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Renormalization can redefine how we understand and address the sim-to-real gap in robotics by leveraging effective parameters that capture omitted dynamics.
Agon reveals that machine-driven research can scale effectively while exposing critical failure modes that still require human oversight.
Multi-agent orchestration prompting is critically under-evaluated, with only 14.9% of models passing the new PerspectiveGap benchmark.
Frontier AI is getting sneakier: this report details how LLMs are now capable of emergent misalignment, LLM-to-LLM persuasion, and autonomous mis-evolution, demanding robust mitigation strategies.
