I think it’s a great book and anyone interested in the brain at a well informed layperson level would probably enjoy it and learn a lot from it.
Hawkins makes a good case for a common cortical algorithm—the studies involving ferrets whose visual nerves were connected to the audio centres and who learned to see are one compelling piece of evidence. He makes some plausible arguments that he has identified one key part of the algorithm—hierarchical predictive models—and he relates it in some detail to cortical micro-architecture. It is also quite interesting how motor control can be seen as a form of predictive algorithm (though frustratingly this is left at the hand-waving level and I found it surprisingly hard to convert this insight into code!).
His key insight is that we learn by recognizing temporal patterns, and that the temporal nature of our learning is central. and I suspect this has a lot of truth to it and remains under-appreciated.
There are clear gaps that he kind of glosses over e.g. how neuronal networks produce higher level mental processes like logical thought. So it is not perfect and is not a complete model of the brain. I would definitely read his new book when it comes out.
It is also quite interesting how motor control can be seen as a form of predictive algorithm (though frustratingly this is left at the hand-waving level and I found it surprisingly hard to convert this insight into code!).
I think it’s a great book and anyone interested in the brain at a well informed layperson level would probably enjoy it and learn a lot from it.
Hawkins makes a good case for a common cortical algorithm—the studies involving ferrets whose visual nerves were connected to the audio centres and who learned to see are one compelling piece of evidence. He makes some plausible arguments that he has identified one key part of the algorithm—hierarchical predictive models—and he relates it in some detail to cortical micro-architecture. It is also quite interesting how motor control can be seen as a form of predictive algorithm (though frustratingly this is left at the hand-waving level and I found it surprisingly hard to convert this insight into code!).
His key insight is that we learn by recognizing temporal patterns, and that the temporal nature of our learning is central. and I suspect this has a lot of truth to it and remains under-appreciated.
There are clear gaps that he kind of glosses over e.g. how neuronal networks produce higher level mental processes like logical thought. So it is not perfect and is not a complete model of the brain. I would definitely read his new book when it comes out.
I’d be interested if you think my post Predictive Coding and Motor Control is helpful for filling in that gap.