大胆预测，2026 年 PPT 将不再是打工人的噩梦。但随之而来的新问题是：当 AI 能够完美代劳时，我们该如何使用 AI 生成更好的 PPT，避免自己沦为 AI 的「念稿机器」？
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Crucially, this distribution of border points is agnostic of routing speed profiles. It’s based only on whether a road is passable or not. This means the same set of clusters and border points can be used for all car routing profiles (default, shortest, fuel-efficient) and all bicycle profiles (default, prefer flat terrain, etc.). Only the travel time/cost values of the shortcuts between these points change based on the profile. This is a massive factor in keeping storage down – map data only increased by about 0.5% per profile to store this HH-Routing structure!