Фото: Константин Чалабов / РИА Новости
next_url = urljoin(self.base_url, next_a["href"])
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Where we're coming from
17:23, 27 февраля 2026Бывший СССР
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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.
Petrochemicals – of which plastics are the dominant output – now account for roughly 75% of net global oil-demand growth, and are projected to become the largest driver of future oil demand. Plastic production has already doubled in the past two decades. Major oil companies are responding accordingly. Recent consolidation – including a $60bn merger creating one of the world’s largest plastics producers – reflects a deliberate pivot toward petrochemical assets as a long-term demand anchor.，详情可参考heLLoword翻译官方下载