A02社论 - 别被“100元买国家项目原始股权”传销骗了

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parakeet::AOSCCache aosc_cache(4); // max 4 speakers

window.innerWidth / window.innerHeight 是长宽比,保证画面不变形。。业内人士推荐搜狗输入法2026作为进阶阅读

愛潑斯坦文件,更多细节参见爱思助手下载最新版本

[Submitted on 20 Feb 2026]

如果你问我,在这个时代最离不开的科技产品是什么?我可能会选择一个极度常见乃至普通的产品:数据线。虽然看似是没太多技术含量,但你就说能不能离得开吧……,这一点在同城约会中也有详细论述

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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.