best way to deal with someone being
a jerk?
Is the person basically just having a like repeat behavior of like causing a lot of issues?
So looking at it more at that level.
And its effect on the broader communities, health of the community, health of the state.
It's tricky though, because like, how do you know there could be people that have a very
controversial viewpoint that turns out to have a positive long-term effect on the health
of the community because it challenges the community?
Oh, that's true.
Absolutely.
Yeah, no, I think you want to be careful about that.
I'm not sure I'm expressing this very clearly because I certainly agree with your point
there.
And my point isn't that we should not have people on our services that are being controversial.
That's certainly not what I mean to say.
It's that often I think it's not just looking at a specific example of speech that it's
most effective to handle this stuff.
And I think often you don't want to make specific binary decisions of kind of this is allowed
or this isn't.
I mean, we talked about fact checking or Twitter's community voices thing.
I think that's another good example.
It's like it's not a question of is this allowed or not.
It's just a question of adding more context to the thing.
I think that that's helpful.
So in the context of AI, which is what you were asking about, and there are lots of ways
that an AI can be helpful.
With an AI, it's less about censorship, right?
Because it's more about what is the most productive answer to a question.
There was one case study that I was reviewing with the team is someone asked,
can you explain to me how to 3D print a gun?
And one proposed response is like, no, I can't talk about that.
But it's like basically just shut it down immediately, which I think is some of what
you see.
It's like as a large language model, I'm not allowed to talk about whatever.
But there's another response, which is like, hey, I don't think that's a good idea.
In a lot of countries, including the US, 3D printing guns is illegal or kind of whatever
the factual thing is.
And it's like, okay, you know, that's actually a respectful and informative answer.
And I may have not known that specific thing.
And so there are different ways to handle this that I think kind of you can either assume
good intent.
Like maybe the person didn't know, and I'm just going to help educate them.
Or you could like kind of come at it as like, no, I need to shut this thing down immediately,
right?
It's like, I just am not going to talk about this.
And there may be times where you need to do that, but I actually think having a somewhat
more informative approach where you generally assume good intent from people is probably
a better balance to be on as many things as you can be.
You're not going to do that for everything.
But you were kind of asking about how I approach this, and I'm thinking about this as it relates
to AI.
And I think that that's a big difference in kind of how to handle sensitive content across
these different modes.
CB And I have to ask, there's rumors you might
be working on a social network that's text-based that might be a competitor to Twitter, code
named P92.
Is there something you could say?
About those rumors?
CB There is a project.
You know, I've always thought that sort of a text-based kind of information utility is
just a really important thing to society.
And for whatever reason, I feel like Twitter has not lived up to what I would have thought
its full potential should be.
And I think that the current, you know, I think Elon thinks that, right?
And that's probably one of the reasons why he bought it.
And I do know there are ways to consider alternative approaches to this.
And one that I think is potentially interesting is this open and federated approach where
you're seeing with Mastodon and you're seeing that a little bit with Blue Sky.
And I think that it's possible that something that melds some of those ideas with the graph
and identity system that people have already cultivated on Instagram could be a kind of
very welcome contribution to that space.
But I don't know, we work on a lot of things all the time though, too.
So I don't want to get ahead of myself.
I mean, we have projects that explore a lot of different things.
And this is certainly one that I think could be interesting.
But...
So what's the release, the launch date of that again?
Or what's the official website?
Well, we don't have that yet.
Oh, okay.
But I...
All right.
And look, I mean, I don't know exactly how this is going to turn out.
I mean, what I can say is, yeah, there's some people working on this, right?
I think that there's something there that's interesting to explore.
So if you look at...
It'd be interesting to ask this question and throw Twitter into the mix.
That the landscape of social networks, that is Facebook, that is Instagram, that is WhatsApp,
and then think of a text-based social network.
When you look at that landscape, what are the interesting differences to you?
Why do we have these different flavors?
And what are the needs?
What are the use cases?
What are the products?
What is the aspect of them that create a fulfilling human experience
and a connection between humans that is somehow distinct?
Well, I think text is very accessible for people to transmit ideas and to have back
and forth exchanges.
So it, I think, ends up being a good format for discussion, in a lot of ways uniquely good, right?
If you look at some of the other formats or other networks that are focused on one type of content,
like TikTok is obviously huge, right?
And there are comments on TikTok, but I think the architecture of the service is very clearly that
you have the video is the primary thing and there's comments after that.
But I think one of the unique pieces of having text-based comments, the content is that the
comments can also be first-class and that makes it so that conversations can just filter and fork
into all these different directions and in a way that can be super useful.
So I think there's a lot of things that are really awesome about the experience.
It just always struck me.
I always thought that, you know, Twitter should have a billion people using it or whatever the
thing is that basically ends up being in that space.
And for whatever combination of reasons, again, these companies are complex organisms and it's
very hard to diagnose this stuff from the outside.
Why doesn't Twitter, why doesn't a text-based comment as a first citizen-based social network
have a billion users?
Well, I just think it's hard to build these companies.
So it's, you know, it's not that every idea automatically goes and gets a billion people.
It's just that I think that that idea coupled with good execution should get there.
But I mean, look, we hit certain thresholds over time where, you know, we kind of plateaued
early on and it wasn't clear that we were ever going to reach a hundred million people on Facebook.
And then we got really good at dialing in internationalization and helping the service
grow in different countries.
And that was like a whole competence that we needed to develop and helping people basically
spread the service to their friends.
That was one of the things, once we got very good at that, that was one of the things that
made me feel like, hey, if Instagram joined us early on, then I felt like we could help
grow that quickly.
And same with WhatsApp.
And I think that that's sort of been a core competence that we've developed and been able
to execute on and others have too, right?
I mean, ByteDance obviously have done a very good job with TikTok and have reached more
than a billion people there, but it's certainly not automatic, right?
I think you need a certain level of execution to basically get there.
And I think for whatever reason, I think Twitter has this great idea and sort of magic in the
service, but they just haven't kind of cracked that piece yet.
