There's no shortage of ideas for improving real-world processes. Most of those ideas are bunk, and we're constrained by the amount of experiments[1] we are will

There's no shortage of ideas for improving real-world processes. Most of those ideas are bunk, and we're constrained by the amount of experiments[1] we are willing to run/fund, and the quality of data[1] that those experiments can collect, and the reproducibility[1] of those experiments. Having an AI shout random ideas is very easy for software people to grok, but isn't going to help. If you want AI to assist with this, you'd need to build an 'AI' that can run the real-world experiments, and that's a few orders of magnitude harder than feeding a text corpus to an LLM. 'Thinking' about this problem isn't the hard part, the hard part is doing it. Even using an LLM for something like a meta-analysis of existing research is unlikely to find many profitable avenues of exploration. [1] Experimental research is incredibly difficult, which is a fact that's highly underappreciated by people working in abstract and theoretical disciplines.