主干道被乱停的车辆堵得水泄不通，路边散落着蔫掉的菜叶和塑料垃圾，地面上散布着不少干涸的痰迹。街道的脏乱仿佛成了一种默许，违停与垃圾不再被视为问题。鸣笛声此起彼伏，人们谈论的多是家长里短，而非“头上的星空与心中的道德律”。在这样的环境里，我们也不自觉地爱上议论是非、拆解他人。
一群研究人員決定測試「正向思考」是否能提高人工智慧（AI）聊天機器人的準確率，結果卻出乎意料。他們向不同的聊天機器人提問，嘗試稱讚它們「聰明」，鼓勵它們認真思考，甚至在問題結尾加上一句「這會很有趣！」。然而，這些方法都沒有產生一致的效果，但其中一種方法脫穎而出。當他們讓AI假裝自己身處《星際迷航》場景，它的基礎數學能力竟然有所提升。看來，它真的能把我傳送上去。
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英國首名嬰兒透過已故捐贈者子宮移植誕生
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Can these agent-benchmaxxed implementations actually beat the existing machine learning algorithm libraries, despite those libraries already being written in a low-level language such as C/C++/Fortran? Here are the results on my personal MacBook Pro comparing the CPU benchmarks of the Rust implementations of various computationally intensive ML algorithms to their respective popular implementations, where the agentic Rust results are within similarity tolerance with the battle-tested implementations and Python packages are compared against the Python bindings of the agent-coded Rust packages: