David Eagleman

So that's the difference is that a live wire child can figure out all kinds of things in the world.

AI can only do these very basic things right now.

I mean, eventually, eventually we might.

Certainly not right now.

I mean, you can just, you know, turn the computer off.

I mean, there's a, yeah, it's still doing what it is told as in, hey, I want you to absorb a billion pictures of cows and horses and then get really good at being able to determine the difference between these.

So what it does is it trains on a training set of, let's say, a billion images where it's labeled, okay, this is a cow, this is a horse, this is a cow.

And then it's extraordinarily good, better than human at discriminating cows from horses.

But in real life, we don't have training sets with billions of examples.

We don't have that luxury.

You have to learn everything on the fly.

All animals do have to learn the world on the fly and get good at it.

And this is where we outshine AI by a long way.

It's going to be pretty different.

I mean, for one thing, we'll be much better at actually being able to measure what's going on in the brain.

So for example, right now, our best technology is called functional magnetic resonance imaging, fMRI.

You stick somebody in the brain scanner and you can tell

sort of crudely where the activity is happening in the brain.

And, you know, we make all kinds of theories and we do, you know, I've written hundreds of papers on this topic, but the fact is it's a crude technology.

What we really need to understand how the brain is working is to be able to see the activity in each one of the 86 billion neurons in real time.