Comment The Bayesian Bandwagon (Score 5, Interesting) 117
The problem with people like Kurzweil, Jeff Hawkins, the folks at the Singularity Institute and the rest of the AI community is that they have all jumped on the Bayesian bandwagon. This is not unlike the way they all jumped on the symbolic bandwagon in the last century only to be proven wrong forty years later. Do we have another half a century to waste, waiting for these guys to realize the error of their ways? Essentially there are two approaches to machine learning.
1) The Bayesian model assumes that events in the world are inherently uncertain and that the job of an intelligent system is to discover the probabilities.
2) The competing model, by contrast, assumes that events in the world are perfectly consistent and that the job of an intelligent system is to discover this perfection.
Luckily for the rest of humanity, a few people are beginning to realize the folly of the Bayesian mindset. When asked in a recent Cambridge Press interview, "What was the greatest challenge you have encountered in your research?", Judea Pearl, an Israeli computer scientist and an early champion of the Bayesian approach to AI, replied: "In retrospect, my greatest challenge was to break away from probabilistic thinking and accept, first, that people are not probability thinkers but cause-effect thinkers and, second, that causal thinking cannot be captured in the language of probability; it requires a formal language of its own."
Read The Myth of the Bayesian Brain for more, if you're interested.