David Eagleman

Essentially, these artificial neural networks took off from a very simplified version of the brain, which is, hey, look, you've got units and they're connected. And what if we can change the strength between these connections? And in a very short time, that has now become this thing that has read everything ever written on the planet and can give extraordinary answers.

But it's not yet the brain or anything like it. It's just taking the very first idea about the brain and running with it. What a large language model does not have is an internal model of the world. It's just acting as a statistical parrot. It's saying, okay, given these words, what is the next word most likely to be given everything that I've ever read on the planet?

But it's not yet the brain or anything like it. It's just taking the very first idea about the brain and running with it. What a large language model does not have is an internal model of the world. It's just acting as a statistical parrot. It's saying, okay, given these words, what is the next word most likely to be given everything that I've ever read on the planet?

But it's not yet the brain or anything like it. It's just taking the very first idea about the brain and running with it. What a large language model does not have is an internal model of the world. It's just acting as a statistical parrot. It's saying, okay, given these words, what is the next word most likely to be given everything that I've ever read on the planet?

And so it's really good at that, but it has no model of the world, no physical model. And so things that a six-year-old can answer, it is stuck on. Now, this is not a criticism of it in the sense that it can do all kinds of amazing stuff and it's going to change the world, but it's not the brain yet. And there's still plenty of work to be done to get something that actually acts like the brain.

And so it's really good at that, but it has no model of the world, no physical model. And so things that a six-year-old can answer, it is stuck on. Now, this is not a criticism of it in the sense that it can do all kinds of amazing stuff and it's going to change the world, but it's not the brain yet. And there's still plenty of work to be done to get something that actually acts like the brain.

And so it's really good at that, but it has no model of the world, no physical model. And so things that a six-year-old can answer, it is stuck on. Now, this is not a criticism of it in the sense that it can do all kinds of amazing stuff and it's going to change the world, but it's not the brain yet. And there's still plenty of work to be done to get something that actually acts like the brain.

I suspect so, because there are 8.2 billion of us who have this functioning in our brains. And as far as we can tell, we're just made of physical stuff. We're just very sophisticated algorithms. And it's just a matter of cracking what that algorithm is.

I suspect so, because there are 8.2 billion of us who have this functioning in our brains. And as far as we can tell, we're just made of physical stuff. We're just very sophisticated algorithms. And it's just a matter of cracking what that algorithm is.

I suspect so, because there are 8.2 billion of us who have this functioning in our brains. And as far as we can tell, we're just made of physical stuff. We're just very sophisticated algorithms. And it's just a matter of cracking what that algorithm is.

The big textbook that we have in our field is called Principles of Neuroscience, and it's about 900 pages. And it's not actually principles. It's just a data dump of all this crazy stuff we know. And in 100 years, I expect it'll be like 90 pages.

The big textbook that we have in our field is called Principles of Neuroscience, and it's about 900 pages. And it's not actually principles. It's just a data dump of all this crazy stuff we know. And in 100 years, I expect it'll be like 90 pages.

The big textbook that we have in our field is called Principles of Neuroscience, and it's about 900 pages. And it's not actually principles. It's just a data dump of all this crazy stuff we know. And in 100 years, I expect it'll be like 90 pages.

We'll have things where we put big theoretical frameworks together and we say, ah, okay, look, all this other stuff, these are just expressions of this basic principle that we have now figured out. Do you pay much attention to behavioral economics? Yes, I do. What do you think of it? Oh, it's great. And that's probably the direction that a lot of fields will go is how do humans actually behave?

We'll have things where we put big theoretical frameworks together and we say, ah, okay, look, all this other stuff, these are just expressions of this basic principle that we have now figured out. Do you pay much attention to behavioral economics? Yes, I do. What do you think of it? Oh, it's great. And that's probably the direction that a lot of fields will go is how do humans actually behave?

We'll have things where we put big theoretical frameworks together and we say, ah, okay, look, all this other stuff, these are just expressions of this basic principle that we have now figured out. Do you pay much attention to behavioral economics? Yes, I do. What do you think of it? Oh, it's great. And that's probably the direction that a lot of fields will go is how do humans actually behave?

One of the big things that I find most interesting about behavioral economics comes back to this issue about the team of rivals. When people measure in the brain how we actually make decisions about whatever, There are totally separable networks going on. Some networks care about the valuation of something, the price point.

One of the big things that I find most interesting about behavioral economics comes back to this issue about the team of rivals. When people measure in the brain how we actually make decisions about whatever, There are totally separable networks going on. Some networks care about the valuation of something, the price point.

One of the big things that I find most interesting about behavioral economics comes back to this issue about the team of rivals. When people measure in the brain how we actually make decisions about whatever, There are totally separable networks going on. Some networks care about the valuation of something, the price point.

You have totally other networks that care about the anticipated emotional experience about something. You have other networks that care about the social context, like what do my friends think about this? You have mechanisms that care about short-term gratification. You have other mechanisms that are thinking about the long-term, what kind of person do I want to be?