Copilot (the existing gpt-3 one) definitely helps at writing unit tests. Yeah, sometimes it doesn't nail it, but one thing it can do reliably is to repeat a pattern, and I don't know about you, but my unit tests tend to repeat the same pattern (with some tweaks to test this-or-that-case). Quite often it infers the correct change from the name I gave the test method, but even if it doesn't it'll write a 90% correct case for me. I imagine the GPT-4 version will do more of the same with better results.
It cannot replace reasoning, but it can augment it (by suggesting patterns and implementations from its latent space that I hadn't thought of), and worst case it can replace quite a bit of typing.
Long-term, it remains to be seen how far bigger/better/stronger LLMs can push the illusion of rationality. In many fields, they may be able to simply build their ability to pattern-match to beyond some threshold of usefulness. Perhaps (some subset of) programming will be one of them.
Copilot (the existing gpt-3 one) definitely helps at writing unit tests. Yeah, sometimes it doesn't nail it, but one thing it can do reliably is to repeat a pattern, and I don't know about you, but my unit tests tend to repeat the same pattern (with some tweaks to test this-or-that-case). Quite often it infers the correct change from the name I gave the test method, but even if it doesn't it'll write a 90% correct case for me. I imagine the GPT-4 version will do more of the same with better results.
It cannot replace reasoning, but it can augment it (by suggesting patterns and implementations from its latent space that I hadn't thought of), and worst case it can replace quite a bit of typing.
Long-term, it remains to be seen how far bigger/better/stronger LLMs can push the illusion of rationality. In many fields, they may be able to simply build their ability to pattern-match to beyond some threshold of usefulness. Perhaps (some subset of) programming will be one of them.