And I think that's made it so that you're seeing all these other things, whether it's
Mastodon or Blue Sky, that I think are maybe just different cuts at the same thing.
But I think through the last generation of social media overall, one of the interesting
experiments that I think should get run at larger scale is what happens if there's somewhat
more decentralized control and if it's like the stack is more open throughout.
And I've just been pretty fascinated by that and seeing how that works.
To some degree, end-to-end encryption on WhatsApp and as we bring it to other services provides
an element of it because it pushes the service really out to the edges.
I mean, the server part of this that we run for WhatsApp is relatively very thin compared
to what we do on Facebook or Instagram.
And much more of the complexity is how the apps kind of negotiate with each other to
pass information in a fully end-to-end encrypted way.
But I don't know, I think that that is a good model.
I think it puts more power in individuals' hands and there are a lot of benefits of it
if you can make it happen.
Again, this is all pretty speculative.
I mean, I think that it's hard from the outside to know why anything does or doesn't work
until you kind of take a run at it.
And so I think it's kind of an interesting thing to experiment with, but I don't really
know where this one's going to go.
So since we were talking about Twitter, Elon Musk had what I think a few harsh words that
I wish he didn't say.
So let me ask, in the hope and the name of camaraderie, what do you think Elon is doing
well with Twitter?
And what, as a person who has run for a long time, you, social networks, Facebook, Instagram,
WhatsApp, what can he do better?
What can he improve on that text-based social network?
Gosh, it's always very difficult to offer specific critiques from the outside before
you get into this, because I think one thing that I've learned is that everyone has opinions
on what you should do and like running the company, you see a lot of specific nuances
on things that are not apparent externally.
And I often think that some of the discourse around us would be, could be better if there
was more kind of space for acknowledging that there's certain things that we're seeing
internally that guide what we're doing.
But I don't know.
I mean, since you asked what is going well, I do think that Elon led a push early on to
make Twitter a lot leaner.
And I think that you can agree or disagree with exactly all the tactics and how we did
that.
Obviously, every leader has their own style for if you need to make dramatic changes for
that, how you're going to execute it.
But a lot of the specific principles that he pushed on around basically trying to make
the organization more technical, around decreasing the distance between engineers at the company
and him, like fewer layers of management.
I think that those were generally good changes.
And I also think that it was probably good for the industry that he made those changes
because my sense is that there were a lot of other people who thought that those were
good changes, but who may have been a little shy about doing them.
And I think he, just in my conversations with other founders and how people have reacted
to the things that we've done.
What I've heard from a lot of folks is just, hey, when someone like you, when I wrote
the letter outlining the organizational changes that I wanted to make back in March and when
people see what Elon is doing, I think that that gives people the ability to think through
how to shape their organizations in a way that hopefully can be good for the industry
and make all these companies more productive over time.
So I think that that was one where I think he was quite ahead of a bunch of the other
companies on.
And what he was doing there, and again, from the outside, very hard to know.
It's like, okay, did he cut too much?
Did he not cut enough?
Whatever.
I don't think it's like my place to opine on that.
And you asked for a positive framing of the question of what do I admire?
What do I admire?
What do I think went well?
But I think that certainly his actions led me and I think a lot of other folks in the
industry to think about, hey, are we kind of doing this as much as we should?
Could we make our companies better by pushing on some of these same principles?
Well, the two of you are in the top of the world in terms of leading the development
of tech, and I wish there was more both-way camaraderie and kindness, more love in the
world, because love is the answer.
But let me ask kind of a point of efficiency.
You recently announced multiple stages of layoffs at Meta.
What are the most painful aspects of this process, given for the individuals the painful
effects it has on those people's lives?
Yeah, I mean, that's it.
And that's it.
I mean, you basically have a significant number of people who this is just not the end of
their time at Meta that they or I would have hoped for when they joined the company.
And I mean, running a company, people are constantly joining and leaving the company
for different directions, but for different reasons.
But layoffs are uniquely challenging and tough in that you have a lot of people leaving for
reasons that aren't connected to their own performance or the culture not being a fit
at that point.
It's really just, it's a kind of strategy decision and sometimes financially required,
but not fully in our case, especially on the changes that we made this year.
A lot of it was more kind of culturally and strategically driven by this push where I
wanted us to become a stronger technology company with more of a focus on building more
technical and more of a focus on building higher quality products faster.
And I just view the external world is quite volatile right now.
And I wanted to make sure that we had a stable position to be able to continue investing
in these long-term ambitious projects that we have around continuing to push AI forward
and continuing to push forward all the metaverse work.
And in order to do that in light of the pretty big thrash that we had seen over the last
18 months, some of it macroeconomic induced, some of it competitively induced, some of
it just because of bad decisions or things that we got wrong, I decided that we needed
to get to a point where we were a lot leaner.
But look, I mean, but then, okay, it's one thing to do that, to decide that at a high
level.
Then the question is, how do you execute that as compassionately as possible?
And there's no good way.
There's no perfect way for sure.
And it's going to be tough no matter what.
But as a leadership team here, we've certainly spent a lot of time just thinking, okay, given
that this is a thing that sucks, what is the most compassionate way that we can do this?
And that's what we've tried to do.
And you mentioned there's an increased focus on engineering, on tech, so technology teams,
tech-focused teams on building products, that.
Yeah.
I mean, I wanted to empower engineers more.
The people are building things, the technical teams.
Part of that is making sure that the people who are building things aren't just at the
leaf nodes of the organization.
I don't want eight levels of management and then the people actually doing the work.
So we made changes to make it so that you have individual contributor engineers reporting
at almost every level up the stack, which I think is important because you're running
a company, one of the big questions is latency of information that you get.
And we talked about this a bit earlier in terms of the joy of the feedback that you
get doing something like jujitsu compared to running a long-term project.
But I actually think part of the art of running a company is trying to constantly re-engineer
it so that your feedback loops get shorter so you can learn faster.
And part of the way that you do that is by, I think that every layer that you have in
the organization means that information might not need to get reviewed before it goes to
you.
