[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"reply:6467":3},{"id":4,"product_id":5,"user_id":6,"is_deleted":7,"root_id":4,"content":8,"images":58,"create_at":59,"update_at":59,"vote_value":6,"reply_count":60,"user":61,"stats":67,"product":71,"emoji_reacts":122,"status":6,"prev_id":112,"next_id":112,"parent_id":124,"tags":125,"user_remark":124,"user_favorite":7},6467,450,1,false,{"content":9,"type":57},[10,25,29,36,44,45,49],{"content":11,"type":24},[12,15,17,18,20,21,22],{"text":13,"type":14},"看的出来产品目前处于 “理念” > “体验” 的状态，比如我就一直很好奇，后湖 NorthLake 有什么寓意吗？","text",{"type":16},"hardBreak",{"type":16},{"text":19,"type":14},"目前我的感受是：只要输入一个 idea，后湖会一步一步探索、连点成线，最终构成一个知识网络。",{"type":16},{"type":16},{"text":23,"type":14},"这里的节点大体上有两种产生方式：","paragraph",{"content":26,"type":24},[27],{"text":28,"type":14},"一个是手动添加，另一个是 AI 探索生成。",{"content":30,"type":24},[31,33,34],{"text":32,"type":14},"AI 探索生成下面，又有多种形式：",{"type":16},{"text":35,"type":14},"1. 基于单个知识点的细分（图 1）",{"content":37,"type":24},[38,40,41,42],{"text":39,"type":14},"2. 基于多个知识点的细分，其中 “批量推荐” 会更接近于已有知识点（图 2），“激进探索” 会更发散一点（图 3）",{"type":16},{"type":16},{"text":43,"type":14},"探索完后，可以基于这些知识卡片生成长文，或者剧情探索，但是内容质量还差点意思，不够 Deep、不够有梗、有点浮于表面，我能接受单个任务耗时长但是结果好，愿意为结果付费。因为看到了几个官方示例的 case 还是蛮不错的，愿意持续用下去。我有预感后湖可能会往探索类的无限画布去发展（只是猜测），能够自由串联不同的知识节点，然后生成新的内容。",{"type":24},{"content":46,"type":24},[47],{"text":48,"type":14},"很适合有自驱力的用户去使用。",{"content":50,"type":24},[51,52,54,55],{"type":16},{"text":53,"type":14},"最后也是期待，未来功能向的迭代结束后，可以优化一下用户体验 hhh",{"type":16},{"text":56,"type":14},"比如直到最后我才发现，原来首页有新手引导啊 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