Idea: a theorem verifier with the mindset of a toddler. When it starts it rejects everything, so you have to show it the two theorems it already knows like a hundred times before it'll admit that some things are, in fact, true

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@christianp And hundred examples to convince it that the definitions are indeed motivated.

@christianp I'd be surprised if someone doing machine learning hasn't thought of something similar.

@christianp
def run_prover():
while True:
print("Why?")
raw_input()

there, digitoddler 2.0 :>

@christianp So, a bayesian approach?

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