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Hello everyone.

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Welcome to lunch. Not for you and me,

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but welcome to lunch. Um,

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uh, I think we've had a, uh, a great day

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so far and, uh, and I'm honored to have

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with me, uh, Sam Alman, uh, joining us

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for our discussion about,

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uh, AI and and where we're going from

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here. So, um,

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so thanks for thanks for joining us. You

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have really the greatest countries in

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the world all around you. So would you

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mind giving us a little history like how

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do how do you go from being Sam Alman to

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being the head of AI and really at the
frontier like sort of walk us through

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how you got from there to here?

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>> First of all, thank you very much
for having me. Um as you said, this is

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greatest countries in the world and it's
it's a great honor to get to address all

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of you at the same time. Um

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I I was always an AI nerd. I was like
a real sci-fi nerd as a kid. I thought AI

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was the coolest thing. I always wanted
to work on it. Um, I never like really

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thought I'd actually get to do it.
I kind of can't believe this happened to

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me, but I I always I always
thought it was awesome. I went

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to school to study it at the time.

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Nothing was working and I kind of gave
up on it and I went on this side quest

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of entrepreneurship, which was also

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great. Um, and then in 2012,

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um, everything changed. None of us paid

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enough attention, but there was a a real
watershed moment where all of a sudden

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deep learning started to work and it got
better with more compute. And I paid a

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lot of attention to that for the next
couple of years. And by the time 2015

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rolled around, I was like, hey, this is
really this is going to happen. Like we

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got to take we got to try this could be
like the most important thing ever. Uh

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and so we thought for a while about what

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to do and started OpenAI. Uh and

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>> so what year did you start OpenAI?
uh the very end of 2015 um we announced it

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and then the first day of work was like

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January of 2016.

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>> So all right so you start in uh in in

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2016 and and what are your like what's

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the big goal that you start
with and then how does that evolve?

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So we knew that there was this magic

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piece of technology. We knew that we

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could apply compute

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to a problem and to learn it. And we

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knew that the more compute we used, the
smarter and more capable the system got.

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We didn't really know anything else.
We didn't know how we were going to um

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what kind of system we were going
to build. This was way before the idea of

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language models. We were trying to train

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a robot hand to do a Rubik's cube. Um
we were trying to, you know, show that we

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could play video games. And we were
really developing the algorithms and

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trying to understand how this amazing

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property of the universe worked. And and

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then not until about 2018

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did we start making progress on

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unsupervised learning. And then the

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first GPT1 model and not until 2020 did

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we train GPT3 which was the first model

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that I think actually was over some
threshold of of usability. even that

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most people in the world looked at this
and said, you know, okay, the model can

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like generate a co coherent sentence.

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That was really the limit at the time.

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Kind of impressive, but like what
is this going to what is this going to

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mean? And why is why is this going to

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like matter to the economy or society or
anything else? Um, but we had discovered

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by this point these scaling laws which
said, well, if we could, you know, apply

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like a trillion dollars of compute to

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this idea, something quite amazing
would happen. And people said, "Well, you

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can't apply a trillion dollars to compute,
so it doesn't matter." And we

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sort of said, "Why not?" Like, let's try.

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So,

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you've got the idea and and it's moving

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forward, but when when does it come

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together that it's really bottling

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knowledge? Like, h how does it

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different people at OpenAI would give
you different answers to this, but I

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would say Mo the kind of consensus to

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the degree there is one
was the time of GPT4. This was like

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I believe this was like March of 2023

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but I may be wrong on the timeline there.
Um we had that model for maybe

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eight months before it launched. that we
had had time internally to really get to

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know it. And that was the time
where people even some of the people

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internally had been skeptics of this

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approach would looked at it and said

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this is going to go very far. Um and it

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hasn't been that long since that moment
you know three and a half years now. uh

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and

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and the fact that we now have a system

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uh and we're launching our new model
soon which is another step forward and

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there be many more step forwards coming
soon after that. Um but that it is so

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capable that it is discovering new

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knowledge doing science able to add huge

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economic value create entire comp pieces

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of complex software. Um this is

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this is like a very crazy moment. I

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think it hit us. Yeah. Over a period of

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time, but centered around this GPT4

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period.

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>> So you understand that

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you can sort of capture education,

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right? You capture knowledge. Um how how

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should the the G20
economies think about this?

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I I don't want to overstate things,
but I'm like very excited about our new

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model, so forgive me if I get a little

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bit too enthusiastic here. Um, I

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I think this, for example, will be
the greatest boom in entrepreneurship and

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the creation and development of small

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businesses um the world has ever seen.

