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[music]

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[music]

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>> Please welcome Swyx, Sara Goa, A Lad

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Gill, and Chairman and Chief Executive

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Officer of Microsoft, Satya Nadella.

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>> [cheering]

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>> Hello. Satya? >> Uh I'm so
excited to be here. Welcome to

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a crossover episode of No Priors
and Lain Space with Satya Nadella. Um

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congratulations on an amazing build.

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>> No, thank you so much and it's great to
be with both of you. I listen to both of

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you or both the podcasts all the time.

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It's great to be on it.
>> Thank you so much.

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>> Sara has been talking about um these
amazing uh announcements from across the

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Microsoft estate all morning
for I think 3 hours. What is the uh

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what's the most important
reflection or takeaway you have?

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>> I I'd say there are

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uh

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perhaps the the biggest one for me is

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let's sort of conceptualize this more as

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an ecosystem play as opposed to a single
model or even a single platform, right?

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I mean yeah, whatever
I at least for me having

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grown up at Microsoft, having seen
whatever four major platform shifts,

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uh I sort of fall into that uh

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uh camp where a platform is defined by

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fundamentally its ability to create more
value above the platform versus what's

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captured in the platform. And so if you

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you view what's happening right now, I

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think this morning's keynote
was how can any company

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whether it's an AI-native company a

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traditional enterprise company,

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participate as a first-class participant

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where they can point to AI they created.

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Right? It's not that they don't use
other people's AI. Of course, they will.

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But to me, what's the path? What's
the recipe? How do I do it? What does the

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stack look like? What does the tooling
look like? What is valuable? How do you

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do that? That's it.
That's sort of our job to do.

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Yeah. >> Ecosystem strategy is uh very
complicated, right? Because you end up

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building certain components, partnering
for certain components, supporting them.

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You just announced this big suite of
models. Like, tell us a little bit about

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the uh training strategy for Microsoft.

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>> Yeah. So So, the thing
that we wanted to do with

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the MAI models was to build, and as

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Mustafa talked about, first of all,
a great lineage, right? Starting with

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pre-training

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uh with very good data quality,

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uh doing all the ablations, making sure

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because in in some sense, it's become
even harder to build a clean lineage

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model. Yes, because there's
so much stuff out there

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uh that you truly need to ablate out
to be able to have a fantastic pre-trained

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model. In fact, that's one of the
challenges of a lot of the open weight

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models is they look great on one

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benchmark or two, but they're not great
on practice. So, that's why, in fact,

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even in the RFDs are

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are pretty gone really excited about

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these MAI models because how the heck

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can a small 5B model hill climb?

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Uh and it goes back a little bit to what

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I think is ultimately the key thing to

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do, which is try to pursue finding that

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cognitive core. Uh so, to me, starting

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with a clean lineage, then creating that

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ability for companies to be able to use

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this, right? Not just as a generalist,

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but to create their own specialist
by building this hill climbing scaffold

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around it, right? So, it's not just
the model, but you have a hill climb

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scaffold around it, then you
will start building your RLE. You

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will start collecting the traces. Most
importantly, you'll have private emails

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because we know all the emails out there
are good, interesting, but they're not

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really that critical at this point
because they all can be maxed. And so,

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the point is each company will have its

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own private email. And so,

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that end-to-end platform story

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around our models is sort of uh what I
think is interesting. And then the one

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other thing, Sarah,
is since you brought that up is

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I do feel there's a new frontier. Like
people talk about the frontier and are

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you operating at the frontier?

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Um interestingly enough, if you
add a little temporality to it,

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you can use, let's say, in in in fact,
that the Land O'Lakes demo we showed was

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pretty cool. We used whatever GPT-55,
right? Then you collected a bunch of

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traces, and then you took a 5B reasoning

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model and achieved higher uh so,
that is another aspect of what it

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means to appear you know,
operate at the frontier.

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>> Yeah. I I think uh I first of all
have to congratulate you on basically

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building a frontier neural lab inside
of Microsoft in 2 years. Um I'm wondering,

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you know, you have all this AI strategy
that you're rolling out. I'm wondering,

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what do you know now that you wish you
would tell yourself 2 years ago where or

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2 or 3 years ago? 3 years for the Jensen
partnership, 2 years for uh MAI.

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>> Yeah, I mean,
I think the the thing with

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that I reflect quite a bit, right? Which
is sort of obviously I got into all this

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when I got excited by the the scaling
laws paper and, you know, when, you

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know, even the OpenAI partnership came
about when those folks said, "Hey, we're

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going to really throw a lot of computer
transformers." Uh and they've held,

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right? The thing that I always look back

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and say, "Wow, these things um

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do have capability that they're climbing

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up with I mean, this, you know, this
crude way of saying it is intelligence

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is log of compute kind of works.

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Now, what I think we underestimated

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perhaps is the real world complexity

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of deploying these so that they actually

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deliver the value in the real world,
right? So the outcomes as measured by

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any benchmark

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is interesting, important, but the true

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eval is when people out there are able
to do unique things that they only can

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value. And it's very measurable.

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Right? That I wish we had sort of even
like had more in our consciousness,

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right? Which is as an industry
because right now I think

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when people say, "Wow, I don't want a

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token max." It's an artifact of us not

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having thought ourselves as an industry

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that we are using tokens to create value

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every step of the way. So I think that's
kind of what I wish we had gotten there,

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but I'm glad we are here.
>> What are some other use cases that

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you've seen that have created the most
value for your customers? Because I know

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that people talk a lot about code and I
think it's pretty clear that that's

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something that's having very large-scale
impact. Are there other areas that you

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find in common that your customers
are really benefiting?

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>> Yeah, I think yeah, to your point,
obviously coding is now got but it's

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interesting by the way Elijah to even
talk about the coding, right? Which is

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coding is worked so well that we now
have to rebuild the IDE, right? I mean

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it's kind of nuts to see what we saw
large is like, "Oh my god, I have these

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100 agent sessions. I the cognitive load

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it transfers back to me as a human is so

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excessive that now I need a new UI. Uh

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oh, by the way, I like the the chat as

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the only artifact is also impossible.
So that's why we need a canvas. So it's

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kind of interesting for all the things
about where is software needed or where

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is UI needed? Uh you kind of need that

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even for code, right? In a fully agentic
world. But that said, one of the things

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that we are starting to see, we started
seeing with co-work, but even some of

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the work we showed with auto autopilot,

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right, on what you see with claws, is a

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good one, because if you sort of think

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about a lot of human capital is doing

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the glue work, right? If you now can

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augment that with tokens {slash} agents

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that are long-running, durable,

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right, then your ability to scale even

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what is still judgment and glue work

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gets amplified like coding does.

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So you can like I'm positive that 6
months from now we'll all be saying,

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"Oh, wow, like all through
night the night there

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was a bunch of stuff that all these

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autopilots that I have working on my
behalf with my delegated authority, so

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to speak, right? I can sort of given
even my identity, did a bunch of work.

