最新・注目の動画配信中の動画を見る天気予報・防災情報天気予報・防災情報を確認する新着ニュースキム総書記の妹 ヨジョン氏が朝鮮労働党「総務部長」に就任 午後3:32水戸女性殺害 車に位置情報特定するタグ取り付けたか 再逮捕へ 午後3:24ペットボトル緑茶 値上げの動き 海外の抹茶ブームも影響か 午後2:56トランプ氏 アンソロピックのAI技術 政府機関使わないよう指示 午後2:23新着ニュース一覧を見る各地のニュース地図から選ぶ
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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.