When people think of AGI, they imagine

what it would be like to have a personal

assistant who answers all their

questions and works 24/7. But that just

underestimates the real collective edge

AIs will have, which has nothing to do

with raw IQ, but rather with the fact

that they are

digital. Currently, firms are extremely

bottlenecked in hiring and training

people. But if your workers are AIs,

then you can copy them millions of times

with all their skills, judgment, and

tacet knowledge

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intact. This is a fundamentally

transformational change because for the

first time in history, you can just turn

capital into compute and compute into

labor. You can turn trillions of dollars

into the electricity, chips, and data

centers needed to sustain populations of

billions of digital

employees. Think about how limited a

CEO's knowledge is today. How much did

the real Steve Jobs really know about

what's happening across Apple's vast

empire? He gets filtered reports and

dashboards, attends key meetings, and

reads strategic summaries. But he can't

possibly absorb the full context of

every product launch, every customer

interaction, every technical decision

made across hundreds of teams. His

mental model of Apple is necessarily

incomplete. Now imagine Mega Steve, the

central AI that will direct our future

AI firm. Just as Tesla's full

self-driving AI model can learn from the

driving records of millions of drivers,

Mega Steve might learn from everything

seen by the millions of distilled Steve

Apparachics. Every customer

conversation, every engineering

decision, every market response. I think

it's hard to grapple with how different

this will be from human companies and

institutions. You're going to have this

blobs with millions of entities rapidly

coming into and going out of existence

who are each thinking at superhuman

speeds.

It will be a change in social

organization as big as was the

transition from hunter gatherer tribes

to a massive modern joint stock

corporations. The boundary between

different AI instances starts to blur.

Mega Steve will constantly be spawning

specialized distilled copies and

reabsorbing what they've learned on

their own. models will communicate

directly through latent representations,

similar to how the hundreds of different

layers in a neural network like GPT4

already

interact. Merging will be a step change

in how organizations can accumulate and

apply

knowledge. Humanity's great advantage

has been social learning, our ability to

pass knowledge across generations and

build upon it. But human social learning

has a terrible handicap. Biological

brains don't allow information to be

copypasted. So you need to spend years

and in many cases decades teaching

people what they need to know in order

to do their job. Or consider how

clustering talent in cities and top

firms produces such outsiz benefits

simply because it lowers the friction of

knowledge flow between individuals.

Future AI firms will accelerate this

cultural evolution with millions of

AGIs. Automated firms get so many more

opportunities to produce innovations and

improvements, whether from lucky

mistakes, deliberate experiments, denovo

inventions, or some

combination. Historical data going back

thousands of years suggests that

population size is the key input for how

fast your society comes up with more

ideas. AI firms will have population

sizes that are orders of magnitude

larger than today's biggest companies.

And each AI will be able to perfectly

mind meld with every other. AI firms

will look from the outside like a

unified intelligence that can instantly

propagate ideas across the organization,

preserving their full fidelity and

context. Every bit of tacid knowledge

from millions of copies gets perfectly

preserved, shared, and given due

consideration.

So what becomes expensive in this world?

Roles which justify massive amounts of

inference compute. The CEO function is

perhaps the clearest example. Would it

be worth it for Apple to spend $100

billion annually on inference compute

for Mega Steve? Sure. Just consider what

this buys you. Millions of subjective

hours of strategic planning, Monte Carlo

simulations of different five-year

trajectories, deep analysis of every

line of code and technical system, and

exhaustive scenario planning. The cost

to have an AI take a given role will

become just the amount of compute the AI

consumes. This will change our

understanding of which abilities are

scarce. Future AI firms won't be

constrained by what's rare or abundant

in human skill distributions. They can

optimize for whatever abilities are most

valuable. Want Steve Waznjak level

engineering talent? Cool. Once you've

got one, the marginal copy costs

pennies. Need a thousand worldclass

researchers? Just spin them up. The

limiting factor isn't finding or

training rare talent. It's just compute.

Imagine Mega Steve contemplating, hm,

how would the Federal Trade Commission

respond if we acquired eBay to challenge

Amazon? Let me simulate the next 3 years

of market dynamics.

Ah, I see the likely outcome. I have 5

minutes of data center time left. Let me

evaluate 1,000 alternative

strategies. The more valuable the

decisions, the more compute you'll want

to throw at them. A single strategic

insight from Mega Steve could be worth

billions. One of the coolest things

about this video is that we did not

shoot a single frame of video for it.

Every single visual that you see from

the photorealistic humans, the

claimation octopuses were all generated

by V2, which is Google's

state-of-the-art video generation model.

I wrote this essay a couple months ago,

and then I had this idea that we should

try to turn it into a video. And so, I

worked with this wonderful director,

Peter Salaba, who was able to use V2 to

turn all of these ideas into the kind of

video that would have previously taken

us a full team of cinematographers and

animators to make. For example, one of

the things I wanted to show is what an

AGI hive mind might look like. And so

Peter had this idea that you could have

a FPV drone fly through an antill that's

full of working ants. VO gave him a

bunch of tasteful candidates for this

and a bunch of other prompts that we

then stitched together into the Final

Cut. We literally could not have made a

video like this without VO. And now V2

is available in the Gemini app. You can

try it by going to gemini.google.com,

google.com, selecting it from the drop

down and typing your own idea into the

prompt bar. By the way, we made this

whole video with VO before we even

started chatting with Google. So, it was

especially exciting that we could then

have them as a sponsor. All right, back

to the

essay. The most profound difference

between AI firms and human firms will be

their evolvability. As Gwen Brandwin

observes, why do we not see exceptional

corporations clone themselves and take

over all market segments? Why don't

corporations evolve such that all

corporations or businesses are now the

hyperefficient descendants of a single

corporation while all other corporations

having gone extinct in bankruptcy or

been acquired? Why is it so hard for

corporations to keep their culture

intact and retain their youthful lean

efficiency? Or if avoiding aging is

impossible, why not copy themselves or

otherwise reproduce to create new

corporations like themselves?

Corporations certainly undergo selection

for kinds of fitness and do vary a lot.

The problem seems to be that

corporations cannot replicate

themselves. Corporations are made of

people, not interchangeable, easily

copied widgets or strands of DNA. The

corporation may not even be able to

replicate itself over time leading to

scleroticism and

aging. The scale of difference between

currently existing human firms and fully

automated firms will be like the gulf in

complexity between proaryotes and

ukarotes. Proarotic organisms such as

bacteria are relatively simple and have

remained structurally similar for over 3

billion years. In contrast, the

emergence of ukarotic cells which

possess more complex internal structures

like nuclei and organels enabled a

dramatic leap in biological complexity

and gave rise to all the other

astonishing organisms with trillions of

cells working together tight knits. This

evolvability is also the key difference

between AI and human firms. As Garn

points out, human firms simply cannot

replicate themselves effectively.

They're made of people, not code that

can be copied.

So would a fully automated company

simply become the last company standing?

Why would other firms even exist? Could

the first business to automate

everything just form a massive

conglomerate and take over the entire

economy? While internal planning can be

more efficient than market competition

in the short term, it needs to be

balanced by some slower but unbiased

external feedback. A company that grows

too large risks having its internal

goals drift away from market reality.

That said, the balance may shift as AI

systems improve. AI corporations will be

more software-like with perfect

replication of successful subdivisions

and faster feedback loops. And this

internal planning system needs to be

connected to some measure of real

success or

failure. And this is exactly what the

market provides.

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Hey, baby.

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