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I don't think "snake oil" is the right paradigm here. In ML/AI, lots of honest researchers are wrong; being a scientist who's wrong doesn't make you a criminal.

That said: Hawkins' principles are very different both from what the brain does, and from what the state of the art in machine learning does. My impression is that HTM's attempt to be too general and assume too little about the problem.

For vision in particular, most successful computer vision algorithms (as well as what we know about the visual cortex's mechanisms) make extensive use of information related to the fact that the image is an image. That is: edges are probably more likely to be continuous than broken; locally constant curvature is more likely than not; textures and colors usually continue over the surface of an object; objects occlude other objects; etc. Brains and effective computer vision algorithms hard-code a lot of information about the nature of the problem they're solving. Hawkins wants to bypass that, and I think it's probably too ambitious an aspiration.

Then again, if he makes it, more power to him.

I don't think we should be prejudiced against someone who comes from the tech industry and wrote a popular book. It's certainly not "snake oil" -- it seems to be a good-faith attempt to solve an important problem. I think the odds are against it working, but that's not a moral condemnation.




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