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这是月之暗面“模型即Agent”的逻辑。目前,绝大多数Agent产品的智能上限仍由模型能力决定,只有拥有强大、可控、具有上下文和复杂推理能力的自研基座模型,才能支撑起用户理想中的“Agent”,而这也更符合Kimi长期聚焦长文本的优势。

But those tricks, I believe, are quite clear to everybody that has worked extensively with automatic programming in the latest months. To think in terms of “what a human would need” is often the best bet, plus a few LLMs specific things, like the forgetting issue after context compaction, the continuous ability to verify it is on the right track, and so forth.

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// block: Wait for space (unbounded pending queue)

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