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.
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나무 돌보는 ‘자연인’이 월300만원…나무의사 자격증 관심 커지는 이유는[은퇴 레시피]，详情可参考夫子
电池性能随时间衰减的问题，一直是电动车车主和潜在二手车买家的核心关切。然而，该领域的巨大技术进步表明，这些担忧正变得越来越缺乏依据。一项英国研究为此提供了有力证据，该研究分析了来自36家不同制造商的超过8000块电池。