> You were talking about code writing, now you switched to debugging. Those are wildly different tasks
No, they're basically the same thing, intrinsically linked and inseparable. Likely represented together in training sets, too. I'm surprised anyone would say that. Are you a programmer?
> For debugging LLM-s reproduce fine-tuning datasets made by humans actually doing debugging on some code.
Not really, they are primarily trained on LLM-generated trajectories from executable training environments.
> And yes, the problems AI found in your code were similar to the problems humans found when writing those datasets.
So they're only similar now? I suppose, in the way that I learned how to solve bugs while learning to program and now I can fix similar ones? I guess we can now agree that LLMs are capable of learning and extrapolating knowledge to new problems?
No, they're basically the same thing, intrinsically linked and inseparable. Likely represented together in training sets, too. I'm surprised anyone would say that. Are you a programmer?
> For debugging LLM-s reproduce fine-tuning datasets made by humans actually doing debugging on some code.
Not really, they are primarily trained on LLM-generated trajectories from executable training environments.
> And yes, the problems AI found in your code were similar to the problems humans found when writing those datasets.
So they're only similar now? I suppose, in the way that I learned how to solve bugs while learning to program and now I can fix similar ones? I guess we can now agree that LLMs are capable of learning and extrapolating knowledge to new problems?