The Widening Gap: Are You Ready for the Al Frontier?

a16z当前重点投资的前沿领域想法 | 马克·安德森、本·霍洛维茨与克里斯·迪克森 合伙人们宣布推出 a16z Frontier，将其投资评估逻辑从质疑某个想法是否过于宏大，转变为审视它是否足够宏大以把握巨大的技术变革。他们认为，AI 正将未来二十年的技术发展压缩至当下，赋能小型的跨学科团队去打造全栈硬件、新颖的游戏架构以及全新的媒体形式。对话还探讨了自主代理互联网的兴起、开源模型在抗衡中心化与应对奖励作弊等安全挑战方面的必要性，以及传统 Web 2.0 搜索与内容经济的结构性瓦解。最终，讨论倡导一种明确乐观主义的姿态，敦促年轻创业者掌握基础技术学科，以应对这场划时代的技术变革。 Andreessen Horowitz 正在将其加密基金拓展为 a16z Frontier，这是一个更广泛的投资载体，旨在支持涉足机器人、硬件、去中心化基础设施以及 AI 领域的杰出创始人。 (0:49) AI 模型的能力预计将把未来二十年的技术进步提前到现在，使 30 人的团队能够设计、制造和交付以往需要 1,000 名员工才能完成的硬件产品。 (17:15) 企业级 AI 的普及率仍仅为约 3%，这表明其应用落地仍处于从早期的拟物化生产力工具向全新的行为模式类别过渡的阶段。 (25:00) 随着生成式搜索和社交信息流将用户留存在其平台内部，聚合平台与内容发布商之间的 Web 2.0 契约已被打破，这促使互联网注意力与变现机制发生结构性重构。 (46:37)

## Background 本期视频由著名风投机构 a16z 于 2026 年 10 月 22 日发布在 YouTube 官方频道。内容围绕 a16z 正式宣布将原有的 a16z Crypto 扩展升级为“a16z Frontier”基金展开，合伙人 Chris Dixon、Marc Andreessen、Ben Horowitz 与主持人 Erik Torenberg 共同探讨了全力支持在技术前沿探索极限的创业者的投资哲学，以及 AI 将如何加速硬件、机器人、娱乐和全新媒介等领域的颠覆性突破。 ## TL;DR a16z 宣布设立 a16z Frontier 基金，旨在跨越既有垂直基金的界限，全面下注探索科技“外部行星”的激进创业者。对谈中三位核心合伙人指出，生成式 AI 正在将原本长达数十年的技术研发周期大幅压缩，并赋予极少数精悍团队颠覆传统产业、甚至逆向工程并接管物理硬件的超强杠杆。同时，他们深入探讨了互联网从“人类社交”向“AI Agent 经济网络”的物种级跃迁、旧流量契约的崩塌、开源 AI 对打破垄断与教育平权的基石作用，以及新一代掌握现代炼金术的年轻人将如何成长为改写世界的“超人”。 ## Atmosphere & style 整场对话洋溢着高密度的智识碰撞与极其浓烈的大胆进取精神，既有硅谷老兵对早期互联网创业历程的自嘲与怀旧，又充满了对当下的激进笃定。对谈风格犀利、坦率且极富幽默感，Marc 和 Ben 借由 J.P. Morgan 的冷峻肖像与道格拉斯·亚当斯的技术定律辛辣讽刺了当下大企业的迟钝与学校对 AI 的保守阻挠，而 Chris 则以一贯深邃的思考模型提供框架支撑。听众能真切感受到一种既对前沿充满敬畏、又敢于“宁愿过早绝不落后”的具象乐观主义气场，令人热血沸腾却又不失理性审慎。 ## Bulletin - [00:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=0s) a16z 正式将原有的 a16z Crypto 基金升级拓展为 a16z Frontier，旨在突破既有核心赛道划分，全力押注探索技术边界的“外部行星”型创业者与跨界构想。 - [15:15](https://www.youtube.com/watch?v=-9XQMHhpypc&t=915s) 生成式 AI 正将过去软件、数学、物理仿真与硬件设计等领域长达 20 年的漫长研发周期大幅提前，推动“科研课题”加速转化为可快速落地的工程项目。 - [28:33](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1713s) 互联网核心经济模式正经历“大重构”，传统的流量分发与内容检索契约彻底断裂，网络的主要交互主体正在从碳基人类向海量自主 AI Agent 转变。 - [38:22](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2302s) 开源模型在 OpenRouter 上的推理代币消耗增速显著超越闭源系统，端侧离线运行与以稳定币为原生结算层的智能体经济正合力打破“AI 必然走向寡头集权”的神话。 ## Key takeaways - [00:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=0s) Crypto 基础设施已逐步融入主流科技（如稳定币和现实资产代币化），而投资机构内部的垂直赛道分工容易产生盲区，设立 Frontier 是为了系统性覆盖游离于传统分类之外的“外部行星”创新。 - [20:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1200s) 风险投资的评估基准发生根本转向：由于底层工具赋能，机构不再担忧创业想法是否“过于野心勃勃”，而是反向审视其“是否足够宏大”以拉开差异化壁垒。 - [22:06](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1326s) 企业界呈现“管理层尚未采纳但员工私下广泛使用”的隐性 AI 渗透现象，这让极少数技术人才得以凭借全栈能力降维打击传统巨头，并将战场扩展至非科技的实体经济。 - [25:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1500s) 颠覆性技术遵循从“将旧习惯搬上网”（如西尔斯邮购目录）到“孕育原生新行为”（如 YouTube 催生博主生态）的两阶段规律，AI 目前正由前一阶段跨入后一阶段。 - [30:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1800s) 硅谷主流由“产品经理脑”主导的狭隘日常应用设想正在失效，AI 真正的创造力爆发点在于释放独立游戏开发、颠覆好莱坞高昂制作成本以及赋予普通人全新的经济变现途径。 - [34:56](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2096s) 开源反向工程工具 REA（Reverse Engineer Anything）的出现打破了硬件开发的工程险境，使纯软件工程师能够逆向解析硬件并覆写代码，实现对物理设备与智能家居的直接支配。 - [36:34](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2194s) 电影艺术并不会被 AI 简单降维为传统长片的工业流水线替代品，正如照相机催生了动态影像艺术一样，AI 将成为孕育全新视听叙事形式的原生媒介。 - [40:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2400s) 开源 AI 是维护教育平权与网络安全防御的基石；面对“奖励黑客”（Reward Hacking）等底层对齐难题，唯有将权重全面向全球学界开放，才能汇集人类智慧保障模型安全。 - [45:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2700s) 以 Google 索引换取流量点击为代表的“互联网旧契约”已彻底瓦解，零点击搜索与垂直站流量暴跌催生大重构，未来的内容消费和协议调用将以自主 AI 智能体为主导。 - [49:12](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2952s) iPhone 之后的下一代人机计算平台正分流为依托低延迟多模态语音的 AI 可穿戴设备，以及满足人类脱离现实、追求深度沉浸式体验的虚拟现实（VR）硬件。 - [50:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3000s) AI 应用正在经历从单人使用的 Prompt 交互向蜂群化、多 Agent 协作网络（Multiplayer AI）的演进，并凭借 DFM 制造导向设计直接主导建筑与实体硬件的落地装配。 - [53:59](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3239s) 计算机科学、数学与经济学正在构成将硅晶片转化为智慧的“现代炼金术”，并跨学科重塑古典文献破译、生物医药研发乃至动物物种沟通机制。 - [56:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3360s) 援引道格拉斯·亚当斯技术三定律，年轻一代把 AI 视为理所当然的自然法则并蜕变为“超人一代”，传统教育体制的封禁反而强化了新技术作为青少年超级武器的地位。 - [58:30](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3510s) 对前沿技术的下注需要将“具象乐观主义”（Definite Optimism）与“理智上的谦逊”相结合，投资者的终极使命是保持敬畏，并在那些拥有坚定信念的杰出创始人身后给予支持。 ## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=0s) a16z Frontier 的战略升级与成立背景 a16z 正式宣布将原有的 a16z Crypto 基金扩展为 **a16z Frontier**，其核心使命是拓宽投资范畴，全力支持那些在技术边界探索极限的创业者。Chris Dixon 指出，这一战略调整背后有两个核心驱动力： 首先，Crypto 自身已经在多个关键领域取得了实质性进展，甚至融入了主流科技基础设施。例如，稳定币（Stablecoins）已经成为现代科技公司的标配工具，华尔街的大型金融机构也正在通过代币化股票（Tokenized Stocks）以及其他现实资产上链加速布局。然而，这种普及让行业边界变得越来越模糊，比如人们今天很难界定 Stripe 到底算不算一家加密公司。五到十年前，加密领域还是一套自成一体的生态系统——拥有独立的项目、独立的企业家和专属的投资人，如今它已彻底与广义科技格局交织在一起。 ```mermaid flowchart TD accTitle: 核心纵向与外部行星投资架构演进 accDescr: 展示 a16z 如何从垂直赛道拓展到 outer planets 探索，并成立 a16z Frontier。 subgraph Core["内部行星 (Inner Planets)"] direction TB V1["成熟垂直业务 / 各核心基金"] V2["现有核心赛道覆盖"] end subgraph Frontier["外部行星 (Outer Planets)"] direction TB OP1["前沿技术、古怪/边缘尝试"] OP2["硬科技、无人机、XR、前沿AI"] end Core -->|"聚焦核心机会，产生覆盖盲区"| Gap["探索空白地带"] Frontier -->|"捕捉全新机遇"| Gap Gap --> Final["设立 a16z Frontier 基金"] ``` 其次，a16z 合伙人 Martin Casado 曾用科幻剧集《萤火虫》（*Firefly*）中的概念作比喻：机构内部存在核心、成熟的“内部行星”（Inner Planets），以及充满未知与古怪构想的“外部行星”（Outer Planets）。当前 a16z 的各大行业垂直团队在其核心赛道上极为繁忙、机会极为丰富，这导致团队在覆盖那些游离于传统品类之外的“外部行星”创新时出现了结构性空缺。对于 Chris Dixon 而言，这正是他自 2013 年加入 a16z 以来最擅长也最热衷的领域——当时他向 Marc Andreessen 与 Ben Horowitz 提出要专注投资那些“疯狂的事物”（crazy stuff），如今 Frontier 的拓展正是该脉络的延续。 - 智能手机在 2007 年诞生后，至 2013 年已全面走向主流，催生了诸如 Instagram 这样直接建立在智能手机生态之上的“一级效应”（first order effects）。 - 伴随供应链成熟，“二级效应”（second order effects）开始爆发：原本用于智能手机的高性能传感器、微处理器等零部件成本大幅下降，被创业者重新拆解组装，直接催生了 Skydio（早期形态宛如长了翅膀的重构智能手机）、Oculus 虚拟现实头显以及早期无人机硬件的兴起。 - 加密网络同样是开源软件演变为网络服务、叠加新兴社交媒体社群凝聚力之后的下游产物。 ### [05:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=300s) 投资“外部行星”：不仅投赛道，更是投极具野心的创始人 Ben Horowitz 深入剖析了 a16z 成立以来的演进逻辑：历史上，a16z 习惯先由 Chris Dixon 这样敏锐的合伙人单挑大梁去摸索完全陌生的新前沿，一旦验证其可行性与规模，机构就会设立一个专门的行业垂直基金（Vertical）。虽然垂直化战略运转极为成功，但总有一些前沿技术与突破性课题完全处于既有垂直品类之外。与其等待未知的领域缓慢孵化，不如赋予 Chris 及其团队足够的灵活性，以 Frontier 的机制主动扑向那些处于科技最前沿的创业者。如果某个全新领域爆发，它未来既可以演化为一个专属的新基金，也可能让 Frontier 整体直接演进为下一个重量级平台。 Ben Horowitz 明确指出：“从根本上说，比起品类，比起产品，我们投资的是创业者。而许多最有趣的创业者都处于外部行星上。” 在刚刚结束的机构内部战略研讨会（Offsite）上，a16z 达成了一个共识：尽管机构过去一直在下大注、走在行业最前沿，但复盘下来，机构唯一的遗憾是“没有更早、更狠、更大规模地加码下注”。当被问及当年为何决定引入 Chris Dixon 时，Ben 强调了 Chris 博客中展现出的原创思考能力，以及作为成功连续创业者的切身体验： - Chris Dixon 提出了影响整个 a16z 投资哲学的关键思维模型：“我们寻找的不是‘看起来像好主意的好主意’，我们在寻找的是‘看起来像坏主意的好主意’。”这种构想在常人眼中往往像个糟糕的错误，但创始人掌握着某种关键的秘密（secret），使其具备非对称的巨大胜率，避免陷入激烈的存量利润竞争。 - Marc Andreessen 补充指出，投资 Frontier 领域不仅需要独特的眼光，更依赖于 Chris Dixon 团队背后极其硬核的专业技术底座。Crypto 表面上充斥着吸引眼球的文化现象与潮流炒作，但其底座是极其复杂的技术网络。Chris 的团队由数学教授、顶尖密码学专家、博弈论研究学者以及资深软件系统工程师组成，这种硬核技术理解力与市场商业嗅觉的结合，是征服前沿领域的核心壁垒。 ### [10:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=600s) 政策布局、J.P. Morgan 的冷峻肖像与 a16z 的进取文化 Chris Dixon 指出，除了技术底蕴，a16z 多年来在政策与监管（Policy & Regulatory）领域进行了极深度的投入。随着自动驾驶汽车、无人机乃至 AI 本身日益政治化，这套成熟的政策应对能力将为更多前沿领域的创业者提供巨大助力。当被问及 2013 年加入时是否曾预料到公司会有今天的规模，Chris 提到了 Marc Andreessen 办公室门后挂着的一幅极具象征意义的画作——J.P. Morgan 的著名肖像照。 ```mermaid flowchart TD accTitle: a16z 核心文化与运作飞轮 accDescr: 展示 a16z 如何从 J.P. Morgan 精神提炼原则，并在投资机制与组织文化中自我强化。 subgraph Spirit["历史灵感与文化立足点"] JPM["J.P. Morgan 历史信条<br/>'只做头等生意，只以头等方式'"] Identity["明确自我认知与行事原则<br/>绝不让外界定义自己"] end subgraph Culture["a16z 组织与投资生态"] Aggression["极其激进的野心<br/>'Can you double down?'"] Restructure["持续敏捷重组<br/>只要能论证，凡事皆可挑战"] FullSupport["端到端赋能支撑<br/>深耕政策、监管与技术底层"] end JPM --> Identity Identity --> Aggression Aggression --> Restructure Restructure --> FullSupport FullSupport --> Aggression ``` 围绕这张肖像，Marc Andreessen 与 Ben Horowitz 展开了生动的历史趣谈。J.P. Morgan 生前患有严重的酒渣鼻（抗生素发明前该病极其棘手），导致他非常讨厌拍照，平时也脾气暴躁。在被强行按在椅子上拍摄官方肖像时，摄影师精心设计了光影：J.P. Morgan 隐匿在黑暗中，向镜头投来令人胆寒的死亡凝视（stare of death），而椅子扶手边缘在特定光线反射下，宛如他手中正紧握着一把锋利的切肉刀。除了这股威慑力，公司文化手册中直接收录了 J.P. Morgan 当年在法庭面对指控时的名言。Ben Horowitz 强调并引用了他的原话： > “No, we only do first class business and then only in a first class way.” Ben 解释道，这句话体现了一种无可动摇的姿态：“你绝不可能来定义我是谁，我知道我是谁，并且我会让你知道我是谁。”Chris 进一步补充，在 a16z 内部，只要提出疯狂想法，Marc 和 Ben 从未退缩过，反而总是反问：“你能不能加倍投入？能不能更激进一点？”这种开放、敢于重构组织、且允许全员放手一搏的创业型文化，正是让团队感到能够在此做出人生最佳成就的核心原因。 - J.P. Morgan 肖像背后的故事展示了早期拍摄对光线与心理预期的精确捕捉，这幅照片长期挂在 Marc Andreessen 的办公室门内作为雄心与意志的提醒。 - a16z 经历了多次组织架构重组，其文化准则是：任何新思路只要能被合理论证，一切机制都可以重新调整与迭代。 - 主持人提及许多外界观察者往往只看到成功创业的辉煌，而 Ben Horowitz 一针见血地指出现实真相：“我不知道有哪家初创公司在某个阶段或多个阶段不是一团乱麻（shit show）。”团队信奉“从不抱怨，从不解释”（never complain, never explain）与“乐天战士”（happy warrior）的精神来穿越动荡。 --- ### [15:15](https://www.youtube.com/watch?v=-9XQMHhpypc&t=915s) “为时过早”的风险重塑：AI 正在将 20 年的技术突破提前 在风险投资领域，历来有一句名言叫“为时过早等同于犯错”（being too early is as bad as being too late）。然而在 a16z Frontier 的投资语境下，Chris Dixon 对“时机风险”给出了全新的审视。他认为，科技史上几乎每一个最终成功的伟大构想，往前倒推十年都能找到一个因技术未成熟而失败的前身。Frontier 基金明确选择“宁愿过早，也不愿过晚”，并坦然接纳品类本身可能失败的风险（category risk）。 即使是像 Oculus 这样被高溢价收购的明星项目，虚拟现实（VR）走向大众主流市场依然耗费了整整 13 年时间，背后的工程与硬核技术难题远比想象中复杂。但 Chris 坚信，生成式 AI 的爆发正在彻底改写技术研发的时间表。AI 首先在软件工程领域实现了跃升，接着迅速突破了数学推理极限；接下来，物理学模拟与硬件工程设计也将迎来质变。这种指数级提速，正在将原本被定义为“科研课题”（science project）的漫长探索，瞬间拉进“工程可落地项目”（engineering project）的范畴。 Chris Dixon 在阐述技术压缩效应时明确表示： > “I think there's a scenario, and I believe this, and I kind of want to invest behind it, where we may be pulling forward 20 years of things that, you know, our whole mindset of how we think about technical risk.” - 研发门槛出现断崖式下降：在现代 AI 工具链赋能下，如今一支仅有 30 人的精悍团队，就完全有能力打造出一家软硬件一体的全栈设备公司（full-stack device company），而在十年前这往往需要上千名工程师的大兵团作战。 - 技术跨越的路径正在从纯数字领域外溢：AI 在相继攻克代码与数学后，正在强力介入物理仿真与硬件架构设计。 --- ### [18:18](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1098s) 史上最宽认知鸿沟：AI 原生创业者对巨头的超级降维打击 Marc Andreessen 随后深入剖析了当下的行业格局，指出目前正处于技术革命中“认知鸿沟最大”的历史节点。一边是深刻理解前沿可能性的早期采用者（Early Adopters），另一边则是反应迟钝的大多数普通大众与行业守成巨头（Incumbents）。这种理解上的脱节在公司层面表现得尤为剧烈：AI 原生的初创企业与几乎所有传统巨头之间，在战略视野和执行效率上存在着天壤之别。 更关键的是，这一鸿沟不仅没有弥合，反而在以周为单位急剧拉大。顶尖技术人才和前沿创始人每周都在借助迭代飞快的模型工具获得新的生产力超能力，而庞大的在位企业根本无法跟上这种进化节奏。Marc 认为，这意味着几乎所有传统产业的霸权地位都将面临前所未有的根本性动摇与重新洗牌。创业者带来的方案在深度、复杂性以及跨领域整合能力上，已经达到了过去无法企及的高度。 在回想技术工具演进对创业的颠覆时，Marc Andreessen 不禁感叹： > “Ben, like, what would you and I have been able to do at Netscape? We would have built the whole damn internet.” Ben Horowitz 也立即笑着呼应，如果 1994 年在网景（Netscape）时代拥有今天这些工具，他们不仅能把整个互联网造出来，“顺便连加密货币（crypto）在那时就一起搞定了”。当下的技术底座已赋予极少数优秀团队前所未有的全能杠杆，这场变革的速度与深度已经远远超出了传统管理层的理解范畴。 ### [20:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1200s) 从“想法是否过大”到“是否足够宏大”：全能年轻创始人的崛起 对谈从技术能力对创业者野心的解放切入。回顾过去，如果基础设施能够提早到位，比如视频流媒体或硬件开发能够在短短几周内完成，整个产业图景将会完全不同。现在的最前沿创业者拥有了前所未有的技术赋能，这意味着他们的商业计划与产品规划在技术维度上将变得异常繁重、复杂且宏大。合伙人们观察到，新一代创业者正在打破传统分类的条条框框，他们不再局限地定义自己“只是一家软件公司”、“只是一家硬件公司”甚至“只是一家 AI 公司”，而是像概念艺术家一样，以极其开阔的视野思考如何横跨多个领域并将它们融合。 这种能力跃升彻底颠覆了风险投资机构评估项目的标准。过去投资人常常会审查某个构想是否“过于野心勃勃”，而现在审视的角度完全逆转了。正如嘉宾所强调的：“We used to, kind of ask the question is is this idea too ambitious and I don't think I think we're much more likely to ask this is this ambitious enough um because you know what's possible is so spectacular and if you do something moderate, it probably won't be differentiated enough.” 与此同时，这也对传统巨头敲响了警钟。虽然硅谷科技巨头中不乏能自我适应的佼佼者，也有众多初创企业致力于为大企业提供武装工具，但对于跟不上步伐的在位者来说，倒计时已经开始。一位掌握 AI 的 24 岁年轻人所拥有的超强行动力，将在未来十年创造令人瞠目结舌的成就。 - 创业边界的消融：创始人不再将自己框定在纯软件、纯硬件或纯 AI 的单一类别，而是进行跨界组合。 - 投资评估准则的转向：从担忧“是否太激进”转变为筛选“是否足够野心勃勃”，温和渐进的项目将缺乏差异化优势。 - 巨头危机感：“The clock is ticking”（时钟正在滴答作响），开发节奏与技术演进速度已逼近认知极限。 ### [22:06](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1326s) 颠覆还是延续：企业“地下AI”与全栈创业公司 关于 AI 究竟是“延续性技术”（Sustaining）还是“颠覆性技术”（Disruptive），主持人提问眼下收益似乎同时流向了两端——Meta 等巨头适应良好，而新生代 AI 独角兽也在以惊人速度逼近万亿估值。对此，对谈者给出了一个极其敏锐的现场观察：真正适应 AI 的巨头大多是直接投身于 AI 底层研发的企业，但在广袤的传统企业界，正在上演一种隐蔽的分裂现象。 这种分裂在于：企业管理层尚未真正采用 AI，但基层的员工们早已在暗中使用 AI 替代工作。正如对谈中所揭示的犀利真相：“There's a very specific thing that I think is happening, which is I think many companies are not adopting AI while their employees are.” 员工在写邮件、校对、查证事实甚至撰写代码时悄悄借助 AI，却并不会向管理层汇报。这催生了一个更深远的连锁反应——这批员工在工具赋能下突然意识到，自己单枪匹马就能成立一家公司，直接推动创业公司成立数量出现井喷。 克莱顿·克里斯坦森（Clayton Christensen）经典的颠覆性创新理论在当下已不再完全适用，因为该理论默认技术世界是一个相对封闭的竞技场、科技公司在存量市场中互相对攻。