As debates swirl around plateauing LLM performance, "reasoning" paradigms are hailed as the next frontier for technological & commercial growth. How much of this is genuine progress vs excessive hype?
Recent reports of folks at Lawrence Livermore Lab using o1 to help with actual experimental problem set up is informative. Motivated users will figure out how to use reasoning models effectively with specific prompts. They probably care less about whether the model is actually reasoning or not, and more about outcomes.
The argument about whether or not the models actually reason is frankly mainly relevant because enterprise users likely lack specificity and precision in their prompts. This necessitates robustness in the model's ability to reason consistently across varied and underspecified end user requests. Aside from this the discussion is somewhat academic.
Recent reports of folks at Lawrence Livermore Lab using o1 to help with actual experimental problem set up is informative. Motivated users will figure out how to use reasoning models effectively with specific prompts. They probably care less about whether the model is actually reasoning or not, and more about outcomes.
The argument about whether or not the models actually reason is frankly mainly relevant because enterprise users likely lack specificity and precision in their prompts. This necessitates robustness in the model's ability to reason consistently across varied and underspecified end user requests. Aside from this the discussion is somewhat academic.