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> With AI systems, almost all bad behaviour originates from the data that’s used to train them Careful with this - even with perfect data (and training), model

• beyarkay 1y ago
  Indeed, this has been the most contentious line in the whole piece :D How do you define "perfect" data and training? I'd argue that if you trained a small NN to play tic-tac-toe perfectly, it'd quickly memorise all the possible scenarios, and since the world state is small, you could exhaustively prove that it's correct for every possible input. So at the very least, there's a counter example showing that with perfect data and training, models will not get stuff wrong.
  • kees99 1y ago
    Having too much parameters in your model, so that all of sample/training data is preserved perfectly, is usually considered a bad thing (overfitting). But you're right - if dataset is exhaustive and finite, and model is large enough to preserve it perfectly - such overfitted model would work just fine, even if it's unlikely to be a particularly efficient way to build it.