Top pick  ·  Generative AI & Diffusion

From Pixels to Actions - Towards Native Vision-Language-Action Policies

NEO-VLA lets action policies use visual features at all network layers, outperforming fixed-encoder models.

Why it matters: Builders get more reliable robot control by accessing visual cues early in the model, not just at the final encoder output.

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Trending  ·  Reasoning & Agents

FrontierPhysics: Evaluating Agents for End-to-End Physics Research

FrontierPhysics benchmarks AI agents on full-cycle physics research tasks, revealing current models struggle to produce correct, publishable work.

Why it matters: Builders need realistic evaluation of AI's ability to conduct genuine scientific research, not just answer isolated questions.

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