I’ve just finished reading Ray Kurzweil’s new book, “How to Create a Mind”. In it I found a wealth of good information, especially in the form of thought experiments.
Kurzweil’s latest work ties in a mass of data about the brain, pattern recognition, and his own experiences, creating a sort of roadmap to creating strong AI. The account is clearly written and concepts are well explained. He includes some interesting research, perhaps most intriguing are the experiments with split-brain patients, illuminating more subtle aspects of consciousness.
The grand theory presented in the book, the Pattern Recognition Theory of Mind, has some nice features. It promises completely asynchronous processing to emulate the brain’s same ability, as well as uniformity of elements. This uniformity is part of what enables arbitrary regions to be configured to process different types of information, given sufficient exposure to their respective type of data.
Kurzweil’s formulation of hierarchical pattern recognition seems to stem almost exclusively from Hidden Markov Models, specifically of the hierarchical variety. While these models are indeed useful for many applications, missing throughout the book is an explanation of any explicit role of time. In Jeff Hawkins’ “On Intelligence”, temporal patterns take a central role in the theories presented, distinguishing it from most traditional machine learning designs. By contrast, Kurzweil’s PRTM (Pattern Recognition Theory of Mind) does not take time directly into account. We’re left to assume that temporal patterns are implicit in the changing of spatial patterns, though some definite remark on that would have been helpful.
Most of the book’s real value does not come from detailed algorithmics or mathematical ingenuity, but again from the deep and illuminating thought experiments presented. Kurzweil has a way of exposing subtle relationships in concepts that no other author can, save Marvin Minsky (another personal favorite, who was a mentor of Kurzweil’s). The book delivers a powerfully enlightening look into the intricate world of pattern recognition, and presents fascinating a viable avenues of exploration for making intelligent machines. Anyone who is interested in the brain, AI, robotics, or just technology in general should definitely give this a read.