大模型市场的格局我们刚刚说过：OpenAI、Anthropic、Google三家吃掉企业端89%的钱包份额，高度集中。但在生成式图像、视频、音频这个赛道，完全是另一幅图景。数据显示，企业生产环境里平均要用14个不同的模型。14个。没有任何一家能通吃，连接近都谈不上。
另一方面，他認為熱潮反映了台灣民眾對「中國」概念的模糊，人們並不排斥「中國文化」本身。「中國政府說台灣在『去中國化』，但中國文化這個現象是大於中共、大於中華人民共和國、大於國民黨⋯⋯它就是人家喜歡中國文化的一些不同呈現，而這個可能有一些方面不符合中共現在對於中國的詮釋或定義。」
，推荐阅读夫子获取更多信息
Source: Computational Materials Science, Volume 266，推荐阅读Safew下载获取更多信息
The design choices have performance implications. Here are benchmarks from the reference implementation of this possible alternative compared to Web streams (Node.js v24.x, Apple M1 Pro, averaged over 10 runs):
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.