Reading about those studies is pretty interesting. Usually the neurons do most of the heavy lifting, adapting to the I/O chip input and output. It’s almost an admittance that we don’t yet fully understand what we are dealing with, when we try to interface with our rudimentary tech.

Dear lord, I found Elon’s Lemmy account.

Notably, computer science is not neurology. Neither is equipped to meddle in the other’s field. If brains were just very fast and powerful computers, then neuroscientist should be able to work with computers and engineers on brains. But they are not equivalent. Consciousness, intelligence, memory, world modeling, motor control and input consolidation are way more complex than just faster computing. And Turing completeness is irrelevant. The brain is not a Turing machine. It does not process tokens one at a time. Turing completeness is a technology term, it shares with Turing machines the name alone, as Turing’s philosophical argument was not meant to be a test or guarantee of anything. Complete misuse of the concept.

The human brain is not a computer. It was a fun simile to make in the 80s when computers rose in popularity. It stuck in popular culture, but time and time again neuroscientists and psychologists have found that it is a poor metaphor. The more we know about the brain the less it looks like a computer. Pattern recognition is barely a tiny fraction of what the human brain does, not even the most important function, and computers suck at it. No computer is anywhere close to do what a human brain can do in many different ways.