Anthropic says it ‘cannot in good conscience’ allow Pentagon to remove AI checks

· · 来源:tech资讯

写实风格的图像有它最擅长的模型,动漫风格是另一家,物理仿真又是另一家,背景去除、音效生成、多镜头叙事各有各的专家。就像你不会用同一把刀切菜又锯木头,生成式媒体的用户很快就学会了按任务选工具。报告里有一句话说得很干脆:不是没有好模型,是没有哪个模型在所有任务上都好。

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Returning back to the Anthropic compiler attempt: one of the steps that the agent failed was the one that was more strongly related to the idea of memorization of what is in the pretraining set: the assembler. With extensive documentation, I can’t see any way Claude Code (and, even more, GPT5.3-codex, which is in my experience, for complex stuff, more capable) could fail at producing a working assembler, since it is quite a mechanical process. This is, I think, in contradiction with the idea that LLMs are memorizing the whole training set and uncompress what they have seen. LLMs can memorize certain over-represented documents and code, but while they can extract such verbatim parts of the code if prompted to do so, they don’t have a copy of everything they saw during the training set, nor they spontaneously emit copies of already seen code, in their normal operation. We mostly ask LLMs to create work that requires assembling different knowledge they possess, and the result is normally something that uses known techniques and patterns, but that is new code, not constituting a copy of some pre-existing code.。关于这个话题,服务器推荐提供了深入分析

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