4 ms·
We know all of the rules of tic-tac-toe. We have no idea how much we dont know about genetics. The things we know can still be incorporated in various ways wit
by dwiel 8y ago
We know all of the rules of tic-tac-toe. We have no idea how much we dont know about genetics.
The things we know can still be incorporated in various ways with deep learning, but we avoid having to make as many obviously not universally applicable assumptions as with less complex statistical methods.
- teekert 8y agoExactly, there is simply no way for a human to understand this stuff without (some layers of) abstraction, each abstraction introduces bias and/or error.
- ssivark 8y ago> we avoid having to make as many obviously not universally applicable assumptions The point of the above koan is that there are always assumptions (priors) whether you like them or not. You can make them explicit or random and unknown. This is the crux of the bias-variance tradeoff [1]. Whether deep NNs manage to circumvent that in any meaningful way (especially outside the domain of spatial/temporal analog signals) is an open question. [1]: https://en.wikipedia.org/wiki/Bias%E2%80%93variance_tradeoff https://en.wikipedia.org/wiki/Bias%E2%80%93variance_tradeoff