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Then of course I'll need my new ADE
to say, "What did you do?" Like that. My

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Did I do this work and so on. So I
think that that's where compressing of

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workflows, completing
of tasks, that's where I

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think a lot of the value gets created.

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>> you raise a really interesting point,
which is there's the actual agent is

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doing the code, and then there's
a harness around it. And that's the

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environment, that's the context,
that's everything you're setting up as a

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developer around actually a coding
agent. What is the harness for the

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enterprise? Is there an equivalent
concept for broader productivity work,

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or how do you think about
that concept sort of generally?

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>> So so some sense you kind of want the

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harness to define the models, the the

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data, and the tools,
and so that you have a

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loop across those three. And so what we
are trying to first of all make sure is

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each of our products that we build,
right, whether it's GitHub Copilot or

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the security copilot the stuff we showed
with M-Dash, or even the discovery for

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science, it doesn't matter.
All of them are multimodal harnesses

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um tools access so that you can do this

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progressive uh disclosure of tools even

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so that they're token efficient. Uh and

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then you're feeding it with very rich

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context because that's sort of the other

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hard lesson we've learned in the last 2

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years is oh my god the amount of work

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you need to do to prep the context layer

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uh such that your plan can execute in

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the most efficient way is where the magic
is. So we have in our case we have

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the get up harness which essentially
we're using across all our products.

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It's available in foundry and we're
open like you can use your llama harness

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whatever or you can use the um

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you know any open harness or any harness

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of yours and train with your tools and
multiple models and your context. And so

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that's the pitch because right now a lot
of dialogue is um hey if I train the

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harness plus tools and the model

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together you get evals. And what we're

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proving out is and the best example of

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that is what we did with M dash right

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because when it launched uh

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it found bugs or vulnerabilities that

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were not found by mythos.

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Uh and so there is existence proof I

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would claim that you can
have a multimodal harness

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uh that can in fact be more uh

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performant in the real world.

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>> So premise behind
the uh training at the

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independent frontier labs is really you
know we're going to have these models

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and we'll have an API business and we'll
support enterprise and startups but

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a first party product be it productivity
or code or search drives the majority of

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revenue. That's a different value
equation than you're describing. I think

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with the Microsoft ecosystem uh if if
that's the case tell me if it's the case

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cuz obviously you have first party
products and you have enablement

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products. Um what is the role of the
develop like what's going to be hard and

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the set of skills and the value
capture the developer has in that world?

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>> Yeah, so I think that there's
always going to be the case that

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someone who's super successful
and as a platform builder can also have

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first-party products.

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It was true with Windows, it was true uh

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with uh the the SaaS side and the cloud

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side as well with us and others and so

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on. But, the thing that is is it should

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not be a limiter to other people

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achieving that same success, right? That

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I think is the core difference, which is

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the the network effects this time around

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around intelligence are such because

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they learn from data and not really lots

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of data. It's just the few samples that

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you have to see to understand what's

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novel about something. So, that's why

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the game becomes how to protect, so

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that's why I would say every company

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having private evals maybe the biggest IP.
Right? I think about it. Like,

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what's that private eval that you can
then use even a frontier model to hill

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climb on and not leak the traces maybe

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one of the biggest drivers

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uh of IP. Like, so in other words,

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another acid test is you have an eval

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that's private. You're using a a model

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A. Can you switch it to model B and you

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know, climb up? If you can, then you're
in control. If you can't, you're not in

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control. And that's where even the
harness becomes super important, right?

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So, therefore, having an open harness,

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letting all models come in, having your

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evals, your contacts, your tools help

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you hill climb, I think is the skills

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that an AI native startup needs,
a SaaS company needs, or every enterprise

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needs. >> Yeah, I think in a very real
way, you are Microsoft historically as an

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operating systems company and then
becoming a cloud company. Maybe like the

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third act is that you're harness or eval's

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company. Whatever whatever the the sort
of conglomerate of concepts that you

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want to put together. Um I I I think
like enabling every company to have like

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frontier intelligence or what what I
forget the the exact term that you used.

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Um is the is the mission, right? That
is that is the platform promise that you

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build with us, you will get
your intelligence for your data.

240
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>> That's it. That to me that is the like

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if there was one tagline for this entire

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developer conference is

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can everybody operate at the frontier

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with their frontier intelligence, right?

245
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To me that is so
important because otherwise

246
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I I don't know how you achieve stable
equilibrium, right? Which is how do I

247
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then go and say, "Wow, my company is

248
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going to have a terminal value because I

249
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now know how to continuously compound on

250
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top of what's a platform that gets
better, right?" So when like Windows

251
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obviously came out,

252
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Adobe built, Autodesk built,

253
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or even like take but Jensen said, "We
built DX." And he built, you know, CUDA

254
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on top of it. Right?
I mean, I always say to Jensen,

255
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"God, I got the short
end of that." But I wish

256
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we had recognized it. But nevertheless,

257
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but that idea that you can build a

258
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platform layer that someone
else can then extend out

259
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and build their own intelligence layer
in this case, I think is everything,

260
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right? Without it, why have a developer
conference? I can just come and have you

261
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all sort of just worship at the altar
of one model. But that's not a developer

262
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conference. >> Uh backstage
we you had a discussion

263
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about what is IP or what is the the
value in a company. It used to be the

264
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length of human experience at a company.

265
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And now it's this other thing,
which is the eval's, the

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experience in sort of applying agents
to the company. He I just want you to like

267
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flesh that out a little bit more cuz >>
Yeah, it's It's way to frame it, right?

268
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Because you have at the end of the day
every company is going to have both the

269
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human capital that is still going to be

270
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super valuable because humans

271
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and their ability to find the gaps that

272
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exist at all times is going to be
the way we all will create value, right? I

273
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mean so I'm definitely in the camp that

274
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this is going to be about expressing new

275
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forms of human agency and ambition
even as token capital goes up, right? So

276
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let's say any corporation
has lots of tokens and

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lot of human capital. The question is

278
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how do you compound the two? So if you
have a like if you take in teams, I have

279
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a bunch of agents doing work and a bunch
of humans doing work and the traces

280
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between those

281
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that is really important context of the

282
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how that enterprise is creating value.

283
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Then that goes back to train not a

284
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generalist model, but to train the train

285
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the company veteran agent.
Right, that is super valuable again,

286
00:16:20,720 --> 00:16:23,757
right? Which is when a company goes says
it should in fact go on to the balance

287
00:16:23,840 --> 00:16:25,437
sheet is how I think about it, right?

288
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That's what in fact they may be like
human capital was never possible to go

289
00:16:29,880 --> 00:16:33,277
put on a balance sheet because
you didn't know how to capture

290
00:16:33,360 --> 00:16:37,317
the tacit knowledge, whereas now I
think you can with the agents that have

291
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learned through the through
time, through all the traces.

292
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So that's what at least
we think will happen.