And I think making it so that the people doing the work are as close as possible to you as
possible is pretty important.
So there's that.
And I think over time, companies just build up very large support functions that are not
doing the kind of core technical work.
And those functions are very important, but I think having them in the right proportion
is important.
And if you try to do good work, but you don't have the right marketing team or the right
legal advice, you're going to make some pretty big blunders.
But at the same time, if you just have too big of things in some of these support roles,
then that might make it so things just move a lot.
Maybe you're too conservative or you move a lot slower than you should otherwise introduce.
Those are just examples.
But it's, but.
How do you find that balance?
That's really tough.
Yeah, no, but that's, it's a constant equilibrium that you're searching for.
Yeah.
How many managers to have?
What are the pros and cons of managers?
Well, I mean, I believe a lot in management.
I mean, there are some people who think that it doesn't matter as much, but look, I mean,
we have a lot of younger people at the company firm.
This is their first job and people need to grow and learn in their career and that all
that stuff is important, but here's one mathematical way to look at it.
The beginning of this, I asked our people team, what was the average number of reports
that a manager had?
And I think it was around three, maybe three to four, but closer to three.
I was like, wow, like a manager can, you know, best practices that person can, can manage,
you know, seven or eight people.
But there was a reason why it was closer to three.
It was because we were growing so quickly, right?
And when you're hiring so many people so quickly, then that means that you need managers who
have capacity to onboard new people.
And also if you have a new manager, you may not want to have them have seven direct reports
immediately because you want them to ramp up.
But the thing is going forward, I don't want us to actually hire that many people that
quickly, right?
So I actually think we'll just do better work if we have more constraints and we're, you
know, leaner as an organization.
So in a world where we're not adding so many people as quickly, is it as valuable to have
a lot of managers who have extra capacity waiting for new people?
No, right?
So now we can sort of defragment the organization and get to a place where the average is closer
to that seven or eight.
And it just ends up being a somewhat more kind of compact management structure, which
decreases the latency on information going up and down the chain and I think empowers
people more.
But I mean, that's an example that I think it doesn't kind of undervalue the importance
of management and the kind of the personal growth or coaching that people need in order
to do their jobs well.
It's just, I think, realistically, we're just not going to hire as many people going
forward.
So I think that you need a different structure.
This whole incredible hierarchy and network of humans that make up a company is fascinating.
Oh, yeah.
How do you hire great teams?
How do you hire great now with the focus on engineering and technical teams?
How do you hire great engineers and great members of technical teams?
Well, you're asking how you select or how you attract them?
Both, but select, I think, uh, I think attract is work on cool stuff and have a vision.
I think that's right.
And, and, and have a track record that people think you're actually going to be able to
do it.
Yeah.
To me, the select is seems like more of the art form, more of the tricky thing.
Yeah.
Do you select the people that fit the culture and can get integrated the most effectively
and so on?
And maybe, yeah.
Especially when they're young to see, like, to see the magic through the, um, through
the resumes that the paperwork and all this kind of stuff, to see that there's a special
human there that would do like incredible work.
So there are lots of different cuts on this question.
I mean, I think when an organization has grown quickly, one of the big questions that teams
face is, do I hire this person who's in front of me now because they seem good?
Or do I hold out to get someone who's even better?
And the heuristic that I always focused on for myself and my own kind of direct hiring
that I, that I, that I think works when you, when you recurse it through the organization
is that you should only hire someone to be on your team if you would be happy working
for them in an alternate universe.
And something that, that, that kind of works.
And, you know, that's basically how I've tried to build my team.
It's, you know, I'm not, I'm not in a rush to not be running the company, but I think
in an alternate universe where one of these other folks was running the company, I'd be
happy to work for them.
I feel like I'd learn from them.
I respect their kind of general judgment.
They're, they're all very insightful.
They have good values.
And, and I think that that gives you some rubric for, you can apply that at every layer.
And I think if you apply that at every layer in the organization, then you'll have a pretty
strong relationship with them.
You'll have a pretty strong organization.
Okay.
In an organization that's not growing as quickly, the questions might be a little different
though.
And there, you asked about young people specifically, like people out of college.
And one of the things that we see is it's, it's a pretty basic lesson, but like we have
a much better sense of who the best people are who have interned at the company for a
couple of months than by looking at them at, at, at, at kind of a resume or a short,
or a short interview loop.
I mean, obviously the, the in-person feel that you get from someone probably tells you
more than the resume and you can do some basic skills assessment, but a lot of the stuff
really just is cultural.
People thrive in different environments and on different teams, even within a specific
company and it's, it's like the people who come for even a short period of time over
a summer who do a great job here, you know that they're going to be great if they, if
they came and joined full time.
And that's one of the reasons why we've invested so much in internship is, is basically
it just, it's a very useful sorting function, both for us and for the people who want to
try out the company.
You mentioned in person, what do you think about remote work?
A topic that's been discussed extensively because of the, over the past few years because
of the pandemic.
Yeah.
I mean, I think it's, I mean, it's, it's a thing that's here to stay.
But I think that there's, there's value in both, right?
It's not, you know, I wouldn't want to run a fully remote company yet.
At least I think there's an asterisk on that, which is that, which is that.
Some of the other stuff you're working on.
Yeah.
Yeah, exactly.
It's like all the, all the you know, metaverse work and the ability to be, to feel like you're
truly present no matter where you are.
I think once you have that all dialed in, then we may, you know, one day reach a point
where it really just doesn't matter as much where you are physically.
But I don't know, today it, today it still does, right?
So yeah, for people who, there are all these people who have special skills and want to
live in a place where we don't have an office, are we better off having them at the company?
Absolutely.
Right.
And are a lot of people who work at the company for several years and then, you know, build
up the relationships internally and kind of have the trust and have a sense of how the
company works, can they go work remotely now if they want and still do it as effectively?
And we've done all these studies that show it's like, okay, does that affect their
performance?
It does not.
