I did a GRPO run (multiple now actually) with a per sample rubric that leans heavily on subjective preference judgements that BERT wouldn't have the learning ca

I did a GRPO run (multiple now actually) with a per sample rubric that leans heavily on subjective preference judgements that BERT wouldn't have the learning capacity for: not to metion you'd need to finetune hundreds of instances and host them somewhere. And even if BERT wasn't woefully underintelligent for the task... have 100+ instances of BERT running locally faster than Jev API response times? Sweet rig you must have... LLMs would not be fast enough without constrained decoding tricks that people fundamentally don't seem to understand make the models much dumber, and sure wouldn't be cheaper or faster. Again I feel this deep discomfort because presumably you're somewhat intelligent but your opening salvo made it hard not to scream DO YOU EVEN HAVE A SINGLE CLUE WHAT IT DOES instead of giving you my actual answer... yet you're speaking from the chest! If I didn't try it for myself I would have been 100% sucked into you and this ocean of clueless negativity. - I apologize if that sounds harsh but it angers me because why should I have to deal with this kind of noise in an already insanely noisy environment? What do you gain from being cluelessly pessimistic? And dwelling a but more I think it breaks one of my most used filters which was assuming people who know the "old world" of AI/ML are better at judging the "new world" full of hype and noise. Maybe my frustration is also just fear that things moved so quickly that the "old world" is becoming increasingly irrelevant. That'd be really disappointing.