All of geduardo's Comments + Replies

I don't think I can agree with the affirmation that NNs don't have memory of previous training runs. It depends a bit on the definition of memory, but in the weights distribution there's certainly some information stored about previous episodes which could be view as memory.

I don't think memory in animals is much different, just that the neural network is much more complex. But memories do happen because updates in network structure, just as it happens in NNs during a RL training.

It could be that I overuse the word complexity in the text, but I think it is essential to convey the message. And honestly, I find the terms "intelligence" and "understanding" more obscuring that the term complexity. Let me try to explain my point in more detail:

  • I understand intelligence as a relative measure of the ignorance of the dynamics of a decision-making system. Let's use four types of chess players to illustrate the idea:
    • The first player is a basic "hard-coded" chess engine, for example, based on MTD-bi search (like [sunfish](thomasahle/sunfish:
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