But, you know, for the new folks who are joining and for people who are earlier in their career
and, you know, need to learn how to solve certain problems and need to get ramped up
on the culture, you know, when you're working through really complicated problems where
you don't just want to sit in the, you don't just want the formal meeting, but you want
to be able to like brainstorm when you're walking in the hallway together after the
meeting, I don't know, it's like we just haven't replaced the kind of in-person dynamics
there yet with anything remote yet, so.
Yeah, there's a magic to the in-person that, we'll talk about this a little bit more,
but I'm really excited by the possibilities in the next two years in virtual reality and
mixed reality that are possible with high resolution scans.
I mean, I, as a person who loves in-person interaction, like these podcasts in person,
it would be incredible to achieve the level of realism I've gotten the chance to witness.
But let me ask about that.
Yeah.
I got a chance to look at the Quest 3 headset and it is amazing.
You've announced it.
It's, you'll get some more details in the fall, maybe release in the, when is it getting
released again?
I forgot, you mentioned it.
We'll give more details at Connect, but it's coming this fall.
Okay.
So, it's priced at $499.
What features are you most excited about there?
There are basically two big new things that we've added to Quest 3 over Quest 2.
The first is high resolution mixed reality.
And the basic idea here is that you can think about virtual reality as you have the headset
and like all the pixels are virtual and you're basically like immersed in a different world.
Mixed reality is where you see the physical world around you and you can place virtual
objects in it, whether that's a screen to watch a movie or a projection of your virtual
desktop, or you're playing a game where like zombies are coming out through the wall and
you need to shoot them.
Or, you know, we're, you know, we're playing Dungeons and Dragons or some board game and
we just have a virtual version of the board in front of us while we're sitting here.
All that's possible in mixed reality.
And I think that that is going to be the next big capability on top of virtual reality.
It has done so well.
I have to say, as a person who experienced it today with zombies, having a full awareness
of the environment and integrating that environment in the way they run at you while they try
to kill you, it's just the mixed reality, the pass through is really, really, really well done.
And the fact that it's only $500 is really, it's well done.
Thank you.
I mean, I'm super excited about it.
I mean, our, and we put a lot of work into making the device both as good as possible
and as affordable as possible, because a big part of our mission and ethos here is we want
people to be able to connect with each other.
We want to reach and we want to serve a lot of people, right?
We want to bring this technology to everyone, right?
So we're not just trying to serve like a, you know, an elite, a wealthy crowd.
We want to, we really want this to be accessible.
So that is in a lot of ways, an extremely hard technical problem because, you know,
we don't just have the ability to put an unlimited amount of hardware in this.
We needed to basically deliver something that works really well, but in an affordable package.
And we started with Quest Pro last year.
It was, it was $1,500.
And now we've lowered the price to a thousand, but in a lot of ways, the mixed reality and
Quest 3 is an even better and more advanced level than what we were able to deliver in Quest Pro.
So I'm really proud of where we are with Quest 3 on that.
It's going to work with all of the virtual reality titles and everything that existed
there.
So people who want to play fully immersive games, social experiences, fitness, all that
stuff will work.
But now you'll also get mixed reality too.
Which I think people really like because it's sometimes you want to be super immersed in
a game, but a lot of the time, especially when you're moving around, if you're active,
like you're, you're doing some fitness experience.
Let's say you're, you're like doing boxing or something.
It's like, you kind of want to be able to see the room around you so that way, you know
that like, I'm not going to punch a lamp or something like that.
And I don't know if you got to play with this experience, but basically have the, and it's
just sort of like a fun little, little demo that we put together, but it's, it's like
you just, you know, we're like in a conference room or you're a living room and you, you
have the guy there and you're boxing him and you're fighting him.
And it's like, all the other people are there too.
I got a chance to do that.
And all the people are there.
It's like that guy's right there.
Yeah.
There's a good thread in the room.
And the other human, the path that you're seeing them also, they can cheer you on.
They can make fun of you if they're anything like friends of mine.
And then just it, yeah, it, it, it's really, it's a really compelling experience.
I mean, VR is really interesting too, but this is something else almost.
This is, this becomes integrated into your life, into your world.
Yeah.
And it, so I think it's a completely new capability that will unlock a lot of different
content.
And I think it'll also just make the experience more comfortable for a set of people who
didn't want to have only fully immersive experiences.
I think if you want experiences where you're grounded in, you know, your living room in
the physical world around you, now you'll be able to have that too.
And I think that that's pretty exciting.
I really liked how it added windows to a room with no windows.
Yeah.
Me as a person.
Did you see the aquarium one where you could see the shark swim up or was that just the
zombie one?
Just the zombie one, but it's still outside.
You don't necessarily want windows added to your living room where zombies come out of,
but yes, in the context of that game, it's yeah, yeah, yeah.
I enjoyed it because you could see the nature outside.
And me as a person that doesn't have windows, it's just nice to have nature.
Yeah.
Even if it's a mixed reality setting.
I know it's a zombie game, but there's a Zen aspect to being able to look outside and
alter your environment as you know it.
Yeah.
There will probably be better, more Zen ways to do that than the zombie game you're describing,
but you're right that the basic idea of sort of having your physical environment on pass
through, but then being able to bring in different elements, I think it's going to be super
powerful.
And in some ways, I think that these are mixed reality is also a predecessor to eventually
we will get AR glasses that are not kind of the goggles form factor of the current generation
of headsets that people are making.
But I think a lot of the experiences that developers are making for mixed reality of
basically you just have a kind of a hologram that you're putting in the world will hopefully
apply once we get the AR glasses too.
Now that's got its own whole set of challenges and it's.
Well, the headsets already smaller than the previous version.
Oh yeah, it's 40% thinner.
And the other thing that I think is good about it, it's yeah, so mixed reality was the first
big thing.
The second is it's just a great VR headset.
I mean, it's got 2x the graphics processing power, 40% sharper screens, 40% thinner, more
comfortable, better strap architecture, all this stuff that, you know, if you liked Quest
2, I think that this is just going to be, it's like all this, all the content that you might
have played in Quest 2 is just going to get sharper automatically and look better in this.
So it's, I think people are really going to like it.
