AI不需要用户精确表达需求。"周末露营带什么吃的"这样模糊的、场景化的描述就能被理解和转化为具体的商品推荐。它不需要用户耗费精力搜索、比价、筛选，两三轮对话就能走完从需求理解到下单的全流程。基于用户个性化的信息和意图理解，AI甚至能推荐用户"自己都没想到"的解决方案，帮助用户发现新品牌和新产品。
In Mongo, when using w: 1 in a write concern, the write operation is acknowledged after being successfully applied to the primary's instance memory. However, w: 1 alone does not guarantee durability unless combined with j: true (journaling). Running standalone Mongo, as we did in the tests, defaults to j: false. I have explicitly set it to true in the testing script to make write comparisons to Postgres objective. You can dive deeper into this here: https://www.mongodb.com/docs/manual/reference/write-concern/#acknowledgment-behavior and here: https://www.mongodb.com/docs/manual/core/journaling/. Unfortunately, docs are a bit convoluted about it
，更多细节参见新收录的资料
优点：输出范围在 (0,1)，可以表示概率
伊朗此前已為這種可能性做好準備，有報導指，不僅哈梅內伊，其他多名高層官員的接替方案亦已制定。
当开发者尝试去做端侧大语言模型推理时，会发现虽然这些电脑名为 AI PC，但并没针对 AI 推理用途做什么优化。微软 Copilot 本身的核心算力来自 Azure 云端，和端侧自身的算力几乎无关。买了一台 Windows AI PC 的用户，最能感知到的 AI 提升，大概是实时字幕和照片自动分类。