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.
Овечкин продлил безголевую серию в составе Вашингтона09:40
The tech industry's biggest mobile show may not quite have the clout it once did, when the likes of Samsung, Sony, LG, and HTC showcased new flagships there each year, but it still attracts more phone launches than CES does two months earlier. It's especially popular with the Chinese manufacturers who are still fighting for space in the global market, along with niche manufacturers who turn up with extra-durable "rugged" devices, or battery beasts that are more powe …，详情可参考heLLoword翻译官方下载
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It can be fine-tuned for specific tasks such as generating images of a certain，详情可参考WPS下载最新地址
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