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If you have a great idea, but you didn't

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have the resources or the ability to get

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enough capital together or hire enough
experts to work on it or to figure out

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what it's going to take to invent a new
piece of science or manage a complex

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supply chain, you can do that with AI

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now. Um, and I remember after chatbt

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launched, one of the stories that has
stuck with me the most from that moment

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was a guy that managed a laundromat.

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Apparently, laundromats are usually good
businesses. Wouldn't have been obvious

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to me. Apparently, they are. Um, but
this one was not going well. And he was

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using chatbt for everything. Um, to make

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his marketing materials, to, you know,

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manage give him advice on legal contracts,
to manage like relationships

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with vendors, this long list of stuff.

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He he was really the first person I met

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that had figured out how to use AI to

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effectively run a business. And this was
amazing to me at the time. Now, I know

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you all have heard stories about this a
bunch and it's no longer surprising, but

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in 2023, the fact that someone was using

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Chat GBT, broken and embarrassing though
it was at the time, to let them manage a

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business that otherwise they couldn't

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have done was was like quite remarkable.

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Um, in 2025, we saw a real acceleration

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of this with coding agents and and white
collar work agents. Um, I think we'll

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see a third thing soon where we'll have
these long-term persistent agents that

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can work like a real virtual
collaborator constantly helping. But,

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um,

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it it's it's it's amazing to me what is

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happening with the boom in

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entrepreneurship and business creation

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because of AI. If I were a country, um,

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you know, many of you are going to take
very different approaches to how you

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regulate AI, how you welcome it into
your country, how you use it. But for

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sure, I think it is non-negotiable that
you have to use it. The economic growth

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and benefit to people that can come from
this. Um, the value to a country is too

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high to ignore. uh there will be
different ways people try to do this but

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this is like you know the smartest

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people in the world uh decided to move

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to your country to learn your language

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um to work very hard on whatever problem
you'd like um to go discover new things

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that you need and you can put as much
of this to work as you want some of you

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will choose to build data centers some
of you will choose to rent data centers

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from other people because you don't want
them in your country I think all that's

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fine um but we want to help we want to

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support not just our company, our whole

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industry like we want to bring this

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incredible magic of,

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you know, intelligence in a bottle,
education in a bottle um to all of you.

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I think this is like this is an

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incredible moment for the world. What

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people can do with this and the economic

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boom that will come with it, the sort of

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individual increased quality of life.

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People talk about, you know, medical
care and what that means, education,

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what that means, services that only very

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rich people used to have access to,
now anybody can have with AI. Um, and the

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ability for people to just come up
with ideas and get them to fruition so

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quickly, uh, is going to be incredible.

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Do you do you think that um

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your company can create the context

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um that people can use to create uh

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their outcomes or do you think there'll

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be an industry sort of surrounding you

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that will contextualize it? Because
if you think about it, you say the the

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smartest people in the world move in to
my neighborhood and they're willing to

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work for me. But if I don't know what
to ask them to do, that's not really a fun

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dinner party having the smartest people
in the world sitting with you and they

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can't really have a conversation, right?

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So, how do we how do we think about
context that that's not going to come

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from us and I don't think that should.

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Um we are we will provide this this

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engine you know we will provide this

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incredible

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commodity of AI that can you can use for
whatever you want but the people of the

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world and I have complete trust in the
people of the world's creativity and

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ambition um will have to figure out what

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to ask it to do what ideas to to to

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throw this at what what problems and what
context in a particular society or

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company is important to understand what
to Um so that won't be our role. I don't

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think we'd be good at it even if it were.
Um but we will be able to enable

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everyone around the world to bring
that context and those questions and those

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ideas. So should

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should the governments of the world

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think of AI

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and companies like
your company differently

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than they thought about prior

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technology? Meaning the if if what

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you're bringing them is, you know,
the smartest people in the world, an

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educated

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capacity, then if they look at that as

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technology and they uh keep it out of

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their country or they constrain it, are

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they are they constraining their

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capacity to think and grow and build?