293
00:16:43,960 --> 00:16:47,997
>> I think the SEC is going to have
to have accounting standards for token

294
00:16:48,080 --> 00:16:52,957
expertise. >> Uh you're
talking about the equilibrium

295
00:16:53,040 --> 00:16:56,157
state and a stable
equilibrium where companies

296
00:16:56,240 --> 00:17:00,237
have this compounding value and can see
terminal value for themselves. Another

297
00:17:00,320 --> 00:17:02,717
challenge to you know, the considered

298
00:17:02,800 --> 00:17:04,877
equilibrium of okay, there are

299
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applications and workflows that are sort

300
00:17:07,680 --> 00:17:12,317
of common to a vertical or a horizontal
and this was like the generation of SaaS

301
00:17:12,400 --> 00:17:16,157
companies and you know, Microsoft has
lots of SaaS properties as well. And

302
00:17:16,240 --> 00:17:18,477
then there are things that are very
specific to every enterprise that

303
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they're differentiated against.

304
00:17:20,480 --> 00:17:23,437
Um I'm sure you have heard much
and participated much of the debate about

305
00:17:23,520 --> 00:17:28,397
the end of software because all these
workflows are are cheap to generate now.

306
00:17:28,480 --> 00:17:32,557
Um do you think the equilibrium looks
different between what agents get built

307
00:17:32,640 --> 00:17:35,797
in enterprises versus
in their vendors in the future?

308
00:17:35,880 --> 00:17:41,117
>> Yeah, so I think what's happening
there is see we we had a particular way we

309
00:17:41,200 --> 00:17:45,837
captured uh I would say workflow

310
00:17:45,920 --> 00:17:50,717
in apps, right? Because we built
a a data model, right? We schematized some

311
00:17:50,800 --> 00:17:52,517
part of some business process.

312
00:17:52,600 --> 00:17:55,197
>> Mhm. >> We then built
a bunch of business logic.

313
00:17:55,280 --> 00:17:57,637
>> Yep. >> And then we
put a bunch of UI on top of

314
00:17:57,720 --> 00:18:00,877
it, right? So that's kind of what every
SaaS company >> configuration, right?

315
00:18:00,960 --> 00:18:02,597
>> 20 20 years that was >> Right.

316
00:18:02,680 --> 00:18:07,037
>> And that was it. So interestingly
enough, now you kind of get to

317
00:18:07,120 --> 00:18:11,917
re-litigate that vertical stacking,
right? So I still think, for example,

318
00:18:12,000 --> 00:18:15,997
that data model that you built
underneath every SaaS application is

319
00:18:16,080 --> 00:18:20,317
super good, right? It like why reinvent
it? Like I I my general ledger better be

320
00:18:20,400 --> 00:18:23,837
a general ledger.
I don't need new schema creation.

321
00:18:23,920 --> 00:18:26,997
>> Yeah. >> Uh in fact,
that entity relationship

322
00:18:27,080 --> 00:18:30,837
uh is actually pretty good
robust thing that I want to feed.

323
00:18:30,920 --> 00:18:31,877
>> And you want it to be stable.

324
00:18:31,960 --> 00:18:34,797
>> That's right. >> Yeah.
>> Then same thing with business logic,

325
00:18:34,880 --> 00:18:37,117
right? If If you look at uh we have this

326
00:18:37,200 --> 00:18:38,957
product called Power BI, right? It is

327
00:18:39,040 --> 00:18:42,597
like dashboards galore people created.

328
00:18:42,680 --> 00:18:44,917
The beauty underneath that dashboard is

329
00:18:45,000 --> 00:18:47,317
a very rich semantic model, right?

330
00:18:47,400 --> 00:18:49,757
Someone took the pain to create a

331
00:18:49,840 --> 00:18:53,037
dashboard and do all the measures.

332
00:18:53,120 --> 00:18:55,437
And you want that that's business logic,

333
00:18:55,520 --> 00:18:57,637
right? I want that to be available to

334
00:18:57,720 --> 00:19:01,077
me. So I think the challenge of the SaaS

335
00:19:01,160 --> 00:19:04,197
business model is we packaged one way.

336
00:19:04,280 --> 00:19:09,157
We now have to learn how to unbundle
these things and re-bundle in new ways

337
00:19:09,240 --> 00:19:10,997
and discover new business models, right?

338
00:19:11,080 --> 00:19:15,357
I mean if you look at it, te- what's
happening today with Microsoft 365 is a

339
00:19:15,440 --> 00:19:17,997
great example. Right?
We have this thing called Work

340
00:19:18,080 --> 00:19:22,717
IQ. In fact, like what we are realizing
is, oh my god, like you know, if you

341
00:19:22,800 --> 00:19:26,717
look at In fact, there's a historical
parallel to, right? We sold first

342
00:19:26,800 --> 00:19:30,597
Exchange and SharePoint and uh
you know, before Teams, we had a

343
00:19:30,680 --> 00:19:33,917
thing called Link Server and what have
you. And we thought, oh, that's all

344
00:19:34,000 --> 00:19:38,117
going to move to the cloud, but little
did we realize that oh the number of

345
00:19:38,200 --> 00:19:42,677
people who will use servers in the cloud
is 10x 100x, right? Because people were

346
00:19:42,760 --> 00:19:45,677
not buying servers, they were
just buying a subscription.

347
00:19:45,760 --> 00:19:47,277
The same thing is now happening with

348
00:19:47,360 --> 00:19:50,477
M365 because with Work IQ,

349
00:19:50,560 --> 00:19:55,357
we have exposed what is perhaps the most
important database in a company that

350
00:19:55,440 --> 00:20:00,317
never got used as a database because it
is only captive to our apps, right? It

351
00:20:00,400 --> 00:20:04,157
is all email operated on it, Teams
operated on it, Word, Excel, PowerPoint,

352
00:20:04,240 --> 00:20:06,637
SharePoint. But now, like this is one of

353
00:20:06,720 --> 00:20:11,277
the coolest things I get to do with Work
IQ. I go to a GitHub repo and I say,

354
00:20:11,360 --> 00:20:13,477
"Hey, I attended a bunch of design

355
00:20:13,560 --> 00:20:16,397
meetings last week related to this repo.

356
00:20:16,480 --> 00:20:19,957
Can you capture all that and tell me
what changes I should make?" I mean,

357
00:20:20,040 --> 00:20:24,197
think about that. Right? It literally
can go look at all those transcripts,

358
00:20:24,280 --> 00:20:26,357
come back with a plan to change a code

359
00:20:26,440 --> 00:20:28,597
base. Right? Previously, you could never

360
00:20:28,680 --> 00:20:31,637
have thought of using M365 for something

361
00:20:31,720 --> 00:20:33,957
like that. So, the value creation

362
00:20:34,040 --> 00:20:36,877
opportunity now in the agent world is in

363
00:20:36,960 --> 00:20:41,237
fact 10x more. But it does require us
to have, for example, there's going to be

364
00:20:41,320 --> 00:20:43,637
usage around M365, right? Which is going

365
00:20:43,720 --> 00:20:46,477
to be perhaps more than even the end

366
00:20:46,560 --> 00:20:48,437
users. And we have to even re-architect.

