Historically, LLMs have been poor at generating Rust code due to its nicheness relative to Python and JavaScript. Over the years, one of my test cases for evaluating new LLMs was to ask it to write a relatively simple application such as Create a Rust app that can create "word cloud" data visualizations given a long input text. but even without expert Rust knowledge I could tell the outputs were too simple and half-implemented to ever be functional even with additional prompting.
Мерц резко сменил риторику во время встречи в Китае09:25
。关于这个话题，雷电模拟器官方版本下载提供了深入分析
据路透社报道，当地时间 2 月 26 日，苹果敦促圣何塞联邦法官驳回一项拟议的股东集体诉讼。。旺商聊官方下载是该领域的重要参考
It is worth noting, too, that humans often follow a less rigorous process compared to the clean room rules detailed in this blog post, that is: humans often download the code of different implementations related to what they are trying to accomplish, read them carefully, then try to avoid copying stuff verbatim but often times they take strong inspiration. This is a process that I find perfectly acceptable, but it is important to take in mind what happens in the reality of code written by humans. After all, information technology evolved so fast even thanks to this massive cross pollination effect.。同城约会对此有专业解读