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Sonnet 5 发布、中国4900美元机器人、Fusion首座电站获批|Philip Johnston 对谈 | #268

Peter DiamandisSalim IsmailDave BlundinDr. Alexander Wissner-GrossPhilip Johnston

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TL;DR
  • Anthropic 的 Fable 5 下线,让前沿模型的使用权变成一阶监管与供应链风险。 这款旗舰模型因美国政府以国家安全为由将其撤下,已离线15天;据报道,Stripe 曾用它在一天内重构5000万行代码,Axios 称其可能在几天内恢复。现实层面的建议很直接:「不要把产品或公司建立在单一模型之上」,并应预期跨境获取前沿智能将逐步进入许可制。

  • Sonnet 5 与其说是能力突破,不如说是 Anthropic 为填补 Fable 5 供应短缺而推出的高价过渡产品。 Dave Blundin 称其「能力有些平庸,但价格很高」,Alexander Wissner-Gross 则认为其价格—性能曲线异常,因为 Opus 4.8 看起来仍然更强。不过,受限的算力供给以及 Anthropic 集成式 Claude 产品栈,可能足以让它继续卖得出去:「AI 已经卖光了。」

  • 人形机器人硬件正逼近商品化经济学,投资价值将转向软件、专用工作流和制造规模。 Unitree R1 的报价为4900美元,Morgan Stanley 对中国市场的预测从14,000台上调至50,000台,并预计2030年达到500,000台;中国已经拥有约140家人形机器人硬件公司。Philip Johnston 认为,一旦机器人能够组装其他机器人,体力劳动可能会「便宜到无需计量」。

  • 机器人赛道的机会远不止押注一个通用人形机器人赢家。 Blundin 将未来3—10年定义为从白领 AI 转向机器人建设数据中心及其他工业系统的阶段;Diamandis 又将场景扩展到生物科技、厨房、晶圆搬运、擦窗,以及美国规模达10亿美元的清理屋檐排水槽市场。清理屋檐排水槽加擦窗,被定义为一个全球200亿美元的机会。Diamandis 提醒,家庭园艺有「100万个边界情况」,而 Johnston 认为枯燥、肮脏和危险的工业工作大概率会先实现商业化。

  • 能源政策正从环境约束转向 AI 驱动的产能建设,裂变将在聚变规模化前承担过渡角色。 瑞士正在逆转弃核路线,尽管其4座老旧反应堆已经供应全国40%的电力;Helion 获批的 Orion 电站则计划在2028年向 Microsoft 提供50 MW。聚变更深层的意义在于下游效应会不断叠加:「一旦能源变得充裕,其他一切稀缺都可以谈判。」

  • Helion 获得监管批准,让聚变更接近基础设施项目,但它还不是眼前电力紧缺的答案。 约50家私人聚变公司已融资约60亿美元;Commonwealth Fusion 计划在2032年前后建设400 MW电站,Helion 则已融资约10亿美元、估值54亿美元。短期需求仍需依靠提升电网利用率和错峰调度来满足,而紧凑型聚变最终的「杀手级应用」可能包括地面基荷、推进系统,以及低效率但低成本的储能。

  • 轨道算力正从科幻命题变成已经验证的基础设施,但发射能力仍是瓶颈资源。 StarCloud 已将 NVIDIA H100 送入轨道,训练 nanoGPT、运行 Gemma 并处理 SAR 影像;StarCloud 3 设计为一艘200 kW、3吨级航天器,若每次 Starship 发射部署50艘,可新增约10 MW算力。Philip Johnston 预计未来10年大多数新增算力都会部署在太空,但承认届时轨道算力占总量的比例可能仍低于5%。

  • 垂直整合正成为 AI、发射、连接和频谱领域的决定性组织形态。 SpaceX 可以把火箭、卫星、频谱、Starlink、直连手机服务以及日益增长的轨道算力整合在一起;Rocket Lab 收购 Iridium 后,则获得了全球协调的 L 波段频谱,并与发射和卫星制造业务形成组合。Johnston 更看好光链路最终占据主导地位:「激光是太空通信的未来」,而且还有一个额外优势:它不受监管。

摘要 · 为研究而整理的核心内容

1. 专家一再把指数级市场线性化

  • Diamandis 开场回顾了太阳能、电动车和电池的预测:曲线一再被画成水平线,但实际渗透率却持续复合上行。Salim Ismail 给出的解释不是数学问题,而是制度问题:专家能够准确测量一项技术,却会错过「围绕它形成的复合生态」,而30年的经验往往只是教会一个人「怎样不要做某件事」。

  • Wissner-Gross 给出了简洁的修正方法:「把实际历史数据取对数,再交给专家做线性外推。」Ismail 最喜欢的反面样本,是每隔两年就会重现一次的摩尔定律终结论——他说这类文章已经持续出现了约60年。

  • Diamandis 将预测失灵直接连接到人形机器人。Morgan Stanley 对中国市场的估算从14,000台上调到26,000台,再到50,000台,并预计2030年达到500,000台;Elon Musk 给出的区间则从数千万台延伸至2030年的50 million台,并预计2030年代初达到数十亿台。

2. 超级智能将通过机器走出数据中心

  • Wissner-Gross 的演进路径始于稀缺机器人承担工厂和物流工作,随后进入每人约1台人形机器人的家庭服务阶段,再往后,当人均机器人数量达到10台或100台以上,场景会变得更加陌生。在这种密度下,人形不再享有特殊地位,微型机器人、纳米机器人和专用形态将接手那些原本不具备经济性的实体任务。

  • 他的核心判断是:「超级智能注定会从数据中心溢出到街头」,主要载体是自动驾驶汽车和通用机器人。人类可能会迅速穿越低机器人、每人1台机器人以及每人多台机器人的阶段,而不会停留在熟悉的家庭助手形态。

  • Blundin 认为未来1—2年将围绕 AI 算法、芯片设计和白领自动化展开;但在3—10年后,机器人系统将开始自动化建设数据中心。Diamandis 又将案例扩展到生物科技、化学混合、凝胶读取、厨房和建筑。

  • 机会未必会集中到140家通用机器人赢家手中。Blundin 认为市场可以容纳「数千家乃至数万家」机器人公司:仅美国清理屋檐排水槽的年市场规模就达到10亿美元,而一台同时处理屋檐排水槽和窗户的机器,对应的全球市场估计为200亿美元。

