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.
You also need to consider things like price and subscription plans, but these features are a good place to start with your selection process. Once you've picked a favorite option, you can consider the wide range of subscription plans on offer from leading services. There should be something that suits everyone.。业内人士推荐搜狗输入法2026作为进阶阅读
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至于基于 NPU 和桌面平台的 LiteRT-LM 运行时，相关工作已经在进行中。一旦 Google 开放 iOS 的公共 API（预计在 2026 年初），我们将添加全面支持。桌面平台也在我们的计划之中——敬请期待，即将推出。
Москвичей предупредили о резком похолодании09:45