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I am always tempted to say this time
is different. This is really special. You

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know, this is and I suspect

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well to zoom out even further than that

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as a kid my understanding of

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the world was that there were these few
punctuated moments in history each of

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which was a very different thing.
You had um the agricultural revolution and

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then you had the industrial revolution
and then you had the computer revolution

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and these were all completely different
unrelated things and there were not that

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many lessons to learn from them and they
were best understood in isolation and

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even if you zoomed into one pick the

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industrial revolution um the right way

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to understand that was um 20 or 30

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important pieces of technology that were
all developed over a period of a couple

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hundred years that came together in this

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important way. uh

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as an adult I look at it as you know it

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has been a single revolution a single
exponential of technology. Each

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generation has built on the scaffolding
of the generations before put a new

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brick in place. People have been able
to see or layer of scaffolding to stick

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with the analogy. People have been able
to climb and see a little higher and do

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the new thing. Um, if you think about
what it took to get us to this point

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where we can build AI, um, it was all
of those previous revolutions uh, stacked

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together. And it was the collective
discovery of science throughout society

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and the global economy that we all

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contribute to that made this incredible

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thing possible and now happen.
And it is tempting whenever you're in the

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moment to say this is the last
revolution. This is the biggest

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revolution. There will be more after this.
There will be uh bigger things

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after this. people will use AI to invent
whatever thing that comes next. It's

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probably very difficult for us to

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imagine right now. Um and

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and I think the right answer is to look
at the history of technology as one

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continuous exponential. The history
of the economy and society as one

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continuous exponential. Um and I really
mean that. It's not just the technology.

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It's this social fabric
and the kind of complex structure

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of the world that allows this technology
to flourish and people to figure out

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what to do with it. And you have
to embrace it continuously all the way

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through. If you miss out on any part
of it, um you're not ready for the next

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thing that will come. If you if you

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don't enable your people and your
businesses with AI, uh they will not

243
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invent the next level of the scaffolding.
But there will be more

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things and I think it is tempting to say
this one is different and it clearly is

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really important. Um but I
would view it as a continuum.

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So

247
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we all read about the the various

248
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companies at the frontier. Can you can

249
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you sort of differentiate them for us?

250
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What what do you what do you view Open

251
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AI as best at? What what's the you know

252
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your DNA if you will that separates you

253
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from the others and what are you great at?
And just give us that sort of from

254
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your perspective. Um

255
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I think from a from what matters to this

256
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room um we are the pragmatic centrists.

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We we realize like we want to be we
want to be accurate in how we talk

258
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about what we see in the future.
We don't want to fall into the trap of

259
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blind optimism. We don't want to fall
into the trap of dumerism. This is

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clearly complex. There's clearly
a combination of both excitement and

261
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anxiety of transformation and risks that

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the world has to navigate. Um but

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by getting pulled into either extreme we

264
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are not going to successfully figure out

265
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the challenges in front of us. Um we

266
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want to be a reliable partner. Uh we
want like we really do view what we are

267
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doing as a platform as a service to the
world. We realize that different people

268
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around the world are going to use it
very differently and we want to put

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sufficient constraints on our system
to avoid catastrophic risks. But we really

270
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do want to respect all of your
sovereignity and that you're going to

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use it in very different ways. And we
personally may not always like it. Um,

272
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but I don't like everything that people
do with electricity either. And I still

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think everybody should get to have it.

274
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Um, so

275
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oh and then also I would say like
we want the whole global economy to

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succeed. We do not want to be the only
company. Um, we do not want to suck up

277
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all the value. We do not think that
is good for global stability. nor do we

278
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think that's possible for the way that
people need to flourish and people need

279
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to stay at the center of this. Oh, I'll
get to that one more thing after this.

280
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Um, and we want to like enable every

281
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entrepreneur, every government, every
big company in the world to thrive with

282
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this technology. Uh, the last thing I'll
say that I think differentiates us from

283
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some of the other companies is we are
very firmly and very proudly on team

284
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humanity. Um, we would like to build

285
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tools for people. We would like people's

286
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lives to be better. Um we think that

287
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people need to be at the center of the

288
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economy and society and global

289
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decision-m um and that people should run

290
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the future in AI.

291
00:16:46,640 --> 00:16:51,517
>> So it it seems that entrepreneurship

292
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should be really the fire starter of all

293
00:16:54,000 --> 00:16:56,797
this, right? You're are you the you know

294
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the the kindling of it? I mean maybe

295
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sort of tell me how entrepreneurship and

296
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and uh open AI sort of work together.

297
00:17:07,040 --> 00:17:09,197
Before OpenAI, I used to run a startup

298
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accelerator and I had always been
interested, not always, after I came to

299
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college, I'd always been interested
in entrepreneurship. And then having had

300
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this incredible front row seat, I really

301
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became convinced that entrepreneurship

302
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was maybe the most important

303
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novel force in all of capitalism. Um,

304
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and I fell in love with it. and

305
00:17:35,120 --> 00:17:37,757
watching what new companies were able to

306
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do and watching how

307
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large of a percentage of the new ideas
that mattered in the tech industry over

308
00:17:46,320 --> 00:17:49,837
the last you know 20 years or whatever
came from startups and not big

309
00:17:49,920 --> 00:17:52,877
companies. Um now having seen us in

310
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other industries I am a huge believer in

