WEBVTT

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Open AAI founder and CEO Sam Alman

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sounded very enthusiastic during the

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Cisco AI summit about the launch [music]

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of Codex, the software development agent

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that helps developers write, understand,

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debug, and refactor code by

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understanding natural language prompts.

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Altman feels like the launch of Codex

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marks another CH GBT moment that can

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lead to full AI companies.
In these highlights, he explains why

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>> this is going to change how all
of OpenAI works and change how other

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companies work. Um, it yeah, the model's

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really hit some threshold and I think
now the interface and harness has caught

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up and

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I think this is the first this you're
talking about chatbt moments. I think

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this is like the first time
I felt another chat GPT moment

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>> for here is a a clear
clear glimpse of the

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future of knowledge work and how
enterprises and individual people are

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going to use AI to work in a completely

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different way. The idea that a coding

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model can create a full complex piece of
software but also interact with the rest

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of the real world to build a company
around it is a very big deal. And then

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this this notion of what's happening
right now, I'm sure you're tracking this

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with Moldbook and um what happened with
Claudebot. Is it just a passing fad or

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do you think that there's something
that we should take away from that on um

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>> No, I think it is definitely not a

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passing well mold book maybe. I don't

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know. But uh Open Claw is not. Um,

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I

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I think this idea that code is really

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powerful, but code plus generalized

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computer use is even much more powerful

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is here to stay. The fact I

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when I initially installed Codex, I
said I was never going to give Codex full

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control of my computer with without
checking what it was doing. And that

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lasted about like two hours because
it was so useful. And then I and then I

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kind of got persuaded by people that I
really shouldn't have it running like

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that. So now I have two laptops until
I figure out how this is all going to

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work. But giving an AI agent full use of

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your computer and your web browser with

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all your sessions leads to incredible

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stuff. And that seems here to stay. the

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the the

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idea that we can take

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a codeex style workflow and expand it to

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all knowledge work. Um so that whatever

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you're doing codecs can be or what some

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version of that can be using your

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computer and using the web for you and

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editing documents and

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whatever other kind of work you need. um

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feels like a genuine transformation in

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how knowledge work will happen and that

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I think OpenClaw did an incredible job

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of

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bringing many ideas together to make

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that feel usable and real and that seems

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certain to be part of our future.

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I think moldbook is cool. Uh, and I

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think it points to something that will

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be real and maybe it will be mold book.

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Uh, but there will be new kinds of

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social interaction where you have many

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agents in a space interacting with each

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other on behalf of people. Uh, leading
to all sorts of new things. It's like

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you you can imagine a totally new kind
of social network where everybody makes

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an agent or many agents and puts them
in there and the agents are talking and

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doing stuff and finding them people and
information and collaborating with other

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people's agents to come up with new
ideas that I'm sure there will be an

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interesting I think the future of social
may look something like that very

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different than today whether it's
a mult book or not uncertain I think the

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obvious constraints are the biggest ones

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uh still energy

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manufacturing enough hardware, all that

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kind of stuff. The non-obvious ones that

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are most top of mind for me, one, how

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are we going to balance the sort of

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security and data access versus the

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utility of all of these models?

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>> Um, I don't think anyone has a great

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answer to this yet. I it feels to me

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like there is a new kind of security or

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data access paradigm that needs to be
invented for this. Um, another is how

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are we going to rewrite all software
to be equally usable by humans and AIs?

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There's like a bunch of weird quirks
right now about trying to do that with

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the way software work. >> And does
that change the architecture of

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the software itself where you're going
to optimize it for agents more so than

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humans? And so it fundamentally
changes how you build software.

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>> Yes. And there's like big examples of

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that and then there's like dumb examples

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of that. So, for example, uh I

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I would love my agent to be able to use

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Slack on my behalf because I hate
drowning in Slack and I think it's like

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this chaotic mess for me and but it's

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important. Uh but the way it works right

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now is my agent can use the Slack web

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interface and go read all my threads and

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do something for me. But then it has
marked a bunch of stuff as red in the

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process of doing that and
it's broken my workflows.

