每轮遍历后，最大元素会"冒泡"到末尾
「我認為這提醒我們，要把握每一個機會告訴大家冷靜下來，拜託，我們不能把一切視為理所當然。」
4 days agoShareSave。Line官方版本下载是该领域的重要参考
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.，更多细节参见WPS官方版本下载
"There has to be a better way in line with our history," Isaacman said. "We did not just jump right to Apollo 11. We did it through Mercury, Gemini, and lots of Apollo missions, with a launch cadence every three months. We shouldn't be comfortable with the current cadence. We should be getting back to basics and doing what we know works."
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