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You have described that AI is a plat

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plat uh platform shift

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and what does what does that mean?

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Question one, where do you see that

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shift going in the next few years?
And importantly, the third part of my

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question would be fast forwarding
a few years, five years,

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what's going to seem obvious in

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hindsight that feels less clear today?

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You know, first of all, um it's great uh

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to be back here, uh Larry, and it's um I

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had a chance, in fact, yesterday when

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you put out the letter uh to kick off

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the forum and read it. And um and in

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there, you sort of had this one line of

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uh really I think when it comes to AI,

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the real question in front of all of us

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is how do you ensure that the diffusion

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of AI happens and happens fast? I mean I

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think you had that line of how do the

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models, the data and the infrastructure

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spread more evenly to create surplus

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everywhere. If you sort of think about

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it, the the way I come at this is not

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that um this has always been the arc of

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computation, right? You can sort of take
it in the last 30 years or the last 70

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years. It's always been about can you

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digitize

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artifacts on about people, places, and

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things and then build analytical and

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predictive [clears throat] power. Right?

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That's what the mainframes did. That's
what the mini computer did. That's what

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the client server error did. That's
what the web error did. The mobile cloud

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error did. So it like it depend

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irrespective of which paradigm or

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platform. It has been one continuous arc

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of saying let's make better sense of

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this world

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um by reasoning about it in digital form

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because in some sense once you have
these artifacts in digital form you can

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use a more malleable
resource like software

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>> right >> um which
doesn't have the same type of

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you know I'll call it [clears throat]

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marginal cost economics associated with

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it that allows us to then build more

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insight and more uh more capability and

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in that context AI I would say is of the

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same class at least like the web or the

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internet um or mobile or PC or the cloud

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or and maybe even greater and so to me

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right now where we are is you know let's

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take just what's happened with software

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engineering right which is one you know

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is knowledge work um you know you could

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say it's elite knowledge work

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>> it started off uh you know in fact my

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own belief in this generation
of AI and its capability

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uh really got built up when I first saw
GitHub copilot do code completions right

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so for the longest time we had the dream
that if you're a software developer can

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you predict the next sort of word or the

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next uh line of code uh and suddenly it

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started working with these models u then

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You said okay if I can do that then can

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I actually go and bring back you know

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the flow for a software developer
by going to a chat session and asking any

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question and it comes back with answers
that then uh you can use in your coding

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flow right so that was the next thing
then you said well if that's working can

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I assign it small tasks that was the
agent mode uh now you have complete

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[clears throat] autonomous agents where
you can give it your entire project

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right it can work uh you know >> 24/7
>> it can work for 24/7 7. I mean it's

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still we've got some ways to go
for these things to remain coherent long

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time but nevertheless it's getting

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better and better and interestingly

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enough you look at it uh the software

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developer still is got a lot of agency
in it right so that's why I kind of

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still think that you know going
and thinking of these as somehow living

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outside of the realm of human agency is

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probably not the right
way to think about it.

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