367
00:20:48,520 --> 00:20:51,197
Like in fact, like what I used to serve

368
00:20:51,280 --> 00:20:55,277
an inbox or a mailbox cannot be used to

369
00:20:55,360 --> 00:20:59,357
serve an agent. Uh and so,
that's sort of what we're doing.

370
00:20:59,440 --> 00:21:03,157
>> I don't believe in like permanent
business models for any of these

371
00:21:03,240 --> 00:21:06,877
domains, but in the near term,
do you have a prediction between

372
00:21:06,960 --> 00:21:11,837
uh you know outcomes based
pricing token based pricing

373
00:21:11,920 --> 00:21:15,597
enterprise bundles >> Yeah
the way I think about this is

374
00:21:15,680 --> 00:21:19,157
always we have like let's
even take the per user pricing.

375
00:21:19,240 --> 00:21:23,397
>> Mhm. >> The per user
pricing is really an

376
00:21:23,480 --> 00:21:27,597
artifact of someone creating
a budget needing certainty.

377
00:21:27,680 --> 00:21:31,437
Right because it's the most important
thing like somebody wants a budget.

378
00:21:31,520 --> 00:21:33,957
>> Mhm. >> They need a per
user and and per user is

379
00:21:34,040 --> 00:21:37,517
just a set of entitlements to usage.

380
00:21:37,600 --> 00:21:38,997
Right that's kind of what it is and so

381
00:21:39,080 --> 00:21:41,677
the way is if the first bundling will be

382
00:21:41,760 --> 00:21:46,477
take some usage bundle it into per
user stacks and you know then sell

383
00:21:46,560 --> 00:21:50,157
subscriptions. So subscriptions I think
are going to be there per user is going

384
00:21:50,240 --> 00:21:53,917
to be there. Then the next big thing
will be consumption. So people will say

385
00:21:54,000 --> 00:21:57,517
I want consumption. And it's also
possible that people will say I don't

386
00:21:57,600 --> 00:22:00,397
even want to pay for any of the
subscriptions or the consumptions

387
00:22:00,480 --> 00:22:04,557
outcome. But remember most
people love outcomes until they

388
00:22:04,640 --> 00:22:07,317
have an outcome. Because once you
have an outcome it's like giving away

389
00:22:07,400 --> 00:22:11,717
royalty. Right I mean like I've talked
to customers who love you know outcome

390
00:22:11,800 --> 00:22:16,117
based pricing and I say I'm all in until
they oh my god like what are you talking

391
00:22:16,200 --> 00:22:19,597
about you're sharing in my outcome no
no no I want you to go back to per user

392
00:22:19,680 --> 00:22:23,277
pricing and I want you to consumption
price. Right so I think that debate will

393
00:22:23,360 --> 00:22:26,757
go on and all all
the all of these business

394
00:22:26,840 --> 00:22:28,637
models have a particular time and a

395
00:22:28,720 --> 00:22:32,197
place versus one to rule them all. And

396
00:22:32,280 --> 00:22:36,557
if anything if you're a SAS vendor
or you're a platform vendor having that

397
00:22:36,640 --> 00:22:40,557
flexibility and quite frankly we face
this with GitHub. Right we just recently

398
00:22:40,640 --> 00:22:43,157
announced a per user pricing on GitHub.

399
00:22:43,240 --> 00:22:45,037
Because little you know

400
00:22:45,120 --> 00:22:48,517
GitHub co-pilot was constructed at a per

401
00:22:48,600 --> 00:22:52,037
user level before we understood even

402
00:22:52,120 --> 00:22:54,877
the intensity of usage of agents. Right

403
00:22:54,960 --> 00:22:59,157
it was an interactive way for a
developer to use code complete maybe

404
00:22:59,240 --> 00:23:01,637
task. It was not like oh I launched

405
00:23:01,720 --> 00:23:04,517
10,000 you know, agents that are going

406
00:23:04,600 --> 00:23:09,637
on all day. Right? So, that is what
the adjustment is about. So, now that we

407
00:23:09,720 --> 00:23:13,317
really want there will always be
a per user, but there will have to be a

408
00:23:13,400 --> 00:23:16,117
consumption meter. >> How do
you think about the durability of

409
00:23:16,200 --> 00:23:19,477
SaaS more generally? One thing I've
observed is in a lot of enterprises

410
00:23:19,560 --> 00:23:23,677
internally, there'll be teams that
almost have agent euphoria. They're so

411
00:23:23,760 --> 00:23:26,357
excited about the explosion of things
they can build that they're trying to

412
00:23:26,440 --> 00:23:29,037
rebuild a lot of applications or going
to other SaaS vendors and saying we're

413
00:23:29,120 --> 00:23:32,517
not going to work with you anymore
or we're considering an internal project.

414
00:23:32,600 --> 00:23:35,197
And it seems like in 6 to 9 months maybe
some of those people will come back and

415
00:23:35,280 --> 00:23:38,197
say actually we we can't rebuild
everything. How do you think about

416
00:23:38,280 --> 00:23:40,397
what's durable in this
world and what isn't?

417
00:23:40,480 --> 00:23:42,717
>> I I think I think we have to go through

418
00:23:42,800 --> 00:23:46,637
one full budget cycle on this to really

419
00:23:46,720 --> 00:23:52,397
see the uh uh the sort of the emergence of
the equilibrium. Because at the end of the

420
00:23:52,480 --> 00:23:56,317
day there's marginal
cost to even generating

421
00:23:56,400 --> 00:23:57,797
the app. Right? So, in fact, there can

422
00:23:57,880 --> 00:23:59,997
be even a a simple way to say it like if

423
00:24:00,080 --> 00:24:03,357
you should always acquire something if

424
00:24:03,440 --> 00:24:07,117
the marginal cost
of building and maintaining

425
00:24:07,200 --> 00:24:09,957
uh something on your own is higher.

426
00:24:10,040 --> 00:24:13,957
Uh right? That should be like it's
a quantifiable right? A quantifiable

427
00:24:14,040 --> 00:24:18,037
thing. And the maintenance part
is important. Right? Even like you got to

428
00:24:18,120 --> 00:24:22,437
remember like hey, you know, all the
security stuff that now AI will find you

429
00:24:22,520 --> 00:24:26,277
better fix them too fast. Uh of course,
there's a coding agent to help you with,

430
00:24:26,360 --> 00:24:30,197
but then that burns tokens. Right? So,
whose responsibility is it? It's kind of

431
00:24:30,280 --> 00:24:34,677
like a a cycle that you've got to think
through. And I think we have gone

432
00:24:34,760 --> 00:24:38,477
through the excitement that I can
generate a lot of software. I think the

433
00:24:38,560 --> 00:24:43,077
next thing would be what software do I
really want to generate? What software

434
00:24:43,160 --> 00:24:45,397
do I want to use from others? How do I

435
00:24:45,480 --> 00:24:50,797
compose these two into some agentic
workflow that I have agency over? Right?

