Konstantin Kisin

They're great at just, like, I would have to hire, you know, the ancient Greeks would hire one-on-one tutors for...

for their pupils, and this is how you got Alexander being tutored by Aristotle.

And there's something powerful about this way of learning, one-on-one, where you can just directly ask questions and learn.

And so they're amazing at just teaching you stuff, because you get this one-on-one tutor that notices your confusion as soon as you have it.

You can really probe at your understanding in different ways.

But I take your point that some of the models are not there yet on a lot of these kinds of biases that they have.

Yeah.

Maybe one way to approach this question is to think about

At a very basic level, a system that is an AGI should be able to do anything that a human does.

Now, I want to emphasize that current AIs are nowhere close to this.

You and I can say, we can do physical work.

We can work in a factory, we can go mow the lawn, we can pick up this cup.

Robots are not good enough to do that yet.

So the fact that robotics is not there yet already means that we're far from that big definition of AGI.

Wait, robots can't pick up a cup?

They can, but they have to... My understanding is that they have to be trained in specific environments where they'll have seen, this is what this house looks like, and I need a specific kind of cup that I'm dexterous enough to pick up.

But if you replace this with one that's more circular and is tougher to grip...

You and I don't need to have seen that house a hundred times to then just go in and pick it up.

The robot just needs a tremendous amount of data to be flexible in these ways, or it's not flexible in those ways.

So being AGI would be able to be able to learn as fast as humans, not just have that distilled knowledge.