10 years ago, cheap GPUs were used to train lots of units using backpropagation. Nowadays, it's not so clear why we need such a large number of layers in the first place. And was that simply down to the give it more data? And it had enough neurons, enough computational depth, is it? What was it, David, that really was the step-tage?
In our last episode we talked all about intelligence, specifically about what made us intelligent. In this episode we jump into artificial intelligence, and we're joined again by David Krakauer, President and William H. Miller Professor of Complex Systems at the Santa Fe Institute.
This episode was recorded before the release of GPT-4, so David doesn't mention it specifically, but he does take us through the history of artificial intelligence, from Alan Turing, all the way to machine learning and neural networks. And he's going to ask the question: Are we really building something that's intelligent, or are we just building mimics and parrots?
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