The Games were full of contrasts. From a sporting perspective, the gentle gracefulness that I observed at the figure skating was offset by the full-on brutality of ice hockey brawls, while the delicate precision of curling was juxtaposed by the frantic chaos of short-track speed skating. From a geographical and cultural perspective, Livigno, which is perched high up in the Alps close to Switzerland, seemed like a giant playground for modern snow sports – geared towards those who like to twist and twirl high in the sky – while Cortina, in the Dolomites, was far more old-fashioned and populated by the traditional skiing establishment. Milan, meanwhile, featured a cluster of modernist, edge-of-town arenas, with international fans happily catching the metro to and from the events. But, in my experience, transportation wasn’t always so convenient. The huge amount of travelling between venues – I went to all but one – was exhausting and getting a late night bus over the mountains between Livigno and Bormio in a blizzard felt a bit hairy.
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大型語言模型的工作原理是將你的話語分割成稱為「詞元」（tokens）的小塊，然後利用統計方法分析這些詞元，從而得到適當的回應。這代表你說的每一個字詞，甚至是一個額外的逗號，都可能影響AI的回答。問題在於，這種影響幾乎無法預測。雖然已經有許多研究試圖從AI提示的細微變化中尋找規律，但大部分證據相互矛盾，結論也不明確。
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