3. 商品化机器人本体将价值推向软件和工作流

  • Unitree R1 展示了高度动态的动作,售价被引用为4900美元——「一辆便宜二手车的价格」。Diamandis 将这一价格视为机器人的 Raspberry Pi 时刻:个人创业者可以买下一具实体,自主试验而无需获得公司许可,再把发布的技能变成新的收入层。

  • Johnston 认为,自我复制是关键成本门槛。如果人形机器人能够组装人形机器人,单位成本将逼近原材料加能源;由于服务经济中约三分之二涉及体力劳动,机器人可能会对体力工作产生类似智能体对知识工作的影响——将其边际成本推向零。

  • Diamandis 认为制造门槛没有那么神秘:CNC 铣床和自动车床已经能够加工零件。剩下的人类工作往往只是取下一个部件、放入下一台机器,再完成最终组装,因此「机器人制造机器人」的第一步,是自动化这些转移流程,而不是先教会人形机器人从原材料开始加工金属。

  • Diamandis 称园艺包含「100万个边界情况」,Johnston 则给出了商业化节奏上的制约:工业领域以及枯燥、肮脏、危险的工作,可能需要10年才能消化,之后才轮到通用家务。Diamandis 还提示,廉价的中国机器人本体可能引发类似前沿模型出口限制的国家安全进口管制。

4. 无人机先成为急救响应者,再成为武装警察

  • 奥兰多6月17日的部署使用了9个机库和11架联网 Skydio 无人机,接到符合条件的911坐标后出动,并由通过 FAA 认证的飞行员控制。一次单机试验显示,无人机约有三分之一的时间比巡逻警员更早抵达现场,并在97%的案例中提供了有用信息。

  • Diamandis 承认隐私问题显而易见,但仍支持在明确规定数据留存、访问和使用方式的前提下部署。他最有力的理由是医疗救援:无人机可以立即携带除颤器穿过交通拥堵;Wissner-Gross 则回忆称,一家墨西哥保险公司曾使用无人机在车辆移动前记录事故现场。

  • 萨克拉门托提供了更具争议的边缘案例:一架携带磁铁的无人机从一名疑似熟睡的嫌疑人身边移走了一把刀。Blundin 认为实体介入属于小众场景,距离普及还很远;Wissner-Gross 则预计,未来无人机的分布密度最终会接近消防栓,并以蜂群方式部署。

  • 讨论既保留了无处不在的监控可能带来的好处,也保留了其风险。Diamandis 强调在火灾刚起时进行扑救;Wissner-Gross 回忆称,监控无人机曾让象牙盗猎者不敢靠近;他还提到荷兰警方训练鹰向毒贩的无人机投放网,而 Blundin 指出,乌克兰的光纤无人机会在地面留下成缕的光纤。更大的警告是:监控可能降低犯罪,却仍可能制造一条敌视自由与创新的「滑坡」。

5. 欧洲重新认识到,充裕电力就是战略产能

  • 瑞士正在逆转福岛核事故后实施的弃核路线:4座老旧反应堆目前已经供应全国约40%的电力,接下来将升级,而不是简单退役。作为对比,节目提到法国有57座在运反应堆,英国有9座,西班牙有7座。

  • Ramez Naam 认为法国相对成功的原因在于可复制性:法国批量生产同一种反应堆设计,而不是每建设一座电站都重新启动工程和审批流程。不过,尽管欧洲的核能态度明显软化,他并不太看好其他欧洲国家能够复制法国的建设规模。

  • Wissner-Gross 将这次转向归因于失去俄罗斯能源、核能投资不足,以及稀缺文化与升高的气温和电力需求发生碰撞。Diamandis 的政策判断是,AI 正在把能源从主要的环境议题转变为「产能问题」,并成为国家层面、由利润驱动的必需品;短期基荷供电仍要依靠裂变。

6. 聚变已从未来主义承诺走向获批基础设施

  • 节目统计称,约50家私人融资的聚变公司已经筹集约60亿美元。Commonwealth Fusion 的托卡马克式项目计划在2032年前后建设首座400 MW电站;Helion 在融资约10亿美元后估值达到54亿美元,并于6月16日获得华盛顿州批准 Orion 项目,计划从2028年起向 Microsoft 提供50 MW电力。

  • Wissner-Gross 不接受「停滞50年后突然出现奇迹」的说法。聚变三重积——等离子体密度、约束时间和温度的乘积——一直在稳步改善,就像压缩指标曾预示语言模型的进展一样:「如果你长期观察正确的指标或正确的性能函数,就能预测它何时会发生。」

  • Helion 的架构差异在于直接回收电力。氘和氦-3等离子体以超过每小时1 million英里的速度相向加速、合并,并在超过10特斯拉的磁场中被压缩;增强的等离子体场改变磁通量,直接在磁线圈中感应电流,从而跳过加热水、产生蒸汽、驱动涡轮机的传统链条。

  • 时间表仍然充满张力。无论是规模化聚变还是新增裂变产能,都预计无法在2030年代初至中期之前解决眼前的电力短缺,因此过渡方案只能是提升电网利用率,以及把夜间电力转移到峰值时段。更长期看,节目嘉宾认为紧凑型太空推进,甚至效率仅10%的储能反应,都可能在能源变得「便宜、便宜、便宜、便宜、便宜」之后成为杀手级应用。

7. AI 正把受损历史变成可恢复数据

  • 由 Nat Friedman 和 Daniel Gross 发起、奖金180万美元的 Vesuvius Challenge,从被维苏威火山在公元79年碳化的卷轴中恢复出了22列古希腊文。CT 扫描和 AI 将无法物理展开的材料进行数字展开;在近2000年的不可读状态之后,还有数百卷等待处理。

  • Wissner-Gross 将这一成果视为「计算考古学」的第一步:足够强大的扫描和推理能力,可能从残留状态中重建地球历史的更大部分。他举出的具体例子是环境 DNA——即使源头已经消失,生物痕迹仍可能以气溶胶形式存在,或嵌入土壤之中。