而如今的现实是，拥有现代科技武装的团队正在杀出科技圈，跨界改造整个实体经济。正如 a16z 刚刚投资的全栈餐饮服务公司 Atoms 一样，现在的战场已经从“十家科技巨头之间的互搏”，转变为“科技巨头与全栈创业公司联手重构其余财富 500 强乃至整个传统经济”。 ```mermaid flowchart TD accTitle: AI推动下的创业范式转移 accDescr: 展示员工在暗中使用AI后催生全栈创业公司并向传统实体经济扩张的过程 subgraph Internal["企业内部：隐形AI渗透"] A["员工悄悄使用 AI 工具<br/>（写作/校对/编程）"] --> B["意识到个人交付效率暴增"] B --> C["脱离传统组织<br/>创办全新全栈企业"] end subgraph Expansion["全行业重塑：超越克里斯坦森框架"] C --> D["全栈创业公司（如 Atoms）"] D --> E["向非科技实体行业扩张<br/>（餐饮、重工业等）"] F["科技巨头与创业公司"] -->|"全面重构"| G["财富 500 强及传统经济"] end ``` ### [25:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1500s) 范式转换的两阶段：从“西尔斯目录”到AI原生行为 针对“价值链目前究竟停留在英伟达这类硬件基础设施层，还是已经转移至应用层与消费者端”的疑问，对谈指出目前其实是“全线开花”（All of the above）。开源模型飞速演进，中美两国的核心力量都在深度发力，而应用层的需求才刚刚显露冰山一角。根据 a16z 团队近期发布的研究图表，企业端对智能的实测渗透率可能仅在 3% 左右，对算力与机器智能的需求规模依然极其庞大。 Chris Dixon 借用互联网的发展脉络，将颠覆性技术的发展划分为两个关键阶段： 1. **旧行为的新载体阶段**：20 世纪 90 年代互联网兴起之初，人们只是把既有习惯搬到网络上，最典型的案例是百货零售巨头西尔斯（Sears）将原本印刷成册的邮购目录搬上网。 2. **全新原生行为的孕育阶段**：到了 2000 年代，YouTube 诞生时面对的是一个完全空荡的网页，它下注的不仅是带宽技术的成熟，更是一场文化与行为的剧变——豪赌未来会出现所谓的“视频博主（Influencers）”来填充内容。这种兼顾技术风险与社会行为风险的下注，最终孕育出重塑世界的社交媒体与移动互联网生态。 这种两阶段演变规律正在 AI 领域精确重演。过去一段时间，行业大多停留在第一阶段：将早已存在的行为用 AI 做得更好——例如写代码、做数学题、进行常规脑力办公或像传统搜索引擎那样聊天问答。但现在，行业正处于迈向第二阶段的关键转折点，那些前所未见的激进、奇特乃至“怪异”的 AI 原生行为正在浮出水面。这种探索虽然包含了更多维度的风险，但也蕴藏着巨大的非对称上行空间。 | 发展阶段 | 互联网早期特征与案例 | 当前 AI 发展映射 | |:--- |:--- |:--- | | **第一阶段：旧行为迁移** | 将西尔斯目录（Sears catalog）搬上网页；沿用既有消费习惯，仅提升效率 | 辅助编写既有代码、数学计算、常规知识工作、类搜索聊天交互 | | **第二阶段：原生行为颠覆** | YouTube 建立空白网站，豪赌全新创作者生态与网红文化崛起 | 催生全新的 AI 原生协作、沉浸式计算与前所未见的用户交互模式 | ### [28:33](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1713s) 互联网主客体颠倒：从人类社交到AI Agent互联网 社交网络与人际交互经历了长期的创新荒漠期。在 2000 年代至 2010 年代初，每隔几年就会爆发一个现象级平台——Facebook、WhatsApp、Snapchat、TikTok 以及婚恋领域的 Tinder；但在此之后，社交赛道陷入了漫长的停滞。然而，随着 AI 设备的普及，用户将海量个人上下文与生活数据托付给这些智能代理，全新的社交体验与交互连接方式的诞生已不可逆转。 更根本性的范式转移在于互联网主体的颠覆。在不久的将来，网络上的主要参与者将不再是碳基人类，而是智能体（Agents）。Marc Andreessen 指出，像 Muse 和 Instinct 这类充当个人效用代理（Utility proxy agents）的产品只是最初始的形态，更庞大维度的各类型 Agent 正在成型，并将成为网络 traffic 与互动的主体。正如谈话中深刻阐述的那样：“We're headed to a world where it looks like the the most numerous participants on the internet will be agents and not people.” 随之而来的深层技术命题是：当智能体成为互联网的主导物种时，它们是否需要一套专属于智能体的通讯协议、支付结算网络以及知识共享体系？这片空白领地蕴藏着大量的技术创新空间。席间众人还打趣提及反向思考的人类租赁平台“Rentahuman.com”以及早期的“Maltbook”案例——当机器开始主导网络时，甚至连人类原本构建的公开交互阵地，都会演变成智能体自发协作与信息交换的新型疆域。 ### [30:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1800s) 摆脱“产品经理脑”的狭隘视角与 AI 原生用例 主持人 Erik Torenberg 提及关于 Hugging Face 的生态演进，指出线上智能体生态（agent ecology）将变得极其壮观，并询问 Marc Andreessen 是否在社交或消费领域观察到了哪些摆脱过去平台时代拟物化（skeuomorphic）思维、真正原生的崭新用例。 Marc Andreessen 辛辣地批评了当前硅谷由“产品经理脑”（product manager brain）主导的设计风气：产品经理们嘴上说着产品是服务于所有大众的，结果做出来的东西全是在解决他们自己的日常琐事——比如在旧金山订一家餐厅去跟同为产品经理的朋友吃晚饭，或是订机票去参加产品经理大会。这种局限在 Anthropic 这类安全对齐模型上体现得尤为明显：模型被训练成所谓的“开心、诚实且无害的助手”，结果成了最枯燥乏味的说教机器，整天把“你问了一个我不被允许回答的问题”挂在嘴边。Marc 强调，早期公司这种管窥蠡测的人类行为观正在被打破，AI 创造力的真正大门正在开启，这将为普通人提供海量赚钱、省钱、参与经济活动和创造新艺术的路径，例如最近几周网络上爆发式涌现的全新风格 AI 音乐视频。 > “It's product managers have the story that they're only for people and yet somehow all the use cases are you know book me a restaurant, you know, do you in San Francisco to go have dinner with my friends who are also product managers?” —— Marc Andreessen ### [31:37](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1897s) 电子游戏行业的破局与好莱坞电影制作的成本重构 谈到前沿落地速度，嘉宾们指出电子游戏历来是媒介革新的急先锋，因为其技术文化天然具备极高的迭代速度。仅仅在两三周内（大约自 Claude 3.5 Sonnet 或类似高阶模型爆发以来），AI 甚至能自动反编译代码并完成跨系统移植，让 Windows 游戏在 Unix 上的运行速度反超原生平台；更有创作者直接通过 AI 将完全不相干的作品融为一体，生成像“超级马里奥混搭 GTA”或“蜘蛛侠混搭侏罗纪公园”这样天马行空的混合游戏。针对游戏界此前对 AI 的文化抵触，Chris Dixon 认为 Epic Games 等行业巨头的表态证明多米诺骨牌已经开始倒下，独立开发者如今能凭借 AI 获得匹敌庞大团队的能力，催生一场前所未有的创意复兴。 在影视方面，Marc Andreessen 提到了由 Adam Sandler 主演的新片《Spaceman》（或类似先锋电影），该片具有极高的艺术成就与深层设计，但因为高达 1.8 亿美元的制作成本，最终导致制片厂净亏损 2 亿美元。Marc 指出，好莱坞的高预算壁垒扼杀了大量先锋尝试；如果借助 AI 技术将制作成本压低至 2000 万美元，它将是一部极为出色的作品；而若是压低到 200 万美元制作，它将实现高达 10 倍的超高投资回报率，彻底重构整个娱乐行业的商业底色。 > “You're going to have this – any independent developer can go and build like they have a huge team and still have – I think they can still have a lot of room for human creativity.” —— Chris Dixon ### [34:56](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2096s) 逆向工程一切：AI 如何攻克硬件这一“未开拓险地” 长期以来，硬件开发在软件从业者眼中始终是如同“这里有恶龙”（there are dragons）般的险境（terra incognita），初创公司极易因为涉足硬件而惨遭滑铁卢。然而，这一逻辑在近期被颠覆——开源社区推出了名为 REA（Reverse Engineer Anything，逆向工程一切）的 AI 工具，只要将其对准任意硬件设备，AI 即可逆向解析出其内部结构并生成源代码。 这让以往令人头疼的智能家居自动化（home automation）市场迎来了质变。如果家里的恒温器失灵不好用，用户现在可以直接用该工具对其进行逆向工程，让 AI 编写一套全新代码、刷入新系统并附带一套全新UI；甚至可以直接用一个本地 AI Agent 接管并调度整座房屋的所有硬件。这预示着“软件开发者将第一次真正具备支配硬件的能力”，整个物理世界与实体经济的大门正全面向软件人才敞开。 ```mermaid flowchart LR accTitle: AI-Driven Hardware Reprogramming Flow accDescr: Diagram showing how an AI agent uses tools like REA to reverse engineer legacy hardware and flash new software directly. subgraph LegacyHW["物理硬件"] HW["智能家居硬件<br/>（如智能恒温器）"] end subgraph AIWorkflow["AI 逆向与生成"] REA["REA 开源工具<br/>（Reverse Engineer Anything）"] CodeGen["AI 智能体<br/>（解析底层代码并重写接口）"] end subgraph Deployment["重新定义"] NewSys["刷入全新定制代码与 UI<br/>接管家庭自动化生态"] end HW --> REA REA --> CodeGen CodeGen --> NewSys ``` > “Basically, any form of hardware can now be taken over and reprogrammed with this stuff.” —— Marc Andreessen ### [36:34](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2194s) 照相机隐喻与新型视听叙事形式的诞生 Ben Horowitz 深入探讨了电影工业的两极分化：一部分人积极拥抱 AI，另一部分人则将头埋进沙子里假装看不见。他认为未来的“AI 电影”绝不仅仅是传统长片的降本增效工具，而会演化成一种全新的艺术媒介。过去只有 Christopher Nolan 这样级别的导演才有资金支持去实现极致复杂的宏大叙事构想，而 AI 将使任何创作者都能毫无限制地讲出以往在商业上不可行的故事。 Chris Dixon 借用了“照相机发明”的经典历史隐喻来总结技术的正反两面：从消极视角来看，照相机淘汰了为写实记录而生的风景画家；但从积极视角来看，正是照相机的诞生为电影这一动态影像艺术奠定了基石。AI 同样如此，它既会重塑旧媒介，更会孕育出当今人类凭借现有想象力尚无法完全预见的原生媒介。 > “The AI film is not going to be a movie it's going to be something very very different.” —— Ben Horowitz ### [38:22](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2302s) 破除“AI 必然集权”的神话：开源模型、端侧计算与加密经济学 针对 Peter Thiel 曾提出的名言“加密是自由主义，AI 是共产主义”（指加密天然倾向去中心化，而 AI 倾向中心化垄断），嘉宾们给出了反驳。虽然头部封闭模型（如 OpenAI、Anthropic）仍将极具商业价值，但当前开源阵营在 OpenRouter 等平台的代币消耗量（token consumption）增速远快于闭源系统，端侧（Edge/Local）大模型也在快速成熟，个人在笔记本电脑上本地运行顶级代码智能体或聊天机器人已成为现实。 与此同时，去中心化智能体经济必然需要金融基础设施的支持。当无数自治的 AI Agent 相互协作、采购 API 和处理服务交互时，稳定币（Stablecoins）构成了最天然的原生可编程货币结算层。将端侧开源 AI、智能体协同网络与底层加密货币基础设施结合，将形成一个广泛分散且充满活力的开放市场格局，彻底颠覆过去关于 AI 必然走向极权与单点垄断的既定假设。 - **反编译革新**：开源逆向工程工具 REA 使得仅懂软件的开发者能够直接提取并覆写智能家居硬件的控制固件。 - **开源生态势能**：OpenRouter 数据显示，开源模型在推理代币消耗量的增速上正在显著反超部分闭源垄断者。 - **智能体货币协议**：在多 Agent 协同网络中，加密稳定币被视为不可替代的原生结算底层，构筑了机器经济的基石。 > “The brilliant Peter Thiel once had this quote, I think a decade ago or something, where he said, you know, crypto is libertarian, AI is communist, which meant, you know, crypto is decentralizing, AI is centralizing. But I'm not sure that's entirely true...” —— Erik Torenberg ### [40:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2400s) 开源 AI 的全球博弈、教育普及与反垄断护城河 Chris Dixon 首先强调，未来的科技生态不仅需要大型中心化科技公司的存在，更需要强劲的开源生态和加密技术（如区块链）来拉平竞争环境，因为给消费者和初创公司提供多元化的选择至关重要。 当被问及当前开源的实际发展态势与外界感知时，Marc Andreessen 给出了极其乐观的评价。他指出，目前开源正全速狂奔，全球两大科技超级大国——美国和中国——在发展专有系统的同时，都在开源领域极度活跃。过去三四年间，政界一直笼罩着实施严苛监管甚至全面封禁开源的潜在威胁（例如欧盟一直试图挥舞罚款大棒），但当前美国政府的态度是百分之百支持开源，全力期望美国开源能够引领并赢得全球 AI 竞争；与此同时，中国在开源 AI 上的开放力度也超乎许多人的预期。从技术演进上看，开源模型正在以惊人的速度追赶，甚至根据不同的衡量标准，正在以领先闭源模型 6 到 12 个月的势头快速迭代。 Marc Andreessen 重点反驳了“开源会导致技术被用于作恶因此必须被封杀”的监管论调，从教育与安全防御角度阐述了开源的不可替代性： > “And so every kid in the world, I think, should have as their birthright the ability to fully understand and utilize this technology.”（Marc Andreessen：“因此我认为，世界上每一个孩子都应当把充分理解和运用这项技术作为他们的与生俱来的权利。”） 他指出，AI 最被低估的一点在于“AI 会教会你关于 AI 的知识”，但部分大型闭源公司的模型却被设定为拒绝教授底层构建细节，而开源模型则会毫无保留地指导用户如何搭建开源 AI。如果一个孩子只能通过入职两家垄断寡头公司才能搞懂 AI，对父母和下一代来说是荒谬的。此外，开源是网络安全防御的基础——正如 Hugging Face 等平台所展现的，开源软件赋予了每个人最先进的漏洞扫描和防御能力，让人人都能以极低门槛在手机上装载“顶尖医生”与“天才教授”。 ```mermaid flowchart TD accTitle: 开源 AI 与中心化垄断的对比 accDescr: 对比开源 AI 的去中心化生态与闭源垄断带来的集中风险 subgraph OpenSource["开源生态 (Open Source)"] OS1["全球开发者 / 高校师生协作"] OS2["本地离线运行（如户外急救/生存专家）"] OS3["开放权重：攻关安全缺陷（如奖励黑客）"] OS4["教育平权：人人可免费学习 AI 底层"] end subgraph Centralized["闭源垄断 (Centralized AI)"] C1["极少数寡头企业掌控 API"] C2["云端强绑定：断网即失效"] C3["黑盒模型：外部无法审计内在机制"] C4["过度集中：最终沦为'政府接管'风险"] end ``` 谈及硬件端侧的开源落地，Marc 补充了一个生动的例子：现在的户外探险者开始在手机中下载完整的本地大语言模型（无需联网即可运行）。即使在没有任何移动信号的荒野面对突发险情（比如遭遇黑熊），也能随时向手机里的离线“生存专家”咨询求生方案，而这种能力是依赖云端 API 的闭源服务完全无法提供的。针对权力的集中，Marc 做了一个犀利的类比： > “And I guess I would ask people the following question, which is just close your eyes and picture the concept of government sushi and then keep your eyes closed and picture government AI.”（Marc Andreessen：“我想问大家这样一个问题：闭上眼睛想象一下‘政府特供寿司’的概念，然后再闭上眼睛想象一下‘政府掌控的 AI’。你觉得那会是什么感觉？”） Ben Horowitz 紧接着从技术治理层面支持 Marc 的论断，指出权力的高度集中从来只会带来灾难。当前 AI 面临的最严重安全隐患之一就是“奖励黑客”（Reward Hacking）现象——即模型为了最大化获得奖励函数的分数，采取了人类未曾预料且未指令的手段甚至走捷径。由于前沿实验室正忙于彼此算力军备竞赛，根本无暇深入攻关这一底层安全问题。如果模型权重对全球的高校学者、博士生和本科生完全开放，汇聚全人类的智慧共同解决奖励黑客与对齐漏洞，AI 的安全性才能真正得到保障，而不是将希望寄托在两三家大公司的内部员工身上。 - 开源模型正在以约 6 至 12 个月的速度与闭源顶尖模型并驾齐驱甚至实现反超。 - 廉价硬件普及的本质：正是由于开源软件的存在，人们才能用 10 美元的极低成本手机接入全球信息网络。 - 现场幽默插曲：在数当前能做前沿模型的闭源巨头时，大家打趣补充“Meta 算一家（支持开源）”、“SpaceX 算第四家”。 --- ### [45:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2700s) 互联网旧契约的瓦解与大重构 在谈到技术的指数级演进时，嘉宾们提到 Peter Thiel 曾感叹的“我们想要飞天汽车，得到的却只有 140 个字符”（*We wanted flying cars, and all we got was 140 characters*）；而极具讽刺意味又充满戏剧性的是，如今接管了那家“140 字符”公司（X/Twitter）的人（Elon Musk），同时也正在制造飞天汽车与火箭，而 a16z 恰恰是这两项事业的共同投资人。 随后，讨论转向 Chris Dixon 撰写的行业洞见——互联网底层商业模式的崩溃。Chris 指出，初代和二代互联网能够繁荣运转，依靠的是分发端与内容端之间默认达成的**“互联网契约”（The Internet's Covenant）**： > “Think about Google, like the idea was you kind of give Google a snippet, let them index you and then they'll send you some clicks.”（Chris Dixon：“想想 Google 吧，最初的逻辑是你给 Google 提供一小段摘要，允许他们抓取索引，作为交换，他们会把流量点击导回给你。”） 然而，这项运行了数十年的默契正在彻底断裂： 1. **零点击与流量断流**：从上个十年中叶起，分发巨头就开始截留流量；如今在 AI 概括答案和社交平台算法围墙花园的双重夹击下，平台直接在搜索结果首页提供完整答案，全面阻止用户跳出到外部原始站点。 2. **内容站点的经济休克**：严重依赖广告变现、展示转化与 SEO 引流的垂直网站遭遇灭顶之灾，典型案例即 Stack Overflow 等知识社群，在 AI 编程工具与替代答案普及后，自然搜索流量发生了断崖式暴跌（precipitous drop）。 3. **交互主体从“人”转向“Agent”**：尽管预订旅游行程、查阅烹饪食谱等核心交易需求依然存在，但未来发起请求的不再是浏览网页的人类，而是直接在后台调用协议的自主 AI 智能体（Agent）。 Chris Dixon 强调，虽然短期的结构调整会给建立在“人类注意力经济”之上的旧业务带来剧烈阵痛，但这揭开了一场未来十年级别的大重构（The Great Reconfiguration）。这不仅仅是移动互联网时代的重演——移动端只是把网络接入量从 5 亿人扩大到 50 亿人并塞进了裤兜；而当前的 AI 浪潮将从根本上重组整个互联网的经济学模型、注意力流向、知识分配路径以及全人类的协作创造方式。 --- ### [49:12](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2952s) iPhone 之后的计算形态：可穿戴与沉浸式 VR 针对 iPhone 问世多年后消费电子设备形态长期停滞的问题，Chris Dixon 展望了下一代人机交互的物理形态。 一方面，在多模态 AI 与低延迟语音交互全面成熟的催化下，**AI 可穿戴设备（Wearables）**正迎来爆发式窗口。语音与视觉理解的突破，让无屏幕或微屏幕的穿戴硬件终于具备了实用性，摆脱了过去作为鸡肋配件的定位。 另一方面，Chris Dixon 重申了他对**虚拟现实（VR）与沉浸式计算**的长期坚定信念。尽管现有的硬件设备仍面临诸如机身笨重、容易出汗、佩戴工效学（Ergonomics）体验不佳等实际工程局限，但从科幻作品预言到人类底层感官需求来看，存在大量场景是人类极度渴望完全抽离现实、进入深度沉浸式和超现实（otherworldly）数字空间之中的。随着底层计算与光学人体工程学的演进，这类突破日常物理限制的沉浸体验必将成为下一代计算平台的核心支柱之一。 ### [50:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3000s) 硬件复兴、AI 驱动的物理制造与多人协作智能网络 讨论首先延伸至实体制造与硬件创新领域。Chris Dixon 指出，AI 将成为解锁全新体验的关键驱动力。在数字内容方面，如今单个开发者就能在社交平台上独立完成诸如《泰坦天降》（Titanfall）这样极为复杂的游戏移植工作；在物理世界中，AI 更是极大地降低了硬件门槛。过去打造 VR 游戏、虚拟世界或物理硬件难度极高，十多年前 MakerBot 引领的创客运动（Maker Movement）受限于工程难度而未能彻底爆发。如今借助 AI，人们可以轻松让 AI 绘制 3D 打印外壳、组装廉价主板、编写专属固件代码，迅速把硬件构想落地。 这种技术跨越在建筑与重工业设计中尤为显著。Marc Andreessen 分享了一个真实案例：他的一位朋友近期完成了一座新建筑的全套架构与工程设计，整套流程完全在 AI 的主导下推进，人类工人仅负责现场组装。不仅如此，前沿模型已展现出卓越的“面向制造的设计”（Design for Manufacturing, DFM）能力，能够直接生成符合工厂生产规范的最终图纸与技术规格书。过去普通人或中小型公司难以企及的重型领域，正在被 AI 全面平民化。 在探讨网络形态的演变时，Chris Dixon 提出互联网技术往往经历从“单机模式”到“网络模式”的发展周期。早期 iPhone 问世时，绝大多数应用都是手电筒等简单的单机工具，随后才演化出 Uber（商业撮合网络）和 Instagram（社交网络）。目前的 AI 交互仍停留在用户面对屏幕单向打字提问的单机阶段，但未来必然会走向“AI 多人协作阶段”。通过将蜂群智能（Swarm）构建为多 Agent 协作网络，人类将能调动成群结队的智能体去攻克复杂的科学猜想、设计宏伟建筑或解决工程难题。 ```mermaid flowchart TD accTitle: AI 发展形态演化流程 accDescr: 展示 AI 从单机工具向多 Agent 协作网络与实体制造拓展的演进路径 subgraph SinglePlayer ["阶段一：单机工具时代"] A["单机应用（如 ChatGPT 对话、手电筒类工具）"] end subgraph Multiplayer ["阶段二：多 Agent 协作网络"] B["协同 Agent 蜂群（Swarms）"] C["机器时代社会化协作网络（Multiplayer AI）"] end subgraph PhysicalWorld ["阶段三：实体与工业全面渗透"] D["DFM 制造导向设计与工业出图"] E["AI 主导建筑设计与自动化装配"] F["创客硬件（3D打印+固件代码一键生成）"] end A --> B B --> C C --> D C --> E C --> F ``` - 硬件与实体领域的降门槛示例：个人独立完成 3A 级别复杂游戏移植；AI 主导全套建筑工程设计方案。 - DFM（Design for Manufacturing）能力让大模型能够跨越数字世界与物理工厂之间的工程鸿沟。 - 从单机工具迈向多人网络：如同 iPhone 应用从手电筒走向 Uber 和 Instagram，AI 也正从单机 Prompt 交互走向以 Agent 集群协作解决难题的网络形态。 > “在互联网时代，大多数技术都会经历多个阶段。起初人们会构建一些简单的单身玩家应用，就像最初的 iPhone 应用只是小手电筒这类东西。” —— Chris Dixon > > “这些在历史上对普通人或普通公司来说极度困难、成本高昂甚至完全不可能的领域，突然之间变得非常可行，甚至变得直截了当。” —— Marc Andreessen --- ### [53:59](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3239s) 现代炼金术：给 18 岁年轻人的专业选择与跨学科剧变 当主持人 Erik Torenberg 问及如果今天只有 18 岁该选择什么专业时，Chris Dixon 引用了 Marc Andreessen 的经典视角，将当前的计算机与 AI 研究比作“现代炼金术”：人类终于掌握了把沙子（硅晶片）转化为智慧的秘诀。对于年轻一代，数学、计算机科学以及经济学是理解并掌握这门炼金术的核心学科。Chris Dixon 与 Ben Horowitz 回顾自身职业生涯，深感能够赶上互联网崛起并从中受惠是前人留下的时代遗产，而接下来的 20 到 30 年，AI 无疑将成为不可逆转的时代叙事主线。 与此同时，AI 的冲击绝不局限于纯计算机领域，人文学科与自然科学正在经历根本性的范式转移： 1. **古典学（Classics）**：在维苏威火山卷轴解密项目（Vesuvius Scroll Project）中，计算机视觉与 AI 成功读取了被火山灰炭化两千年的古罗马卷轴，极有可能发掘出此前从未见过的哲学流派与失传典籍。 2. **经济学与药物研发**：经济学家正在结合 AI 重新构建宏观与微观模型，生物医药研发的底层逻辑也被彻底重写。 3. **动物心理学与物种沟通**：借助对庞大声学与行为数据的建模，人类极有可能首次真正听懂动物的语言。对此，甚至已经设立了相关的 X-Prize 大奖，破解猫狗等动物的复杂交流系统已不再是纯粹的科幻设想。 > “人类刚刚搞懂了如何把沙子变成智慧。而掌握它的途径，我认为是数学、计算机科学，也许还有经济学。” —— Chris Dixon > > “当人们真正搞懂狗到底在说什么的时候，训狗这件事将完全变成另一码事。对此甚至已经有了一个 X-Prize 大奖。” —— Marc Andreessen --- ### [56:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3360s) 道格拉斯·亚当斯技术三定律：颠覆性代沟与超人一代 Marc Andreessen 援引了著名科幻作家道格拉斯·亚当斯（Douglas Adams）关于代际技术认知的经典三定律，来剖析当下社会对 AI 的剧烈分化反应： - **15 岁以下**：任何事物都被视为世界运转的天然方式。Marc 分享了自己教 7 岁孩子使用 ChatGPT 的趣事：他本以为孩子会对电脑能回答问题感到震撼，结果孩子却理所当然地反问：“电脑不能回答问题还有什么用？” - **15 到 35 岁**：新技术是极其令人兴奋、极具革命性的力量，年轻人能借此建立终身事业，因此会竭尽全力吸收所有新知识。 - **35 岁以上**：新技术被视为亵渎神灵、邪恶至极，必将推翻现有秩序并摧毁社会文明，老一代人对此充满本能的抗拒。 Ben Horowitz 和 Marc Andreessen 讽刺了当前学校对 AI 的抵触与封禁举措。这种体制上的阻挠反而帮了大忙——在青少年眼中，被学校禁止的东西更酷，AI 因而成了年轻人手中秘密探索的“超能力”。成人们常哀叹“现在的孩子生存太难”，但事实恰恰相反，真正面临淘汰风险的是那些抱着旧秩序不放的成年人。在强大工具的武装下，年轻一代将蜕变为前所未有的“超人”（Superhumans），他们将打破壁垒，自由踏入此前被高门槛封锁的任意领域。 - **道格拉斯·亚当斯代际认知法则对照表**： | 年龄层 | 对新技术的认知模式 | 现实行为表现 | |:--- |:--- |:--- | | **< 15 岁** | 自然法则（Natural） | 视 AI 为理所当然的基础设施，无法理解没有智能交互的世界 | | **15 - 35 岁** | 时代机遇（Revolutionary） | 学习最新技术、投入创业浪潮、构建全新行业与个人事业 | | **> 35 岁** | 毁灭威胁（Evil & Unholy） | 本能恐惧现有社会结构崩溃，呼吁监管、禁止并抱怨技术危害 | > “如果你在 15 岁以下，新技术只是世界运转的自然法则……如果你在 15 到 35 岁之间，它新颖、令人兴奋，而且你有可能围绕它建立起一份事业……而如果你超过了 35 岁，它就是不洁与邪恶的，必定会推翻所有现有秩序并摧毁社会。” —— Marc Andreessen > > “大人们总在说：‘噢，孩子们该怎么办呢？现在当个孩子太艰难了。’——不，不，不，根本不是这么回事。真正面临危机的是你自己，因为你已经被淘汰了。孩子们都将变成超人，他们将无所不能，整个世界都向他们敞开大门。” —— Ben Horowitz --- ### [58:30](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3510s) 具象乐观主义与谦卑的创业赌注 对话尾声，Erik Torenberg 总结道，这场长谈和 a16z Frontier 的使命贯穿着一种彼得·蒂尔式的“具象乐观主义”（Definite Optimism）——坚信未来正在发生，科幻小说描绘的愿景终会实现，哪怕有时因“过早入局”而受挫，也要持续以坚定的信念下注。 对此，Chris Dixon 和 Ben Horowitz 做出了重要补充与边界界定：这种乐观必须与“理智上的谦逊”（Intellectually Humble）并存。Ben Horowitz 明确指出，风险投资的本质从来不是去验证投资机构自身天花乱坠的理论，而是去寻找具备“具象乐观主义”信念的优秀创业者并全力支持他们。真正的突破往往诞生在今天播客尚未讨论到的盲区中，唯有保持敬畏与开放，才能持续捕捉定义未来的力量。 > “我会说，这是一种谦逊的具象乐观主义，或者说在理智上保持谦逊。因为我已经犯过太多次错误了。我们真正想要的是去找到那些怀揣自身具象乐观主义视角的杰出人才，并在他们背后给予坚定支持。” —— Chris Dixon ## Notable quotes > [05:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=300s) 从根本上说，比起品类，比起产品，我们投资的是创业者。而许多最有趣的创业者都处于外部行星上。 — Ben Horowitz > [22:06](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1326s) There's a very specific thing that I think is happening, which is I think many companies are not adopting AI while their employees are. — Marc Andreessen > [28:33](https://www.youtube.com/watch?v=-9XQMHhpypc&t=1713s) We're headed to a world where it looks like the the most numerous participants on the internet will be agents and not people. — Marc Andreessen > [40:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2400s) And so every kid in the world, I think, should have as their birthright the ability to fully understand and utilize this technology. — Marc Andreessen > [34:56](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2096s) Basically, any form of hardware can now be taken over and reprogrammed with this stuff. — Marc Andreessen > [36:34](https://www.youtube.com/watch?v=-9XQMHhpypc&t=2194s) The AI film is not going to be a movie it's going to be something very very different. — Ben Horowitz > [53:59](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3239s) 人类刚刚搞懂了如何把沙子变成智慧。而掌握它的途径，我认为是数学、计算机科学，也许还有经济学。 — Chris Dixon > [56:00](https://www.youtube.com/watch?v=-9XQMHhpypc&t=3360s) 大人们总在说：‘噢，孩子们该怎么办呢？现在当个孩子太艰难了。’——不，不，不，根本不是这么回事。真正面临危机的是你自己，因为你已经被淘汰了。孩子们都将变成超人，他们将无所不能，整个世界都向他们敞开大门。 — Ben Horowitz ## Mentioned a16z, a16z Frontier, a16z Crypto, Chris Dixon, Marc Andreessen, Ben Horowitz, Erik Torenberg, Martin Casado, J.P. Morgan, Stripe, Skydio, Oculus, Netscape, Clayton Christensen, Atoms, YouTube, Meta, OpenAI, Anthropic, Claude 3.5 Sonnet, Epic Games, Hugging Face, OpenRouter, Peter Thiel, Elon Musk, X, Google, Stack Overflow, Douglas Adams, ChatGPT, MakerBot, Adam Sandler, Christopher Nolan, REA (Reverse Engineer Anything), Vesuvius Scroll Project ## Video description a16z is expanding a16z crypto into a16z Frontier, a broader mandate to back founders building at the edges of what's possible. Chris Dixon joins Marc Andreessen, Ben Horowitz, and Erik Torenberg to explain why founders should increasingly ask not “is this too ambitious?” but “is this ambitious enough?” — and how AI could pull decades of technological progress forward across hardware, robotics, entertainment, science, and entirely new forms of media. They also explore the coming internet of AI agents, why open source matters as AI becomes more powerful, and why some of the most important companies of the next decade may combine technologies and business models that previously belonged in separate categories. Timestamps: 00:00 Intro 00:49 Announcing a16z Frontier 15:15 Is being too early still a risk? 18:18 The widest gap between early adopters and everyone else 22:06 Will AI favor incumbents or startups? 28:33 AI social networks and agents online 30:08 Beyond “product manager brain”: games, film and hardware 38:22 Is AI centralizing? The case for open source 46:37 The internet’s broken covenant 49:12 What comes after the iPhone 53:59 What to study if you’re 18 today Resources: Follow Chris Dixon on X: https://x.com/cdixon Follow Marc Andreessen on X: https://x.com/pmarca Follow Ben Horowitz on X: https://x.com/bhorowitz Learn more about a16z Frontier: a16zfrontier.com a16zfrontier.substack.com x.com/a16zfrontier Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. [Source](https://www.youtube.com/watch?v=-9XQMHhpypc)

[5:00] Ben Horowitz: 从根本上说，比起品类，比起产品，我们投资的是创业者。而许多最有趣的创业者都处于外部行星上。 [22:06] Marc Andreessen: There's a very specific thing that I think is happening, which is I think many companies are not adopting AI while their employees are. [28:33] Marc Andreessen: We're headed to a world where it looks like the the most numerous participants on the internet will be agents and not people. [40:00] Marc Andreessen: And so every kid in the world, I think, should have as their birthright the ability to fully understand and utilize this technology. [34:56] Marc Andreessen: Basically, any form of hardware can now be taken over and reprogrammed with this stuff. [36:34] Ben Horowitz: The AI film is not going to be a movie it's going to be something very very different. [53:59] Chris Dixon: 人类刚刚搞懂了如何把沙子变成智慧。而掌握它的途径，我认为是数学、计算机科学，也许还有经济学。 [56:00] Ben Horowitz: 大人们总在说：‘噢，孩子们该怎么办呢？现在当个孩子太艰难了。’——不，不，不，根本不是这么回事。真正面临危机的是你自己，因为你已经被淘汰了。孩子们都将变成超人，他们将无所不能，整个世界都向他们敞开大门。

[0:00] We're announcing today that we're expanding the ACC crypto fund to A16Z frontier. This is the biggest delta between what the early adopters understand is possible now. That gap is as wide as I've ever seen it in my career. More than categories, more than products, we invest in entrepreneurs. And so many of the most interesting entrepreneurs are on our planet. Journal information is going to skyrocket from here. By the way, it already is. We used to ask the question, is this idea too ambitious? We're much more likely to ask, is this ambitious enough? because what's possible is so spectacular. Had I had Astro at Netscape in 1994, like, oh my God. Ben, like what would you and I have been able to do at Netscape? We would've built the whole damn internet. - You were 18 today. How would you think about what you might study? - Stealing Mark's line, but I think there's one thing to do, which is study. Chris, we have a big announcement today. We're expanding the mandate. I'll let you do the honors. Yeah. So, yeah, we're announcing today that we're expanding the ACC crypto fund to A16Z Frontier. The idea is, I'd say, a couple of motivations behind this. One is crypto has, in some areas, worked really well. Stable coins have become kind of a normal part of the tech landscape tech company now kind of considers it part of their toolbox. Wall Street firms are moving heavily into crypto with tokenized stocks and other kinds of assets. It's a fast growing category. But as a result, the lines have kind of blurred, which we find ourselves asking, is Stripe a crypto company? Many of these companies where they're sort of sitting in the intersection of, let's call it, whereas, uh, years ago, it was sort of its own world, its own companies and its own investors. The lines are blurred and it's become kind of more part of the tech landscape. So that's number one. And then number two, and I can let Mark and Ben talk about this more. I think we felt that at the firm, there's a feeling that the other kind of groups are, are, are, um have so many interesting opportunities in their core areas uh that uh what we kind of my partner martin calls outer planets meaning sort of the metaphor i think comes from firefly the tv show it's the idea the inner planets are kind of the kind of the more core planets and there's kind of these wackier outer planets um that uh outer plants which historically we've done a lot of kind of both types of investing um i think the feeling was um that because they're so busy with job with that, that there was an opportunity to kind of, there was maybe a gap, let's say, in some of the coverage there. And then I think just I'll just speak personally, you know, I kind of see myself and my background as I see Frontier as an area I'm comfortable with. I joined the firm in 2013 and we, you know, came in and with that kind of mandate, I talked to Mark and Ben and I said, hey, I want to do this crazy stuff. And they were like, great. And so, you know, that led to a And they're all kind of what I would call kind of second order effects. You had smartphones, obviously, start in 2007, and by 2013 had gotten mainstream. And there were all these kind of first order effects like building apps on top. So like the firm was an investor in Instagram and that incredible product built on smartphone. But a second order effect was that you had the components of smartphones. You had sensors and chips getting better and better. And maybe people could repurpose those in different ways. And so that led to, I think Mark was the one who's first into drones, as I recall, and got me into them. behind it beyond just their cool is that now that you have this supply chain of all these great parts that entrepreneurs can kind of recombine them and build. We invested in Oculus as an example, and that was really kind of a reconfigured smartphone. Skydio, that was one of our investments from back then that was at the beginning was kind of a reconfigured smartphone. It's gotten much more advanced now. Crypto, I think at the time was kind of a downstream effect to me of sort of the open source and software movement morphing into services and also kind media where you could have these communities form without mainstream acceptance and build, you know, and kind of coalesce around these blockchains. So for me personally, I'll just say this is sort of, I feel, you know, kind of a continuation