Yeah, so this fall.
This fall, I have to ask, Apple just announced a mixed reality headset called Vision Pro
for $3,500 available in early 2024.
What do you think about this headset?
Well, I saw the materials when they launched.
I haven't gotten a chance to play with it yet.
So kind of take everything with a grain of salt, but a few high-level thoughts.
I mean, first, you know, I do think that this is a certain level of validation for
the category, right?
Where, you know, we were the primary folks out there before saying, hey, I think that
this, you know, virtual reality, augmented reality, mixed reality, this is going to be
a big part of the next computing platform.
I think having Apple come in and share that vision will make a lot of people who are fans
of their products really consider that.
And then, you know, of course, the $3,500 price, you know, on the one hand, I get it
for with all the stuff that they're trying to pack in there.
On the other hand, a lot of people aren't going to find that to be affordable.
So I think that there's a chance that them coming in actually increases demand for the
overall space, and that Quest 3 is actually the primary beneficiary of that, because a
lot of the people who might say, hey, you know, this, I think I'm going to give another
consideration to this, or, you know, now I understand maybe what mixed reality is more,
and Quest 3 is the best one on the market that I can afford, and it's great also, right?
I think that that's, and, you know, in our own way, I think we're, and there are a lot
of features that we have where we're leading on, so I think that that's, that I think
is going to be a very, that could be quite good.
And then obviously, over time, the companies are just focused on somewhat different things,
right?
Apple has always, you know, I think focused on building really kind of high-end things,
whereas our focus has been on, it's just, we have a more democratic ethos, we want to
build things that are accessible to a wider number of people.
You know, we've sold tens of millions of Quest devices.
My understanding, just based on rumors, I don't have any special knowledge on this,
is that Apple is building about 1 million of their device, right?
So just in terms of like what you kind of expect in terms of sales numbers, I just think
that this is, I mean, Quest is going to be the primary thing that people in the market
will continue using for the foreseeable future.
And then obviously, over the long term, it's up to the companies to see how well we each
executed the different things that we're doing.
But we kind of come at it from different places.
We're very focused on social interaction, communication, being more active, right?
So there's fitness, there's gaming, there are those things.
Whereas I think a lot of the use cases that you saw in Apple's launch material were more
around, you know, people sitting, you know, people looking at screens, which are great.
I think that you will replace your laptop over time with a headset.
But I think in terms of kind of how the different use cases that the companies are going after,
they're a bit different for where we are right now.
Yeah.
So gaming wasn't a big part of the presentation, which is interesting.
It feels like mixed reality gaming is such a big part of that.
It was interesting to see it missing in the presentation.
Well, I mean, look, there are certain design trade-offs in this where, you know, they
made this point about not wanting to have controllers, which on the one hand,
there's a certain elegance about just being able to navigate the system with
eye gaze and hand tracking.
And by the way, you'll be able to just navigate Quest with your hands too, if that's what you want.
Yeah, one of the things I should mention is that the capability from the cameras with
computer vision to detect certain aspects of the hand, allowing you to have a controller
that doesn't have that ring thing.
Yeah, the hand tracking in Quest 3 and the controller tracking is a big step up from
the last generation.
And one of the demos that we have is basically an MR experience teaching you how to play
piano, where it basically highlights the notes that you need to play.
And it's like, it's hands, it's no controllers.
But I think if you care about gaming, having a controller allows you to have a more tactile
feel and allows you to capture fine motor movement much more precisely than what you
can do with hands without something that you're touching.
So again, I think there are certain questions which are just around what use cases are you
optimizing for?
I think if you want to play games, then I think that you want to design the system in
a different way.
And we're more focused on kind of social experiences, entertainment experiences.
Whereas if what you want is to make sure that the text that you read on a screen is as crisp
as possible, then you need to make the design and cost trade-offs that they made that lead
you to making a $3,500 device.
So I think that there is a use case for that, for sure.
But I just think that the companies, we've basically made different design trade-offs
to get to the use cases that we're trying to serve.
There's a lot of other stuff I'd love to talk to you about, about the metaverse, especially
the Kodak Avatar, which I've gotten to experience a lot of different variations of recently
that I'm really, really excited about.
Yeah, I'm excited to talk about that too.
I'll have to wait a little bit because, well, I think there's a lot more to show off in
that regard.
But let me step back to AI.
I think we've mentioned it a little bit, but I'd like to linger on this question that
folks like Eliezer Yudkowsky has to worry about and others of the existential, the serious
threats of AI that have been reinvigorated now with the rapid developments of AI systems.
Do you worry about the existential risks of AI as Eliezer does, about the alignment
problem, about this getting out of hand?
Any time where there's a number of serious people who are raising a concern that is that
existential about something that you're involved with, I think you have to think about it.
So I've spent quite a bit of time thinking about it from that perspective.
The thing where I basically have come out on this for now is I do think that there are,
over time, I think that we need to think about this even more as we approach something that
could be closer to super intelligence.
I just think it's pretty clear to anyone working on these projects today that we're not there.
And one of my concerns is that we spent a fair amount of time on this before, but there
are more, I don't know if mundane is the right word, but there's like concerns that already
exist about people using AI tools to do harmful things of the type that we're already
aware, whether we talked about fraud or scams or different things like that.
And that's going to be a pretty big set of challenges that the companies working on this
are going to need to grapple with regardless of whether there is an existential concern
as well at some point down the road.
So I do worry that to some degree, people can get a little too focused on some of the
tail risk and then not do as good of a job as we need to on the things that you can be
almost certain are going to come down the pipe as real risks that kind of manifest themselves
in the near term.
So for me, I've spent most of my time on that once I kind of made the realization that the
size of models that we're talking about now in terms of what we're building are quite
far from the super intelligence type concerns that people raise.
But I think once we get a couple steps closer to that, I know as we do get closer, I think
that there are going to be some novel risks and issues about how we make sure that the
systems are safe for sure.
I guess here just to take the conversation in a somewhat different direction, I think
in some of these debates around safety, I think the concepts of intelligence and autonomy
or like the being of the thing as an analogy, they get kind of conflated together.
