Dwarkesh Patel

is in his view that you just have to imitate your elders in order to learn that skill because you can't think your way through how to hunt and kill and process a seal.

You have to just watch other people maybe make tweaks and adjustments.

And that's how cultural knowledge accumulates.

But the initial step of the cultural gain has to be imitation.

But maybe you think about it a different way.

I do think you make a very interesting point that continual learning is a capability that most mammals have.

I guess all mammals have.

So it's quite interesting that we have something that all mammals have, but our AI systems don't have, right?

Whereas maybe like the ability to understand math and solve difficult math problems depends on how you define math.

But like this is a capability our AIs have, but that almost no animal has.

And so it's quite interesting what ends up being difficult and what ends up being easy.

Perilics.

That's right.

For the era of experience to commence, we're going to need to train AIs in complex real-world environments.

But building effective RL environments is hard.

You can't just hire a software engineer and have them write a bunch of cookie-cutter validation tests.

Real-world domains are messy.

You need deep subject matter experts to get the data, the workflows, and all the subtle rules right.

When one of Labelbox's customers wanted to train an agent to shop online, Labelbox assembled a team with a ton of experienced engineering internet storefronts.

For example, the team built a product catalog that could be updated during the episode because most shopping sites have constantly changing state.