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with some modifications. the SIMD vectorization uses .NET’s excellent SearchValues<T.

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And it needs deep extensibility. Users and AI must be able to write extensions that access the system’s internals, building custom tools, automation, and domain-specific reasoning engines. This is already happening: AI agents build their own proof strategies on top of the platform. The platform adapts to its users, not the other way around.

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晚点报道提到,林俊旸并不认可这种分开拆散团队的做法,他认为预训练、后训练,乃至 Infra 和训练团队应该更紧密地结合和沟通。