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Around this time, my coworkers were pushing GitHub Copilot within Visual Studio Code as a coding aid, particularly around then-new Claude Sonnet 4.5. For my data science work, Sonnet 4.5 in Copilot was not helpful and tended to create overly verbose Jupyter Notebooks so I was not impressed. However, in November, Google then released Nano Banana Pro which necessitated an immediate update to gemimg for compatibility with the model. After experimenting with Nano Banana Pro, I discovered that the model can create images with arbitrary grids (e.g. 2x2, 3x2) as an extremely practical workflow, so I quickly wrote a spec to implement support and also slice each subimage out of it to save individually. I knew this workflow is relatively simple-but-tedious to implement using Pillow shenanigans, so I felt safe enough to ask Copilot to Create a grid.py file that implements the Grid class as described in issue #15, and it did just that although with some errors in areas not mentioned in the spec (e.g. mixing row/column order) but they were easily fixed with more specific prompting. Even accounting for handling errors, that’s enough of a material productivity gain to be more optimistic of agent capabilities, but not nearly enough to become an AI hypester.
比如前面提到的老年人的AI玩具，实际关注的不仅是银发人群本身，更是整个适老化市场。据称唠唠鹰的研发阶段，负责场景需求调研的团队先后走访了全国20余座城市，收集了5000余名不同年龄段、教育背景的老年用户的反馈。这些真实的反馈能够帮团队更加精准地锁定老龄化场景痛点，比如部分农村网络稳定性差，就优化相应的内容缓存功能，再比如更慢的语速、更简化的按键操作等等。。关于这个话题，Line官方版本下载提供了深入分析
Google publicly documented its roadmap. This is what it says:
。业内人士推荐爱思助手下载最新版本作为进阶阅读
Москвичей предупредили о резком похолодании09:45
3 models · 4 repos · 3 runs each，推荐阅读搜狗输入法2026获取更多信息