  • Ismail 强调,这类重建未必是 LLM 问题;专用神经网络可以对极小的碎片进行插值,因为某些碎片只对应一种符合历史的解释。Diamandis 和 Ismail 强调了激励机制:奖金可以吸引全球专家参与,而 XPRIZE 模式声称,累计问题解决支出约为奖金规模的30倍。

8. Grok 重返前沿的路径是暴力算力加垂直整合

  • Grok 4.5 被描述为建立在一个1.5万亿参数的 V9 基础模型之上,Musk 承诺在今年剩余时间内每月发布一个新版本。Wissner-Gross 认为,更具冲击力的承诺是每月预训练——不是蒸馏或微调,而是每月「从零开始训练一个全新的模型」。

  • 尽管 Wissner-Gross 此前形容 Grok 被送上了生命维持系统,但他并未收回对竞争格局的担忧:OpenAI 和 Anthropic 看起来像是前沿模型双寡头,中国开放权重模型落后数月。他更新后的最佳情景是,SpaceX 级别的算力加上现成算法,可以让 Musk 「用暴力方式杀回前沿」。

  • Ismail 认为,Musk 眼中的核心对手是 Google,而不是 Anthropic,因为模型与定制硅片协同设计,可能带来一个据称10—100倍的性能释放。Diamandis 则补充称,数百亿美元现金储备,以及从 SpaceX 和 Tesla 转来的工程师,为覆盖模型、算力、芯片和部署的垂直整合技术栈提供了支撑。

  • Cursor 被描述为一个短期「大脑移植」,但还不是完整答案。它的开发者轨迹可以改善代码生成,并形成模型使用—工作流飞轮;但 Wissner-Gross 的关键保留意见是:在人机协作数据上做后训练,能力有其上限,xAI 仍需建立一个让模型开发更好模型的闭环。

9. Fable 5 让前沿智能服从国家许可

  • Anthropic 的旗舰模型因美国政府以国家安全为由将其撤下,已经不可用15天。据 Axios 报道,它预计将在几天内恢复;商务部长 Lutnick 认为 Anthropic 正在处理相关风险,但五角大楼和 NSA 尚未最终签字。

  • 能力基准来自 Stripe 据报道对 Fable 5 的使用:一天内重构5000万行代码,据称这项工作原本需要工程师耗时数月。Diamandis 将政府的处理方式比作管制弹药:模型被下线,之后再重新许可用户使用。

  • Wissner-Gross 给出了两种相互竞争的历史解读。宽厚的解读是,中国机构因此失去约1个月的推理轨迹蒸馏窗口;更尖锐的解读是,这是前沿智能进入类似冷战的「区块体系」的相变时刻:美国人受到使用限制,外国用户只能接触落后数月的模型。

  • Diamandis 追问,这次暂停是否至少给了关键系统时间来防御 Fable 5。Wissner-Gross 基本否定了这一结论:GLM-5.2 等不受限制的中国模型仍然可用,而把用户排除在最好的美国模型之外,会进一步促使中国实验室追赶,令这次下线可能成为「净加速器」。

10. Sonnet 5 更清楚地将稀缺性变现,而非证明技术优势

  • Blundin 的第一反应是商业判断:Fable 5 价格翻倍,但仍不可或缺,因此 Sonnet 5 以另一个高价填补供应中断。「AI 已经卖光了」;需求超过芯片供给,Anthropic 收入增长,而只有价值最高的工作负载才能稳定使用最好的模型。

  • Wissner-Gross 认为这次发布在技术上「很奇怪」。Sonnet 5 看起来确实比 Sonnet 4.6 更强,但 Anthropic 自己的智能体任务曲线似乎仍显示,旧款 Opus 4.8 在成本和性能上更优——这与预期的模型演进相反,按预期应当是 Sonnet 从 Opus 蒸馏,Haiku 再从 Sonnet 蒸馏。

  • Diamandis 和 Wissner-Gross 都谈到了生态锁定。Claude Code 和 Claude Cowork 可以保留上下文、提示词、连接器以及积累的知识产权,同时将简单工作下放给 Sonnet 或 Haiku;更换供应商可能更便宜,但需要第三方来管理上下文。因此 Anthropic 可能成为「AI 领域的 Apple」,依靠集成式产品栈有效运转来收取更高价格。

11. StarCloud 已将 GPU 算力送入轨道

  • StarCloud 成立于2024年1月,目前在 Redmond 约有20名工程师,分别来自 SpaceX 和地面数据中心公司。StarCloud-1 于2025年11月搭乘 Falcon 9 发射,携带5块 GPU,其中包括 NVIDIA H100;它训练了 Karpathy 的微型 nanoGPT,运行 Gemma,处理合成孔径雷达数据,并做了商业价值较低的 Doom 游戏运行。

  • StarCloud-2 已预订于1月发射,发电能力约为 StarCloud-1 的100倍,搭载 H100、NVIDIA Blackwell 芯片、比特币挖矿 ASIC,以及用于构建轨道 EC2 类环境的 AWS Outpost。Johnston 表示,它还将携带「迄今为止太空中最大的商用可部署散热器」。

  • StarCloud-3 设计为一艘3吨级、200 kW航天器,配备巨型100米展开结构。约50艘可以装入 Starship 的拼车分配器尺寸,如果 Starship 达到 Johnston 预期的制造节奏,每次发射将新增约10 MW算力。

12. 轨道算力先在边缘场景获胜,再靠基础设施成本扩张

  • Johnston 从太空太阳能开始计算:把电力传回地球会损失约90%—95%,只有当发射成本接近每公斤50美元时才具备可行性。把数据中心直接搬到能源所在地,则将估算的发射盈亏平衡成本提高到每公斤约500美元,这成为 StarCloud 2024年白皮书和公司战略的基础。

  • 商业模式是基础设施,而不是自营超大规模云服务商。在与 Crusoe 的一项协议中,StarCloud 提供一个包含电力、散热和连接能力的盒子;客户自行选择并出资购买芯片,再向自己的用户出售算力,并向 StarCloud 支付类似地面托管的租赁费用。

  • 第一批市场是处理其他卫星的数据,因为发射成本仍然很高。Johnston 举的例子是:接收100 GB的 SAR 影像,在轨道上定位一辆坦克,只下传其坐标,最多可以省去3天的地面站过站时间。待3—4年后 Starship 发射频率提升,StarCloud 计划在能源成本上与地面数据中心竞争。

