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The human brain has always been compared to our most advanced technologies. It used to be compared to the telephone, then digital computers, and now to deep learning models. At least deep learning model has some merit because artificial neural networks are in part inspired by a very simple model of how our brain neurons work in a network, or rather how neuropsychologists would explain reinforcement learning to a computer scientist.

However this is a great simplification, and borders on an absurd reduction. You can model our brains using linear algebra, however that doesn’t mean our brains are linear algebra computer. There is a whole lot more going on than neurons receiving feedbacks from other neurons which adjusts the weight for subsequent firing. A lot of our behavior is actually inherited (I know I spent a whole week here on HN arguing with IQ advocates on the nuance of that statement), neurochemicals and hormones add a whole another level of statefulness not seen in artificial neural networks, the brains ability to make computations is actually pretty limited (especially next to a GPU). I mean, cordiseps exists, meaning a fungus can infect an organic system and control its behavior, there is 100% chance that some yet to be discovered viral and bacterial agents, not sharing any of our DNA—and certainly not “connected” to the “weight matrix”—are also influencing our behavior (just not as dramatically), and there is 100% chance they interact with our DNA also controlling our “innate” behavior.

What is going on in our brains can only be modeled using statistical ordering of semantic words and actions. The real world brain is always going to be infinitely more complicated than this model.



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