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- Sim-to-Real Gaps May Help Explain Uneven AI Progress
An analysis argues that the sim-to-real gap may help explain why AI has made rapid progress in programming and mathematics while its real-world impact in many professions remains modest. Programming and mathematical reasoning can be replicated and verified in digital environments, whereas many white-collar professions involve people and physical environments that are difficult to simulate. The analysis uses robotics examples to illustrate the challenge. It also cites GDPval, where the best score reportedly rose from 47.6% for Claude Opus 4.1 when the benchmark was released to more than 85% for current leading models.
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