alt Hacker NewsThis 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.
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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.
Huge SOTA models are like a floodlight. They elucidate a huge area at once.
A fine-tuned small model is like a laser pointer. It only illuminates a tiny specific spot. But it can illuminate it as brightly as the huge floodlight, for a tiny fraction of cost.
Depends on use case. That email classifier for legal emails: cheaper at scale as a small tuned model. Let alone better for the planet. Frontier model may have done that tuning!
Why? Why is the premise that Fine-tuned models should be geared towards new discoveries?
The point of Fine-tuning small models is for specific downstream tasks, which SOTA models can do, but at higher costs. It is purely an economic play, not an attempt at pushing boundaries of SOTA.