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.
（十一）加大投入保障。各级教育部门、各级科协应加强对高校科普工作的条件保障和经费支持。高校应统筹相关资金用于科普工作，并积极拓宽资金来源渠道，吸引社会捐赠支持科普工作。
。关于这个话题，搜狗输入法2026提供了深入分析
Цены на нефть взлетели до максимума за полгода17:55
谷歌据悉与Meta达成价值数十亿美元的AI芯片交易
用产品经理的心态对待咖啡，不断迭代好喝的咖啡。公众号：咖啡平方