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I agree that we don't know what is possible in hypothetical future models, but claims about understanding in the current models are overblown (at least by peopl

I agree that we don't know what is possible in hypothetical future models, but claims about understanding in the current models are overblown (at least by people like the article author). For example, I gave GPT-4 some chess games and asked it to evaluate the final move of each game as good or bad and explain its evaluation. It clearly had some understanding of the board state and what makes a move good or bad, but the answers were mostly plausible-sounding nonsense, far worse than what a novice chess player would come up with. I have to assume that its level of understanding of other topics isn't any different; it's just easier to expose the flaws with something that has objectively true and false answers.

peterfication 4y ago
This is probably something that will be fixed with an OpenAI to "some chess AI"-plugin. Then for the current model it's just enough to understand that it's a chess problem.
- fasterik 4y ago
  Maybe, but my point is that if it's this bad at understanding chess, which a fairly simple and objective domain, why should we have confidence it has understanding in other domains where it's harder to prove wrong answers wrong? We aren't going to be able to come up with specialized plugins that fix its mistakes in every conceivable domain. The amount of trust people are putting in the current models seems to indicate that they think it's roughly at a human level of understanding, which doesn't seem to be the case. And if we are actually trying to solve the problem of general intelligence, we can't just sweep things under the rug and say "plugins will fix it".