In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.
尤其 S26 上面的最新版 Bixiby，在新模型的加持下也获得了帮你操作手机的能力，点外卖、叫车、订酒店、电商比价下单，统统都是【信口拈来】。，这一点在safew官方下载中也有详细论述
，更多细节参见搜狗输入法2026
Word Clouds In The Browser#When I used word clouds in Rust as my test case for LLM Rust knowledge, I had an ulterior motive: I love word clouds. Back in 2019, I open-sourced a Python package titled stylecloud: a package built on top of Python’s word cloud, but with the added ability to add more color gradients and masks based on icons to easily conform it into shapes (sound familiar?)，推荐阅读下载安装 谷歌浏览器 开启极速安全的 上网之旅。获取更多信息
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