You've misunderstood the bitter lesson if you think it applies here. It's not "frontier LLMs are always better", it's "algorithms that scale with compute/data will usually end up surpassing algorithms that are based on human understanding".
replyFine-tuning an open-source LLM with reinforcement learning in order for it to be better at a specific task does not go against the bitter lesson at all.
> You've misunderstood the bitter lesson if you think it applies here.
replyThat's fair because I am stretching it.
I think there's AI companies that understand and scale AI. Then there's the rest that are doing a modern version of writing domain specific knowledge using skills, and maybe a large collection of their own data.
Maybe these focused models outperform in their own niche similar to how hand-written rules outperformed in their own niches. But long-term, they get outpaced quickly by generalized approaches.