436
00:24:50,880 --> 00:24:55,757
Because I think there'll be very little
tolerance for anybody who's inflexible

437
00:24:55,840 --> 00:24:59,837
uh at the vendor level.
Uh but at the same time, I think that

438
00:24:59,920 --> 00:25:04,797
anyone who has got that flexibility
shows up, delivers the value, will be

439
00:25:04,880 --> 00:25:08,597
back at again, right? We're selling
software, but with just different

440
00:25:08,680 --> 00:25:13,037
business models, in fact.
>> Uh speaking about building software, um

441
00:25:13,120 --> 00:25:15,997
one of my favorite moments from I think
a previous build, maybe 1 or 2 years

442
00:25:16,080 --> 00:25:19,077
ago, was they had a they they there
was a section of you building your own

443
00:25:19,160 --> 00:25:21,597
software. I'm curious if
you're building anything now.

444
00:25:21,680 --> 00:25:26,317
>> Yeah, so I I think the you know, first
of all, let's face it, right? Building

445
00:25:26,400 --> 00:25:31,317
software has made it possible for even the
incompetence of a CEO of a company like

446
00:25:31,400 --> 00:25:32,157
ours, [laughter]

447
00:25:32,240 --> 00:25:34,517
uh you can build. So, thank God. But

448
00:25:34,600 --> 00:25:39,237
that said, I I I I do feel that

449
00:25:39,320 --> 00:25:41,757
you know, something like um

450
00:25:41,840 --> 00:25:44,317
GitHub Copilot to me, and especially the

451
00:25:44,400 --> 00:25:47,397
new sessions app or the new app, has

452
00:25:47,480 --> 00:25:51,037
just made it so much more possible

453
00:25:51,120 --> 00:25:54,397
for you to have agency over artifacts

454
00:25:54,480 --> 00:25:56,157
that you felt you couldn't touch before,

455
00:25:56,240 --> 00:26:01,437
right? So, to for me as a CEO even, to go
to a codebase, uh to be able to learn

456
00:26:01,520 --> 00:26:05,037
about it, like I remember joining
Microsoft long back, you know, first,

457
00:26:05,120 --> 00:26:07,517
and then you say, "Well, everybody
had to go in and look at, you know,

458
00:26:07,600 --> 00:26:12,517
whatever, Cutler's Mallet or what
have you, to learn how to do good C C++

459
00:26:12,600 --> 00:26:13,877
code." Um

460
00:26:13,960 --> 00:26:16,437
so, now that ability to be more full

461
00:26:16,520 --> 00:26:20,517
stack up and down is so good. But that

462
00:26:20,600 --> 00:26:24,157
doesn't mean every one of us should be
doing the same thing. The question is,

463
00:26:24,240 --> 00:26:28,437
how do you then have the ability
to inspect things, learn things, see

464
00:26:28,520 --> 00:26:31,197
things, um I think it's
just so much more. And

465
00:26:31,280 --> 00:26:33,357
so, to me, what I'm building a lot of is

466
00:26:33,440 --> 00:26:36,357
these long-running foundry agents,

467
00:26:36,440 --> 00:26:38,637
uh right? So, there's autopilots. So,

468
00:26:38,720 --> 00:26:41,037
the easiest thing is, to me, I think I

469
00:26:41,120 --> 00:26:44,037
just built one uh even last week, where

470
00:26:44,120 --> 00:26:47,757
the idea was, hey, can I have an agent

471
00:26:47,840 --> 00:26:50,557
that is continuously monitoring,

472
00:26:50,640 --> 00:26:53,157
essentially, my own chief of staff

473
00:26:53,240 --> 00:26:55,117
autopilot, right? We're going to have

474
00:26:55,200 --> 00:26:59,117
that obviously in Scout. That's what

475
00:26:59,200 --> 00:27:01,677
we showed, but it is so easy and trivial

476
00:27:01,760 --> 00:27:04,077
to build. I took it work IQ. I said take

477
00:27:04,160 --> 00:27:06,437
work IQ, go

478
00:27:06,520 --> 00:27:09,037
and build a foundry long-running agent,

479
00:27:09,120 --> 00:27:11,837
store all the memory in

480
00:27:11,920 --> 00:27:16,237
using Raven, right? Basically at my back
end as a service. And lo and behold, it

481
00:27:16,320 --> 00:27:18,437
built it and not only built it, I could

482
00:27:18,520 --> 00:27:23,797
say publish to Teams and it published
the damn thing to Teams. So, the ability

483
00:27:23,880 --> 00:27:27,397
to have you know some
end-to-end project like

484
00:27:27,480 --> 00:27:29,517
this complete is just pretty miraculous.

485
00:27:29,600 --> 00:27:32,477
>> How do you think that impacts
the different types of engineering roles

486
00:27:32,560 --> 00:27:36,277
that exist in the future because right
now I think there's you know a dozen

487
00:27:36,360 --> 00:27:40,597
different types of engineers that you
can be from QA, front end, etc. You

488
00:27:40,680 --> 00:27:43,917
know, there's a big swath. I've heard
some people argue that in four or five

489
00:27:44,000 --> 00:27:47,237
years we'll basically end up with four
engineering roles. It'll be people who

490
00:27:47,320 --> 00:27:51,597
are managing agents. It'll be forward
deployment engineers or FTEs. It'll be

491
00:27:51,680 --> 00:27:55,437
security engineers and then people
working on large-scale infrastructure

492
00:27:55,520 --> 00:27:58,877
for a small number of services and then
everything else just collapses into the

493
00:27:58,960 --> 00:28:01,597
agentic world. >> Do you think
that's a correct view of the world?

494
00:28:01,680 --> 00:28:05,757
>> Yeah, I mean I think I think we'll
have to experiment our way through it. But

495
00:28:05,840 --> 00:28:08,357
what you said is what there are some

496
00:28:08,440 --> 00:28:10,757
very at scale things. At LinkedIn, they

497
00:28:10,840 --> 00:28:14,437
did structurally change

498
00:28:14,520 --> 00:28:17,917
and it you know basically built up a new
discipline called full stack builder,

499
00:28:18,000 --> 00:28:21,957
right? So, they went and said, "Hey,
let's bring people from design and

500
00:28:22,040 --> 00:28:26,557
product management, front end
engineering, all put them together,

501
00:28:26,640 --> 00:28:30,157
but also have an edge, right? It's not
like the design person still doesn't

502
00:28:30,240 --> 00:28:33,157
have the design edge or the front end
person doesn't have the front end edge,

503
00:28:33,240 --> 00:28:36,077
but you can give yourself bigger scope

504
00:28:36,160 --> 00:28:37,997
in role so that you're not confined to

505
00:28:38,080 --> 00:28:40,677
one role. And then

506
00:28:40,760 --> 00:28:45,077
equally infrastructure has become very
critical, right? So, in other words,

507
00:28:45,160 --> 00:28:47,677
like I mean our R&D team,
I mean one thing we've

508
00:28:47,760 --> 00:28:51,117
is even for the Excel team, for example,

509
00:28:51,200 --> 00:28:55,077
building the RLE in which a reward can

510
00:28:55,160 --> 00:29:00,037
be learned is actually one of the hardest
sort of infrastructure problems.