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>> Yeah. >> So I don't
like that's just a silly

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example of how software is not like
a lot of software is not quite meant for

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an AI and a person to be using it

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together. Um maybe we'll want AIs to

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like have different sort of user
accounts in some ways using

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the same kinds of things. maybe a lot of

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software will get rewritten so that it's

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primarily or largely used by AI but also
still works for people using it the

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oldfashioned way. Um, another kind of

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non-obvious block is how like one of
the most powerful things about AI is you

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could do this sort of always
on computing where you could have

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an AI um listening to your meeting
or watching your meeting and you know

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watching what you're
doing on your computer and

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uh then just like add a lot of value and
do stuff for you. We don't even our like

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existing computer hardware is not really
meant for that. our permissioning system

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and how we think about what an AI gets
to see and do stuff with and what it

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gets to keep is not really meant for that.
Um, our legal system doesn't

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really support that. Well, you'd like
to be able to, you know, record a meeting

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and learn something from it and delete
the recording. Uh, so I think there's a

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lot of just usability things like that.

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The the capability overhang feels to me

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like the biggest it has ever felt.
I used to say like a few months ago maybe

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I would have said it feels bigger than
any time except right when CHBT right

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before CHBT launched. It now feels even
bigger than that. Even though people are

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using AI for a lot of stuff. Um the fact

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that AI can make small
but increasingly big scientific

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discoveries. The fact that AI can write
full pieces of software. The fact that

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soon AI can do more generalized

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knowledge work. Um those are all huge

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huge things like we have always said

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that you know we're going to automate

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research use that to be able to automate
the economy use that to be able to

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deliver incredible new value to people

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and share all these benefits and this

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whole new technological world. Uh
and we always said that as a sort of like

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abstract sometime in the future thing.

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And yet now AI is doing research and AI

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is able to do huge amounts
of economic work. And

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this, as you said, has happened many
times in the past, but living through it

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definitely feels like, huh, this is not
quite how it seems like it should go.

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The the diffusion,
the absorption is so slow.

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>> Yeah. >> Um, >> is it slower
than you thought it would be?

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>> Yes. But I think I was just naive and

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didn't think about it that hard. And in

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retrospect and looking at the history,

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it shouldn't be surprising. It feels

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fast in some ways uh relative to other

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things like you know CHBT grew crazily

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quickly uh relative to any other piece

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of software before. Um

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Codex is growing extremely quickly. I

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expect the general purpose computer use

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knowledge work to grow quickly and yet

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looking at what's capable looking at

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what's possible it does feel sort of

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surprisingly slow uh in terms of advice

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figuring out how to set up enterprises

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such that they can quickly absorb these

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new tools and not have a year or

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multiple years of how are we going to

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think about the sort of data
access and security questions that

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are currently blocking people even at

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the level today of adopting things like

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codecs that feels very important and I
don't want to make a too dramatic of a

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prediction but I think the companies

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that are not set up to be able to adopt

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let's call them AI co-workers
very quickly um will be at a huge

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disadvantage and it is going to take a lot
of work and some risk to be able to adopt

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The Codex app is the first time to me
it has truly felt like interacting with a

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teammate. >> Yeah. >> Um it
and I I think like one of the

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lessons there is even if you have
amazing technology which the models got

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I think 52 was the model that got super

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good but even once you get there's still

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so much value in how you package it, how

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you how you have users interact with it,

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how easy you can make it. But this it

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really does to me now feel in a way
that talking to chatbt has always clearly

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felt like a tool that I am like
working with a collaborator now.

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>> Right. Right. >> And

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that seems very much like
the shape of things to come.

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All the evidence we see right now is

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that AI models will continue to get much

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more capable and also that they will get

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much less expensive and use many fewer

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resources per task.
And all of the history we've seen of

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every time that happens is people want

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to use them much much more. So we are

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planning for a world where

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AI usage grows at an accelerated pace

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each year. Do you think people are
underestimating the capacity that's

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going to be needed even now after
everything that's being built out?