311
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entrepreneurship. I also think that,

312
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you know, like I talked to a lot
of people around the world and they would

313
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much rather run a great lifestyle
business than go work as like a

314
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corporate cog and I think that's great
too. Like I think that's just we should

315
00:18:09,600 --> 00:18:14,557
enable that. Um, one of the things I got
excited about early with AI, of course

316
00:18:14,640 --> 00:18:16,477
AI is going to transform big companies

317
00:18:16,560 --> 00:18:17,997
and of course AI is going to transform

318
00:18:18,080 --> 00:18:21,997
governments, but what AI can do

319
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for entrepreneurs and for people that

320
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want to take an idea and bring it into

321
00:18:27,600 --> 00:18:32,237
the world quickly um is really quite
amazing. When I was running the startup

322
00:18:32,320 --> 00:18:35,597
accelerator, it lasted for three
months and the work that

323
00:18:35,680 --> 00:18:39,517
>> it lasted for three months. You were in
it for three months and the work that we

324
00:18:39,600 --> 00:18:41,437
expected a startup to accomplish in

325
00:18:41,520 --> 00:18:43,917
three months is now probably doable in

326
00:18:44,000 --> 00:18:47,837
like 17 minutes with codeex. This is

327
00:18:47,920 --> 00:18:51,837
just amazing. The world is not caught
up with what this is going to mean. Not

328
00:18:51,920 --> 00:18:56,477
just for the economic value that gets
created from that, but how quickly

329
00:18:56,560 --> 00:18:59,917
people can test ideas, build things, get
feedback from real customers. We're all

330
00:19:00,000 --> 00:19:02,877
just going to get much better stuff.

331
00:19:02,960 --> 00:19:06,477
So, you use the term uh I want to sort

332
00:19:06,560 --> 00:19:10,637
of flush it out a bit
a bit non-negotiable.

333
00:19:10,720 --> 00:19:13,357
Can you maybe uh help everybody

334
00:19:13,440 --> 00:19:18,317
understand what you mean about that and
and what that means for each of uh our

335
00:19:18,400 --> 00:19:23,400
partner ministers who
are here today with them?

336
00:19:24,720 --> 00:19:26,797
>> Again, I'm biased.
I'm trying to talk my

337
00:19:26,880 --> 00:19:29,437
book here. Forgive me for this analogy.

338
00:19:29,520 --> 00:19:32,877
Um, I think it would be approximately as

339
00:19:32,960 --> 00:19:37,437
bad of an idea to say we're not gonna
have AI in our country as it was to say

340
00:19:37,520 --> 00:19:40,637
we're not going to have electricity
in our country, you know, back 100 plus

341
00:19:40,720 --> 00:19:44,797
years ago. I think this is something
at that level. Um, this is something that

342
00:19:44,880 --> 00:19:47,437
every person and every business and

343
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really the entire

344
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machine of society is going to need to

345
00:19:53,200 --> 00:19:56,317
deliver the quality of life that your

346
00:19:56,400 --> 00:20:00,957
citizens should demand. Now,
electricity also came with some

347
00:20:01,040 --> 00:20:04,317
complexities, and it took a little
while for us to figure out how to make it

348
00:20:04,400 --> 00:20:08,157
safe, but we made fairly rapid progress
as a society to make it generally pretty

349
00:20:08,240 --> 00:20:12,877
safe, even though it can do a lot of bad
things. Um, and at this point, we barely

350
00:20:12,960 --> 00:20:16,157
think about electricity. You know,
we turn these lights on, we expect them to

351
00:20:16,240 --> 00:20:19,917
work. You know, if this the power shut
off and I had to scream because this

352
00:20:20,000 --> 00:20:24,077
microphone was not working,
like I would be annoyed about that. You

353
00:20:24,160 --> 00:20:26,477
I won't go through all the examples.
I see all the phones on the table. Like

354
00:20:26,560 --> 00:20:30,237
you just it would be hard for society
to function well without electricity at

355
00:20:30,320 --> 00:20:33,677
this point. But we don't think about
it much. We think about you know there's

356
00:20:33,760 --> 00:20:37,277
light at night. That's great.
We can hear these people speak in the room

357
00:20:37,360 --> 00:20:39,517
without them having to yell. That's nice.
Our phones can do these amazing

358
00:20:39,600 --> 00:20:41,117
things for us. We care about our phones.

