Tom Simonite, Wired
The brain is solving a very different problem from most of our neural nets. You’ve got roughly 100 trillion synapses. Artificial neural networks are typically at least 10,000 times smaller in terms of the number of weights they have. The brain is using lots and lots of synapses to learn as much as it can from just a few episodes. Deep learning is good at learning using many fewer connections between neurons, when it has many episodes or examples to learn from. I think the brain isn’t concerned with squeezing a lot of knowledge into a few connections, it’s concerned with extracting knowledge quickly using lots of connections.
https://www.wired.com/story/googles-ai-guru-computers-think-more-like-brains/
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