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This is: Jeff Hawkins on neuromorphic AGI within 20 years, published by Steven Byrnes on the LessWrong.
I just listened to AI podcast: Jeff Hawkins on the Thousand Brain Theory of Intelligence, and read some of the related papers. Jeff Hawkins is a theoretical neuroscientist; you may have heard of his 2004 book On Intelligence. Earlier, he had an illustrious career in EECS, including inventing the Palm Pilot. He now runs the company Numenta, which is dedicated to understanding how the human brain works (especially the neocortex), and using that knowledge to develop bio-inspired AI algorithms.
In no particular order, here are some highlights and commentary from the podcast and associated papers.
Every part of the neocortex is running the same algorithm
The neocortex is the outermost and most evolutionarily-recent layer of the mammalian brain. In humans, it is about the size and shape of a dinner napkin (maybe 1500cm²×3mm), and constitutes 75% of the entire brain. Jeff wants us to think of it like 150,000 side-by-side "cortical columns", each of which is a little 1mm²×3mm tube, although I don't think we're supposed to the "column" thing too literally (there's no sharp demarcation between neighboring columns).
When you look at a diagram of the brain, the neocortex has loads of different parts that do different things—motor, sensory, visual, language, cognition, planning, and more. But Jeff says that all 150,000 of these cortical columns are virtually identical! Not only do they each have the same types of neurons, but they're laid out into the same configuration and wiring and larger-scale structures. In other words, there seems to be "general-purpose neocortical tissue", and if you dump visual information into it, it does visual processing, and if you connect it to motor control pathways, it does motor control, etc. He said that this theory originated with Vernon Mountcastle in the 1970s, and is now widely (but not universally) accepted in neuroscience. The theory is supported both by examining different parts of the brain under the microscope, and also by experiments, e.g. the fact that congenitally blind people can use their visual cortex for non-visual things, and conversely he mentioned in passing some old experiment where a scientist attached the optic nerve of a lemur to a different part of the cortex and it was able to see (or something like that).
Anyway, if you accept that premise, then there is one type of computation that the neocortex does, and if we can figure it out, we'll understand everything from how the brain does visual processing to how Einstein's brain invented General Relativity.
To me, cortical uniformity seems slightly at odds with the wide variety of instincts we have, like intuitive physics, intuitive biology, language, and so on. Are those not implemented in the neocortex? Are they implemented as connections between (rather than within) cortical columns? Or what? This didn't come up in the podcast. (ETA: I tried to answer this question in my later post, Human instincts, Symbol grounding, and the blank-slate neocortex.)
(See also previous LW discussion at: The brain as a universal learning machine, 2015)
Grid cells and displacement cells
Background: Grid cells for maps in the hippocampus
Grid cells, discovered in 2005, help animals build mental maps of physical spaces. (Grid cells are just one piece of a complicated machinery, along with "place cells" and other things, more on which shortly.) Grid cells are not traditionally associated with the neocortex, but rather the entorhinal cortex and hippocampus. But Jeff says that there's some experimental evidence that they're also in the neocortex, and proposes that this is very important.
What are grid cells? Numenta has an educational video here. Here's my oversimplified 1D toy example (the modules can als...
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