Today's Connections: Sports Edition is for people who love sports movies and shows.
为了在相对公平的环境下对比，我决定将人工干预降到最低：只提供基础内容和最简单的指令，以此测试各家软件生成能力的「下限」。这不仅是因为（囊中羞涩）测试积分有限，更为了模拟真实的「开箱即用」场景——毕竟，作为普通用户，大多数人只想要一个能用的 PPT，而不是被强迫系统学习提示词工程。
。关于这个话题，Line官方版本下载提供了深入分析
a16z的报告里举了几个例子，把这个问题讲得很具体。投行分析师用Hebbia，几百份公开文件自动分析完，财务模型直接生成，以前要熬几个通宵做的事情，现在可以去睡觉了。医生用Abridge，它能实时记录医患对话，自动整理病历和后续跟进事项，医生看诊时不用再一边问话一边盯着屏幕敲字。还有做财务对账的Basis，跨系统自动核对试算表，原本需要人工反复比对的工作变成几分钟的事。，这一点在同城约会中也有详细论述
🔟 桶排序 (Bucket Sort)，推荐阅读Line官方版本下载获取更多信息
Git packfiles use delta compression, storing only the diff when a 10MB file changes by one line, while the objects table stores each version in full. A file modified 100 times takes about 1GB in Postgres versus maybe 50MB in a packfile. Postgres does TOAST and compress large values, but that’s compressing individual objects in isolation, not delta-compressing across versions the way packfiles do, so the storage overhead is real. A delta-compression layer that periodically repacks objects within Postgres, or offloads large blobs to S3 the way LFS does, is a natural next step. For most repositories it still won’t matter since the median repo is small and disk is cheap, and GitHub’s Spokes system made a similar trade-off years ago, storing three full uncompressed copies of every repository across data centres because redundancy and operational simplicity beat storage efficiency even at hundreds of exabytes.