511
00:29:00,120 --> 00:29:03,637
And so you kind of need even new talent,
right? Distributed systems people even

512
00:29:03,720 --> 00:29:06,957
in what was considered
an end-user app team

513
00:29:07,040 --> 00:29:10,477
because it's a different skill set. So
yes, infrastructure science is the other

514
00:29:10,560 --> 00:29:14,077
one, obviously. So I think
we'll see how these evolve,

515
00:29:14,160 --> 00:29:17,037
right? Where's the reals, I mean,
always the world will have a bunch of

516
00:29:17,120 --> 00:29:18,877
specialists.

517
00:29:18,960 --> 00:29:23,677
You know, I think the generalist role is

518
00:29:23,760 --> 00:29:25,637
going to be the most exciting, right?

519
00:29:25,720 --> 00:29:29,477
Because the leverage of a generalist

520
00:29:29,560 --> 00:29:33,317
is where we're going to see the maximum
returns, right? When when you said,

521
00:29:33,400 --> 00:29:38,877
"Hey, I'm coding. I'm now a general like
what I've basically translated knowledge

522
00:29:38,960 --> 00:29:40,037
work,

523
00:29:40,120 --> 00:29:42,197
right, which I did where I created a

524
00:29:42,280 --> 00:29:46,637
Word document or a spreadsheet or even

525
00:29:46,720 --> 00:29:48,557
and now I can build an app, right? It's

526
00:29:48,640 --> 00:29:51,117
in the same sentence,

527
00:29:51,200 --> 00:29:56,117
right? That idea that, "Oh wow,
my generalist skills have gotten a higher

528
00:29:56,200 --> 00:29:59,077
leverage." I think is what we're
going to see across the board.

529
00:29:59,160 --> 00:30:03,597
>> Music to the ears of CEOs and VCs that
are like a little dangerous and a lot of

530
00:30:03,680 --> 00:30:04,997
fun. >> Golden age for idea people.

531
00:30:05,080 --> 00:30:09,157
>> Idea people with a lot of agency. If
you take that idea of personal agency and

532
00:30:09,240 --> 00:30:13,717
you just zoom it out to the
organizational context, um

533
00:30:13,800 --> 00:30:17,917
uh my partner Mike Vernal, who actually
started his career at Microsoft, just

534
00:30:18,000 --> 00:30:21,157
wrote an essay where one of the big
takeaways is it's an age where you can

535
00:30:21,240 --> 00:30:25,597
be much more ambitious and you need to be
given the pace of the environment and

536
00:30:25,680 --> 00:30:28,157
how quickly actually users and companies

537
00:30:28,240 --> 00:30:30,357
are open to adopting new technologies.

538
00:30:30,440 --> 00:30:34,957
Um how do you think about I feel silly
asking this of somebody running a, you

539
00:30:35,040 --> 00:30:37,957
know, trillion-dollar-plus company
already, but how do you think about how

540
00:30:38,040 --> 00:30:40,557
Microsoft can be more ambitious now?

541
00:30:40,640 --> 00:30:44,637
>> It's a great question. Um I think um

542
00:30:44,720 --> 00:30:46,997
I think the the thing in these type of

543
00:30:47,080 --> 00:30:48,837
transitions

544
00:30:48,920 --> 00:30:53,357
is to have a conceptual model

545
00:30:53,440 --> 00:30:55,677
of how

546
00:30:55,760 --> 00:30:58,637
work can change

547
00:30:58,720 --> 00:31:01,877
to go after outcomes that you could

548
00:31:01,960 --> 00:31:06,637
hardly imagine previously, right?
In fact, Kevin Scott has this nice line,

549
00:31:06,720 --> 00:31:10,837
right? Which is um when you
can make the impossible like

550
00:31:10,920 --> 00:31:13,317
when you're making hard things easier

551
00:31:13,400 --> 00:31:18,197
that's sort of one point of leverage
but true ambition is about making the

552
00:31:18,280 --> 00:31:21,437
impossible possible. So

553
00:31:21,520 --> 00:31:24,437
now the thing that is missing a little

554
00:31:24,520 --> 00:31:26,597
bit in all of our organizations is what

555
00:31:26,680 --> 00:31:30,117
is that new conceptual model of what can

556
00:31:30,200 --> 00:31:33,717
we build? What was impossible
and what can we build?

557
00:31:33,800 --> 00:31:37,357
And I'll give you one example of this,
right? Which is I take great inspiration

558
00:31:37,440 --> 00:31:41,597
from sort of the people who were
managing the Azure net network.

559
00:31:41,680 --> 00:31:44,717
And they came to the This
was from even last year.

560
00:31:44,800 --> 00:31:48,437
You know, we were scaling. You saw that I
I talked about sort of how we built in

561
00:31:48,520 --> 00:31:53,717
the last 15 months more Azure capacity
than we built in the first 15 years. I

562
00:31:53,800 --> 00:31:56,157
mean, it's crazy. Right?
It's pretty wild. And it's the

563
00:31:56,240 --> 00:31:59,557
same team. So they saw that and they
said, "Bob, this just ain't going to

564
00:31:59,640 --> 00:32:02,877
work if we don't
reconceptualize our work."

565
00:32:02,960 --> 00:32:05,597
So they built Essentially, they said,

566
00:32:05,680 --> 00:32:07,997
"Our job is not to do Azure networking.

567
00:32:08,080 --> 00:32:10,477
Our job is to build the agentic system

568
00:32:10,560 --> 00:32:12,557
does that does Azure networking." Right?

569
00:32:12,640 --> 00:32:15,637
These are the folks managing the 500

570
00:32:15,720 --> 00:32:19,317
plus fiber operators managing the van,

571
00:32:19,400 --> 00:32:23,477
right? All over. And fiber operations
ultimately is a physical operation.

572
00:32:23,560 --> 00:32:27,357
Things get cut. Things get you know,
have to be repaired. You know, we have

573
00:32:27,440 --> 00:32:29,437
fancy words called devops and so on.

574
00:32:29,520 --> 00:32:33,397
Basically, emails are coming in and you
got to go respond to them, take care of

575
00:32:33,480 --> 00:32:35,557
it. So they built this agentic system.

576
00:32:35,640 --> 00:32:39,037
They even have a character for it.
It's called Miles and it sort of does all

577
00:32:39,120 --> 00:32:42,397
this stuff. Right? They started sort of

578
00:32:42,480 --> 00:32:46,237
screaming for more tokens and so on.
And so they were saying, "Look, we don't

579
00:32:46,320 --> 00:32:47,917
need head count. We need tokens in order

580
00:32:48,000 --> 00:32:50,837
to be able to manage our operation."

