Is ChatGPT Conscious? A Pioneer of AI Explains | Dr. Terry Sejnowski

You see that fly? It can fly. It can find food. It could reproduce. It's doing that with a 100,000 neurons. You have a supercomputer, cost you a $100,000,000. It can't fly. It can't see, and it's not gonna reproduce. Yeah. What's wrong with this picture? Dead silence. Doctor Terry Sichnowski is a professor at the Salk Institute and a global leader in understanding how the brain learns and remembers. A brilliant mind helping us learn how to learn smarter, deeper, and for life. Do humans understand in the same way that these massive models understand? Different people understand things differently. Physicist understands composition of things much better than a person who just picks things up. But but a carpenter understands wood perhaps better than a physicist. In the book, you talk about nature inspired directions for developing. Can you talk about what you mean by nature inspired? Well, okay. So, these large language models are completely helpless by themselves. Yep. You know, they depend completely on us. They depend on us for the power to give them inputs for, you know, improving them and so forth. I mean, you know, they're they're really cahoots. I know who you are. A lot of people know who you are. I saw you referenced in, the Jeff Hinton announcement, which, of course, I would like you to have been included, but but, because Boltzmann machines played, such a critical role in that development. So can you give listeners that are not familiar, have not seen our past episodes, a brief introduction of, your work and, your work, at the NeurIPS Foundation, and then, about your new book, which is what I really wanted to talk about. Well, yes. So, Craig, my background is in physics, PhD, theoretical physics from Princeton. And at that point, I realized that, you know, physics had reached these high such high levels that in order to make progress, you had to have an accelerator that was Yeah. You know, miles across or set up a satellite. And so I was very attracted to the brain Mhmm. Because it was just as mysterious as the universe. But it was something you could actually study, you know, in in the lab. And I I met Jeff at a small conference, you know, here actually in San Diego, that he organized on associate of memory back in '79. That was quite a while ago. And we just hit it off. I mean, it was clear that we both had the same goals, you know, to try to understand, you know, how the brain could possibly solve these difficult problems, number one. Number two, what was, you know, computational capabilities of of very large scale, network models, and it was in its infancy back then. And so, that you know, we we you know, John Hopfield was my thesis adviser, and and, one we ended up, generalizing his model by adding noise to it, of all things, you know, to heat …