zlacker

>>moored+(OP)
This stuff smells like maybe the bitter lesson isn't fully appreciated.

You might as well just write instructions in English in any old format, as long as it's comprehensible. Exactly as you'd do for human readers! Nothing has really changed about what constitutes good documentation. (Edit to add: my parochialism is showing there, it doesn't have to be English)

Is any of this standardization really needed? Who does it benefit, except the people who enjoy writing specs and establishing standards like this? If it really is a productivity win, it ought to be possible to run a comparison study and prove it. Even then, it might not be worthwhile in the longer run.

>>iainme+Qb
I'd argue we jumped that shark since the shift in focus to post training. Labs focus on getting good at specific formats and tasks. The generalization argument was ceded (not in the long term but in the short term) to the need to produce immediate value.

Now if a format dominates it will be post trained for and then it is in fact better.

>>ianbut+yk1
Anthropic and Gemini still release new pre-training checkpoints regularly. It's just OpenAI who got stupid on that. RIP GPT-4.5

>>Der_Ei+ks1
All models released from those providers go through stages of post training too, none of the models you interact with go from pre-training to release. An example of the post training pipeline is tool calling, that is to my understanding a part of post training and not pre training in general.

I can't speak to what the exact split is or what is a part of post training versus pre training at various labs but I am exceedingly confident all labs post train for effectiveness in specific domains.