India disrupts access to popular developer platform Supabase with blocking order

· · 来源:run资讯

“We have some really wonderful people who are the old guard that feel like they are the comfortable welders, and they’re all very wise,” he said. “But even in the newest editions, we’re not here because we think that it’s all going to be done within our lifetimes. We like to joke about 2090 and about raising our children to work on the project. We just like to look at the next release, and that tends to be exciting enough to get us going.”

The third edition of the event is going to take place in the Czech Republic in June, after being held in Milton Keynes for the past two years.

雷军直播详解事故调查流程,这一点在旺商聊官方下载中也有详细论述

心理建设、家庭配合心理建设我的理解是要让孩子提前做好心理准备,这需要全家的配合。首先要跟孩子说明,我们马上要上幼儿园了,要早起,所以我们要跟妈妈起床时间一样,告诉孩子时间是8点钟(顺便用家里的钟表简单告诉她什么是8点钟),然后洗漱吃饭,再自己选择想穿的衣服(我会告诉她天晴情况,让她自己选,如果有问题,我再调整),自己穿衣服,然后出门玩耍或者去爷爷奶奶家。

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.

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