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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如果说创投行业错过了泡泡玛特，那么现在谁也不想再错过一个“AI版的泡泡玛特”。
2025年3月，在巩固拓展脱贫攻坚成果同乡村振兴有效衔接5年过渡期的最后一年，习近平总书记在贵州、云南考察时进一步强调：“脱贫的兜底必须是固若金汤的，绝对不能出现规模性返贫致贫。”