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>> Right now they're saying like $5
trillion will be spent on this over the

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course of >> Yeah, maybe
if that really gets spent

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quickly uh that will be enough. And I

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and I think it's also possible that

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along the way we have some supply gluts

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temporarily. Um but over a period of

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decades it seems certain to me that the

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world is going to need a lot more tokens
even though the and we'll make you know

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each token way more efficient. You'll
all have a device in your pocket running

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super powerful models off of a battery
and what but you know there will still

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be this drive for more and more and

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more. Um

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I think the world has come to realize

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this and capitalism is doing its thing

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and supply chains are reconfiguring. Uh

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policy is changing and we are going to

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build an incredible amount of

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infrastructure. Now is it enough? Uh

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people always talk about the total

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market demand for AI. It feels to me

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something like the market demand
for electricity or energy. You can't you

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can't talk about that as a general thing.
You can say how much demand there

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will be at different price levels.
Um and in this case you can say at

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different price levels for different

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quality like how smart it is or how fast

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it is or thing like
things like that. Um but

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if we continue to make AI really capable
and really cheap, there will be a ton of

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demand at some price. If it's more
expensive, there will be uh you know

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less demand. But I would
like the world to just get

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to use a ton of it. Uh we're in this
capability over now as we mentioned

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where people are like oh you know can
use it for chat or maybe some people

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understand you can use it for code.
I think this will just be like how we do

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stuff, how companies run, how scientific

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discovery happens, how we use most

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software personally in our lives and

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making a lot of it if we can have it
at a reasonable price seems like a very

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good bet.

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>> Do you worry about um

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the fact that the US has not had as much

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of a lead on the open source side? Talk

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to us a little bit about that. like

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>> I do worry about that. Um

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>> yeah, I think we should
>> we should do more.

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>> Yes. >> Uh so what's what's
stopping you from doing it?

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>> Focus and time, but I think
we need to solve that somehow. To

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>> to be clear,
I think it's most important

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that we lead on frontier models and I

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expect those to be accessed via APIs and

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other products. So I it would be okay

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but not great if we didn't also have the

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open source lead. Um people want their own
models. People want control of their

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own models. Uh people want
to run models locally. Especially

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>> if you think about a world where you
have a model that is going to see your

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whole life. You're going to have
a new kind of device that's

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sort of always on and kind of keeping
track of everything and adds huge value

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to you. I at least would really like

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that running on inference eye control.

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Um and and so I think people are going

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to need this. Uh you know again if we
get behind obviously it's not the end of

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the world but I would really like us
to lead there and I think there will be

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increasing demand for locally running

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private models.

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We have kind of

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two large products and now we have some

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others that are coming up. We have

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chatbt and our API business. Um and

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now we have codeex which looks like it's

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going to get very big uh and a few other

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things. The and in the future we'll have

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consumer devices and robots and all

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sorts of other parts of this too. Uh

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people do seem very willing to pay
for AI as a subscription service. Uh not

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everybody but a lot of people are more
than we thought would. Um, businesses of

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course are willing to pay
for things like Chachet Enterprise,

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>> but even consumers,
you've reconditioned

00:14:31.520 --> 00:14:34.397
the consumers quite a bit. Like >>
consumers, I mean, we have I don't know

00:14:34.480 --> 00:14:37.597
the exact number off the top of my head,
but you know, many many tens of millions

00:14:37.680 --> 00:14:39.597
of consumers paying a subscription fee.

00:14:39.680 --> 00:14:42.717
>> Yeah. >> Uh, and

00:14:42.800 --> 00:14:45.837
that was a surprise to me to be honest,

00:14:45.920 --> 00:14:49.357
a happy one. Um, so that I think can go

00:14:49.440 --> 00:14:50.957
further and as we add things like

00:14:51.040 --> 00:14:52.957
codecs, people are willing to pay much

00:14:53.040 --> 00:14:56.717
much more there. um advertising

00:14:56.800 --> 00:15:01.517
for mass scale consumer businesses does
seem like a good model. Uh although I

00:15:01.600 --> 00:15:03.277
think we'll have to be very careful in

00:15:03.360 --> 00:15:07.277
how we do that. Uh and then

00:15:07.360 --> 00:15:11.197
businesses increasingly want

00:15:11.280 --> 00:15:14.557
something like an AI cloud subscription
>> where they're like I want to partner

00:15:14.640 --> 00:15:15.997
with an AI company. I want you to like

00:15:16.080 --> 00:15:19.837
handle security and context linking and

00:15:19.920 --> 00:15:23.837
access and I want to be able to run lots
of agents on it. I want like a general

00:15:23.920 --> 00:15:26.477
purpose platform there. I want some
agents from you, some agents from other

00:15:26.560 --> 00:15:30.237
people. I may even want to run
other people's models. I want a Chach

00:15:30.320 --> 00:15:35.117
enterprise license. I want a ton of API
access. Uh you know, things like that.