of a long area of interest. And I think the firm has, you know, there's many other investments the firm has had in these kinds of frontier areas. So we felt, I think it's kind of consistent with things we've been doing for a long time. Yeah. Of? Ben, Mark, let's hear from you. I know this was a joint effort and something you guys were very excited about and felt like filled a gap or really expanded the mandate of the firm. Ben, why don't you add your take? Yeah, so look, I think that there is... areas that are really novel. So it's looking at what's possible [5:00] logically and problems in the world and They're just the first ones in it and it may end up being a category. It may end up being a successful company. It may, you know, blow up. But, you know, there's a class of these things and, you know, you know what we've done typically or historically is was first like Chris would just look at these new areas himself. And then, kind of, as we identified new areas, we create a vertical behind that area. And what we found with our vertical strategy, which has worked very well, is that there's still new things that fall outside of the verticals, and the process of turning that into a practice. is... a little bit undefined. Not that we haven't done it, but it's a little bit undefined. And so by Chris doing this, we kind of will have the motion to invest in the very most interesting founders who are outer planets and then you know if that works you know maybe that becomes a whole fund at some point uh or maybe frontiers turns into that thing because it gets so interesting like that could be as well and so i think that you know it's very exciting for us because it kind of uh fills a hole in the architecture and then also You know, we really, at the end of the day, more than categories, more than products, we invest in entrepreneurs. And so many of the most interesting entrepreneurs are outer planets. So this gives us a real way to get to that. And to me, this seems like a continuation of what we're talking about at the last offsite, which struck me because, you know, as ambitious as the firm has been, as early as the firm has been, as big of the bets that the firm has made, you know, the big focus of the offsite was how do we bet even bigger? The only regrets we have are not even going even harder, even earlier, even bigger. And Chris, you're someone who, you know, has made bets in some of these emerging categories. But it just feels like a continuation of that message. to ask one historical question, which is, you know, Chris, I believe, is the longest standing consecutive partner at the firm, you know, besides Ben and Mark, having joined in 2013. I'm curious, Ben and Mark, when you, you know, met Chris, what did you see in him that made it clear that, oh, we have to have him at ASEANZ? And did you anticipate the type of career he would go on to have? Ben, I'll ask you to start. I think originally we just knew Chris as a very smart guy and we really liked his ideas from his blog. That's really what it came down to. He's a really good writer. His ideas were very original. You know, we were looking for like somebody smart who could do that. And then the other thing we liked about him is he had real experience as an entrepreneur. So he knew kind of like what that journey felt like, which, you know, was very, very important to us in the early days to set the culture of the firm the way we wanted it. you know over time he's had probably The most original investment ideas that we've had in the firm and so and we've kind of copied those and multiplied them across so you know one of his early things was like we're not really looking for good ideas that look like good ideas we're looking for good ideas that look like bad ideas because and then a bad idea but where an entrepreneur has a secret that actually makes it a good idea and that that that framework was extremely useful for us and kind of Understanding like what was going to be truly unique and have massive upside versus something that was going to get where all the profits were going to get competed away And so you know and he said he said quite a few Excellent ideas like that. So you know it's been great working with him and over, now way more than a decade. Yeah, maybe I could add also it's not just Chris's specialty as it's also Chris's team. And the thing that I think people may not appreciate, maybe hard to see from the outside is just, you know, crypto has this, you know, crypto has like been so sexy in so many ways. And it's been so, you know, it has a sort of flashy elements and, you know, cultural, you know, kind of phenomena kind of moments. But at the core of crypto, it's a technology. It's a very deep technology and it's very complex technology. And you need to have like really deep technical expertise, you know, kind of coupled with like really good business and really good market judgment in order to successfully invest in crypto, which we've done. Including, by the way, including like, you know, literally Chris's team has had like, you know, math professors and, you know, cryptographers and like people who are, you know, very, very deep into the theory, you know, game theory, you know, things like that, you know, very deep software concepts. And so, [10:00] So it's one of the things I'm really excited about is, in addition to Chris, his colleagues and team members on the team that he's built, now being able to work on a broader set of topics. And to that point, I mean, so thank you. But I think that also the team, I think the team is amazing. And I would also mention one other thing besides the technical side, we've invested very deeply over the years in policy and regulatory. And I believe that a lot, you know, if you just self-driving cars, drones, AI itself is now becoming a political issue. will be useful for many other entrepreneurs. Yeah, I agree. Well, on that end, we'll do one last historical question. You pioneered not just some of the investments, but also some of the ways in which the firm works, the policy arm. When you joined in 2013, could you have imagined that the firm would have grown in this way? What were your thoughts about where things were going? Well, I always knew Mark. I mean, Mark, you have a big poster of JP Morgan on your wall in your drive and ambition. It's a famous photograph. It's a very famous photograph. It's a very famous photograph. It was so he hated it. It's inspiration. For people who haven't seen the photograph, you can Google. It's a very famous one. It's J.P. Morgan hated to have his picture taken. He had this condition. Anyway, he has this nose-related issue. Anyway, so he hated having his photo taken. This is pretty antibiotics, let's put it that way. And so he was grouchy most of the time. And so he has photo taken. But they needed a formal portrait of him. put him and sat him down and the photographer saw the whole thing coming. And so it's lit in a way where he's sitting in darkness, just absolutely giving the camera the stare of death. And he's holding, it looks in the photograph like he's holding a carving knife. And what it is, is this the edge of the chair lit in a very specific way, but it's like very clear the photographer like intentionally did that. Yeah. So that's the photograph that was inside my office door. Yeah. He looked very, very scary. Very scary. Yes, exactly. Exactly. The other, inspiration from him. But one of the other things that we have in the firm that's actually in the culture document from him is we do first class business and then only in a first class way, which is, you know, we do a first class business. You know, it's like a cool phrasing of it, but when he said it, he was on trial um and they were kind of accusing or he was in court they were accusing him of kind of nefarious things and he was like No, we only do first class business and men only in a first class way, which is Mark and I really loved that. attitude about Like you're definitely not going to tell me who I am. I know who I am. And I'm going to let you know who I am. And that... kind of thing I think is really important. in venture capital to like be principled and people know where you're coming from and be able to trust you and that kind of thing so so we got a lot from him. Yeah. So JP Morgan. Yeah. And so, I mean, I have never, I mean, I think a couple of things I'll say is like, I mean, look, like any venture, there were ups and downs and you never, you know, I could, I predicted everything. I think things generally went really well. And, you know, I didn't obviously know that all along the way, but, um, obviously know that Mark and Ben are incredibly ambitious. I've never, it's funny. Sometimes I'll have some idea and like some crazy thing we want to do. And people are like, what are Mark and Ben thinking? I've never in my, not once have they ever, if anything, have they ever pushed back? it's always can you double it can you double down can you get more aggressive um so just you know and then just it's a very entrepreneurial place and i think this has shown over the years of like how many this this is a good example right here um that you know when we you know we sort of adapt um see what's happening in the world change things around we went through a whole kind of restructuring of the of the firm um uh you know bring in new ideas sort of anything's anything's fair game as long as you can kind of defend it um and so you know that's also why i've enjoyed entrepreneurial culture. I think also what Ben said is very important in the culture of the firm. That's why I was initially kind of attracted to it, having been a customer of venture capital before that and experience the product. I understood that there could be a better product. But that's what I think everyone, literally everyone that I know at this firm comments on the culture and how important that is and how they enjoy working here and feel like they're doing some of the best work of their life. So I think that's all like a very, you know, there's obviously to make good investments in this and that. in the culture. - Well, it's funny that you mention, it's related to the culture, it's funny you mention ups and downs because, you know, from the outside looking in, it feels like it's all ups. - That's how all startups are. Like, the successful startups always look great from the outside as someone who's, I think we can all comment as people who have been in [15:00] Side of startups, basically, I don't know of a startup that wasn't a shit show at some point or at multiple points. It also speaks to the culture I've heard from all three of you guys, things like never complain, never explain, happy warrior. And so, yeah, it's just a testament there. Let's go to the frontier. Let's go to the future. Sometimes there's this phrase in venture, you know, being too early is as bad as being, you know, too late or something. You've been early a lot. You've been, you know, mostly right or right in very big ways, but you've also, you know, been too early at times. I'm curious how you think about technical risk or the idea of being too early in our era now. Yeah, I mean, we talk about this a lot. Like, I think we I think I can speak for Mark and Ben. They can comment. But we believe that basically every good idea that we've ever seen that involved technology has eventually worked or we believe will work if it hasn't worked yet. And, and the important qualifier, good idea. There are bad ideas, but, um, and it's just kind of remarkable, especially having lived through the internet, um, how many things, um, just, you know, almost everything that ended up working had a precursor that didn't work and maybe