int n2 = right - mid; // 右子数组长度
另一个被反复忽视的约束，来自抽佣本身的结构变化。早期的抽佣往往表现为清晰的单一比例，但随着平台业务复杂化，收费逐渐被拆分为技术服务费、营销推广费、会员费、广告费等多项组合。抽佣不再是一个价格，而是一套规则。对供给侧而言，理解与比较成本显著上升；对平台而言，收费的可解释性开始影响交易秩序与信任基础。
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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.