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Owain Evans’ idea of feeding a historical LLM non-anachronistic images is, I think, well worth doing. But it’s also worth expanding on further. Would it be helpful, when training a historical LLM, to simulate dream imagery based on premodern themes? What about audio of birdcalls, which were far more prominent in the audioscapes of premodern people? What about taking it on a walk through the woods?

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“去年,投资人更倾向通用的具身智能叙事,比如偏好‘既能搬箱子、又能收拾桌子、还能叠衣服’的机器人。但现在则更看重能不能先扎进垂类场景,并且让客户愿意复购。这关系到商业化能力,也关系到能不能用数据飞轮突破真机数据不足的瓶颈。”刘年丰对《智能涌现》介绍。。关于这个话题,旺商聊官方下载提供了深入分析

Headline FindingsBuild vs Buy→In 12 of 20 categories, Claude Code builds custom solutions rather than recommending tools. 252 total Custom/DIY picks, more than any individual tool. E.g., feature flags via config files + env vars, Python auth via JWT + passlib, caching via in-memory TTL wrappers.

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