Michael Reiss' Genius Theory on the Brain

Dr. Reiss, author of (perhaps) the strongest Go program at the moment (Go++) got inspired by Jeff Hawkins' work as well, and came up with the an Earth-shattering theory (at least for me):

http://www.reiss.demon.co.uk/neural/neural.htm

Mick postulates: "If this theory was proven correct then it may suggest that the most common task being performed by neurons in real brains is to continuously attempt to learn to predict the activities of other neurons but based on different inputs."

Bone For Microsoft

The boffins at Microsoft appear to be stuck with their Bayesian network after they copied it from me, and they have been trying to pick my brain using nefarious means.

Here-ya-go:

Interview with Jeff Hawkins on his book "On Intelligence".

Paper by Jeff Hawkins on Hierarchical Temporal Memory.

Powerpoint presentation for his talk at IBM's Almaden Institute.

..and the lecture itself:




HTM's are currently perhaps the best way to make a Go program using a neural network. A game of Go is a temporal "world" with "causes" (chains, order-liberties, patterns etc.) and a HTM is able to make predictions (finding good moves, in HTM-terms: "beliefs"). It learns pattern sequences over time and is much more sophisticated and powerful than any other "ordinary" ANN. So it would be a logical evolutionary step for Microsoft's Bayesian pattern network.

Finally, a link to his book.