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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.
。safew官方下载是该领域的重要参考
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如何把一株紫苏“吃干榨尽”?沈奇团队研究发现,紫苏富含挥发油、酚酸类以及花青素类物质,具有强抗氧化、抗炎、抗过敏、抗菌、抗病毒等功效。紫苏酚酸以迷迭香酸为主,高光可诱导紫苏迷迭香酸含量大幅提高。该团队基于应用需求开展品质定向选育,成功选育紫苏优良新品种7个,并对紫苏抗衰老的作用和功效物质进行深入研究。