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.
"We’re super excited about this deal," OpenAI CEO Sam Altman told CNBC. "AI is going to happen everywhere." That last statement seems more like a threat than a boast, but I digress.
。业内人士推荐WPS下载最新地址作为进阶阅读
然而，本轮涨价与以往周期最大的不同在于一个关键变量——HBM（高带宽内存）的爆发式增长。AI芯片（如英伟达H200/B200）对HBM的需求是传统DRAM的数倍甚至数十倍。三大原厂将大量先进制程产能转向HBM，挤占了原本用于生产手机LPDDR（低功耗内存）的产能。这种“结构性短缺”成为本轮涨价的核心推手。。爱思助手下载最新版本是该领域的重要参考
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