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In other words, we can tell the neutral nets when they're getting "warmer" or "colder" to desirable speech, but we don't know how they do it.
by pmoriarty 4y ago
In other words, we can tell the neutral nets when they're getting "warmer" or "colder" to desirable speech, but we don't know how they do it.
- HarHarVeryFunny 4y agoWell sort of... The odd thing about large transformers is that there is such a huge qualitative difference between what they learn (hence how they behave) and how they are trained, so it's hard to say that this predict-next-word error feedback is directly controlling their inference behavior. Given what the model is learning, it's perhaps best to regard this predict-next-word feedback not as "this is what I'd like you to generate", but rather something more indirect like "learn to generate something like this, and you'll have learnt what I want you to learn". A bit like Karate Kid and "wax on, wax off", perhaps! The actual desirability of what the model is generating, which depends on what you want to use it for, is really controlled by subsequent training steps, such as: 1) Fine tuning for instruction (prompt) following and conversational ability (this is the difference between ChatGPT and the underlying raw GPT-3 model) 2) Goal-based reinforcement learning to stop the model from generating undesirable content such as telling suicidal people to kill themselves, etc, etc.