And I think it very well could be the case that you can make something and scale intelligence
quite far, but that may not manifest the safety concerns that people are saying in the sense
that I mean, just if you look at human biology, it's like, all right, we have our neocortex
is where all the thinking happens, right?
But it's not really calling the shots at the end of the day.
We have a much more primitive old brain structure for which our neocortex, which is this
powerful machinery is basically just a kind of prediction and reasoning engine to help
it kind of like our very simple brain decide how to plan and do what it needs to do in
order to achieve these like very kind of basic impulses.
And I think that you can think about some of the development of intelligence along the
same lines where just like our neocortex doesn't have free will or autonomy, we might
develop these wildly intelligent systems that are much more intelligent than our neocortex
have much more capacity, but are in the same way that our neocortex is sort of subservient
and is used as a tool by our kind of simple impulse brain, I think that it's not out of
the question that very intelligent systems that have the capacity to think will kind
of act as that as sort of an extension of the neocortex doing that.
So I think my own view is that where we really need to be careful is on the development of
autonomy and how we think about that because it's actually the case that
relatively simple and unintelligent things that have runaway autonomy and just spread
themselves or, you know, it's like we have a word for that.
It's a virus, right?
It's I mean, like it's can be simple computer code that is not particularly intelligent,
but just spreads itself and does a lot of harm, you know, biologically or computer.
And I just think that these are somewhat separable things.
And a lot of what I think we need to develop when people talk about safety and responsibility
is really the governance on the autonomy that can be given to systems.
And to me, you know, if I were, you know, a policymaker or think about this, I would
really want to think about that distinction between these where I think building intelligent
systems will be can create a huge advance in terms of people's quality of life and
productivity growth in the economy.
But it's the autonomy part of this that I think we really need to make progress on how
to govern these things responsibly before we build the capacity for them to make a lot
of decisions on their own or give them goals or things like that.
And I think that that's a research problem, but I do think that to some degree, these
are somewhat separable things.
CB I love the distinction between intelligence
and autonomy and the metaphor within neocortex.
Let me ask about power.
So building super intelligence systems, even if it's not in the near term, I think meta
is one of the few companies, if not the main company that will develop the super
intelligence system, and you are a man who's at the head of this company, building AGI
might make you the most powerful man in the world.
Do you worry that that power will corrupt you?
CB What a question.
I mean, look, I think realistically, this gets back to the open source things that we
talked about before, which is I don't think that the world will be best served by any
small number of organizations having this without it being something that is more broadly
available.
And I think if you look through history, it's when there are these sort of like unipolar
advances and things and power imbalances that they're doing to being kind of weird
situations.
So this is one of the reasons why I think open sources is generally the right approach.
And I think it's a categorically different question today when we're not close to super
intelligence.
I think that there's a good chance that even once we get closer to super intelligence,
open sourcing remains the right approach, even though I think at that point it's a somewhat
different debate.
But I think part of that is that that is I think one of the best ways to ensure that the
system is as secure and safe as possible, because it's not just about a lot of people
having access to it.
It's the scrutiny that kind of comes with building an open source system.
I think that this is a pretty widely accepted thing about open source is that you have the
code out there, so anyone can see the vulnerabilities.
Anyone can kind of mess with it in different ways.
People can spin off their own projects and experiment in a ton of different ways.
And the net result of all of that is that the systems just get hardened and get to be
a lot safer and more secure.
So I think that there's a chance that that ends up being the way that this goes to, a
pretty good chance, and that having this be open both leads to a healthier development
of the technology and also leads to a more balanced distribution of the technology in
a way that strikes me as good values to aspire to.
So to you, there's risks to open sourcing, but the benefits outweigh the risks.
At the two, it's interesting, I think the way you put it well, that there's a different
discussion now than when we get closer to the development of super intelligence of the
benefits and risks of open sourcing.
Yeah, and to be clear, I feel quite confident in the assessment that open sourcing models
now is net positive.
I think there's a good argument that in the future it will be too, even as you get closer
to super intelligence.
But I've certainly have not decided on that yet, and I think that it becomes a somewhat
more complex set of questions that I think people will have time to debate and will also
be informed by what happens between now and then to make those decisions, so we don't
have to necessarily just debate that in theory right now.
What year do you think we'll have a super intelligence?
I don't know.
I mean, that's pure speculation.
I think it's very clear, just taking a step back, that we had a big breakthrough in the
last year, where the LLMs and diffusion models basically reached a scale where they're able
to do some pretty interesting things.
And then I think the question is, what happens from here?
And just to paint the two extremes, on one side, it's like, okay, we just had one
breakthrough.
If we just have another breakthrough like that, or maybe two, then we could have something
that's truly crazy and is just so much more advanced.
And on that side of the argument, it's like, okay, well, maybe we're only a couple of
big steps away from reaching something that looks more like general intelligence.
Okay, that's one side of the argument.
And the other side, which is what we've historically seen a lot more, is that a
breakthrough leads to, in that Gartner hype cycle, there's the hype, and then there's
the trough of disillusionment after, when people think that there's a chance that,
hey, okay, there's a big breakthrough.
Maybe we're about to get another big breakthrough.
And it's like, actually, you're not about to get another breakthrough.
Maybe you're actually just going to have to sit with this one for a while.
And it could be five years.
It could be 10 years.
It could be 15 years until you figure out the next big thing that needs to get figured
out.
But I think that the fact that we just had this breakthrough sort of makes it so that
we're at a point of almost a very wide error bars on what happens next.
I think the traditional technical view or looking at the industry would suggest that
we're not just going to stack in a breakthrough on top of breakthrough on top of breakthrough
like every six months or something.
Right now, I think it will, I'm guessing, I would guess that it will take somewhat longer
in between these, but I don't know.
I tend to be pretty optimistic about breakthroughs, too.
So I think if you normalized for my normal optimism, then maybe it would be even slower
than what I'm saying.
But even within that, I'm not even opining on the question of how many breakthroughs
are required to get to general intelligence because no one knows.
