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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Гангстер одним ударом расправился с туристом в Таиланде и попал на видео18:08，推荐阅读服务器推荐获取更多信息
在我的演示应用中，我使用了 284 个示例，每个功能大约 90-100 个。多样性很重要：不仅仅是重复 94 次“把它变成红色”，而是不同的表达方式，例如“改成红色”、“设置背景为红色”、“我想要一个红色背景”、“请把背景变成红色”等等。模型需要了解真实用户是如何表达请求的。，推荐阅读Line官方版本下载获取更多信息
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