For me, that's the most important question in neuroscience.

How similar is the way the brain learns to how these large language models learn?

And at a very abstract level, I believe it's quite similar.

And now the good fight with Yasha Monk. My guest today is none other than Jeffrey Hinton.

Widely known as the godfather of AI, Jeffrey has invented some of the key architectural innovations

that have made the current AI boom possible.

For example, he was one of the people who figured out how to use the principle of back propagation

in such a way as to allow deep learning. He is also the winner of the 2024 Nobel Prize in physics for foundational

discoveries and inventions that enable machine learning with artificial neural networks. Well,

my agenda for this conversation was twofold. Firstly, for him to explain to us what that means.

What is machine learning with artificial neural networks?

And what exactly was his so important contribution to this field?

Building on the recent episode with David Bow, I think of this as my 101 and 102

of understanding AI. And Jeffrey is, I think, very clear in helping us think conceptually about

what this way of producing information and of enabling machines to think about the world actually

consistent. Well, the second part of a conversation may be of interest to you, even if you're not

that interested in the details of how AI works. We're asking all of the big questions. Is artificial

intelligence actually intelligent?

Is it going to take the jobs of a lot of people?

How should we think about the different kind of risks that are involved in AI?

Is it just about bad people doing things to us? or is it also about bad AI doing bad things to us?

And it's in the final part of a conversation, which is reserved for paying subscribers, that we really try to answer that final question.

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