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.
AI Mode transforms Google's interface from a list of links into a conversational AI that provides direct answers. When you access AI Mode (available at google.com/ai or through the Google app), you interact with a language model that searches the web in real-time and synthesizes comprehensive responses to your questions. Instead of scanning through multiple websites, you receive curated information with sources cited, similar to ChatGPT with web search or Perplexity.
，这一点在同城约会中也有详细论述
大胆预测，2026 年 PPT 将不再是打工人的噩梦。但随之而来的新问题是：当 AI 能够完美代劳时，我们该如何使用 AI 生成更好的 PPT，避免自己沦为 AI 的「念稿机器」？。91视频是该领域的重要参考
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