Apple Paper: Tool-Use Agents Gain More From Diverse Tools and Databases Than More Tasks
rohanpaul_ai · x · 2026-10-29
Apple's paper "Scaling Laws for Tool-Use Agents via Controllable Environment Synthesis" (arXiv:2610.37648) introduces SynthAPI, which controls diversity of synthetic environments across tools, tasks, and databases. From 458,752 tasks and 849 trained models of four sizes, the authors derive a scaling law: as data budgets grow, scaling tool and database diversity beats adding more tasks, and higher data complexity yields larger gains. Agents trained accordingly outperform prior work across four benchmarks.
Related event: Apple Paper Reveals Scaling Laws for Tool-Use Agents(3 posts)→
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