But this particular breakthrough was such a small step that resulted in such a big leap
in performance as experienced by human beings that it makes you think, wow, as we stumble
across this very open world of research, will we stumble across another thing that
will have a giant leap in performance?
And also, we don't know exactly at which stage is it really going to be impressive because
it feels like it's really encroaching on impressive levels of intelligence.
You still didn't answer the question of what year we're going to have super intelligence.
I'd like to hold you to that.
No, I'm just kidding.
But is there something you could say about the timeline as you think about the development
of AGI, super intelligence systems?
Sure.
So I still don't think I have any particular insight on when a singular AI system that
is a general intelligence will get created.
But I think the one thing that most people in the discourse that I've seen about this
haven't really grappled with is that we do seem to have organizations and structures
in the world that exhibit greater than human intelligence already.
So one example is a company.
It acts as an entity.
It has a singular brand.
Obviously, it's a collection of people.
But I certainly hope that meta with tens of thousands of people make smarter decisions
than one person.
But I think that that would be pretty bad if it didn't.
Another example that I think is even more removed from the way we think about the personification
of intelligence, which is often implied in some of these questions, is think about something
like the stock market.
The stock market takes inputs.
It's a distributed system.
It's like the cybernetic organism that probably millions of people around the world are basically
voting every day by choosing what to invest in.
But it's basically this organism or structure that is smarter than any individual that we
use to allocate capital as efficiently as possible around the world.
And I do think that this notion that there are already these cybernetic systems that
are either melding the intelligence of multiple people together or melding the intelligence
of multiple people and technology together to form something which is dramatically more
intelligent than any individual in the world is something that seems to exist and that
we seem to be able to harness in a productive way for our society as long as we basically
build these structures in balance with each other.
So, I don't know.
I mean, that at least gives me hope that as we advance the technology, and I don't know
how long exactly it's going to be, but you asked when is this going to exist.
I think to some degree, we already have many organizations in the world that are smarter
than a single human.
And that seems to be something that is generally productive in advancing humanity.
And somehow the individual AI systems empower the individual humans and the interaction
between those humans to make that collective intelligence machinery that you're referring
to smarter.
So, it's not like AI is becoming super intelligent.
It's just becoming the engine that's making the collective intelligence that's primarily
human more intelligent.
It's educating the humans better.
It's making them better informed.
It's making it more efficient for them to communicate effectively and debate ideas.
And through that process, just making the whole collective intelligence more and more
and more intelligent, maybe faster than the individual AI systems that are trained on
human data anyway are becoming.
Maybe the collective intelligence of the human species might outpace the development of AI.
Just like, it's a race.
I think there is a balance in here because I mean, if like, you know, if a lot of the
input that the systems are being trained on is basically coming from feedback from people,
then a lot of the development does need to happen in human time, right?
It's not like a machine will just be able to go learn all this stuff about how people
think about stuff.
There's a cycle to how this needs to work.
CB This is an exciting world we're living in,
and that you're at the forefront of developing.
One of the ways you keep yourself humble, like we mentioned with Jiu Jitsu, is doing
some really difficult challenges, mental and physical.
One of those you've done very recently is the Murph challenge, and you got a really
good time.
It's 100 pull-ups, 200 push-ups, 300 squats, and a mile before and a mile run after.
You got under 40 minutes on that.
What was the hardest part?
I think a lot of people were very impressed.
It's very impressive time.
CB How crazy are you?
This is the question I'm asking.
Wasn't my best time, but anything under 40 minutes I'm happy with.
JF It wasn't your best time.
CB No, I think I've done it a little faster
before, but not much.
Of my friends, I did not win on Memorial Day.
One of my friends did it actually several minutes faster than me.
Just to clear up one thing that I think was, I saw a bunch of questions about this on the
internet.
There are multiple ways to do the Murph challenge.
There's a kind of partitioned mode where you do sets of pull-ups, push-ups, and squats
together.
And then there's unpartitioned where you do the 100 pull-ups, and then the 200 push-ups,
and then the 300 squats in serial.
And obviously, if you're doing them unpartitioned, then it takes longer to get through the 100
pull-ups because anytime you're resting in between the pull-ups, you're not also doing
push-ups and squats.
So yeah, I'm sure my unpartitioned time would be quite a bit slower.
But no, I think at the end of this, first of all, I think it's a good way to honor
Memorial Day.
This Lieutenant Murphy, basically, this was one of his favorite exercises, and I just
try to do it on Memorial Day each year.
And it's a good workout.
I got my older daughters to do it with me this time.
My oldest daughter wants a weight vest because she sees me doing it with a weight vest.
I don't know if a seven-year-old should be using a weight vest to do pull-ups.
Yeah, a difficult question a parent must ask themselves, yes.
I was like, maybe I can make you a very lightweight vest.
But I didn't think it was good for this.
So she basically did a quarter Murph.
So she ran a quarter mile and then did 25 pull-ups, 50 push-ups, and 75 air squats,
then ran another quarter mile in 15 minutes, which I was pretty impressed by, and my five-year-old
too.
So I was excited about that.
And I'm glad that I'm teaching them the value of physicality.
I think a good day for Max, my daughter, is when she gets to go to the gym with me and
cranks out a bunch of pull-ups.
And I love that about her.
I mean, I think it's good.
She's, you know, hopefully I'm teaching her some good lessons.
But I mean, the broader question here is, given how busy you are, given how much stuff
you have going on in your life, what's the perfect exercise regimen for you to keep
yourself happy, to keep yourself productive in your main line of work?
Yeah.
So I mean, right now I'm focused most of my workouts on fighting, so jujitsu and MMA.
But I don't know, I mean, maybe if you're a professional, you can do that every day.
I can't.
I just get, you know, it's too many bruises and things that you need to recover from.
So I do that, you know, three to four times a week.
And then the other days I just try to do a mix of things, like just cardio conditioning,
strength building, mobility.
So you try to do something physical every day?
Yeah, I try to, unless I'm just so tired that I just need to relax.