359
00:20:41,200 --> 00:20:44,077
We don't think too much about the
electricity that gets generated to power

360
00:20:44,160 --> 00:20:46,637
them. Um and I think the same thing is

361
00:20:46,720 --> 00:20:49,517
going to happen with AI. We won't, my

362
00:20:49,600 --> 00:20:51,277
prediction is we won't be talking about

363
00:20:51,360 --> 00:20:54,557
AI as much as we do in a decade from now

364
00:20:54,640 --> 00:20:56,877
because we'll just expect it everywhere.

365
00:20:56,960 --> 00:20:59,517
You know, like a kid growing up today

366
00:20:59,600 --> 00:21:03,277
will never be smarter than AI, but he or

367
00:21:03,360 --> 00:21:05,597
she will also never

368
00:21:05,680 --> 00:21:10,477
have understood a world where every
product and service that they interact

369
00:21:10,560 --> 00:21:14,957
with is not really smart and really
capable and really helpful. And because

370
00:21:15,040 --> 00:21:17,597
we'll just be so used to that, we won't
think about the AI. will just be like,

371
00:21:17,680 --> 00:21:19,597
"Yeah, I want my products to be good."

372
00:21:19,680 --> 00:21:22,797
You know, if I have an idea, I want
to be able to like make it right away. I

373
00:21:22,880 --> 00:21:26,397
want this software to be created
instantly for me. Um, if I have a

374
00:21:26,480 --> 00:21:28,157
disease, like I expect a cure to get

375
00:21:28,240 --> 00:21:33,597
discovered very quickly. Uh, so I think
countries need to need to embrace this.

376
00:21:33,680 --> 00:21:34,797
Again, there's many ways to do it.

377
00:21:34,880 --> 00:21:38,397
People will set different rules. People
will decide on what they want to build

378
00:21:38,480 --> 00:21:40,717
versus rent, but I think everyone will

379
00:21:40,800 --> 00:21:43,917
need the this new commodity.

380
00:21:44,000 --> 00:21:48,557
If um if we look forward five years and

381
00:21:48,640 --> 00:21:53,357
and we come back to North
Carolina alto together um

382
00:21:53,440 --> 00:21:59,160
what what will be holding us
back do you think in your opinion?

383
00:22:00,480 --> 00:22:03,837
Well, there are clearly challenges that

384
00:22:03,920 --> 00:22:06,157
we have to get right along the way.

385
00:22:06,240 --> 00:22:10,637
There will be specifics. For example,
I'm sure cyber security is a top-of-

386
00:22:10,720 --> 00:22:13,757
mind issue for many of you. Uh we work
with many of the governments in the

387
00:22:13,840 --> 00:22:16,157
room. Uh we work with the state of North

388
00:22:16,240 --> 00:22:18,477
Carolina. Uh we work with companies big

389
00:22:18,560 --> 00:22:22,957
and small and we are

390
00:22:23,040 --> 00:22:27,277
I think we have a big challenge in front
of us like to not to not try to sidestep

391
00:22:27,360 --> 00:22:31,197
this one. I think some things are going
to go very wrong with cyber security

392
00:22:31,280 --> 00:22:35,437
unless people act quite urgently.
There will be other challenges in the next

393
00:22:35,520 --> 00:22:38,637
five years. People talk about uh
biocurity and the the things we're going

394
00:22:38,720 --> 00:22:42,237
to face there. um

395
00:22:42,320 --> 00:22:44,157
there will be bigger ones yet to come

396
00:22:44,240 --> 00:22:46,077
and I think if we don't successfully

397
00:22:46,160 --> 00:22:49,277
navigate those um

398
00:22:49,360 --> 00:22:51,357
society will not be able to adopt AI to

399
00:22:51,440 --> 00:22:54,717
the degree or to the speed with which

400
00:22:54,800 --> 00:22:57,997
people deserve. So getting

401
00:22:58,080 --> 00:23:02,157
successfully navigating the risks
and downsides in front of us is something

402
00:23:02,240 --> 00:23:05,837
that could go very wrong and I think
will set this technology back could set

403
00:23:05,920 --> 00:23:09,037
this technology back a great deal. Um,

404
00:23:09,120 --> 00:23:10,477
another thing that could go wrong is too

405
00:23:10,560 --> 00:23:15,357
much concentration of power. Um,

406
00:23:15,440 --> 00:23:20,637
AI should be in many ways AI should be
an equalizing force in the world. You

407
00:23:20,720 --> 00:23:23,757
talked about what it means to have
like a reset on the educational capacity

408
00:23:23,840 --> 00:23:27,197
available to everybody. Um, you can also

409
00:23:27,280 --> 00:23:31,757
see worlds where AI concentrates because

410
00:23:31,840 --> 00:23:35,277
some people make early investments and
others don't and there's, you know, bad