  • 发射已经是主要瓶颈:公司为次年预订了3次任务,但 Johnston 表示,政府需求消化了20次发射后,Falcon 9 在2028年已经没有运力。StarCloud 正在研究 Relativity Space 和 Stoke Space 的结构方案,同时承认 SpaceX 可能在5年后仍保有发射垄断,但10年后大概率不会。

13. 散热和轨道地产决定戴森蜂群的规模

  • Johnston 预计,晨昏太阳同步轨道能够容纳约10 TW算力,大约是节目引用的美国电网规模的20倍;但他称这种轨道是稀缺的、「罕见而美丽」的地产。Starlink 约460公里、50度倾角的连接轨道,与 AI 偏好的更高轨道不同;约1200公里的高度可以避开600公里平台仍会受到的季节性日食影响。

  • StarCloud 的核心工程主张不是新物理,而是更轻、更便宜的散热器。据称,其铝制液体流道设计每瓦散热所需质量降低10倍,每瓦散热成本较国际空间站散热器低约100倍;StarCloud-2 计划对其进行飞行验证。

  • Johnston 对采用速度的判断刻意慢于新增部署速度:未来10年大多数新增算力可能进入太空,但届时轨道上安装的算力占比仍低于5%。即使20年后,如果超过一半算力位于轨道,他也会感到意外;在约50年的时间尺度上,他预计约99%——最终甚至「99.9%」——的算力会在太空。

  • 再往后,他认可 Optimus 可能成为一台冯·诺伊曼探测器:先向月球运送约100,000台机器人,建设一座 Optimus 工厂,开发速度就会进入「超指数」阶段。月球质量驱动器如果在约20年前后明显到来,无论早于还是晚于这个时间点,都会让他感到意外。

14. 太空企业正把发射、频谱和激光链路组装成完整技术栈

  • Musk 的直连手机计划目标是在约2年内支持兼容手机和卫星,最终实现几乎在任何地方观看视频。Diamandis 推测,SpaceX 未来可能会自行制造或收购手机,而不是长期依赖合作伙伴;节目还讨论了 Starlink 在未来5—10年产生数千亿美元自由现金流的可能性。

  • Johnston 认为 StarCloud 对抗 SpaceX 的优势在于相对成本和客户中立。SpaceX 可能最初会把轨道基础设施留给自己的 Grok 和 xAI 工作负载,而 StarCloud 可以服务竞争实验室;如果其成本持续低于地面超大规模云服务商,OpenAI 等客户就必须在使用竞争对手的技术栈、晚些时候自行建设卫星,以及租用独立容量之间做选择。

  • Rocket Lab 收购 Iridium 被称为另一种垂直整合技术栈:Electron 已发射91次,Neutron 计划在年底前完成首次发射,而 Iridium 带来一张由66颗卫星组成的网络,以及10.5 MHz全球协调 L 波段频谱。Johnston 还指出,Rocket Lab 可以利用异常高的收入倍数,用股票收购能够产生现金流的业务。

  • 无线电频谱今天可能很有价值,但未必是终点。StarCloud-2 搭载3个激光终端;一份 SpaceX 合同则涵盖未来25颗卫星,每颗安装2个即插即用的 Starlink 激光终端,并配备一个兼容 SDA 的政府链路。Johnston 的结论十分明确:「激光是太空通信的未来」,而且还有一个额外优势:它不受监管。

Peter Diamandis

It’s pretty clear that Sonnet 5 now is a way to kind of fill this gap until Fable 5 is back out. A kind of mediocre capability at a high price point, but people will still need to buy it. Anthropic’s flagship model, Fable 5, has been offline for 15 days because the US government pulled it. Now, Axios reports it may be back within days.

Historians will look back and say this period marked the period toward the middle or the endgame of recursive self-improvement. Helion has cleared the required Washington state regulatory approvals for its Orion fusion power plant. It looks like fusion is finally here.

Alex

If you were watching the right metric or the right figure of merit over the long term, you could predict when this is going to happen, and it’s imminent.

Peter Diamandis

All right, mates. Let’s jump into data centers and space. And for that, we’re pleased to bring a friend on.

Philip Johnston

Thanks so much for having me. It’s a huge honor. I’ve been a longtime fan.

Peter Diamandis

Now that’s a moonshot, ladies and gentlemen.

Welcome back to Moonshots, everyone. Your front row seat to the coming singularity in the age of abundance. I’m here with Dave, our managing partner of Link Exponential Ventures and number-one funder of MIT and Harvard AI startups; Salim, our global trotter; our CEO of OpenExO; and, of course, Alex, our in-house ASI. I’m Peter Diamandis, your host and your abundance evangelist. Gentlemen, good afternoon, good morning, good evening, wherever you are.

So, where is Waldo today, Salim? Where on the planet are you, and where have you been?

Salim Ismail

We dropped our son off at a camp in San Sebastián, in Spain—or near there. I’m in Biarritz right now for a few days.

Peter Diamandis

Okay. And you were in Germany before that. I mean—

Salim Ismail

I’ve been in 5 countries in the last 3 days. It’s really been nuts.

Peter Diamandis

Of course. Of course. And, Alex, all well with you?

Alex

Yeah, I’m GDP-maxing, or doing my best. Always be GDP-maxing.

Peter Diamandis

I’m happiness-maxing, gratitude-maxing. And Dave—

Dave Blundin

Good to see you, Peter. I am at Link Studio. Just a word for the wise: we have a ton of Northeastern and Princeton activity, in addition to MIT and Harvard, these days. Of course. We had TechCrunch killing it out in San Francisco. Lip-Bu Tan, Andrew Feldman, the number-two guy at NVIDIA—they were all there on Friday talking to the troops. It’s really rolling.

Peter Diamandis

Amazing. This is the thing we did with Eric Schmidt, Eric Bolson[?], and Daniel Larus[?].

Today, we’re going to cover a bunch of new stories. We’re going to catch up on robotics, energy, and data centers. We’ve got 20 stories across 6 fronts. A lot’s happening, and a lot of capital is flowing. All right, let’s jump in. For those of you joining us for the first time, our mission here at Moonshots is to keep you informed and keep you optimistic about the future that we’re creating. I have 3 stories I want to hit on the abundance front.

