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"with even the latest tools the effort put in to get the model to produce useful output is still some multiple (but not an enormous multiple now, say 2x to 5x) of the effort needed to properly prompt and verify the output. However, I see no reason to prevent this ratio from falling below 1x in a few years, which I think could be a tipping point for broader adoption of these tools in my field"

Given the log scale on compute to improve performance, it is not a guarantee that the ratio can be improved so much in a few years



The y axis is also log scale (log likelihood). It’s a power law, not an exponential law.


I was referring to the o1 AIME accuracy figure (x log scale compute, y is % (not log)) and similar https://openai.com/index/learning-to-reason-with-llms/




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