Comment by chpatrick

4 days ago

Could someone explain how Jev is different from using any old model and constraining the output to "My choice is a/b/c..."?

The argument the article makes is it's not that different. Jev's argument is that they have trained the model to better output probabilities (which is not necessarily a training object of LLMs but we don't actually know that)

Ultimately Jev claims to have a data advantage which is likely where the future lies. They'll have a unique edge in improving general purpose classification / decisioning.

The model can spend more “mental energy” on the decision because it doesn’t have to spend any on phrasing the output.

  • LLMs are constant time per token, if you only let it choose a/b/c/d then there's nothing else it can "spend".

If you believe the marketing, constraining the output this way can make the model much faster and much more type-safe (the model didn’t give you a fifth choice not present in the choices).

  • How is that different from just not letting it output option 5 when you sample from the probabilities?