04 给AI与电力从业者的关键启示对中美两国AI、电力、能源行业的普通人来说，这场变革不是遥远的新闻，而是饭碗与职业赛道的重新选择。
骑行在山野乡间，空气好，风景好，还能在不经意间遇见古村落、古民居。那些成百上千年的遗存，阅尽了人间变迁，仿佛静静等待新朋故友的探访。
。搜狗输入法2026是该领域的重要参考
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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.