LoRA adaptive learning using open-weight models and your own reasoning traces is the thing. The big labs have a mammoth job ahead of them if they want to compete with running your own model - they will basically have to give every single user their own persistent virtual machine. When it's all said and done, I think their only really moat will be as inference/hardware providers. Stripe buying OpenRouter was a very sm…
Can you explain what you mean with "LoRA adaptive learning using open-weight models and your own reasoning traces"?
When you have a few example chats you want a model to emulate - say you made it from your proprietary data, you can train any open model on that data in this cheap way. You don't lose any quality versus not using lora since the models overall knowledge won't shift that much due to your data anyways, so it's a waste to make high dimensional updates.
However, only in some cases is it worth it and equal in quality to just making a good retrieval system and exposing it to claude code or whatever. If a retrieval system over the same data is very difficult, or if the data simply must be proprietary, then you should go for it.
[1] technically "rank", but I'm simplifying