411
00:23:35,360 --> 00:23:39,837
inequities with comput. uh that'd be bad.
So I think if we fail to make AI

412
00:23:39,920 --> 00:23:42,237
abundant, it ends up being something

413
00:23:42,320 --> 00:23:47,117
that is very hotly competed over, rich
people spend a huge amount of money on

414
00:23:47,200 --> 00:23:50,957
and um

415
00:23:51,040 --> 00:23:55,197
that would be a bad outcome. So I think
we need to make it abundant so that we

416
00:23:55,280 --> 00:23:59,197
get the the benefits of lifting
everybody up and not much worse than

417
00:23:59,280 --> 00:24:02,397
inequality. >> Right.
A as you said, if if the smartest

418
00:24:02,480 --> 00:24:04,717
people in the world learned your

419
00:24:04,800 --> 00:24:07,037
language and all agreed to move to your

420
00:24:07,120 --> 00:24:09,677
country and work on whatever you wanted

421
00:24:09,760 --> 00:24:12,477
them to work on, that that has to be the

422
00:24:12,560 --> 00:24:17,597
most incredible thing. Do you think that

423
00:24:17,680 --> 00:24:21,277
since you'll have all the smartest
people speaking all those languages,

424
00:24:21,360 --> 00:24:23,037
can't they figure out a way do you think

425
00:24:23,120 --> 00:24:25,917
over time to deliver the same amount of

426
00:24:26,000 --> 00:24:29,517
compute more inexpensively without the

427
00:24:29,600 --> 00:24:34,637
same use of power without the same I
mean aren't these the kind of things

428
00:24:34,720 --> 00:24:39,277
>> that are going to happen that will
democratize it by sort of by itself in a

429
00:24:39,360 --> 00:24:42,957
way >> it it will still
require huge investment

430
00:24:43,040 --> 00:24:47,357
but yes we will continue to make things
vastly more efficient and we'll figure

431
00:24:47,440 --> 00:24:50,877
out how to make more and better chips
and we'll figure out how to make smarter

432
00:24:50,960 --> 00:24:55,037
algorithms. All of that will happen. But
to put some numbers on the magnitude of

433
00:24:55,120 --> 00:24:57,117
how much we we need this to happen.

434
00:24:57,200 --> 00:24:59,677
Again, I know these numbers in front
of me. I'm not going to get this exactly

435
00:24:59,760 --> 00:25:03,357
right. Um but forgive
me for the approximation.

436
00:25:03,440 --> 00:25:08,157
At the beginning of 2020, um the token
leader in the world was an OpenAI

437
00:25:08,240 --> 00:25:10,237
employee using roughly a 100,000 tokens

438
00:25:10,320 --> 00:25:12,477
a month.

439
00:25:12,560 --> 00:25:15,757
Um, in the middle of 2026,

440
00:25:15,840 --> 00:25:20,157
the token leader that I know of, there
may be somebody using more than this at

441
00:25:20,240 --> 00:25:22,637
outside of OpenAI, um, was using

442
00:25:22,720 --> 00:25:25,517
hundreds of billions of tokens a month.

443
00:25:25,600 --> 00:25:30,397
So, you know, a multi-millionx increase
in six and a half years. And the average

444
00:25:30,480 --> 00:25:34,237
person on Earth had gone from using
effectively zero tokens to 100,000

445
00:25:34,320 --> 00:25:37,597
tokens a month.
That was the global per capita thing.

446
00:25:37,680 --> 00:25:40,797
If we just naively project this forward
again, which seems like a reasonable

447
00:25:40,880 --> 00:25:46,317
thing to do to me. Um, and I hate tokens
as a unit here. It's a dumb one. No one

448
00:25:46,400 --> 00:25:49,677
should care, but like let's just
take that as shorthand for amount of

449
00:25:49,760 --> 00:25:52,877
intelligence. Then

450
00:25:52,960 --> 00:25:57,037
in another six and a half years, the
average per capita use of tokens will go

451
00:25:57,120 --> 00:26:01,757
up to, let's round it down to 100
billion tokens a month. And the person

452
00:26:01,840 --> 00:26:03,437
using the most in the world will be

453
00:26:03,520 --> 00:26:06,157
using

454
00:26:06,240 --> 00:26:08,957
you know 100 quadrillion tokens a month

455
00:26:09,040 --> 00:26:12,877
uh or one quadrillion 100 trillion like

456
00:26:12,960 --> 00:26:14,397
>> no I was right 100 trillion tokens a

457
00:26:14,480 --> 00:26:17,997
month 100 quadrillion tokens a month um

458
00:26:18,080 --> 00:26:23,277
even with great gains on efficiency
we are going to need to build much more

459
00:26:23,360 --> 00:26:27,597
infrastructure unless we
want this to be a highly

460
00:26:27,680 --> 00:26:30,717
priced commodity which we don't we want
this to be abundant We want this to be

461
00:26:30,800 --> 00:26:31,917
inexpensive. We want people to just be

462
00:26:32,000 --> 00:26:34,317
able to use this for whatever they need.