581
00:32:50,920 --> 00:32:53,557
That reconceptualization

582
00:32:53,640 --> 00:32:55,997
of what their work is, right? They They

583
00:32:56,080 --> 00:33:00,757
basically took their work and made it
meta. Right? That meta work is now their

584
00:33:00,840 --> 00:33:03,957
new work. >> Mhm. >> Right?
In the '80s, if somebody had come

585
00:33:04,040 --> 00:33:07,677
to us and said, "4 billion people are
going to get up in the morning and start

586
00:33:07,760 --> 00:33:12,877
typing." My model would have been,
"We need 4 billion typists." But we're not

587
00:33:12,960 --> 00:33:16,757
doing typing. We're doing knowledge work.
So that to me, I think, is it,

588
00:33:16,840 --> 00:33:20,637
right? Which is whether it's Microsoft
or whether it's any organization is to

589
00:33:20,720 --> 00:33:23,557
give ourselves permission to do new

590
00:33:23,640 --> 00:33:27,637
types of meta cognition, meta work using

591
00:33:27,720 --> 00:33:31,757
these new tools to change
the outputs that matter,

592
00:33:31,840 --> 00:33:35,637
uh and then really make the impossible
possible. So completing that dot or that

593
00:33:35,720 --> 00:33:40,117
that connective tissue across those,
I think, is where a lot of the enterprise

594
00:33:40,200 --> 00:33:43,637
value will get created.
>> Can we talk about the data centers?

595
00:33:43,720 --> 00:33:48,677
>> Yeah, please ask. >> Oh, okay.
Well, we This leads nicely into the data

596
00:33:48,760 --> 00:33:52,157
center buildout. I always think just I'm
just impressed with the sheer scale of

597
00:33:52,240 --> 00:33:56,237
the buildout from Microsoft but also
everyone else that this is redefining

598
00:33:56,320 --> 00:33:58,637
what it means to be a hyperscaler. And I

599
00:33:58,720 --> 00:34:03,597
just feel like that that that is
unprecedented scale on finances,

600
00:34:03,680 --> 00:34:06,957
on the way you run the company,
but also the communities that are that are

601
00:34:07,040 --> 00:34:09,637
impacted. Um then just
talk a bit more about what

602
00:34:09,720 --> 00:34:11,317
you're seeing on the ground.
Like when you visit your

603
00:34:11,400 --> 00:34:15,957
>> Yeah, I think there are two aspects
of it. Obviously, the the buildout is

604
00:34:16,040 --> 00:34:20,797
extraordinary. You know,
nothing like this has happened

605
00:34:20,880 --> 00:34:24,717
and it's great to be a one of the
participants in it. Uh but you brought

606
00:34:24,800 --> 00:34:29,797
up the other part, right? I think
at this point it's clear that unless we as

607
00:34:29,880 --> 00:34:32,197
an industry uh

608
00:34:32,280 --> 00:34:36,437
are very principled about ensuring that

609
00:34:36,520 --> 00:34:38,357
the benefits of all the stuff we're

610
00:34:38,440 --> 00:34:41,997
talking about are felt in real ways

611
00:34:42,080 --> 00:34:43,797
at the community level, right? Because

612
00:34:43,880 --> 00:34:47,477
this is not just a a campaign.

613
00:34:47,560 --> 00:34:52,157
Right, it has to be real where people
are saying, "Look, this is not changing

614
00:34:52,240 --> 00:34:56,917
the prices on energy for me." In fact,
if anything, it's bringing down prices

615
00:34:57,000 --> 00:35:00,237
because long-term there's going to be
a better grid. There's going to be more

616
00:35:00,320 --> 00:35:05,077
energy. Water consumption is in fact
not sort of in fact water is being

617
00:35:05,160 --> 00:35:06,997
replenished, right? You got to really,

618
00:35:07,080 --> 00:35:09,797
you know, educate folks on truly what's

619
00:35:09,880 --> 00:35:14,397
happening the the close-loop systems
we're building. We have to invest in the

620
00:35:14,480 --> 00:35:18,277
training, the jobs, the tax base.
In fact, the least talked about stuff is

621
00:35:18,360 --> 00:35:20,757
the amount of jobs that get created

622
00:35:20,840 --> 00:35:23,677
during construction, after construction,

623
00:35:23,760 --> 00:35:27,837
what's the tax base that's there in the
community. And and all this has to be

624
00:35:27,920 --> 00:35:31,277
real. And and if that is the case, then we

625
00:35:31,360 --> 00:35:34,877
will have permission. If it is not, we
won't have permission. It's as simple as

626
00:35:34,960 --> 00:35:38,117
that, right? Which is we we I
think we have to take it as an

627
00:35:38,200 --> 00:35:41,997
industry pretty seriously.
I think it's good for communities to be

628
00:35:42,080 --> 00:35:44,877
skeptical, ask the hard questions for us

629
00:35:44,960 --> 00:35:47,837
to do the hard work, earn that.

630
00:35:47,920 --> 00:35:50,797
But at the end of the day, if this if we

631
00:35:50,880 --> 00:35:55,077
can really be the I've always
felt like in human history,

632
00:35:55,160 --> 00:35:57,517
if you use a lot of energy, but also

633
00:35:57,600 --> 00:36:00,357
create a lot of value for society,

634
00:36:00,440 --> 00:36:04,757
the story has been fantastic. If you
don't do that, it's not been that great.

635
00:36:04,840 --> 00:36:09,237
And this time around I'm a firm believer
that ultimately, if you do have a token

636
00:36:09,320 --> 00:36:14,077
economy that drives productivity,
that drives economic growth, that drives

637
00:36:14,160 --> 00:36:17,637
broad-spread, you know, participation,

638
00:36:17,720 --> 00:36:22,117
better health outcomes,
then I think we will be in a great

639
00:36:22,200 --> 00:36:25,957
place. And that's at least what
we all have to be focused on.

640
00:36:26,040 --> 00:36:29,437
>> Yeah, it makes me think actually that
with all these initiatives that you're

641
00:36:29,520 --> 00:36:33,997
doing, might be easier to see ROI in the
communities first before in an enterprise.

642
00:36:34,080 --> 00:36:36,157
>> Yeah. >> [laughter] >> I I mean,
I think both sides. In fact,

643
00:36:36,240 --> 00:36:40,477
it comes back together. It has to be
the people in the communities are going to

644
00:36:40,560 --> 00:36:45,557
be employed, are going to be participants
uh in the real economy, right? That's I

645
00:36:45,640 --> 00:36:47,357
think the question is like if we if the

646
00:36:47,440 --> 00:36:50,637
broad economy is doing well and the

647
00:36:50,720 --> 00:36:53,197
communities are doing well, the dots get

648
00:36:53,280 --> 00:36:58,077
connected. It's sort of the market
forces are such that we will connect the

649
00:36:58,160 --> 00:37:00,757
dots. And that I think is it. Like you
ought to be able to see the evidence.

650
00:37:00,840 --> 00:37:05,917
You can't be about any one company.
Uh but it has to be broad economic growth

651
00:37:06,000 --> 00:37:08,597
and broad you know, community permission.

