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Brain science research is increasingly bolstering the idea that math instruction rooted in culturally relevant problem-solving helps students draw from their lived experiences and activates distinct areas of the brain, producing durable and deeplearning.
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And in fact the big breakthrough in “deeplearning” that occurred around 2011 was associated with the discovery that in some sense it can be easier to do (at least approximate) minimization when there are lots of weights involved than when there are fairly few.
But actual evolution seems more like deeplearning with a large neural net—where one’s effectively operating in an extremely high-dimensional space where there’s typically always a “way to get there from here”, at least given enough time. And indeed simple models of evolution might give one the intuition that this would happen.
But anticipating that we might need to reprint the book fairly quickly we didn’t consider that an option; it would just take too long to transport books by boat across the Pacific. And although the details are more complicated, the whole notion of deeplearning in neural nets can also be thought of as related.
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