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by blobbers
675 days ago
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I spent some time trying to get chatgpt to write a front end in js. It would plot using a library and then when I complained about a bug it would say "Oh you're right, this library does not implement that commonly implemented method, instead use this code." and then would get in a circle of spitting out buggy code, fixing a bug, and then reintroducing an old bug. It was okay, but kind of annoying. I understand js well enough to just debug the code myself, but I wanted it to spit out some boilerplate that worked. I can't remember if this was chatgpt omni, I was using or if it was still 3.5. It's been a short while. Anyways, it is cool tech, but I don't feel like it offers the same predictive abilities as class ML involving fits, validation, model selection etc for very specific feature sets. |
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The other thing I’ve noticed is something you alluded to: the LLM being “confidently incorrect”. It speaks so authoritatively about things and when I call it out it agrees and corrects.
The more I use these things (I try to ask against multiple LLMs) the more I am wary of the output. And it seems that companies over the past user rushed to jam chatbots into any orifice of their application where they could. I’m curious to see if the incorrectness of them will start to have a real impact.