652
00:37:08,680 --> 00:37:12,357
>> Yeah. What's the biggest
mistake you've made about currently

653
00:37:12,440 --> 00:37:17,477
or whatever you most updated your personal
models on regarding societal impact of AI?

654
00:37:17,560 --> 00:37:21,357
>> So, you're saying what's the the >>
What have you updated most on in terms

655
00:37:21,440 --> 00:37:24,877
of societal impact of AI? >> I think the

656
00:37:24,960 --> 00:37:28,877
um the the most uh

657
00:37:28,960 --> 00:37:33,197
critical thing is the first question we
even started with, which is we need to

658
00:37:33,280 --> 00:37:35,037
tell

659
00:37:35,120 --> 00:37:38,117
the story and make it real

660
00:37:38,200 --> 00:37:42,757
that everybody has a real shot to

661
00:37:42,840 --> 00:37:46,117
participate as a first-class participant

662
00:37:46,200 --> 00:37:48,917
in this new economy. Right? That's kind

663
00:37:49,000 --> 00:37:52,437
of I think in the next 12 months, 18

664
00:37:52,520 --> 00:37:55,197
months, we need a way for people to say,

665
00:37:55,280 --> 00:37:57,397
"Oh, wow, I get it." Right? There's

666
00:37:57,480 --> 00:38:00,197
going to be tremendous capability,

667
00:38:00,280 --> 00:38:05,397
tremendous amount of infrastructure,
but I can see what is going to happen

668
00:38:05,480 --> 00:38:06,957
whether it's the benefits like health

669
00:38:07,040 --> 00:38:09,717
outcomes or my ability to create a

670
00:38:09,800 --> 00:38:13,677
startup or my ability to run my local

671
00:38:13,760 --> 00:38:16,957
sort of uh store more efficiently, it's

672
00:38:17,040 --> 00:38:19,877
just happening and I see that uh benefit

673
00:38:19,960 --> 00:38:22,597
myself. Right? That to me

674
00:38:22,680 --> 00:38:26,917
you know, earning that permission in a
path-dependent way, we can't wait. See,

675
00:38:27,000 --> 00:38:28,877
the one thing you learn I've now learned

676
00:38:28,960 --> 00:38:31,477
is I think the world is going to be way

677
00:38:31,560 --> 00:38:35,157
skeptical of tech and tech companies

678
00:38:35,240 --> 00:38:39,557
that say, "Trust us. We've got it.
The future is going to be

679
00:38:39,640 --> 00:38:40,797
glorious."

680
00:38:40,880 --> 00:38:45,437
Uh you kind of have to deliver tangible

681
00:38:45,520 --> 00:38:50,517
benefits. Um And but frankly,
politicians winning

682
00:38:50,600 --> 00:38:54,837
elections uh because they
have advocated for that.

683
00:38:54,920 --> 00:38:59,917
That will be at least
my adjustment because without it um

684
00:39:00,000 --> 00:39:02,997
thinking that somehow because it's too
important this time around. It's too

685
00:39:03,080 --> 00:39:05,957
much of the economy
for it not to be the case.

686
00:39:06,040 --> 00:39:08,597
>> So, one very simple framework I have

687
00:39:08,680 --> 00:39:11,117
for, you know, what are what is going to

688
00:39:11,200 --> 00:39:14,397
be the broad benefit of AI um

689
00:39:14,480 --> 00:39:18,717
beyond the communities just working
in technology uh our sort of wealth

690
00:39:18,800 --> 00:39:22,117
creation is going to happen in a ton
of different companies, startups and large

691
00:39:22,200 --> 00:39:25,797
companies. Then you have healthcare.
Uh you you had amazing demos today. There

692
00:39:25,880 --> 00:39:30,317
are companies like Open Evidence.
I think that is happening. Um education

693
00:39:30,400 --> 00:39:34,237
seems like another one that's an obvious
good where we haven't seen as much

694
00:39:34,320 --> 00:39:37,757
impact as I'd expect. Do you have
a hypothesis on why that might be or if

695
00:39:37,840 --> 00:39:39,277
it'll come? >> Yeah,
I mean I think this is where

696
00:39:39,360 --> 00:39:42,197
again, how we think about education, how

697
00:39:42,280 --> 00:39:46,837
you know, recently I met with uh
the founders of Alpha School and learned a

698
00:39:46,920 --> 00:39:51,117
lot about what they were going and going
about it. It is fascinating to listen

699
00:39:51,200 --> 00:39:55,717
uh to how to even rethink uh what
is education really look like because I

700
00:39:55,800 --> 00:39:58,917
think it's actually very important.
Uh and I'm not saying anything

701
00:39:59,000 --> 00:40:01,877
traditionally being done is less
important, right? I was even looking at

702
00:40:01,960 --> 00:40:04,557
the It's fascinating to see I forget to

703
00:40:04,640 --> 00:40:07,437
which Stanford class it was uh the the

704
00:40:07,520 --> 00:40:10,637
Asian guidelines for CS something. Uh

705
00:40:10,720 --> 00:40:13,397
because you still need people to learn.

706
00:40:13,480 --> 00:40:16,517
Uh like it is an interesting AI class
that they were making sure people were

707
00:40:16,600 --> 00:40:20,317
learning how to apply softmax
appropriately versus saying, "Hey, fix

708
00:40:20,400 --> 00:40:24,357
my training run." Uh so,
I think learning concepts is

709
00:40:24,440 --> 00:40:26,677
important. It's going to be a critical.

710
00:40:26,760 --> 00:40:29,837
But, the way we create the incentives,

711
00:40:29,920 --> 00:40:34,077
what are the credentials, how we
value those credentials, what is the

712
00:40:34,160 --> 00:40:35,837
employment opportunity for those

713
00:40:35,920 --> 00:40:37,717
credentials? So, I think that there is a

714
00:40:37,800 --> 00:40:41,197
complete change that has to happen uh

715
00:40:41,280 --> 00:40:44,237
given the way to get to information, way

716
00:40:44,320 --> 00:40:48,397
to educate yourself, way to continuously
keep yourself updated has changed so

717
00:40:48,480 --> 00:40:51,237
much. So, I think interestingly enough

718
00:40:51,320 --> 00:40:54,917
maybe the next big startup and success

719
00:40:55,000 --> 00:40:59,677
story could be someone
who builds a new university

720
00:40:59,760 --> 00:41:01,637
um or a new um

721
00:41:01,720 --> 00:41:04,677
pedagogy even of how to get someone to

722
00:41:04,760 --> 00:41:09,357
go through a curriculum and find
economic opportunity uh that's highly

723
00:41:09,440 --> 00:41:12,077
valuable. >> Well,
that has felt uh perhaps

724
00:41:12,160 --> 00:41:14,957
impossible for a long time, but it's
a great note to end on and something that

725
00:41:15,040 --> 00:41:17,037
might be possible. Yeah. Thank you, Sayan.

726
00:41:17,120 --> 00:41:20,427
>> Thank you so much. Thank you.
I appreciate it. Thank you all.

727
00:41:20,510 --> 00:41:22,530
>> [music]

728
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