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在这种背景下，人情自然也被冲淡了，心齐和团结才显得尤其珍贵。五奶奶讲起她经历的一桩糗事。10年前的秋季，她想把麦子从地里拉回家，因为麦地夹在沟壑里，没有车能走的路，她就跟亲戚借来一头骡子用。
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他近兩個小時的演說中，只零星提及少數想法，包括為美國勞工階層設立新的退休儲蓄帳戶，以及與AI公司達成協議，提供足夠電力給其工廠，以及避免消費者電費上漲。他還重新推銷一些舊有想法，例如提供直接補助幫助美國人支付醫療保險費用的計劃、要求所有選民證明公民身份的法律，以及禁止向非法移民發放商業駕照。
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.