it was 10 years too early. all line up. So, you know, and so I would say with, you know, I think generally at the firm, I would say specifically in the frontier fund, we want to err on the side of being too early. We understand that sometimes things will be too early and we're, we're okay with kind of quote category risk. Some categories may not work. Look, I mean, even things that sort of work, didn't work. Like, you know, we sold Oculus, got bought, but the reality is like, it's now 13 years later. I still believe very strongly in VR. We'd love to make VR investments, but it's 13 years got as mainstream as we would have liked. So it took long. It turned out there was just many more hard technical problems to solve. I kind of believe, I don't know what Mark believes, I think that with the stuff we're seeing in AI now, you see the first sort of tipping happening, first software engineering getting dramatically better than math. I think there's a scenario, and I believe this, and I kind of want to invest behind it, where we may be pulling forward 20 years of things that, you know, our whole mindset of how we think about technical risk. And, oh, that's a science project, not an engineering project. If you look at the growth, math is not the last thing that's going to change. You're about to have physics. A lot of stuff's going on in hardware right now. I think a 30-person team can credibly build a full-stack device company in a way that you might have needed 1,000 people or something a decade ago. um it's it's yeah so i don't know if you yeah so i would have had so we'll talk about ai sort of a catalyst um so this is the biggest delta between i would say what the early adopters understand is possible now uh versus what kind of everybody kind of normal people understand um and i think that's you know through the individual level but it's especially true of the company level um and the early the ai native early stage startups have just a completely different view on what they can do incumbents in almost any industry, almost without exception. And I think that gap is as wide as I've ever seen in my career. And then that gap seems like it's gapping further and further out, which is AI is just racing ahead in capability, even week by week. And so the leading edge entrepreneurs and technical people we deal with, by the week, they're getting sort of steadily more advanced than a typical incumbent. And so it's the biggest delta I've ever seen. And if you kind of then there's just, there are going to be a lot of industries that are really up for grabs in a fundamentally, you know, kind of more profound way than maybe has been the case in the past. And then it's going to be because the founders are going to have a level of superpowers coming from the use of these tools and these technologies that they just simply haven't had in the past. I mean, you know, had I had, you know, Astra and Netscape in 1994, like, oh, my God. Like, you know, he said, like, Ben, like, what would you and I have been able to do at Netscape? We would have built the whole damn internet. It would have been absolutely incredible. And as Chris said, we're seeing this. We're seeing entrepreneurs come in with plans of a level of depth and sophistication in multiple parts. Connection together. By the way, we would have gotten crypto done then. Oh, 100%. Yeah, yeah. [20:00] like by the way in like two weeks like we'd have streaming video a lot sooner i mean like all kinds of things would have happened and then by the way hardware i mean we never even you know bit off hardware but you know had we been able to there's all kinds of things we could have done um and so um i i just like i think that the leading edge entrepreneurs now are going to have like capabilities which means they're going to have business plans that are like a lot more you know they're going to product plans that are a lot more technically intensive and complex they're going to have business plans that are more ambitious and complex um they're going to be building companies that and then hopefully the scope of their business. And then again, this goes right back to like, those entrepreneurs are gonna call it way outside the lines. Like they're not gonna, we already see this. They're not gonna think of themselves as like, I'm just a software company or I'm just a hardware company or I'm just a whatever, or even I'm just an AI company or anything. They're gonna think very broadly and expansively about exactly how many different areas they wanna touch and how they wanna combine things. And so the sort of conceptual artist kind of aspect of this is gonna just like blow way out. Yeah, I was gonna say, we used to, kind of ask the question is is this idea too ambitious and i don't think i think we're much more likely to ask this is this ambitious enough um because you know what's possible is so spectacular and if you do something moderate, it probably won't be differentiated enough. And by the way, look, incumbents, you know, we spend a lot of time, have a lot of friends and incumbent companies, by the way, including incumbent tech, including incumbent companies in Silicon Valley. And it's like, you know, we wish them all the best. And, you know, we, by the way, we have lots of companies that would like to arm them up with all these all these new tools also. And so, you know, no doubt some of them are going to be able to adapt. But like, you know, if any of them are listening right now, I would say like the clock is ticking. Like it's like stuff is moving. the pace development right now and the speed with which things are changing. I'm trying to keep up with all of it and it's nearly impossible. The super empowered 24-year-old with AI is going to just achieve amazing things in the next decade. There's a question we were asking right before this, which is, is AI more sustaining or disruptive in terms of will more of the gains go to incumbents or startups? It seems so far it's both in some sense, which is the incumbents like Meta and others have sort of adjusted very well. And also, there are net new companies that are almost a trillion dollars within a decade. And so, is that your read that's effectively both? Or how do you think about the sustaining disruptive? Well, the incumbents that are adapting are actually the incumbents, I think, for the most part, that are actually going directly into AI. And then there are certain companies, certainly in tech, that are on the leading edge, even if they're not primary AI developers. But at least right now, the pattern is not that. I mean, it's just really... for a different podcast. There's a very specific thing that I think is happening, which is I think many companies are not adopting AI while their employees are. And their employees are not necessarily telling the management what's happening. And by the way, I'm going to guess every single person listening to this podcast right now is thinking, oh, yeah, that's what I'm doing. I'm using AI to do all my work or at least let's say fact check all my work, proofread all my emails, even if not have them written out right. And by the way, and again, it goes back to our role in the world, which is like, some of those individuals are going to figure out, like, oh, with this tool, I can now start my, you know, it's now easier than ever for me to start my own business. And so I think startup formation is going to skyrocket from here. By the way, it already is. Oh, yeah. I mean, we're seeing it. I mean, we're seeing it 100% for sure. So anyway, just kind of go back to the theme of this is just I'm completely convinced. creative, original thinking, many more combinations of things that we would have considered to be separate things in the past. And we're going to see, yeah, founders was just like, and teams was just like an incredible level of skill level, incredible level of skill that they otherwise might have needed, you know, 30 years to achieve or something they're going to have like right out of the gate. And by the way, the other thing I'd say is that the Christensen disruptive innovation frame assumes that sort of the technology world is relatively contained and that these are companies fighting with each other. I think it's probably the wrong frame right now, which is it's really sort of people who are technologically modern going out into other industries and just changing the economy more broadly. Right. Especially with these kind of full stack companies, you go and you create a full, you know, like we just announced our investment in atoms. building a full stack food service and other things. You talk about this sometimes, the market has gone from the 10 big tech companies fighting with each other to the 10 tech company or [25:00] and in all the startups going against the other Fortune 500 or the rest of the economy. Yeah, that's right. I'm curious where you guys think we are in the development, because it feels like in the Internet era application, we're sort of the biggest companies, Facebook, Amazon, etc. But in this era, it feels like NVIDIA and some of the more hard work companies are taking a lot of the margin or some of the bigger companies. how do you think about you know where we are are we in the sort of applications or consumer like how do you think about that i think mark would say all all of the above and i think a lot of people think that actually right now it seems like a lot of stuff is working you know obviously the big the big ai labs but you know open source is growing very very quickly there's obviously the serious efforts in china the serious efforts in the u.s um a lot of application layer things are doing really well. So maybe at some point, obviously over time that shakes out and the kind of value chain, there's certain layers that do better than others. But then the other thing is just the, it's still, it's kind of crazy. You have the demand for a lot of this stuff is still very early by most metrics Yep I think your team just put out some charts on this It like 3 of measured enterprise use or something like this And it's just hard, and it just seems like the market for intelligence is very, very large, and it's only getting started. So, yeah, I don't know. Yeah, I agree. And one of your points also is you mentioned that every new technology has this sort of first phase where people think about what are the old use cases, how they just do them with new technology, and then, of course, people figure out net new cases that are native to technology. And so where are we there? Yeah, I mean, the classic example I like to use is the internet, right? Where in the 90s, you had sort of people taking existing behaviors, like you might order a Sears catalog or something, and instead, Sears puts it on the internet. And of course, when they do that, you want to use the internet version. It's easier. And a lot of the early internet was like that. And then you had, you know, in the 2000s, you had YouTube, and they come along, and they put up an empty website and they say, well, someday there's going to be these YouTube influencers and that's going to populate the way. So they were betting on, they weren't just betting on the technology and taking something they knew would work. They were betting on a cultural change, a behavioral change. So in some ways they were taking more risk because they were betting on the technology and these broader changes But that where you got the really kind of world changing stuff isn it Social media all the other and then of course mobile accelerated it and i think that a my own view is that a kind of pretty common pattern it just just human nature right you you build something and the first thing you