Could someone explain to me what the advantages are of that? How could an AI model trained on input generated by an AI ever be any better than the original AI?
Is it about costs of getting clean datasets?
Is it about costs of getting clean datasets?
E.g. if you're training an LLM on Reddit, there's a good shot that some of the Reddit posts you're pulling in were generated by an AI.
Of course, one challenge is to make sure AI doesn't interfere with moderation. Perhaps this whole situation will spur more work on moderation systems.
Much of the success of chatgpt comes from RLHF, which can be viewed as training on its own data, but only the data which has been determined by a human to be especially good.
If your goal is "engaging content", that's probably a reasonable one. If your goal is "human-generated content", it's not.
I think parent was suggesting that the fact that LLM will inadvertently be trained on AI generated output needs to be accounted for.
BTW an AI trained on a larger dataset generated by an AI trained on a smaller dataset is still technically only knows the smaller dataset. It can just be a better AI trained on the same dataset.
Like a tennis player practicing tennis with a wall?