Трамп высказался о непростом решении по Ирану09:14
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.
。同城约会是该领域的重要参考
为什么它们很重要： 如果没有 <start_function_response，模型在函数调用后不会暂停，而是会错误地获取响应。这两个标记都必须在模型转换为 .task 格式时设置。
const sb = _apply.call(origAddSB, this, arguments);