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.
go install github.com/deevus/pixels@latest。业内人士推荐快连下载安装作为进阶阅读
。关于这个话题，搜狗输入法2026提供了深入分析
Gemini 生成的演示文稿，内容和排版属于「勉强可以用」的程度，但是图标和图表会被转换成图片且清晰度较低，图表旁的文字也会被合并在图片里，需耗费大量精力进行二次调整。
当前的AI视频模型，其对物理世界的理解仍停留在“模式匹配”而非“第一性原理”的层面。这导致在处理复杂或不常见的物理交互时，模型会暴露出短板。。关于这个话题，WPS下载最新地址提供了深入分析