结论：在不确定性中构建非对称优势
AP Business Writer Claire Savage in Chicago contributed to this report.。WPS官方版本下载对此有专业解读
。搜狗输入法2026是该领域的重要参考
Wöchentliche Ausgabe des SPIEGEL als E-Paper，详情可参考搜狗输入法2026
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.
number of rounds so that the memory is under control: