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so we can think of the varying strength of synapses of interconnected biological neurons as evolutionary pre-pretraining for language (with school as pretraining and vocational training as training), and we should translate the learnings of that pre-pretraining to a geometric understanding for computational linguistics, so that we can advantageously apply these learnings as inductive biases to network architecture and weight initialization better

craziest shit i've ever read

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hopefully crazy in an interesting/good way!

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