Dave Blundin

Wait, wait. I’ve just got to make a quick point to everybody watching. If you’ve not seen the last episode with Emad, I’m about three-quarters of the way through it. It’s tough trying to keep up with our own episodes when I miss one, and it was ridiculously amazing. Just a comment there.

Peter Diamandis

Yeah, and Emad’s made some great releases in the last 48 hours on his latest model combinations. All right. So, we’re going to open our first story on robotics.

Before we do, because I want to talk about predictions for how many robots we’re going to have on planet Earth, I was having a conversation with a dear friend, Ramez Naam, today. Ramez is one of the earliest Singularity University faculty members and futurists. He’s extraordinary, and he shared this chart with me that I’d love to discuss. It’s a look at how experts consistently underestimate exponential growth.

In this chart on the left, we see new solar growth, and that yellow exponential line is the actual growth in solar. It’s been growing at an extraordinary rate. What we see in these departures that go horizontal are the predictions that the experts make every year, showing linear or just small incremental amounts of growth. Over and over again, they underestimate it.

The chart in the center is the experts’ predictions on EV growth, and again, we see exponential growth in EVs. The forecasts consistently underestimate the actual growth. Finally, we see the same chart going on in battery sales.

It’s an interesting phenomenon that, while we’re living in this exponential growth, the experts—who are the experts in the way things used to be—are not projecting the growth. They’re staying very, shall we say, sublinear in their estimates. Salim, you and I have seen this before, and we’ve discussed this. Any thoughts?

Salim Ismail

Oh my God. Every presentation I ever give has a segment with several slides showing this. The poster child is a story that came out in 2013 saying Moore’s law would end by 2022. You can go back and look at the technology press, and every 2 years, that article appears. It’s been happening for 60 years, right?

Experts are really good at measuring the technology. They’re terrible at measuring the compounding ecosystem around it. There are some really dramatic examples from Ramez around the energy ones, where solar is vertical and every expert for 10 years goes horizontal in that thing. It’s an endemic problem.

We have that whole headline in the original book, Peter, which we put together, saying, “Beware the experts,” right? And this is the immune system, because when you’ve got somebody with 30 years of experience in something, they’ll tell you how not to do something.

Peter Diamandis

Yeah, agreed. Alex, any thoughts on this particular note?

Alex

No, I think the moral of the story is you should always take the logarithm of the actual history before you hand it to experts for their linear extrapolation, so you can get the right answer out.

Peter Diamandis

Cute.

Alex

I define an expert as someone who can tell you exactly how it can’t happen, right? It’s so true that experts today are so ingrained in the past, because if there’s a disruption, if there’s a revolution that comes, they’re no longer the expert, and so it’s against their best interests.

Peter Diamandis

I want to tie this story to our first robotics story here, and it comes with 2 predictions. The first was Morgan Stanley. Morgan Stanley had originally predicted 14,000 Chinese robots coming out of China, and they upped it to 26,000. Now they’ve just upped it to 50,000, projecting 500,000 robots by 2030.

But the fact of the matter is, there are 140 humanoid robot companies developing hardware in China today. At the same time, you’ve got Elon projecting tens of millions—50 million robots by 2030—and billions going into the early 2030s. On the flip side, what we’re seeing here on the right-hand side is a chart from Andreessen Horowitz that shows we’re going to be seeing about $16 billion of hardware investments in Q1 of 2026.

The US is finally catching up. Alex, I know that you’re heavily committed to this, and Dave, your thesis is that we’re moving from an AI-centric entrepreneurial ecosystem to a hardware-centric ecosystem. I’d love your thoughts on this. Alex, you first.

Alex

As I’ve mentioned on the pod in the past, I think superintelligence is set to spill out of the data centers into the streets. I think the most obvious vehicle for that is autonomous vehicles on the one hand, and humanoid and near-humanoid robots on the other.

I think as we start to increase the number of humanoid—or just, say, general-purpose—robots per capita, there are going to be certain regimes. At the low number of humanoid robots per capita regime, it looks like robots performing industrial applications: robots in factories, robots doing logistics. As we start to get closer to approximately 1 humanoid robot per capita, it looks like domestic robots everywhere. It looks like an iRobot-style regime where everyone has domestic staff.

Interestingly—and this is a point that I don’t think I hear frequently enough—as we start to push well through the approximately 1 humanoid robot per capita regime to 10 or 100 humanoid robots per capita, at that point, I think, to a hobby horse of Salim’s, we start to end up in some pretty exotic futures where there’s no longer necessarily justification for the humanoid form.

We end up with microrobots and nanorobots. There’s a natural sense in which the humanoid form is no longer natural in a world where we have 1,000 general-purpose robots per capita, and we can start solving all of the grand physical-world challenges that would maybe be uneconomical if we only had 1 humanoid robot per capita.

I think we’re going to very rapidly scale through the low-per-capita regime, to the approximately 1-per-capita regime, to the many-per-capita regime. It’s going to be a very exciting scale.

Peter Diamandis

So, Dave, take a second and walk me through your thesis right now. We’ve been investing together in AI companies mostly, and you’ve said that you expect that to sort of fall off, with more investment going into hardware in the next couple of years. Why?

Dave Blundin

Yeah, I think we have to think in terms of 10-year investment themes. Ten years in the age of AI is like 100 years in any normal world.

I do think the next 1–2 years are still dominated by white-collar automation, AI algorithms, chip design, AI that designs chips, and the beginnings of data centers in space. But if you think beyond 2 years in the future, what are the investments that are going to really be big 3, 4, 5, 8, or 10 years from now? The automation of construction of data centers is all going to be robotic.

Peter Diamandis

Biotech, chemical mixing, experiments, reading gels—that's all going to be robotic. And so, the machines that do that—you take a guess: How big do you think the U.S. gutter-cleaning industry is? People who go on your roof and pick the leaves out of your gutter. How much do you spend per year? I do. I looked it up.

Alex

How big?

Peter Diamandis

That use case alone is a billion dollars a year. If you built a robot that cleaned gutters and washed windows, those 2 tasks would represent a $20 billion global market. A $20 billion global market. So that's a theme that will support this. This slide says 140 humanoid robotics companies. There's room in China.

Alex

In China?

