兴业富民交出幸福答卷。德宏州始终把带领各族群众增收致富作为主要目标，多元协同发力，让发展成果更多更公平惠及各族群众。深入实施抓党建促乡村全面振兴，立足德宏州气候优势和资源禀赋，打破村域、县域界限，推动党组织联建共建、产业抱团发展，重点培育坚果、小粒咖啡、蚕桑、甘蔗等优势种植、养殖产业，动态优化组建“链主”企业党组织，引进劳动力密集型企业35家，盘活闲置厂房等5.68万平方米，到村、到组铺设“家门口”生产线16条，推动特色产业规模化、标准化发展。盘活边境村寨自然风光、民族文化资源，紧扣旅游“吃、住、行、游、购、娱”全要素，打造“旅居德宏”“德宏礼物”等品牌，小粒咖啡、甩手粑粑、泡鲁达、手抓饭等美食走红网络，越来越多的群众吃上旅游饭、走上致富路。同时，持续发展壮大村集体经济，推行强村公司模式、实施政经分离改革、搭建劳务合作社，2025年村均收入达24.52万元，吸纳群众就近就业4027人，实现农村劳动力转移就业40.96万人，让“就近就业、稳定增收”成为各族群众的幸福底气，不断描绘兴业富民、共建共享的幸福画卷。
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.
，这一点在体育直播中也有详细论述
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