Agentic Evolution of Physically Constrained Foundation Models

AI increasingly drives automated scientific discovery, yet contemporary generalist agents lack physical grounding, frequently hallucinating hardware-incompatible designs. A paper posted on arXiv on June 25 presents a physically grounded, multi-agent discovery engine that autonomously architects hardware-compliant computing systems. Anchored by an Evolutionary Knowledge Graph that structures past scientific innovations, the framework extracts algorithmic design patterns to automatically build systems that respect real-world hardware constraints. The paper is listed under arXiv ID 2606.25532 in the cs.AI category, addressing a critical gap in AI-driven scientific discovery by introducing physical constraints into the agentic design loop.