The Impending Crash of the Bayesian BandwagonLast August, I wrote a series of posts titled, The Myth of the Bayesian Brain. I argued against the prevailing notion in the AI community that the brain uses some kind of Bayesian statistics to make decisions. I argued that, internally, the brain always assumes that the world is perfect even if its sensory space is inherently noisy. The brain does this bit of magic by filling in any missing information and ignoring irrelevant noise. This cleansing process is essential to reasoning and planning. At least one other researcher (to my knowledge), computer scientist Judea Pearl, has been saying the same thing. Well, a story out of Princeton University points to a new study that corroborates what I have been saying. Essentially, Princeton University researchers found that, when we make an error, the brain's decision making system is not at fault. The system is flawless. The fault is invariably due to faulty sensory information. Here's an excerpt:
Previous measurements of brain neurons have indicated that brain functions are inherently noisy. The Princeton research, however, separated sensory inputs from the internal mental process to show that the former can be noisy while the latter is remarkably reliable, said senior investigator Carlos Brody, a Princeton associate professor of molecular biology and the Princeton Neuroscience Institute (PNI), and a Howard Hughes Medical Institute Investigator.The "great surprise" of Carlos Brody and his team is understandable, given their training within the current Bayesian paradigm. But it's never too late to jump off that silly wagon. I am not one to laugh and say, "I told you so". But I did, didn't I?
"To our great surprise, the internal mental process was perfectly noiseless. All of the imperfections came from noise in the sensory processes," Brody said.
See Also:The Second Great AI Red Herring Chase
The Myth of the Bayesian Brain