It is not "scientific" in the sense that it does not prove its claims. But it's not "pseudo-scientific" either because it doesn't pretend it's proving claims. I

It is not "scientific" in the sense that it does not prove its claims. But it's not "pseudo-scientific" either because it doesn't pretend it's proving claims. It's more like a book of interesting ideas from a smart guy written for a general audience. It's different from most AI in that it's very focused on drawing inspiration from neurobiology, while still being written from a "computer guy" perspective. Here's an excerpt that might give you an idea of what it's like. It's in support of one of his key points, that many current AI methods ignore the role of change over time, whereas in your brain it's crucial. "You know the alphabet. Try saying it backward. You can't because you don't usually experience it backward. Your memory of the alphabet is a sequence of patterns. It isn't something stored or recalled in an instant or in an arbitrary order. The same thing does for the days of the week, the months of the year, your phone number, and countless other things. "Your memory for songs is a great example of temporal sequences in memory. Think of a tune you know. I like to use 'Somewhere over the Rainbow.' You cannot imagine the entire song at once, only in sequence. You can start at the beginning or with the chorus, and then you play through it, filling in the notes one after another. You can't recall the song backward, just as you can't recall it all at once. You were first exposed to 'Somewhere over the Rainbow' as it played through time, and you can only recall it in the same way you learned it." Other interesting discussions are around the role of feedback and hierarchy in the brain's structure. I recommend this book to anyone who's a good programmer with some interest in AI.