Dwarkesh

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1,722 appearances 5 recordings 1 series first heard Apr 2025 last heard 25 Nov

Dwarkesh’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 2 in all, peaking in Nov 2025 with 1.

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Dwarkesh Podcast · AI 2027: month-by-month model of intelligence explosion — Scott Alexander & Daniel Kokotajlo · 3 Apr 2025 podcast

It's more suited to humans.

But imagine that you have to make a business out of you and your hundred closest friends who you agree with on everything.

Maybe they're literally your identical twin.

They have never betrayed you ever and never will.

Like, I think this is just not that hard a problem.

So when I think of like the ways that they train AIs,

I think in our scenario at this point, there are two primary ways that they're doing it.

One of them is just continuing the next token prediction work.

So these AIs will have access to all human knowledge.

They will have read management books in some sense.

They're not starting blind.

There is going to be something like predict how Bill Gates would complete this next character or something like that.

And then there's the reinforcement learning in virtual environments.

So get a team of AIs to play some multiplayer game.

I don't think you would use one of the human ones because you would want something that was better suited for this task.

But just running them through these environments again and again, training on the successes, training against the failures, kind of combining those two kinds of things.

To me, it does not seem like the same kind of problem as inventing all human institutions from the Paleolithic onward.

It just seems like kind of applying those two things.

We have an estimate that about a year after the superintelligences start wanting robots, they're producing a million units of robots per month.

So I think that's pretty relevant because you have, I think it's Wright's Law, which is that your ability to improve efficiency on a process is proportional to doubling the amount of copies produced.

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