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While I'm sure the anti-AI people are taking this and running off with hot takes, the conclusion is still much more mundane: we currently do not have the abilit
by XorNot 2y ago
While I'm sure the anti-AI people are taking this and running off with hot takes, the conclusion is still much more mundane: we currently do not have the ability to have an LLM learn from another LLM.
A suitably powerful AI should be able to do this though, by the example of the fact that humans learn by being taught by other humans (insert nuance of that process here).
So it's an important result, but not a doomsday result because what it tells us is that LLM output fails to capture or stabilize important information from the training corpus and accurately communicate it to a newly trained LLM. So we know we're missing something in how we construct these models, but the ramifications of solving it are also pretty immense: models being able to "teach" new models means the whole cycle of iteration can be sped up considerably.
- kouteiheika 2y ago> we currently do not have the ability to have an LLM learn from another LLM We do. It's called model distillation, and it's relatively straightforward. In fact, training a smaller model on the outputs of a much bigger model will significantly cut down on your training time/create a higher quality model than just training on raw human data (which is often low quality and noisy).
- suprjami 2y agoIt has existed for years: Self-Instruct: Aligning Language Models with Self-Generated Instructions https://arxiv.org/abs/2212.10560 https://arxiv.org/abs/2212.10560 airoboros: using large language models to fine-tune large language models https://github.com/jondurbin/airoboros https://github.com/jondurbin/airoboros