Category: research
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A Social Path to Human-Like AI: 社会互动如何生成新数据
TLDR: Human-like AI may require populations of agents learning through social interaction, where cooperation and competition generate skills beyond single-agent training.
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Talk with Shunyu Yao: feedback is the center of AI research
TLDR: The conversation is useful because it frames AI research as system-driven experimental work: define verifiable problems, build feedback loops, debug carefully, and choose directions where scaling paths are still being shaped.
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Anthropic Blogs: harness engineering and context engineering
The shared lesson across these Anthropic engineering posts is that long agent tasks fail at the runtime layer: context, evaluation, sandboxing, permissions, handoff, and feedback have to be engineered.