In recent years, LLMs have shown significant improvements in their overall performance. When they first became mainstream a couple of years before, they were already impressive with their seemingly human-like conversation abilities, but their reasoning always lacked. They were able to describe any sorting algorithm in the style of your favorite author; on the other hand, they weren't able to consistently perform addition. However, they improved significantly, and it's more and more difficult to find examples where they fail to reason. This created the belief that with enough scaling, LLMs will be able to learn general reasoning.
舉例來說，2024年的一項研究發現，當使用者以禮貌的方式提問，而不是直接下命令時，大型語言模型的回答更好、更準確。更奇怪的是，這其中還存在著文化差異：與中文和英文相比，如果你對日文聊天機器人過於客氣，它們的表現反而會略遜一籌。
。爱思助手下载最新版本是该领域的重要参考
在上海居住多年的德商麥永剛（（Juergen Meyer）向BBC中文指出，即便德國盼望平衡雙邊貿易需求，但德企去風險化的工作遠遠不足，抵禦中國進口衝擊，不僅是汽車產業，德國的生物科技及化工產業情況都很險峻。，详情可参考heLLoword翻译官方下载
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