… It turns out that with some tweaks to the architecture, you can take a giant pre-trained multimodal transformer and then use it as a component in a larger system, a bureaucracy but with lots of learned neural net components instead of pure prompt programming, and then fine-tune the whole system via RL to get good at tasks in a sort of agentic way.
Worth noting that Meta did not do this: they took many small models (some with LM pretraining) and composed them in a specialized way. It’s definitely faster than what Daniel said in his post, but this is also in part an update downwards on the difficulty of full press diplomacy (relative to what Daniel expected).
If we’re using Daniel’s post to talk about whether capabilities progress is faster or slower than expected, it’s worth noting that parts of the 2022 prediction did not come true:
GPT-3 is not “finally obselete” -- text-davinci-002, a GPT-3 variant, is still the best API model. (That being said, it is no longer SoTA compared to some private models.)
We did not get giant multi-modal transformers.
He did get the “bureaucracy” prediction quite right; a lot of recent LM progress has been figuring out how to prompt engineer and compose LMs to elicit more capabilities out of them.
Continuing the quote:
Worth noting that Meta did not do this: they took many small models (some with LM pretraining) and composed them in a specialized way. It’s definitely faster than what Daniel said in his post, but this is also in part an update downwards on the difficulty of full press diplomacy (relative to what Daniel expected).
If we’re using Daniel’s post to talk about whether capabilities progress is faster or slower than expected, it’s worth noting that parts of the 2022 prediction did not come true:
GPT-3 is not “finally obselete” --
text-davinci-002, a GPT-3 variant, is still the best API model. (That being said, it is no longer SoTA compared to some private models.)We did not get giant multi-modal transformers.
He did get the “bureaucracy” prediction quite right; a lot of recent LM progress has been figuring out how to prompt engineer and compose LMs to elicit more capabilities out of them.
A deliberate nod?