Dr. Jeff Beck

Pure empirical inquiry does run risks like that, but I think that that's not the biggest issue.

I think what we need to do is we just need to have a nice, concise framework for saying, oh, look.

I'll give you an example.

We had this problem that popped up a while back.

A gentleman we were talking to is, you've got these robots, and the robots see something they've never seen before.

And, you know, so a robot is like running around.

It comes across like a beach ball.

I've never seen a beach ball in its entire life.

And what you'd like is you'd like the robot to know how to figure out that it's a beach ball and to figure out what its properties are.

And if you tell the robot, like, like if you see something new, just stop.

But you're kind of then that's that's no good.

What you really want to do is you want to figure out a relatively non-invasive procedure for the robot to do what a child would do.

What does a kid do when they see a beach ball?

They run up and they poke it and they say, oh, right, yeah, and then it moved.

It actually experiments with its environment for the purposes of identifying the properties of the objects that exist in it.

Now, I do think we probably want to test this out virtually before it's deployed in the real world because you never know, it might very well be that the optimal experiment is to run up and kick it as hard as you possibly can.

And we certainly want to avoid that.

But something along those lines, a robot that is able to test the theories that it has about how things work in an online way and learn from those results in an online way is definitely part of the goal.

Right.

I mean, offloading your thinking onto a machine, which is something that AI allows, is potentially a big problem.