Peter Diamandis

Yeah. There's room for thousands and tens of thousands of robotics companies specialized for various use cases, everything from wafer movement inside a chip fab to chemical mixing and biotech to gutter cleaning to just everything. Construction has thousands of individual tasks, so it's a very broad, long-term investment theme.

Kitchen work, too. We're already starting to invest in that one. Kitchen-work automation is compelling because fast-food restaurants can buy at scale, and so they'll co-develop with you. This is where Travis Kalanick is focused with his company, CloudKitchens, just fully roboticizing kitchens.

You know what's interesting is this particular note: $16.5 billion in the last quarter was in 500 deals. I used to think that—I'm a huge Star Trek fan—I used to think that Star Wars was kind of silly, with all those hundreds of variations of droids out there, but it looks like it's coming.

Philip Johnston

Peter, it's such an interesting point. I'd be curious to hear your thoughts on this. Historically, the robots have been missing from Star Trek, other than in the first few series, like some type of Data robot. There were no robots. Maybe it was—what are your thoughts on that?

Peter Diamandis

I think they wanted to create a very humanistic series, and Gene Roddenberry was all about the societal implications of technology in this future. Even the computer—right, the computer, whose voice was Gene Roddenberry's wife, Majel, playing that role—was very roboticized. It didn't predict these incredible empathic voices we have on our models today. Yeah, they missed that.

Alex

LCARS, right?

Peter Diamandis

Well, you know, we're going to have Rod Roddenberry with us at the Moonshot Summit. He's going to be on stage, one of the judges of our Future Vision XPRIZE. So we'll sit down and ask him. I think those are important questions to ask: Why did they miss that part of the future?

Alex

Was it just a low production budget? Because they added them in more recent Star Trek series.

Peter Diamandis

Yeah, they retconned them. But still, nothing close to Star Wars. And I think a lot of it had to do with the theme, right? Infinite diversity, infinite creativity. They were focused very much on human interaction—all the aliens that were humanoid, not just because you could put actors in those suits, but because you were always dealing with the interpersonal elements in the plot lines.

So, yeah, we've got lots of companies that are building robots now. Famously, in the U.S., we've got Tesla with Optimus. We have Figure, we have 1X, and in China, probably the robot company that's gotten the most publicity has been Unitree.

We had one of the founders of Unitree on stage with us at the Abundance Summit. I want to play their latest video. It's got 11 million views, and this is a glance at the R1, which is incredibly cheap, selling for $4,900. I mean, this is the price of a cheap used car, which is saying a lot. So let's take a look at the R1.

So, I mean, it's crazy. My point is, it's an extremely capable robot, but the work here is going to be on the software layers, right? You buy this robot. I don't think it does that out of the box, but I think you could probably buy the algorithms that enable you to do that.

But I see an explosion in the number of people experimenting with these robots. At $5,000, that's affordable by almost anybody who has a reasonable income. Alex, where does this go for you?

Philip Johnston

Well, I think the elephant in this particular room, as with Elon demonstrating to the world that you could drive the cost of heavy lift to LEO down to effectively near zero through reusable, propulsively landing rockets, is humanoid robots that are able to assemble other humanoid robots.

If you take the cost of assembly down to near zero, what we're left with is the cost of raw materials and the cost of energy. And that's going to be effectively de minimis. So I think, as we drive—and by “we” in this case, I really mean Chinese organizations, because the West is woefully behind at the moment—as humanity starts to drive the unit cost of general-purpose robotic embodiment down to near zero, at some point we will need to cross the threshold of robots being able to assemble other robots in order to keep driving that cost down.

And then, at that point, we have physical labor too cheap to meter. As I pointed out in the past, approximately 2/3 of the service economy constitutes some sort of physical labor. We can do for the physical world what AI agents are right now in the process of doing to knowledge work, which is basically driving the cost of knowledge work, and soon physical work, down to near zero.

Peter Diamandis

Can I make a point, actually, that we learned at the Gigafactory that I completely think was lost on me, and I think it's critically important? When Elon says humanoid robots building humanoid robots, the CNC milling machine or the auto lathe already exists. It's already making the parts; it's just a file loaded into the machine.

Those machines were designed for a human to go and take the part out of the machine and put it in the next machine. And so the humanoid robot does not need to literally create something with a file and a piece of metal; the automation's already there. It just needs to do the part that the human is doing today, which is moving the part from machine to machine and doing the final assembly.

So it's a much easier problem than “robots making robots” sounds like.

Philip Johnston

Yeah. I think the point I want to make here is we're heading toward commodity pricing on these things. $4,900, right? And so, as we move to commodity pricing, the question is: Where's the value layer?

Peter Diamandis

Well, the value layer clearly will be in the software, and the exact point I want to make is—yeah, I think that's a really important point, and people are going to build apps. Look, if you go back to the original personal computers, you put them out there, and we didn't know what people would do with them. Then, over time, you had more and more applications built.

Now these things show up worked out of the box. There will be profound new skills emerging all the time from these things. I think it's going to take a lot longer than people think, because driving took us 20 years, and that's a very bounded domain space. Humanoid robots doing gardening, et cetera—there are a million edge cases.

What's different here is that—and this is sort of, what does it mean for the entrepreneur out there? You can buy this and begin to build on top of it. This is not something that requires permission from anybody. It's not something that requires a massive corporate budget.

An entrepreneur can buy this for $1,400. It's like the Raspberry Pi moment, and you can start hacking and publishing software to these robots that becomes a new revenue engine. I think that's what's most interesting for me: the explosion of applications that came on top of the iPhone now coming on top of these robots.

Philip Johnston

I agree, but I still think we're going to spend a lot more time figuring out the industrial use cases—the dull, dirty, dangerous jobs—and getting those automated. There's so much scope. It's going to take a decade to get through that before we can get to somebody coming over and doing gardening for you.

Peter Diamandis

You know, we talked in a past pod about Royal We. I mentioned the idea that the export controls we're seeing at the moment imposed on frontier models are, in some sense, regulations on importing foreign—or exporting, depending on your perspective—superintelligence, if you look at them through the lens of immigration policy. But that's the software layer.

I do think—admittedly, maybe this is a spicier take—that as the cost of robotic embodiment, primarily from China at the moment, starts to come down, I would not be surprised to see similar import controls or other national-security-motivated restrictions start to kick in. It's not just about dumping. It's also about taking the embodiment for superintelligence and moving them across borders.

