增值税法第二十二条第三项所称非正常损失项目，包括：
三月初，苹果春季发布会将带着 iPhone 17e 和新 MacBook 系列如期而至；视线投向海外，小米的 Leitz Phone 悄然现身，荣耀的 Robot Phone 也将在 MWC 上正式亮相，视线转向传统手机形态，vivo X300 Ultra 与 OPPO Find N6 正在步步靠近……，更多细节参见爱思助手下载最新版本
个人向：本机MAC部署OpenClaw过程记录。WPS官方版本下载对此有专业解读
It’s Not AI Psychosis If It Works#Before I wrote my blog post about how I use LLMs, I wrote a tongue-in-cheek blog post titled Can LLMs write better code if you keep asking them to “write better code”? which is exactly as the name suggests. It was an experiment to determine how LLMs interpret the ambiguous command “write better code”: in this case, it was to prioritize making the code more convoluted with more helpful features, but if instead given commands to optimize the code, it did make the code faster successfully albeit at the cost of significant readability. In software engineering, one of the greatest sins is premature optimization, where you sacrifice code readability and thus maintainability to chase performance gains that slow down development time and may not be worth it. Buuuuuuut with agentic coding, we implicitly accept that our interpretation of the code is fuzzy: could agents iteratively applying optimizations for the sole purpose of minimizing benchmark runtime — and therefore faster code in typical use cases if said benchmarks are representative — now actually be a good idea? People complain about how AI-generated code is slow, but if AI can now reliably generate fast code, that changes the debate.
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