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What you could do, I guess, is write up 5-6 implementations of it yourself first, then feed those into the training set for the model, and then it should have a decent shot at understanding that particular problem. (maybe /s?)

I guess my question is if you had a good solution you'd done before, and also a good understanding of what kinda changes it needs, why bother with hours of AI prompting?



Presumably the purpose of the exercise was to test the model’s capabilities / “take it for a spin” , not to obtain the working progress (as, as you mention, they already had a working program to do the task).


These models are supposed to be reasoning. Why would you need to do all that work? If I can teach it to an intern, why wouldn't a model that can reason be able to do that?

Unless all the promises and hype are false...


To write a blog post! "I used AI to solve this challenging problem" gets more traction than "I solved this challenging problem"




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