当圣经AI教我玩植2，会发生什么猎奇事件！！！

9月最强无限制ai聊天软件，免费畅玩且无限制，堪比酒馆和的电子魅魔，内置多种模型线路，无论是瑟瑟还是剧情都可随意爽玩！

“人工智能+行动”发布：代替房地产，新一轮产业红利拉开序幕

“人工智能+行动”发布：代替房地产，新一轮产业红利拉开序幕

手把手教ai写口播

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AI视频神器，爆款制造机

当人工智能遇上脑筋急转弯#万万没想到#搞笑视频

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阿尔伯特挑战一二三木头人！他能顺利通关吗？

【没啥用科技】智能脖环，为梦想窒息！

没啥用科技最新发布：莓用智能脖环Useless Hoop，欢迎大家投币预定哦~ 导演:郭毅 文案: 郭毅 秦子旭 拍摄:孔二宝 窦家浩 产品设计:韩伯宇 申希 三维动画:韩伯宇 张宏禹 申希 王朗 平面视觉设计: 张晓明 姚紫藤 出镜演员：杜凯彦 申思 Demo 本身纯属娱乐请勿当真 部分内容由AI参与制作

【老司机必备】Deepseek与Grok的破甲指令，不撤回爽玩的最佳选择！

全网首发！五大AI引擎协同平台正式上线 Gemini2.5Pro、Grok-3和4、GPT5、满血版DeepSeek、Claude-sonnet4、Kimi-k2全都有 同时还有各种指令与教程。纯公益Al站点，免费使用体验! ヾ(•ω•`)o 评论区与简介放不了链接，请三连关注up并评论哦，看到了都会回的!(～￣▽￣)～

天猫精灵猜人物之贺峻霖！

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一口气学会如何思考AI Agent系统设计

This is how I think through designing a full stack AI Agent System, with all key concepts you need -- Vector Database, Retrieval-Augmented Generation (RAG), Semantic Search & Policy Checks, Function Calling and more. The use case I picked is to manage e-Commerce customer support. You can learn it even if you don't come from a technical background. You can build anything. You can learn anything. 💪 Launch Full-Stack App Template: https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase ☕️ Buy me a coffee: https://buy.stripe.com/5kA176bA895ggog4gh - X: https://x.com/ShenSeanChen - Discord: https://discord.gg/TKKPzZheua - LinkedIn: https://linkedin.com/in/shen-sean-chen - Github Link: https://github.com/ShenSeanChen - Instagram: https://www.instagram.com/sean_tech_stories Timeline 00:00 Intro 00:23 Problem to Solve Today 00:59 Goals 02:13 Rules of the Scope 03:39 Backend & Database 04:13 Vector Database VS Relational DB 04:38 What's a Vector Database 05:31 Sketch the AI Agent System Design 05:53 User Auth Gateway 06:32 CRUD with Relational DB 06:49 How Would AI Agents Interact with User Chats 07:08 Introducing Router Agent 07:38 Q&A AI Agent (The Brain/CEO) 08:36 When to Loop in Humans? 09:20 How the Router Agent Proceeds 09:33 Planner Agent 09:58 What is Functional Calling? 10:15 Tools & APIs 11:24 Should We Use AI Agents or Deterministic Workflows 12:28 Retrieval-Augmented Generation (RAG) + Vector Database 14:39 What Happens after RAG 15:45 The Q&A Agent 17:02 AI Agent System Design Overview 17:10 Observability, Metrics, Evals 17:49 CRM Integration 18:29 Final Overview