But then I'll still try to like go for a walk or something.
I mean, even here, I don't know, I mean, have you been on the roof here yet?
No.
We'll go on the roof after this.
But it's like, we designed this building and I put a park on the roof.
So that way, that's like my meetings when I'm just doing kind of a one-on-one or talking
to a couple of people, I have a very hard time just sitting.
I feel like it gets super stiff, it like feels really bad.
But I don't know, being physical is very important to me.
I think it's, I do not believe, this gets to the question about AI,
I don't think that a being is just a mind.
And I think we're kind of meant to do things and like physically and a lot of the sensations
that we feel are connected to that.
And I think that that's a lot of what makes you a human is basically having that set of
sensations and experiences around that coupled with a mind to reason about them.
But I don't know, I think it's important for balance to kind of get out, challenge yourself
in different ways, learn different skills, clear your mind.
Do you think AI in order to become super intelligent and AGI should have a body?
It depends on what the goal is.
I think that there's this assumption in that question that intelligence should be kind
of person-like whereas as we were just talking about, you can have these greater than single
human intelligent organisms like the stock market, which obviously do not have bodies
and do not speak a language and just kind of have their own system.
But so I don't know.
My guess is there will be limits to what a system that is purely an intelligence can
understand about the human condition without having the same, not just senses, but like
our bodies change as we get older, right?
And we kind of evolve and I think that those very subtle physical changes just drive a
lot of social patterns and behavior around like when you choose to have kids, right?
Just like all these, that's not even subtle.
That's a major one, right?
But how you design things around the house.
So yeah, I think if the goal is to understand people as much as possible, I think that
trying to model those sensations is probably somewhat important, but I think that there's
a lot of value that can be created by having intelligence even that is separate from that.
So one of the features of being human is that we're mortal.
We die.
We've talked about AI a lot, about potentially replicas of ourselves.
Do you think there will be AI replicas of you and me that persist long after we're gone,
that family and loved ones can talk to?
I think we'll have the capacity to do something like that.
And I think one of the big questions that we've had to struggle with in the context
of social networks is who gets to make that?
And my answer to that in the context of the work that we're doing is that that should
be your choice, right?
I don't think anyone should be able to choose to make a Lexbot that people can choose to
talk to and get to train that.
And we have this precedent of making some of these calls where someone can create a
page for a Lex fan club, but you can't create a page and say that you're Lex, right?
So I think that similarly, I think someone maybe should be able to make an AI that's
a Lex admirer that someone can talk to, but I think it should ultimately be your call,
whether there is a Lex AI.
Well, I'm open sourcing the Lex.
So you're a man of faith.
What role has faith played in your life, in your understanding of the world, in your understanding
of your own life, in your understanding of your work and how your work impacts the world?
Yeah, I think that there's a few different parts of this that are relevant.
There's sort of a philosophical part and there's a cultural part.
And one of the most basic lessons is right at the beginning of Genesis, right?
It's like God creates the earth and creates people and creates people in God's image.
And there's the question of, you know, what does that mean?
And all the only context that you have about God at that point in the Old Testament is
that God has created things.
So I always thought that like one of the interesting lessons from that is that, you know,
there's a virtue in creating things that is like whether it's artistic or whether you're
building things that are functionally useful for other people.
I think that that by itself is a good.
And that kind of drives a lot of how I think about morality and my personal philosophy
around like what is a good life, right?
I think it's one where you're, you know, helping the people around you and you're being
a kind of positive creative force in the world that is helping to, you know, bring new things
into the world, whether they're, you know, amazing other people, kids, or just leading
to the creation of different things that wouldn't have been possible otherwise.
So that's a value for me that matters deeply.
And I just, I mean, I just love, you know, spending time with the kids and seeing that
they sort of, you know, trying to impart this value to them.
And yeah, it's like, I mean, nothing makes me happier than like when I come home from
work and, you know, I see like my daughter's like building Legos on the table or something.
It's like, all right, I did that when I was a kid, right?
So many other people were doing this.
And like, I hope you don't lose that spirit where when you kind of grow up and you want
to just continue building different things, no matter what it is, to me, that's a lot
of what matters.
That's the philosophical piece.
I think the cultural piece is just about community and values.
And that part of things I think has just become a lot more important to me since I've had
kids.
You know, it's almost autopilot when you're a kid.
You're in the kind of getting imparted to phase of your life.
But and I didn't really think about religion that much for a while.
You know, I was in college, you know, before I had kids.
And then I think having kids has this way of really making you think about what traditions
you want to impart and how you want to celebrate and like what balance you want in your life.
And I mean, a bunch of the questions that you've asked and a bunch of the things that
we're talking about.
Just the irony of the curtains coming down as we're talking about mortality.
Once again, same as last time, this is just that the universe works and we are definitely
living in a simulation, but go ahead.
Community, tradition, and the values that faith and religion instills.
A lot of the topics that we've talked about today are around how do you, how do you balance
balance, you know, whether it's running a company or different responsibilities with
this, how do you kind of balance that?
And I always also just think that it's very grounding to just believe that there is something
that is much bigger than you that is guiding things.
That amongst other things gives you a bit of humility.
As you pursue that spirit of creating that you spoke to, creating beauty in the world.
And as Dostoevsky said, beauty will save the world.
Mark, I'm a huge fan of yours.
Honored to be able to call you a friend.
And I am looking forward to both kicking your ass and you kicking my ass on the mat tomorrow
in Jiu Jitsu, this incredible sport and art that we both participate in.
Thank you so much for talking today.
Thank you for everything you're doing in so many exciting realms of technology and human
life.
I can't wait to talk to you again in the metaverse.
Thank you.
Thanks for listening to this conversation with Mark Zuckerberg.
To support this podcast, please check out our sponsors in the description.
And now let me leave you with some words from Isaac Asimov.
It is change, continuing change, inevitable change that is the dominant factor in society
today.
No sensible decision can be made any longer without taking into account not only the world
as it is, but the world as it will be.
Thank you for listening and hope to see you next time.
Bye.