Comment Re:AI is great for thing that do not matter... (Score 1) 100
But when you have to review and take responsibility for thousands of lines AI spews it is quite another story...
I would generalise this and say that AI code is useful when it is easier to validate than it is to create. AI, as it is defined today, is an approximation engine that only asymptotically approaches reliable correctness. Thus, you must always assume that the output is wrong. Either being wrong doesn't matter of you must take the time to validate the result. My area is designing the logic that goes into chips. Coding effort is dwarfed by verification and debug. Correctness is critical. Once a chip is manufactured, there are no updates. And, yet, companies are now pushing us to use AI, too. A couple of weeks ago, I asked Gemini, Claude, Chatgpt, and xAI to generate a round robin arbiter and associated testbench. None of these models produced design code that would pass their own testbench. Gemini's code wasn't even a wrong round robin arbiter. It was some bizarre hybrid. And this is for a small, well known, foundational block. I can see using AI as a debugging too. If we already have a testbench that identifies the failure, It is easy to check to see if the proposed fix actually works. If it doesn't don't use it. But asking AI produce new, complex, and unfamiliar code seems like a dead loss.