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.
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Q.ai 的核心技术是肌电图（EMG）与微表情分析，这听起来像赛博朋克小说里的设定，但原理其实非常生物学：当我们想要说话时，大脑会向发声器官发送神经电信号。即使我们最终压低声音、甚至根本没有发出声音，喉咙、下颌和脸颊的肌肉依然会产生微弱的生物电波动。
Раскрыты подробности похищения ребенка в Смоленске09:27，更多细节参见搜狗输入法2026