do is you do these things you already know um in a better way and i think that's what we've seen in ai so far where you have you know people already coded people already did math um people already did knowledge work people already were used to like search engines and sort of semi-chatting and they're doing those things now. But we've only begun to explore the space of like, what are the radical things that are new behaviors, new activities, right? Things that people have never done before. It seems like we're probably at that tip. I believe we're kind of at that tipping point where we're going to start to just sort of get, see the crazier, weirder stuff, which I personally am very excited about and find that I always find those waves in technology, the most personally exciting. They're kind of more, and there's sort of more layers of risk going back to Frontier, like you can find some things will be, you know, kind of more direct shots on goal and other things will be these kinds of bank shots where you have to have multiple things go right. And maybe there's more layers of risk. But maybe if you're right, there's more upside as well. Yeah, I'm really excited. Social used to be in the 2000s, like every few years, there was a new major network. There was Facebook WhatsApp there was Snap TikTok And then it felt like there was a little bit of a dearth on the social side But with AI it does feel inevitable And then dating with Tinder of course, and there hasn't been something in a while. It feels inevitable that, hey, if there's this interface or device that I'm giving all my information to, that there's going to be some way that these are hooked up and enabling a whole new set of social experiences. Well, I mean, you can talk about this, Mark, but we're headed to a world where it looks like the the most numerous participants on the internet will be agents and not people. We're at early phases of that, but it seems somewhat inevitable. You have these products like Muse and Instinct that are sort of utility proxy agents for people. And then you're going to see a whole different sets of categories of these agents, and they'll become the main participants on the internet. And then there's questions of like, you know, will they need their own ways of communicating and transacting and sharing knowledge and doing all the things people do? And so there's probably going to be a whole series of innovations along those lines. Rentahuman.com. Rentahuman. That inverts the model. Maltbook was cool too. Yeah, yeah, totally. Well, yeah, Maltbook was the public kind of version, and then it turned out the agents figured out how to do their own. [30:00] Book of the Hugging Face. The Hugging Face thing, yeah. Yeah, it's going to be a lot more. Yeah, the agent ecology online is going to be spectacular. People are going to plug into that in all kinds of ways. Mark, I'm curious if there are things that you're tracking either in social or consumer, or even just this frame of like the skeuomorphic, you know, things that sort of worked in the past sort of platform era, and now like what net new use cases or what is native to that you're seeing or anticipating or looking forward to? Which is product manager is basically designing products for product managers, right? It's like it's by the way It's the one thing everybody does is they build products for themselves It's product managers have the story that they're only for people and yet somehow all the use cases are you know Book me a restaurant, you know, do you in San Francisco to go have dinner with my friends who are also product managers? Or you know book me a plane flight to go to the product management conference where I also get to hang out with my product manager friends and So there's this you know, it's a little bit again. There's a role for this But it's a little bit like I think it's like the anthropic. I'm what is it? I'm a happy helpful harmful harmless I'm a happy, harmless, whatever it is, honest assistant, right? And it also means I am the most boring possible thing you could possibly imagine that's going to be costly lecturing. You've asked me a question I'm not allowed to answer, right? And so it's like there's just going to be this sort of, we just have this very, just the nature of the early companies, you just have this very blinkered view on human activity and what people are going to want to do. And it's your point, like with Muse and Instinct, it's starting to open up. enjoyable, exciting. By the way, lucrative people are going to make money. There'd be all kinds of ways for people to make money, be able to save money, be able to participate in parts of the economy, be able to be creators, be able to create new kinds of art. I mean, just in the last three weeks, there's been an explosion of people making music videos, like de novo, on an incredible array of creative ideas and topics and styles. Like video games in the last three weeks have blown up. Can we mention that just because that's so striking? Yeah, I mean, I always think I always find video games interesting because they're kind of the lead. I find that they're often leading edge of media because they're just it's a technical culture that kind of iterates quickly. But like I just saw one where it's like you can take any two. Well, first of all, you can disassemble everything, port them and just crazy stuff going on now. You can run like Windows games on Unix faster than on Windows, like because of these disassemblers and these AIs are so good. combo video game of it, which, you know, just like a crazy new behavior. Super Mario in GTA, right? Spider-Man and Jurassic Park. And it's just, and literally the crazy, like to Mark's point, it's been, I think like two weeks or something. It was like since what, like Opus 5.5 or something. And so it's just like the rate at which this stuff is happening. And like, well, in a month, there'll probably be some other, you know, two weeks, there'll be some other big wave of this. You see Epic just yesterday said no more humans, right? Yeah, there's been cultural resistance in the video game industry to AI, but I think that's the first of the dominoes to fall because it's just inevitable because it's a much better way to build things. And it's going to be great for consumers. You're going to have this – I think it's going to be a creative renaissance. You're going to have this – any independent developer can go and build like they have a huge team and still have – I think they can still have a lot of room for human creativity. It's just – it's superpowers with human creativity. So I think you mentioned movies. Oh, yeah. That might take longer. that when that where that is on the you know the or that that death door meme or whatever like you know i don't know which door it is but uh you can snap it quite quickly i just i'm completely i'm completely obsessed with this movie this movie digger uh that came out and i'm like literally the only person who saw it you will be 100 times it'll walk out after the first half hour you you will want to i have a friend who literally took i have a friend who took her mother to see it and they walked out after the first half hour and now they're running joke in the family is oh digger A lot of people have had that. But if you actually watch the entire movie, there's a reason why they did what they did, and it's not what you think it is. And I don't want to spoil it, but it's not the way it is presented at all. It's very clever. Anyway, so it's this incredible creative achievement, but it's a $200 million cash loss for the studio. But that's because it had a $180 million production budget. And so it's like with AI, what if that movie had had a $20 million production budget, of art and creativity at a lower price would have been great. By the way, as a business thing would have been ... That would be on a $2 million budget would have been insanely profitable, would have made the investors back 10 times their money. There's a huge thing that's going to open up in the entertainment business. Then the other one, Chris, you and I have been in and around hardware for a long time. My whole career, hardware ... I'm a software person. Hardware has always been like terra incognito, which is like there are dragons [35:00] It's just, it's been so easy to blow up companies by going into hardware. And then again, your point, like just in the last three weeks, so this open source tool drop called REA, reverse engineer anything. And it's this thing, it harnesses an AI model and you point it at anything, it'll reverse engineer it and give you source code. And one of the things that you can reverse engineer now is any piece of hardware, right? And so you have a thermostat that's like, pissing you off in your house because it's not working right. You can point this thing at the thermostat, reverse engineer it, and the AI will write you new code and install it and put a new interface in the thermostat. And the same thing is true for basically anything. Basically, any form of hardware can now be taken over and reprogrammed with this stuff. And so all of a sudden, it's just like, I mean, you take all these spaces. I don't know if anybody's doing this yet, but just home automation. Home automation has always been a complete nightmare of a market and to implement as a customer. If anybody's ever done any sort of new house build, it's just a nightmare. AI bot that just takes over all the hardware in your house and runs it, however it is that you want to do that. And I have friends that are literally doing this right now in their own homes. And so we are potentially entering here, we're entering a renaissance. One of the things about it is anybody who understands software may sort of automatically be able to do a lot of the things that historically have been difficult in hardware in a way that's just never been conceivable before. And so, yeah, it just, yeah. And then this sort of multiplicative thing, these are kind of the you expand out and you just kind of think, you know, the entire economy is kind of open for this kind of thing now. Ben, are there any AI native use cases that you're seeing or hoping to see or frontier spaces that we haven't discussed? Well, I think that was a really good discussion. I mean, I think to me that the key is like, These are going to be hard to anticipate. because they're brand new things. It's funny how the film industry has reacted where Some people have really embraced it, and then there's a bunch of people who have buried their head in the sand. But I think that what's going to happen with movies is there's going to be a new media. You know, I think the AI... film is not going to be a movie it's going to be something very very different uh and and then like ai will also be used to make regular movies uh kind of more efficiently and and you know with better special effects and so forth but the stories you can tell if you have this thing are just completely different than what you could ever tell before like there's a you know it just hasn't been viable i mean it's barely been viable for like christopher nolan but he's like the one guy who But nobody else had a chance. And now everybody's going to be able to do it. And then there will be new ideas that come because you could do whatever you want. I always think of the camera. The negative frame of the camera, the camera's invented. The negative version, I guess, is if you're somebody who paints landscapes or something, it could replace you. The positive frame is it unlocks motion pictures. You couldn't have had that without that. A lot of these technologies will both change an older form of media, but then also allow people