463
00:26:34,400 --> 00:26:37,757
>> So that's the driving force.
If we if we

464
00:26:37,840 --> 00:26:42,397
globally can build enough then it will

465
00:26:42,480 --> 00:26:45,757
intelligence will be broadly distributed

466
00:26:45,840 --> 00:26:48,797
uh more democratized across the world.

467
00:26:48,880 --> 00:26:52,557
Uh the world will be educated or they'll

468
00:26:52,640 --> 00:26:56,477
have the access to education.
Is that sort of the

469
00:26:56,560 --> 00:26:58,557
>> to to go back to the analogy of

470
00:26:58,640 --> 00:27:01,357
electricity? Um, there's this amazing

471
00:27:01,440 --> 00:27:04,877
chart of what it cost to have an hour of

472
00:27:04,960 --> 00:27:09,917
light at night.
And there was a time, one of the

473
00:27:10,000 --> 00:27:11,837
earliest data points you can find is

474
00:27:11,920 --> 00:27:14,797
that it it took an average of 5 hours of

475
00:27:14,880 --> 00:27:16,957
labor at the wage at the time to be able

476
00:27:17,040 --> 00:27:20,477
to pay for one hour of light at night.

477
00:27:20,560 --> 00:27:24,557
Electricity came along. It fell.
We figured out how to make more

478
00:27:24,640 --> 00:27:27,677
electricity. So, there was like,
you know, the supply and demand change

479
00:27:27,760 --> 00:27:32,637
curve. It fell again. We figured out
how to make vastly more efficient light

480
00:27:32,720 --> 00:27:36,557
bulbs. We went from incandescent lights
to LEDs. A whole bunch of other things

481
00:27:36,640 --> 00:27:39,437
happened. And now an hour of light at

482
00:27:39,520 --> 00:27:43,597
night is not something that people think
of at all about the cost. I don't even

483
00:27:43,680 --> 00:27:46,397
know what the number is, but someone
in here can do it. It's it's like very

484
00:27:46,480 --> 00:27:48,397
cheap to run, you know, a five watt bulb

485
00:27:48,480 --> 00:27:52,797
for an hour. Um the

486
00:27:52,880 --> 00:27:56,317
if that hadn't happened if we and all of
those things together had to happen lots

487
00:27:56,400 --> 00:27:59,197
of electricity generation huge
innovation on the efficiency all of

488
00:27:59,280 --> 00:28:04,237
these things if that hadn't happened
then rich people get light at night and

489
00:28:04,320 --> 00:28:06,797
they can study more they have
a compounding effect they can learn more

490
00:28:06,880 --> 00:28:09,517
whatever and and you know poor people

491
00:28:09,600 --> 00:28:13,917
don't so I think it's been very good
that energy has become abundant and that

492
00:28:14,000 --> 00:28:16,157
light at night has become relatively

493
00:28:16,240 --> 00:28:19,757
like shockingly inexpensive Um, if that

494
00:28:19,840 --> 00:28:22,317
same thing happens with AI and anybody

495
00:28:22,400 --> 00:28:24,237
on earth, rich, poor, whatever, can use

496
00:28:24,320 --> 00:28:29,517
AI to get the abundant services that they
need and to express their ideas and

497
00:28:29,600 --> 00:28:33,677
to start their businesses and whatever
else. And we fulfill our mission of

498
00:28:33,760 --> 00:28:38,477
making AI so inexpensive and so smart
that people are just like they think

499
00:28:38,560 --> 00:28:41,917
about it like they think of the cost
of an hour at night of light at night. I

500
00:28:42,000 --> 00:28:45,437
think that'd be really wonderful. And then
this huge reset and democratization

501
00:28:45,520 --> 00:28:47,917
of education you're
talking about can happen.

502
00:28:48,000 --> 00:28:52,317
So are you you know there are look there

503
00:28:52,400 --> 00:28:54,877
are doomers out there who worry about

504
00:28:54,960 --> 00:28:57,597
everything but we know that if you look

505
00:28:57,680 --> 00:28:59,437
back through the industrial re as you

506
00:28:59,520 --> 00:29:01,917
said it it always seems to work out

507
00:29:02,000 --> 00:29:04,797
fine. Are you uh fundamentally

508
00:29:04,880 --> 00:29:07,517
optimistic to what your products will do

509
00:29:07,600 --> 00:29:11,117
to the world and will serve the world?

