3 ms·
I would say overfitting - the net doesn't "understand" the code in any meaningful sense. It just finds fitting examples and jumbles them a bit. Understanding w
by captainmuon 5y ago
I would say overfitting - the net doesn't "understand" the code in any meaningful sense. It just finds fitting examples and jumbles them a bit.
Understanding would mean to have an internal representation related to the intention of the user, the expected behavior, and say the AST of the code. My pessimistic interpretation of this and many other recent AI applications is that it is a "better markov chain".
- LeanderK 5y agoa markov chain can have an internal representation related to the intention of the user. I guess this example just got copied a lot and is therefore included multiple times in the training data, forcing the network to memorise it. Neural networks always memorise things that appear too frequent. Memorized Artifacts in an otherwise working neural network is usually seen as a "bug" (since the training allowed the network to cheat), not as a proof that the network didn't generalise.