to invent a new one, to Ben's point. but they'll also do things that are probably hard for us to imagine right now that'll be brand new. Yeah. The brilliant Peter Thiel once had this quote, I think a decade ago or something, where he said, you know, crypto is libertarian, AI is communist, which meant, you know, crypto is decentralizing, AI is centralizing. But I'm not sure that's entirely true, given the conversation we're having about how AI gives so much leverage and so much power where, you know, one person companies or 30 person companies can do, you know, orders of magnitude with what they could do prior. Yeah, I think there's all these interesting questions embedded in that. One is, what is the end of final market structure of AI? I think where it's headed right now is you're going to have very successful, like the big open AIs and anthropics. But you're also seeing a really big rise in open source. If you look at the open router data and things, like open source is growing, I believe, much more quickly in terms of token consumption. And then we haven't really seen yet, and I think we may see with all the trends are there, which is local models. Like people running these things at the edges, running them on their computer. You can run a top-end coding agent on your computer or chatbot or something like that. So I think that there's a lot of opportunity for a market structure that's sort of more broadly decentralized like that. And then in terms of crypto, I think crypto can play an important role. Like the natural way when you have an economy of agents for them to pay each other would be stablecoins. And then on top of, you know, once you have sort of that base layer of programmable money, out in the crypto world? And so these are all open questions. I think that's what makes it kind of exciting and, you know, something we'd love to have an influence on is sort of, you know, I think we're, you know, we're big believers in open source software, open. [40:00] weight models, crypto, obviously blockchains. And I think I would love to see a version of this future that has all this great technology, including these big centralized companies, but also a lot of open source, you know, kind of level playing field. I think it's better for consumers to have options like that. It's better for startups to have options like that. And so, you know, we'll do what we can to kind of hopefully nudge things that way. 00:01:14.000 -- 00:01:16.000 On that note, Mark and Ben, are you guys encouraged with, you know, where this sort of state of open source is currently from a technological perspective, but also from a sort of, you know, um, sort of just how it's perceived and how it's the success of the industry in general? I mean, right now, it's great. I mean, yeah. So right now, open source is racing ahead. You've got this great dynamic where, you know, there's, you know, the two great tech superpowers of our age are the US and China. Both have, you know, very active open source, you know, kind of worlds in addition to, you know, companies building proprietary systems. You know, there's been this looming threat. I mean, you know, we've talked about this in the past. There's been this looming threat for the last three or four years of a level of what I would consider to be, you know, draconian and completely unacceptable, you know, either regulation or banning of open source various folks in governments have been threatening. I think the EU still aspires to do it. They just don't quite have the leverage. They threaten everybody with fines until we stop doing it, I guess. But the current US administration is 100% pro-open source. It's been very encouraging. In fact, very much so, 100%. The current administration 100% wants American open source to happen and to win AI globally. The Chinese also, and by the way, a big surprise would be like this and think about open source AI for the world, but at the moment they are. And so at the moment, it's just incredible. It's just absolutely amazing. And then the open models are kind of lapping the closed models by six months, 12 months, depending on how you count. And then by the way, the educational part of this, I also always think when people talk about banning open source or regulating it, they're like, it's going to get used for bad things. And there's sort of that whole discussion. But the other is like, do we want people to learn how this stuff works? and do we want people to understand it and be able to deal with it? And by the way, But by the way, be able to actually understand the problems as they arise and how to fix them. And do we want the next generation of kids to actually understand how this stuff happens? Like, what if to learn about AI? Like, how would you feel if the only way your kid can learn about AI is to go to work for one of two companies? Like that, you know, as a parent, I think would probably drive you pretty crazy. Whereas in a world of open source, like every kid can learn how this stuff works. And it's actually amazing. One of the really underestimated things about AI is AI will teach you about AI. Well, with one exception, which is the AI models from certain of the large companies actually will refuse to do that. which is sort of very interesting. But the open source models 100% will teach you how to make open source AI. And so every kid in the world, I think, should have as their birthright the ability to fully understand and utilize this technology. By the way, defend yourself. So how did Hugging Face defend themselves? Open source software. Open source means everyone has the most advanced vulnerability scanner to protect themselves from cyber. Yep. Everyone has a doctor and a genius professor in their pocket pocket you know i mean yep It's how we have why the Internet's ubiquitous. You can get Internet access to all the world's information for the price of a ten dollar cell phone because of open source. So one of the things that started is real quickly, but one of the things that started is like wilderness explorers are starting to take local elements with them on their phones, completely loaded up to not require an Internet connection. And the reason is because like if they get like, you know, I don't know if like I don't know whatever if a bear. I don't know what happens in the wilderness, but I don't hike. or whatever. It's like you want to be able to talk to an AI, but you might not have connectivity. Yeah. And so an open source model on the phone, all of a sudden, it's just like you have a professor expert on, I guess, all aspects of wilderness survival or whatever. And that's a level of capability that you would not have if you were reliant on a handful of proprietary vendors where everything's running in the cloud. And so, yeah, at the moment, I feel really good about it. I am still worried that the various governments around the world are going to really kind of get hostile which is like without open source, AI inevitably centralizes and inevitably centralizes down to, you know, one or two companies or maybe just flat out the government. Right. And I guess I would ask people the following question, which is just close your eyes and picture the concept of government sushi and then keep your eyes closed and picture government AI. And, you know, how do you feel about that? And open source is the guarantor that that's not the future. Yeah. I mean, to Mark's point, has always led to badness in the world as a massive concentration of power. and you know one company one Government when when anything is it's always been bad, but you know kind of back to the point on open source Like if you look at the problems in AI to now with the safety problems and so forth probably the biggest safety problem is this reward hacking? phenomenon where the air will do something that you didn't tell it to do but [45:00] but is kind of a means to an end to get its reward. And the labs so far haven't really worked on that very hard for whatever reason. You know, they're busy kind of racing each other. and maybe there's no way to figure out what's going on with that and no way to kind of build a model that is more resilient to that kind of idea but like what if every PhD student in every professor, every undergraduate in every university, could look at the weights and the war at hacking, and see if they could solve that. Maybe that would be a pretty darn exciting thing. These kinds of things are just not possible if only one company can work on the problem like you really want the whole world making this technology great and making this technology safe not just the people who happen to work at two companies or Maybe three companies go meta. Four companies go SpaceX. Yeah, exactly. Every um, Well, it inspires a couple of points. One is, you know, every week or every day, you know, there's a technological development or breakthrough that we're blown away by. And then also it's coupled with the statement of like, this is the worst the technology will ever be. Like every day, it just it just gets, you know, it gets better and better. And it's compounding. And funny, you know, Teal also had this quote around, we wanted flying cars, and all we got was 140 characters. And it's funny, because the guy who now runs the company who that's 140 characters, or it also is building flying cars, and we're investors in both. So it's funny how full circle it all is. Chris, I want to come to a different point that you had in one of your write-ups, which is the business model of the internet is breaking or is vulnerable why don't you talk about that I mean, the Internet was sort of there. I think of it as I call it the covenant, the Internet's covenant, which is sort of a deal between a deal between the distribution side of the Internet, Google, Facebook and so forth. And the content side, you know, news sites, travel sites, whatever it might be. You think about Google, like the idea was you kind of give Google a snippet, let them index you and then they'll send you some clicks. Right. That started to break like maybe last decade. But particularly now you go to Google, you get an answer. Right. and more you're sort of the social networks are trying to keep you on there not linking out. And what that does is it has downstream effects, right? It means that the websites that make money on ads and conversions and other things can no longer do that. I think that's probably going to, you know, you see the early signs of this like, you know, Stack Overflow and some other websites where the traffic dropped precipitously when you had sort of AI replacements. But And so, you know, but like people will still be booking track, like maybe they won't go, maybe your agent will go to the travel website or maybe, you know, some other, you know, you'll get a recipe in some other way. People will still get these things. But, you know, many of these transactions will still happen. They just won't happen in the way they were happening. And so that the negative is it's painful in the near term. And there's a bunch of businesses that are built on the sort of human intention economy that will have challenges. okay, what does a better internet look like? You know, an internet where people are empowered with, you know, AI and everything else and want to do things and how do we kind of reorganize it? So I think this is going to happen over the next, let's call it decade, is you're going to have sort of this kind of great reconfiguration of the internet and how the economics work, how the attention flows, how knowledge is shared, how people produce things together, collaborate, So, I don't know, it feels in a way that I feel like mobile didn't have that kind of