510
00:29:11,200 --> 00:29:12,877
I I think part of the reason it tends to

511
00:29:12,960 --> 00:29:16,797
work out fine is people worry and they

512
00:29:16,880 --> 00:29:19,917
stress and they look at the downsides
and they try to address those and they

513
00:29:20,000 --> 00:29:22,797
try to learn how we avoid accidents. So

514
00:29:22,880 --> 00:29:25,437
if we go back to an early example even

515
00:29:25,520 --> 00:29:27,917
before electricity of a technology fire

516
00:29:28,000 --> 00:29:32,797
was incredible incredible for human
evolution incredible for letting us cook

517
00:29:32,880 --> 00:29:36,077
our food and heat our homes at night and
whatever else. It also burnt down whole

518
00:29:36,160 --> 00:29:40,637
cities a few times and people really
worried about that because we don't want

519
00:29:40,720 --> 00:29:43,037
cities to burn down and we figured out

520
00:29:43,120 --> 00:29:47,597
fire safety and through a lot of human

521
00:29:47,680 --> 00:29:49,597
ingenuity um through a lot of good

522
00:29:49,680 --> 00:29:51,917
policy definitely through learning from

523
00:29:52,000 --> 00:29:56,637
some very bad accidents we figured out
how to make it safer. Now had we just

524
00:29:56,720 --> 00:30:00,077
said like yeah you know some cities are
going to burn down whatever we got other

525
00:30:00,160 --> 00:30:02,957
problems to work on probably wouldn't
have figured that out and that wouldn't

526
00:30:03,040 --> 00:30:06,957
have been as good. Um, so I think worry

527
00:30:07,040 --> 00:30:10,397
is warranted. Worry is how we anticipate

528
00:30:10,480 --> 00:30:13,437
problems and how we from a matter of

529
00:30:13,520 --> 00:30:17,437
policy and a matter of technology figure
out to address them. But I am optimistic

530
00:30:17,520 --> 00:30:20,317
that we can mitigate the downsides
of this technology. And if you look at

531
00:30:20,400 --> 00:30:24,877
what's happened, you know, if you look
at what the doomers were saying 5 years

532
00:30:24,960 --> 00:30:29,517
ago about the chances of us being able
to make AI of this level, of this sort

533
00:30:29,600 --> 00:30:33,917
of near human, sometimes superhuman
capacity level, you know, broadly

534
00:30:34,000 --> 00:30:37,597
considered safe and reliable.
Not perfect. There have been accidents.

535
00:30:37,680 --> 00:30:40,877
There will be accidents, of course.
I don't think most people would have

536
00:30:40,960 --> 00:30:42,717
thought it was going to go this well as

537
00:30:42,800 --> 00:30:46,477
it has so far. And I I believe in human

538
00:30:46,560 --> 00:30:51,117
ingenuity and the ability for to
solve very difficult, very complex

539
00:30:51,200 --> 00:30:54,237
problems. And I think I
think we'll keep doing that.

540
00:30:54,320 --> 00:30:57,437
And I think the economic value and the

541
00:30:57,520 --> 00:31:02,557
personal value is so huge. Um I met with
someone just this morning and told and

542
00:31:02,640 --> 00:31:05,757
again I'm sure you've all heard stories
like this that they wouldn't be alive

543
00:31:05,840 --> 00:31:08,717
without CHPT. Um and that they had a

544
00:31:08,800 --> 00:31:12,877
very difficult disease and you know got
a diagnosis that doctors weren't able to

545
00:31:12,960 --> 00:31:14,557
>> give them. We shouldn't take that away.

546
00:31:14,640 --> 00:31:17,757
>> No. But we need to figure out how
to make the technology safe so that people

547
00:31:17,840 --> 00:31:22,157
can have more of that. >> Great.
Sam, thank you for joining us. It

548
00:31:22,240 --> 00:31:24,717
was really an incredible conversation.

549
00:31:24,800 --> 00:31:29,277
Um 2:00, so 2 p.m. in the ministerial

550
00:31:29,360 --> 00:31:32,797
room where we will have uh Alex Karp

551
00:31:32,880 --> 00:31:36,317
will be our next guest uh speaking to us.

552
00:31:36,400 --> 00:31:39,517
>> He's a good one.
>> He's a good one. But uh

553
00:31:39,600 --> 00:31:42,717
>> thank you Sam for joining us.
We we really appreciate it. Thank you.

554
00:31:42,800 --> 00:31:49,400
[applause] Thanks. [applause]