A $500 RL fine-tune of a 9B open model beat frontier models on catalog review

This continuous cycle of fine-tuned open models beating frontier on (often vaguely labeled/defined) benchmarks doesn't provide an accurate comparison to the expanding generalized capabilities of the SoTA, which makes them effectively meaningless.

If we were to take these at face value, why is it that the frontier labs' models are making legitimate new discoveries (e.g. Erdős and Jacobian conjectures) and these models are not?

To me, a better signal of capability would be similarly performing novel work at the same or better level, which they presently are not. I say this as someone who very much looks forward to open models being more capable, but to deny the gap is misguided hopeful hype.

The point that the major labs don’t seem to get is that the vast majority of use cases simply don’t need models that have 50 PhDs and can speak 12 languages. Most use cases are defined within constraints where costs matter a lot.

As open weight models and cheap fine tuning services become the norm the whole economic framework of these mega models the labs are in an arms race building just completely crumbles. As does the economic picture that justified the massive infrastructure building that’s now broadly funded by a complex network of debt.

This is what makes open weight models so threatening to them. The political and “it’s China” angle is mostly just a cover for the real reasons why they’re freaked out.

The fact that models are now a pure commodity is bad enough for the big labs. If small open weight models become the norm the big labs are toast.

This is about saving money by using the right tool for the job. If you have a system that does a lot of mundane, repetitive work, you don't need a frontier model to do it.

It doesn't mean frontier models aren't good at harder tasks.

I'm not suggesting that fine-tuned models don't have their place, all I'm saying is that the constant drumbeat of "cheap model X beats more expensive model Z" completely misses that the more expensive model is capable of doing more things at a higher level.

If the appropriate qualifiers were added to say "cheap model X does better at test Y than expensive model Z when we fine tune X to take Y test of existing knowledge" then it would be a more accurate statement, but naturally less impressive.

As someone who worked at multiple startups, I am pretty sure they get it but it doesn’t fit their goals.

They want to moat where they don’t need to compete with other companies because they have something that other companies can’t have.

In my opinion this is a short-sighted and greedy worldview. Haven’t seen it work personally. It is a different version of the month-to-month salary guy thinking he will be a billionaire and having that thrash “mindset”.

The reality is that practically none of those companies will amount to anything and they would be better off weighing the usefulness aspect of their output more. Instead they are imagining they will be Google.

Anthropic and openai ofc are the pinnacle of this greed culture and they correspond to FTX from the crypto trash hype so I don’t think they fit into the scale of sensibility.

Coming from this perspective, it is pretty easy to see what they are.