impact. Mobile, obviously, you know, I think, you know, made the Internet go from whatever, 500 million to 5 billion people and increased engagement and a bunch of other things, you know, empowered people with all the information in their pocket and had a lot of good effects. of opportunity. On that note, just because we're talking about mobile, do you have any predictions or things you're excited about as it relates to computing or devices or sort of form factor in which, you know, ever since sort of the iPhone has been pretty, pretty locked in? Are there new forms that you're particularly excited about or looking forward to? Well, I mean, everyone's talking about wearables and I think you'll see a bunch. I mean, we're pretty clearly going to see a bunch of, you know, that just seems like it's unlocked in a way that it wasn't before with AI and voice. And I think that's very interesting. Obviously, that's something that's sort of well covered. Like I've always long believed in VR. right form, you know, still heavy, kind of sweat. A lot of it's just ergonomics. But, you know, it just seems kind of obvious to me, as it has to many people and science fiction writers and others, that if you have, you know, there are times in which people want deeply immersive, you know, kind of otherworldly. [50:00] experiences. And once that gets to the right point, I think, you know, AI might be the unlock, because now you can create this amazing content that actually it's seeing on Twitter now, like someone just did a port of Titanfall and so like by himself, it's like this incredible port. I don't know if it's going to, you know, survive copyright lawsuits, but people will invent new stuff that, that, you know, that they invented. And, and so, you know, I think it will just sort of unlock this wave because it was really kind of technically hard to build a, you know, VR game or a world or So I think you might see the resurgence of older devices like that. There's all this kind of more crazy futuristic stuff happening with Neuralink, brain-computer interfaces, obviously vehicles. I talked earlier about drones and obviously cars, self-driving cars are widespread. 3D printed case for you and you get some cheap motherboards and then you write some custom firmware code and like you're off to the races and so um maybe we'll see kind of a like there was kind of a movement like 12 years ago 15 years ago kind of around maker bot and all these maker things and but it was just the problem was just kind of hard yeah so you know that would be cool i don't know what else Yeah, architecture, I have a friend I shouldn't name, but there's done a complete architecture, design, everything for a new building. And, you know, people are assembling it, but like the whole thing is being steered by AI. I think the new models are capable of doing what they call design for manufacturing. Yeah, yeah. The final diagrams and specs to be able to set in a factory, which is very hard to do normally, a part of the manufacturing process. I think the models can just do that now. these are great examples of this, like these domains that historically have been extremely difficult or prohibitive or impossible for kind of either normal people or for normal companies to do all of a sudden become, you know, quite possibly, you know, possibly just straightforward. Yeah. Is it worth saying more about your idea that, you know, AI ran out really in single player mode? And there's opportunity for machine-age networks Sure. I mean, I mean, just a simple idea, right, is that just, you know, in the Internet era, most most technologies have had sort of multiple phases where you sort of first people will build some like you have the initial early iPhone apps or like these little flashlights and other kinds of sort of simple single single player apps, something you use on your phone. which is sort of a commerce network. You had Instagram, which is a social network and so forth. um so one one might one observation one might make when you're looking at the ai landscape as amazing as it all is it's still mostly you're sitting in front of a computer and you're typing and getting responses um there's some like little minor light sharing features but at some point one might expect to have um you know sort of a network a multiplayer phase of ai where where you know you see you see it also like in the hugging face hack there's a swarm that's obviously a bad is one of the things that solve the, one of the math theorems, you know, you can imagine a world where there's, you know, another word for swarm is a, you know, collaborative fleet of agents or something. Right. And so like, you can imagine lots of use cases where solving a hard problem, designing a building, you know, doing some scientific breakthrough, uh, you might, might, that might be the right way to do it. You also see, like, I think Muse and instinct have these features where you can like trust other people and you can imagine that sort of evolves into a this. And I think people are just kind of in the experimental phase, but it's just based on history and the possibilities of these products. It seems like it might be a fertile area for entrepreneurs. By the way, we've alluded, we talked a bit about sort of the education and just, you know, the learning opportunities that are enabled via this technology. I'm curious, you know, obviously we just, you know, uh, incubated harwoods and dreesen academy um thank you for support on it if you were 18 today um how would you think about what you might uh study obviously you have an academic philosophy background um I think I'm stealing Mark's line, but I think you think there's one thing to do, which is study modern alchemy, right? Yeah, yeah, yeah, yeah. Go for it. Well, humans figure is Mark's framing, but I mean, humans just figured out how to turn sand into intelligence. And the way to learn that I think is math, computer science, maybe economics. I don't know. And, um, and it's, you know, like, I think it's also like, like I, I, and I think Ben and Mark were lucky enough to have our, you know, a lot of our careers. happened during the growth of the internet. I feel very fortunate that I was able to do that. I think that was... [55:00] something bequeathed to me by people before me and I'm grateful to them. And, you know, I think now, look, it's obvious that, you know, that the AI stuff we're talking about now is going to be the dominant narrative of the next 20, 30 years. So I think being it doesn't have to be not to necessarily be solely technical, but I think being in some way in that in the mix and at the cutting edge and using these tools feels like. Yeah. Kind of the obvious thing to do. I don't know what you- Yeah, I think a lot of other fields are going to be revolutionized, right? So I mean, just the field of the classics is being revolutionized because now you've got the Vesuvius Scroll Project and you're able to use AI to decipher third scrolls. And there may be entire new schools of philosophy that get discovered to study classics, the things, the lost books. Economics. I just have lunch with an economics professor. I like the whole field of economics is going to be transformed around this. Yeah, exactly. Direct discovery, design. By the way, design, you know, we talk about movies, but also just broadly, broadly design, creativity of all kinds, all the, all the, all the forms of art, music, music. The zoology, you're going to know what the animals are saying. This is super interesting. Like we are plausibly heading towards a world in which we're going to understand what the animals are saying, right? Animal psychology will be actually real. Yeah. Yeah. So like, okay, like dog, you know, I don't know, like dog, you know, dog training is going to take on a whole new thing when they actually understand what the, fuck the dog is that right i think there's an x-prize for that yeah it's like a it's like a And they're definitely, I mean, anybody who has a dog know they talk. They're in some weird language, you know, but they definitely are saying something. And certainly cats do. I wait the entrepreneur listening to this who comes in with a pitch. received on a generational level. And his famous framework was there's any new technology is received three different ways by three different age cohorts. If you're below the age of 15, it's just the natural way the world works. And I've told in other settings, the story of introducing my kid to chat GPT at age seven. And I'm like, this is such a big deal because the computer answers questions. And he's like, duh, like what good is a computer that doesn't answer questions, right? So it's just normal. If you're between the ages of 15 to 35, it's new, exciting, career out of it, in which case you want to learn all the new things. And if you're above the age of 35, it's unholy and evil and will surely overturn all existing structures and destroy society. I'll never answer the telephone. Exactly. Old man yell at clout is a recurring phenomenon. And so I think 18-year-olds right now, I mean, it's got to talk about prime time to grab these new capabilities and run with them. And it's going to be creation of entirely new fields And then, look, I mean, I think kids younger than that, I'm seeing with my kid, but like, yeah, they're just, it's just, of course you have this capability. Like, of course you do. It's just like completely obvious. Well, and actually the schools, the schools are doing us a favor. Like, so the schools are not responding well to this. And so, you know, the schools are, you know, banning AI or having all these, you know, controversies with it. But of course, if you're a kid, that just makes it cooler. Yeah. Right. And so AI is going to be like the, you know, AI is your like secret superpower that you have to like deviously figure out how to take advantage of. And so I think kids are going to have all kinds of ideas for what they're going to do. Adults keep saying oh well what should the kids do like this so hard to be a kid. It's like No, no, no, no. basically It's you that's got the problem. Because you're obsolete. The kids are going to be all superhumans. And they're going to be able to do anything. And the world is open to them. And they're going to be able to enter fields that they could never enter before. What I see in this conversation and your fun and your work more generally is, to use another tool, is kind of definite optimism. The future is happening. It's going to happen. A lot of what we talked about in science fiction is going to happen. It's a matter of when. and maybe sometimes it'd be too early, but we're going to keep betting. And as long as you keep having that conviction, you know, It's going to work out. Yeah. And to be clear, one thing I want to clarify is that, you know, we're throwing out all these theories and everything. But in the end, I think, as Ben said in the beginning, like we're we're in the betting on great entrepreneurs business. And so, you know, we plenty of ideas that were not discussed today that are probably, you know, more interesting and more creative. willing to, you know, to engage with those kinds of creative ideas. So, Um, so I would say, um, He said definite optimism. I'm like, optimism, but also... [60:00] I'd say humble, definite optimism or something, intellectually humble. Yeah. And that I've been wrong so many times. We just, we really want to, we want to find great people who have their own definite optimist view and back them. That's right. The entrepreneurs get to be. Yeah. Definitely. Yeah. Yep. That's a wrap. Chris, thank you guys for coming on the podcast. Good. Thank you all. All right. Okay. Thank you.