Or ever, given that the level of abstraction LLMs work at is completely wrong. They can approximate the syntax of things in their training corpus, but logic? The lights are off and nobody's home.
Yes, at the moment GPT4 and the like aren't all that good yet, but they have shown that they have started understanding semantics.
That seems certain. It's why I'm putting serious thought into leaving the industry.
Rather then leaving it's better to adapt. AI is just one of technologies in the list. They come and go, that's the specific of IT. Except AI will stay, it will change with the time, but will never go away. Besides, it's the coolest thing right now. And will create new jobs around itself.
Literally you give it the code and the error and it can walk you through finding the solution.
When I say walk you through, I generally mean when you provide it a function but the error is caused by some input that doesn't conform to expectations. If the error were just a defect in the code it can generally point that out instantly.
Obviously GPT4 is even better.
thats not fixing bugs, that's static analysis. Finding the solution to the specific problem that needs to be solved is a lot more difficult than identifying any problem and then solving it.
90% there? I disagree. 90% would mean that most of the time it gets the translation right. That hasn't been my experience.
I recently fed a very large file into GPT4 and it handed me a few serious bugs that I hadn't noticed after a few self-reviews.