Well, you've heard the Trump administration saying they want to invest in the robotics industry. We've seen, obviously, Tesla and Brett Adcock from Figure getting massive investments to support the growth of these systems. It becomes strategic for the US, and we're going to find out in our next story. Let me just go there for a second, where we're going to start to see robots being used in a number of different areas, including law enforcement.

A drone, of course, is a robot. I'm going to share a particular video here that Alex shared with me. This is out of Orlando, and this is US law enforcement beginning to use drones as first responders. Let's take a listen to this video.

News Anchor

And new at noon, the Orlando Police Department is now using drones as first responders, sending them to some 911 calls to give officers a live look at the scene. A new eye in the sky is now responding to some of Orlando's most serious calls. Orlando Police Chief Eric Smith is addressing a big question from the community.

Community Member

What would you say to the citizens who either are seeing this as an invasion of privacy or an overstep?

Eric Smith

We're not looking in people's windows. We're not spying on people. We're not just flying around just to fly around.

News Anchor

When a qualifying call comes in, a nearby drone can be dispatched to specific GPS coordinates. Then, from the crime center, an FAA-certified pilot can control the drone, giving officers a live view of the scene, including whether a suspect runs, hides, or possibly has a weapon.

Peter Diamandis

So, interestingly enough, this was demonstrated on June 17 as a first deployment. It had what they call 9 docks at different locations and 11 Skydio networked drones. Skydio is sort of the US manufacturer today. It used to be DJI out of China, but we put in import controls on DJI for a number of security reasons. And so, even though Skydio is more expensive—something like 3 to 10 times more expensive than DJI drones—they're getting it.

Interestingly enough, Rick Smith, who's one of my Abundance members, is the CEO of Axon, the company that makes the Taser and the body cams. Axon has the contract here, and they're coordinating all this. They did a trial with a single drone, and it beat patrol officers about a third of the time in getting to the live location. It provided useful information 97% of the time, they claim.

But you can imagine that we're going to have drones on buildings throughout the city, and a drone will get there almost immediately. I can imagine there's fear that people have on this subject, but I think being able to get to emergency locations, making sure you can assess a situation when you need to have medical personnel there, is going to save lives. I want to acknowledge the fear that people have, but I think, on the whole, as long as you have good policy and good governance about how the data is retained or used and who gets access, I think this is an important step for law enforcement.

Alex

It's huge, and we did our very second sprint back in 2015 with Interprotección, which is the largest insurance company in Mexico, with 30 million users. They actually deployed drones because they were so much faster than ambulances at getting to an accident scene, and they would scan and map the whole area so that, before people moved the cars and everything like that, you had full information before anything happened. It was kind of an amazing experience.

So we've seen this trend over a long period of time. I think we can expect to see this accelerate pretty radically just because of the practicality of it. Alex

If I might add, there are regimes where, as the cost of robotic embodiment trends toward near zero and becomes too cheap to meter, we in the West are unaccustomed to this, but China, for a variety of reasons including demographics, has seen it for a number of years.

For example, this is well publicized: the Chinese Communist Party maintains party members or officers on a per-block basis. Certainly, this was the case during the pandemic in China. The West doesn't really have any concept of this.

If you look at how first responders are geographically distributed in the US, it's on a per-municipality basis or by precinct. There's no notion of, say, 1 or more officers per block who are just permanently stationed on a single block. But with drones, this becomes possible. We could have literally drones as densely distributed geographically as fire hydrants are. You could literally just, if there's a problem in a block or a part of a block, remotely activate the drone, and then you have an instant point of presence.

Let me share the second story; it comes out of Sacramento. There was a suspect who had a knife, and they deployed a drone with a magnet to grab the knife and make the scene safe for the police to enter. Let's take a look at this.

Here we see the drone going. The guy is holding a knife. A magnet, or electromagnet, is attached to the knife, and it pulls it out of the guy's hand as he's apparently sleeping. This is interesting. This is a drone that's disarming somebody.

If you guys remember during the Abundance360 Summit, Rick Smith, again with Axon, showed us his Taser-equipped drone, and I went onstage wearing a suit to protect me, and he tased me from his drone. I think this is coming: this use of drones in law enforcement, both for observing and for trying to de-escalate a situation.

The drone market right now is about $100 billion around the world. That's going to be increasing. We're seeing drones being used, obviously, in Ukraine, very famously. Eric Schmidt's been funding a drone company to help the Ukrainians in their fight for independence. Dave, any thoughts from you?

Dave

Yeah, Scientific American did a great research study on why crime rates are down by half in the US, and they keep coming down. It was entirely connected to deployment of first responders in the right place at the right time, largely driven by GPS. But now, with the drone footage, you can get much more accurate.

You know, the first responders want to be there and they want to help, but it's about getting the right people to the right place at the right time. I'm a huge believer that the video footage is going to be massively impactful, and the resolution just keeps going up and up and up and up. The physical side of it, where you're disarming somebody, is a little ways out. You know, that was kind of a—

Peter Diamandis

Niche case.

Dave

Yeah, very niche case. But the video side is right here, right now. And as Alex was saying, you could easily, cheaply have as abundant a fleet as there are fire hydrants. That would cost next to nothing.

Alex

Yeah.

Peter Diamandis

So that's imminent. I'll also point out, if I may, this was all foretold by Minority Report. You remember the scene in Minority Report with the police officers deploying spiders to search an apartment complex for Tom Cruise's character. We're starting to catch up with that now.

Right now, it starts with a couple of police precincts in the US. They're using drones for first response, and my understanding is that it's far more frequent in China right now than in the US or the West in general. But project forward a few years, when there are a variety of new form factors. Maybe we get spiders. Maybe we get drones.

I have to imagine the drone—the flying form factor—is a good deal more versatile for interacting with hostile scenarios. These are going to get smaller and cheaper and more plentiful. We haven't even seen what happens in the West from a first-response perspective when police can deploy swarms of drones rather than just individual drones. But as cost goes down, we will absolutely see swarms.

Dave

Yeah, I mean, again, I think the public is going to have a bit of a fearful reaction to this. It really depends what the drones are armed with. It depends on what the guidelines on the use of drones are, and we need to address that.

