與葡萄牙語一樣，我每天要完成四個簡短的任務與測驗；但這次我需要將 12 個完全聽不懂的聲音，配對到 12 個從未見過的物體圖片上。後來我才得知，這些物體與詞彙都不是真實存在的。我口中念出的其實是中文的聲調，而聲調是中文的重要特徵：不同聲調會改變一個詞的意思。
Москвичи пожаловались на зловонную квартиру-свалку с телами животных и тараканами18:04
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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.
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激活函数虽然只是神经元里的一小步，但却是深度学习的一大步。没有它，深度学习就不会有今天的辉煌。它让神经网络从“线性堆叠”变成了真正的“非线性智能体”，能够处理复杂的视觉、语言和跨模态任务。
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