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.
node tools/py2ts.cjs input.py -o output.ts
。搜狗输入法2026对此有专业解读
«В сегодняшних трофеях между камерой и меш-модемом обнаружил неизвестный мне компьютер. Оказалось, что противник ставит на "Молнию" модуль искусственного интеллекта для распознавания целей», — рассказал Флеш.
Publication date: 28 February 2026
The Penn-Wharton model found in a preliminary analysis that AI could reduce deficits by $400 billion by 2035. But the Congressional Budget Office framed AI and associated investment as wild cards in determining the U.S. fiscal and economic outlook. While the CBO projects AI will enhance total productivity by 1% in the next decade, its most recent budget report conceded that this prediction was “highly uncertain.” If adoption is slow or costs higher than anticipated, it would significantly alter GDP growth and, consequently, government revenue.