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Comment by pen2l | Hacker News Reader

The more constraints there are (e.g. like your example) the better it should perform. So it disappoints me when copilot, knowing what libraries are available in the IDE it's running in, hallucinates up a method call that doesn't exist.

Separately (and apologies for going on a tangent), where do you think we are in the Gartner cycle?

Around GPT3 time I was expecting for trough of disillusionment to come, particularly when we see the results of it being implemented everywhere but it hasn't really come yet. I'm seeing too many examples of good usage (young folks using it for learning, ESL speakers asking for help and revisions, high-level programmers using it to save themselves additional keystrokes, the list is long).

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> hallucinates up a method call that doesn't exist

I actually think it helps to reframe this. It hallucinates up a method call that predictively should exist.

If you're working with boto3, maybe that's not actually practical. But if it's a method within your codebase, it's actually a helpful suggestion! And if you prompt it with the declaration and signature of the new method, very often it will write the new helper method for you!

Hah, hadn't thought of this but kind of love that take!

If you have a long iterative session by the end it will have forgotten the helpful hallucinations at the beginning, so then phantom methods evolve in their name and details.

I wonder if it is better at some languages than others. I have been using it for Go for a week or two and it’s ok but not awesome. I am also learning how to work with it, so probably will keep at it, but it is clearly a generative model not a thinking being I am working with.

No idea about Go, but I was curious how GPT-4 would handle a request to generate C code, so I asked it to help me write a header-only C string processing library with convenience functions like starts_with(), ends_with(), contains(), etc.) I told it every function must only work with String structs defined as:

struct String { char * text; long size; }

...or pointers to them. I then asked it to write tests for the functions it created. Everything... the functions and the tests... worked beautifully. I am not a professional programmer so I mainly use these LLMs for things other than code generation, but the little I've done has left me quite impressed! (Of course, not being a professional programmer no doubt makes me far easier to impress.)

Interesting. I haven’t tried it with C. Hopefully the training code for C is higher quality than any other language (because bad C kills). Do you have a GitHub with the output?

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