Мерц резко сменил риторику во время встречи в Китае09:25
淘宝内部的大模型RecGPT数据显示：LLM对"探索圈"（用户发现新品类）的效率提升超过50%，而对"效率圈"（已知偏好匹配）的提升仅为个位数—这是因为传统推荐系统在效率圈的baseline已经非常高。LLM 的核心战场是帮助消费者打破信息茧房、激活长尾供给。
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We also see even experienced users being caught by less obvious LIMIT behavior in multi-node environments where a table has many shards. Sharding allows users to split or replicate their data across multiple instances of ClickHouse. When a query with a LIMIT N clause is sent to a sharded table e.g. via a distributed table, this clause will be propagated down to each shard. Each shard will, in turn, need to collate the top N results, returning them to the coordinating node. This can prove particularly resource-intensive when users run queries that require a full table scan. Typically these are "point lookups" where the query aims to just identify a few rows. While this can be achieved in ClickHouse with careful index design a non-optimized variant, coupled with a LIMIT clause, can prove extremely resource-intensive.
Стало известно о новых планах Германии по УкраинеBloomberg: Германия хочет поставить ракеты-перехватчики на Украину
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