不少人曾用特斯拉的例子来辩解——这家公司同样用了 10 年时间才首次实现季度盈利。但特斯拉处于完全不同的发展阶段。2003 年特斯拉成立时新能源汽车还仿佛是天方夜谭，而 2014 年蔚来汽车成立时，特斯拉已经发布了 Model S 及 Model X，且已经正式在中国开启交付。
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2026-03-14 00:00:00:0宋曙光3014525610http://paper.people.com.cn/rmrb/pc/content/202603/14/content_30145256.htmlhttp://paper.people.com.cn/rmrb/pad/content/202603/14/content_30145256.html11921 黄浦江边
What happens when you ask a 2026 coding agent like Claude Code to build a chess engine from scratch (with no plan, no architecture document, no step-by-step guidance) in a language that was never designed for this purpose? Building a chess engine is a non-trivial software engineering challenge: it involves board representation, move generation with dozens of special rules (castling, en passant, promotion), recursive tree search with pruning, evaluation heuristics, as well as a way to assess engine correctness and performance, including Elo rating. Doing it from scratch, with minimal human guidance, is a serious test of what coding agents can do today. Doing it in LaTeX’s macro language, which has no arrays, no functions with return values, no convenient local variables or stack frames, and no built-in support for complex data structures or algorithms? More than that, as far as I can tell, it has never been done before (I could not find any existing TeX chess engine on CTAN, GitHub, or TeX.SE). Yet, the coding agent built a functional chess engine in pure TeX that runs on pdflatex and reaches around 1280 Elo (the level of a casual tournament player). This post dives deep into how this engine, called TeXCCChess, works, the TeX-specific challenges encountered during development. You can play against it in Overleaf (see demo https://youtu.be/ngHMozcyfeY) or your local TeX installation https://youtu.be/Tg4r_bu0ANY, while the source code is available on GitHub https://github.com/acherm/agentic-chessengine-latex-TeXCCChess/。关于这个话题，传奇私服新开网｜热血传奇SF发布站｜传奇私服网站提供了深入分析
Владислав Уткин，详情可参考游戏中心
这一政策信号或许影响了西井科技的上市路径选择。作为上海市重点服务独角兽企业之一，西井科技选择留在A股，而非跟随同行赴港或赴美上市。