Noisy sorting algorithms are a useful cognitive tool. Sorting many items is tedious for me, but spamming comparisons is trivial. Convenient implementations exist, but you can now just one-shot it alongside whatever user interface best suits your data using an LLM.
Are there algorithms for related problems that convert psychologically convenient decisions into solutions? Apparently so, there’s a literature! For example, constraint-based optimization. I’m sure there are many others.
Minimal-effort data parsing/UI generation vastly increases the global real-world utility of any robustly implemented human-friendly optimizer. Making a library of sensible defaults for models to riff on could be a worthwhile project for someone with more free time than me.
Noisy sorting algorithms are a useful cognitive tool. Sorting many items is tedious for me, but spamming comparisons is trivial. Convenient implementations exist, but you can now just one-shot it alongside whatever user interface best suits your data using an LLM.
Are there algorithms for related problems that convert psychologically convenient decisions into solutions? Apparently so, there’s a literature! For example, constraint-based optimization. I’m sure there are many others.
Minimal-effort data parsing/UI generation vastly increases the global real-world utility of any robustly implemented human-friendly optimizer. Making a library of sensible defaults for models to riff on could be a worthwhile project for someone with more free time than me.