I read 'On Intelligence' a while back (Hawkins' earlier book), and it's had a lasting impression on me. What I found most interesting from this book was that:

I read 'On Intelligence' a while back (Hawkins' earlier book), and it's had a lasting impression on me. What I found most interesting from this book was that: - Intelligence, in essence, is hierarchal prediction. - Agents' actions are a means to minimize prediction error. - Suprisal, i.e. information that was not predicted correctly, is the information sent between neurons. - All neocortical tissue is fairly uniform; the neocortex basically wraps the lower meninges, which act as device drivers for the body. I have a long-running bet with myself (before GPT long-running, fwiw) that when general models of intelligence do arise, they will be autoregressive unsupervised prediction models. Btw, this general topic 'A Predictive model of Intelligence', reminds me of the SSC post 'Surfing Uncertainty' (https://slatestarcodex.com/2017/09/05/book-review-surfing-uncertainty/ https://slatestarcodex.com/2017/09/05/book-review-surfing-un...)