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.
智能体能力的构成为了在各行各业的应用中发挥出显著价值，理想中的智能体需要具备几个关键条件。
。关于这个话题，同城约会提供了深入分析
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System Settings
。关于这个话题，WPS官方版本下载提供了深入分析
Appendix I: Candidate Sorting。业内人士推荐雷电模拟器官方版本下载作为进阶阅读
When asked about that capability Thursday by The Associated Press, Burger King said the intent is to use Patty as a coaching tool, not a tracker of individual employees.