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Robots using the SWAP model achieved record-breaking parkour feats, including a 2.13 m jump and a 1.63 m climb, demonstrating the power of symmetry in robotic learning.
Gaze behaviors learned through reinforcement alone can lead to unprecedented humanoid locomotion capabilities, including a record 1.2m gap traversal.
Multi-chiplet architectures can unlock significant speedups and memory savings for low-batch MoE inference by dynamically scheduling expert computations across high-bandwidth die-to-die links.
Scaling LLM-based multi-agent systems doesn't just need better prompts or models, but a whole new software engineering approach focused on managing runtime entropy.
