--- title: "AI 深度播客与视频 - 信源与标准 - AI·外脑 | 思行致远" canonical: "https://siyuanailab.com/knowledge/sources/ai-podcasts-videos-directory/" dateModified: "2026-07-07" datePublished: "2026-07-07" --- 打开 AI·外脑目录 AI·外脑 [返回专栏首页](https://siyuanailab.com/knowledge/) × 站内搜索 ⌕ 主要栏目 - [AI 核心概念](https://siyuanailab.com/knowledge/ai-core/) - [工作流](https://siyuanailab.com/knowledge/workflows/) - [工具配置与选型](https://siyuanailab.com/knowledge/toolkits/) - [信源与标准](https://siyuanailab.com/knowledge/sources/) - [场景案例 待开发](https://siyuanailab.com/knowledge/scenarios/) - [职业与能力](https://siyuanailab.com/knowledge/career/) 专题 - [从这里开始](https://siyuanailab.com/knowledge/start/) - [获取与安装](https://siyuanailab.com/knowledge/install/) - [建设日志](https://siyuanailab.com/knowledge/ops/) [信源与标准子目录](https://siyuanailab.com/knowledge/sources/) 信源分级与框架（1） - [AI 学习信源：如何分级与使用](https://siyuanailab.com/knowledge/sources/ai-source-principle/) 官方文档与产品更新（6） - [Google AI 官方动态](https://siyuanailab.com/knowledge/sources/google-ai-official-updates/) - [MCP 官方文档](https://siyuanailab.com/knowledge/sources/mcp-official-docs/) - [Midjourney 官方文档](https://siyuanailab.com/knowledge/sources/midjourney-official-docs/) - [OpenAI 官方文档](https://siyuanailab.com/knowledge/sources/openai-official-docs/) - [Anthropic 官方文档](https://siyuanailab.com/knowledge/sources/anthropic-official-docs/) - [AI 官方文档与产品更新](https://siyuanailab.com/knowledge/sources/ai-official-docs-directory/) 研究论文与预印本（6） - [Anthropic Research](https://siyuanailab.com/knowledge/sources/anthropic-research/) - [arXiv](https://siyuanailab.com/knowledge/sources/arxiv/) - [Google Research Blog](https://siyuanailab.com/knowledge/sources/google-research-blog/) - [Lilian Weng](https://siyuanailab.com/knowledge/sources/lilian-weng/) - [OpenAI Research](https://siyuanailab.com/knowledge/sources/openai-research/) - [AI 研究论文与预印本](https://siyuanailab.com/knowledge/sources/ai-research-papers-directory/) 权威媒体与机构洞察（7） - [a16z AI](https://siyuanailab.com/knowledge/sources/a16z-ai/) - [MIT Technology Review AI](https://siyuanailab.com/knowledge/sources/mit-technology-review-ai/) - [Sequoia AI](https://siyuanailab.com/knowledge/sources/sequoia-ai/) - [TechCrunch AI](https://siyuanailab.com/knowledge/sources/techcrunch-ai/) - [The Verge AI](https://siyuanailab.com/knowledge/sources/the-verge-ai/) - [Y Combinator Blog](https://siyuanailab.com/knowledge/sources/y-combinator-blog/) - [AI 权威媒体与机构洞察](https://siyuanailab.com/knowledge/sources/ai-media-insights-directory/) 深度播客与视频（6） - [AI & I](https://siyuanailab.com/knowledge/sources/ai-and-i/) - [Andrej Karpathy（YouTube）](https://siyuanailab.com/knowledge/sources/andrej-karpathy-youtube/) - [Google DeepMind Podcast](https://siyuanailab.com/knowledge/sources/google-deepmind-podcast/) - [Latent Space](https://siyuanailab.com/knowledge/sources/latent-space/) - [Lenny's Podcast](https://siyuanailab.com/knowledge/sources/lennys-podcast/) - [AI 深度播客与视频](https://siyuanailab.com/knowledge/sources/ai-podcasts-videos-directory/) Newsletter 与策展者（7） - [AI Valley](https://siyuanailab.com/knowledge/sources/ai-valley/) - [AINews by smol.ai](https://siyuanailab.com/knowledge/sources/ainews-by-smol-ai/) - [Ben's Bites](https://siyuanailab.com/knowledge/sources/bens-bites/) - [Every](https://siyuanailab.com/knowledge/sources/every/) - [Peter Yang (Behind the Craft)](https://siyuanailab.com/knowledge/sources/peter-yang/) - [Zara's AI learning library](https://siyuanailab.com/knowledge/sources/zaras-ai-learning-library/) - [AI Newsletter 