00:15:35.200 --> 00:15:38.557
So, I think there will be a a model
there as well. Clear. We don't want to

00:15:38.640 --> 00:15:42.077
take a share of people that are just
like paying us for the API and making

00:15:42.160 --> 00:15:46.557
you know, discoveries like that's great
and that's theirs. Uh I can imagine

00:15:46.640 --> 00:15:48.717
though that like if there is a future

00:15:48.800 --> 00:15:51.917
where we can spend billions of dollars

00:15:52.000 --> 00:15:54.637
on inference and cure an important

00:15:54.720 --> 00:15:57.597
disease. Uh

00:15:57.680 --> 00:15:59.597
we may explore partnerships there where

00:15:59.680 --> 00:16:04.637
we pay for that cost in partnership
with the drug company and then kind of get

00:16:04.720 --> 00:16:09.197
some royalty on it. This is not
something we're doing now, but

00:16:09.280 --> 00:16:10.957
I think the frontier of scientific

00:16:11.040 --> 00:16:13.597
discovery with AI will require so much

00:16:13.680 --> 00:16:16.317
capital that maybe we think of ourselves

00:16:16.400 --> 00:16:19.037
as an investor in some of those cases. I

00:16:19.120 --> 00:16:21.597
can imagine like billions of humanoid

00:16:21.680 --> 00:16:26.237
robots building more data centers
and mining for material and building more

00:16:26.320 --> 00:16:30.397
power plants and all of that. Um, I can
imagine just the economy growing at an

00:16:30.480 --> 00:16:33.917
unprecedented rate as there's all sorts of

00:16:34.000 --> 00:16:36.157
incredible new services and scientific

00:16:36.240 --> 00:16:40.477
discoveries happening. Um, I can imagine

00:16:40.560 --> 00:16:45.037
the Bonoyman probes launching and then
beyond that, I got no idea. And the

00:16:45.120 --> 00:16:49.037
models are going to get so much better
quickly. like I have we've been trying

00:16:49.120 --> 00:16:52.797
to figure out how we communicate about
what we think is happening that does not

00:16:52.880 --> 00:16:55.597
seem like hype or

00:16:55.680 --> 00:16:59.117
um you know crazy but the models are

00:16:59.200 --> 00:17:01.117
just going to get

00:17:01.200 --> 00:17:04.237
very very good this year and that will

00:17:04.320 --> 00:17:06.717
that is a tailwind that I think we can

00:17:06.800 --> 00:17:13.480
build incredible things with headwind uh

00:17:13.600 --> 00:17:16.717
yeah probably some sort of like global

00:17:16.800 --> 00:17:20.797
destabilization, mega supply chain
disruption, something like that.

00:17:20.880 --> 00:17:23.597
>> And and on the on the on the tailwind

00:17:23.680 --> 00:17:25.037
side on the models getting infinitely

00:17:25.120 --> 00:17:28.557
better, do you think in 26 we see a 10x

00:17:28.640 --> 00:17:32.797
improvement, a 100x improvement,
a 5x improvement?

00:17:32.880 --> 00:17:35.597
>> What do you mean by like
a what is a 10x improvement? Like

00:17:35.680 --> 00:17:37.197
>> things that you can problems you can

00:17:37.280 --> 00:17:40.717
solve that you you were

00:17:40.800 --> 00:17:44.557
>> Yeah, I would bet it subjectively feels
something like 10x the end of this year.

00:17:44.640 --> 00:17:48.237
Like that's a I don't know how
to like put an exact metric on that.

00:17:48.320 --> 00:17:52.760
>> Yeah. >> But that feels reasonable.