paperarXivTrust 82 · PrimaryPublished 2d agoLive · yesterday
Two AI Metrics Diverged: Will it Make All the Difference?
As exponential compute scaling continues, will the capabilities of frontier AI models outstrip what is accessible to developers on a small fixed budget? Or will capabilities converge, with "meek models inheriting the earth"? Building on Gundlach et al. (2025b), we show that the answer depends on how we value and measure AI capabilities. We discuss conventional performance measures and show that, while validation loss shows a shrinking gap, on other metrics frontier models grow their lead forever. Classifying performance metrics by their functional forms in relation to training (and inference)
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newsNVIDIA Unlocks AI Compute at Scale, Inviting Capital Partners to Power the AI Infrastructure BuildoutnewsSafely Releasing Frontier Models to CustomersnewsMonitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatchnewsNVIDIA and AWS Collaborate to Bring AI to Production at ScalenewsNVIDIA Unlocks AI Compute at Scale, Inviting Partners to Power the AI Infrastructure BuildoutnewsBernie Sanders unveils $7 trillion plan to give Americans control of AI industrynewsWhy Aren’t We Measuring How AI Affects Humans?