与策展者](https://siyuanailab.com/knowledge/sources/ai-newsletters-curators-directory/) 社交媒体账号（6） - [Andrej Karpathy（X）](https://siyuanailab.com/knowledge/sources/andrej-karpathy-x/) - [Greg Isenberg（X）](https://siyuanailab.com/knowledge/sources/greg-isenberg-x/) - [Justine Moore（X）](https://siyuanailab.com/knowledge/sources/justine-moore-x/) - [Lenny Rachitsky（X）](https://siyuanailab.com/knowledge/sources/lenny-rachitsky-x/) - [Swyx（X）](https://siyuanailab.com/knowledge/sources/swyx/) - [AI 社交媒体账号](https://siyuanailab.com/knowledge/sources/ai-social-accounts-directory/) 信源与标准 · 进阶 # AI 深度播客与视频 杨思远 / 思行致远 · 2026/7/7 · 置信度：高 信源AI播客AI视频学习资源独立站 长视频和深度播客适合建立直觉，但不适合作为事实基准；把它们当作第 3 级信源使用。 # AI 深度播客与视频 > 长视频和深度播客适合建立直觉，但不适合作为事实基准；把它们当作第 3 级信源使用。 --- ## 一、是什么 这张卡整理 AI 领域值得长期关注的深度播客与视频来源。与官方文档不同，它们的价值不在于提供精确参数，而在于呈现一线 builder 的思考方式、产品判断和研究背后的故事。 ## 二、为什么存在 AI 领域变化快、噪音多，三类需求很突出： - **建立直觉**：长视频和深度访谈能把一个复杂概念讲透，比短文更适合入门。 - **理解一线判断**：创始人、研究员、产品负责人会分享决策过程，这些是文档里读不到的。 - **发现新工作流**：builder 常在播客里展示自己怎么用 AI 工具，容易触发迁移到自己的场景。 ## 三、核心机制 | 来源 | 形态 | 定位 | 一句话价值 | 代表作品/入口 | 细节卡 | | --- | --- | --- | --- | --- | --- | | Andrej Karpathy（YouTube） | 长视频 | AI 教育与基础概念 | 用工程视角把 LLM、神经网络讲清楚 | [https://www.youtube.com/@AndrejKarpathy](https://www.youtube.com/@AndrejKarpathy) | [Andrej-Karpathy-YouTube](https://siyuanailab.com/knowledge/sources/andrej-karpathy-youtube/) | | Latent Space | 播客 + Newsletter | AI 工程深度访谈 | 连接研究前沿与工程落地 | [https://www.latent.space/](https://www.latent.space/) | [Latent-Space](https://siyuanailab.com/knowledge/sources/latent-space/) | | Lenny’s Podcast | 播客 | 产品、增长、职业 | 产品领袖的决策与组织经验 | [https://www.lennysnewsletter.com/podcast](https://www.lennysnewsletter.com/podcast) | [Lennys-Podcast](https://siyuanailab.com/knowledge/sources/lennys-podcast/) | | Google DeepMind Podcast | 播客 | AI 研究与科学应用 | 听 Google DeepMind 研究员讲前沿项目 | [https://deepmind.google/discover/the-podcast/](https://deepmind.google/discover/the-podcast/) | [Google-DeepMind-Podcast](https://siyuanailab.com/knowledge/sources/google-deepmind-podcast/) | | AI & I | 播客 | AI 在日常工作流中的应用 | 看顶尖从业者如何把 AI 嵌入知识工作 | [https://www.every.to/ai-and-i](https://www.every.to/ai-and-i) | [AI-and-I](https://siyuanailab.com/knowledge/sources/ai-and-i/) | ## 四、常见误解 | 误解 | 真相 | | --- | --- | | 播客/视频可以作为事实依据 | 口述内容容易有时间错配和记忆偏差，关键参数要回查官方文档 | | 看得多等于学得多 | 长内容消费密度低，必须配合笔记、实践和输出 | | 热门视频一定值得看 | 算法推荐偏向情绪共鸣，要主动筛选与自己问题相关的来源 | | 只听中文内容就够了 | AI 一线讨论仍以英文为主，中文内容往往滞后 | ## 五、怎么用 ### Level 0：建立固定入口 把这张卡里的 5 个来源加入播客 App 或订阅列表，避免每次现找。 ### Level 1：带着问题听 开始前写下一个具体问题，例如： - “Claude Code 的适用边界在哪里？” - “AI Agent 产品化有哪些失败案例？” 听完用一句话回答这个问题。 ### Level 2：与官方文档交叉验证 播客里听到的功能、参数、价格，要回查官方文档或 Release Notes。特别是快速发展的产品。 ### Level 3：沉淀为卡片或工作流 把听到的具体做法、判断框架、失败案例写入知识库，或迁移进自己的工作流。 ## 六、延伸阅读 - 原则卡：[AI学习信源-如何分级与使用](https://siyuanailab.com/knowledge/sources/ai-source-principle/) - 目录卡：[AI官方文档与产品更新](https://siyuanailab.com/knowledge/sources/ai-official-docs-directory/) - 外部参考：Zara’s AI learning library 中的 Video Podcasts 清单 ### 适用场景与行动 **场景：**需要建立 AI 深度播客与视频 的信源目录和选择顺序时。 **适合谁：**想通过长内容理解 AI 趋势的创始人、产品人、内容创作者。 **下一步：**按卡片中的分级与链接挑选 2-3 个来源，放入自己的固定阅读清单。 ### 相关卡片 - ai-source-principle - andrej-karpathy-youtube - latent-space - lennys-podcast - google-deepmind-podcast - ai-and-i 这张卡片由杨思远基于真实工作流和实测经验整理。 如发现信息过时或有误，可通过 [/contact](https://siyuanailab.com/contact) 反馈。 [← 上一张：AI 官方文档与产品更新](https://siyuanailab.com/knowledge/sources/ai-official-docs-directory/) [下一张：AI 研究论文与预印本 →](https://siyuanailab.com/knowledge/sources/ai-research-papers-directory/) [返回 AI·外脑入口](https://siyuanailab.com/knowledge/)