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Foundation models can revolutionize hand-object interaction by systematically categorizing and leveraging diverse priors to enhance robot learning and task performance.
KAT-Coder-V2.5 outperforms existing models in agentic tool-use, showcasing a new paradigm for autonomous coding agents within executable environments.
AgentX can autonomously iterate on recommendation algorithms, outpacing human-driven processes and fundamentally changing how we approach system development.