I mean, getting medical equipment to a site of an accident rapidly—you know, we're going to see eVTOLs, flying cars, delivering ambulance personnel there—but getting a defibrillator, for example, to a location that's jammed by traffic, drones are going to play an important part of this, and they're getting better and better. You were going to say—

Alex

I'm just remembering the counterpoint here. There was a fellow from the Dutch police force at one of our Singularity executive programs, and they were combating the fact that drug dealers were using drones. So they trained a bunch of hawks to drop mesh wires onto the drones to wrap them and tangle them. It's so retro to be training up birds to be attacking drones. It was totally surreal.

Peter Diamandis

That's actually a real problem below a certain size. There are a lot of birds that go after these things. So the really small ones actually have a little bit of a problem in—

Dave

In Ukraine, they're having a huge problem because they've got strands of optical fiber from all of the drones that have attacked them lying everywhere.

Peter Diamandis

Oh, yeah.

Alex

It's a massive issue.

Peter Diamandis

Yeah. Well, I'll tell you, the number-one use of drones I'm excited about came from the Wildfire XPRIZE I talked about in the last pod, where drones are able to get to a fire at inception, put it out rapidly before it causes hundreds of millions or billions in damage and causes the loss of significant life. So—

Dave

And we didn't get our flying cars in the end. I mean, we have flying-car companies, but they're relatively sparse.

Alex

But I do think we're going to have skies over the next few years that are densely filled, I should say, with these drones.

Peter Diamandis

Well, the drone ambulance is the coolest thing ever because no one's going to stand in the way of a drone ambulance, right? It's there to save somebody's life, but that'll unlock all the technology, all of the airspace, all of the regulatory barriers, and also prove the efficacy.

Alex

So that's going to be a great, really cool stepping stone.

Peter Diamandis

One of the Substacks I put out was about the fact that we're heading toward a point where you can know anything you want, anytime you want, anywhere you want. We've got orbital satellites. We have the 200 satellites from Will Marshall at Planet. Then we're going to have an aviation layer from the flying cars and these drones, imaging everything at centimeter and subcentimeter resolution, and then all the autonomous cars gathering terabytes of data on the road. So everything is going to be imaged very soon.

Alex

You know, the spooky side of that, obviously, is loss of privacy, if you believe you have privacy. The positive side is that there's no crime. I put out a part of that blog saying, "When people are observed, they act better." I got a lot of negative feedback on that.

Peter Diamandis

I can imagine.

Alex

It's true. I think when there's a CCTV camera pointing at them, right, they do less—

Peter Diamandis

They do less.

Alex

They behave differently on the global stage. One of the foundations I used to support was the Lindbergh Foundation, which would fly drones over herds of elephants, and the poachers would stay away when the drones were flying over them.

Peter Diamandis

Well, you want to hear a funny story from China? Sean, my son, who just got back from China, was talking to a guy who was mansplaining the entrepreneurial vibe in China and how to build a great company. Sean said, "Well, it's all about the team, right? This is what we preach at Link Ventures: You get great people, they succeed every time."

He said, "No, no, no. It has nothing to do with the team." You're like, "Well, then is it the business plan?" He said, "No, no, no. It's what the government needs next. That's the only thing that matters."

Alex

Wow.

Peter Diamandis

You're like, "Wow, is that discouraging?"

Alex

So I think with the loss of freedom and privacy also comes the loss of innovation. I don't think the drones are going to be taking away all of our privacy and all of our freedom. I don't think that's a real issue. But in general, the slippery slope does kill innovation and entrepreneurship.

Peter Diamandis

Alex, should we talk about the innermost loop?

Alex

Let's do it.

Peter Diamandis

All right. Our first story is out of Switzerland, and it's an important one. Switzerland just voted to lift its ban on nuclear plants. After Fukushima, back in 2017, they phased out nuclear completely. Now they're reversing course.

Just to give you a sense, nuclear has been very slow. The country that succeeded so incredibly well is France, which has 57 operating reactors. The UK has 9, Spain has 7, and Switzerland has 4 aging reactors that supply 40% of its power. They were all due to be shut down, but they're going to be upgraded instead.

I was on Zoom earlier today with Ramez Naam, and Ramez is one of the most extraordinary thinkers in energy. We should have him on the pod.

Alex

We definitely should.

Peter Diamandis

He would do an extraordinary job giving us an overview of all things energy, across solar, batteries, and so forth. He was saying the reason that France actually succeeded as well as it did is because it mass-produces a single reactor design instead of starting from zero, where the costs escalate and get out of hand.

I asked him whether he thought other European countries would follow suit and be able to implement nuclear, and he was like, "Nope, not going to happen." But it's interesting that the buzz on nuclear is beginning to soften, and the need is significant. Alex, your take on this?

Alex

Europe's in a bit of a bind. So maybe here's a really relatable story. Whenever I'm in the Swiss Alps and it's not the winter, it's very difficult to find air conditioning. I think Switzerland and a good portion of continental Europe have a real energy crisis.

They've lost access to cheap Russian oil thanks to recent events. Except for France, they underinvested in nuclear energy. They aren't this amazing native producer of their own solar PV. And they have a culture that one can sort of theorize where the culture comes from, but a culture arguably of energy scarcity.

Now, as global temperatures are rising and power consumption is increasing, Europe is having to do an about-face and discover—sort of learn to love nuclear energy, learn to love energy in general. And the risk, as we've talked about previously—cite the EU 2031 scenario and other scenarios—is that Europe is going to need to start to radically increase its power consumption and power production per capita. Nuclear fission in particular is a very attractive way to do that.

Otherwise, Europe will smolder under heat domes, including the one that Europeans have been suffering under over the past week or two. I forget the exact statistic, but thousands of Europeans are dying due to heat overexposure every year. It's a startling statistic, and it's unnecessary with better air conditioning and higher energy per capita. So I think this is the obvious trend of the future for Europe.

Peter Diamandis

Yeah. Yeah, I mean, the good news is AI demand is going to turn energy from an environmental issue into a capacity issue, a commercial, profit-driven issue.

Alex

Well, but at least the need is a national capacity issue. Every country has to deliver enough energy.

Peter Diamandis

And it's going to get it from fission in the short to medium term, until fusion or whatever comes along to cover the baseload.

So let's talk about fusion in our next story. Interestingly enough, the joke about fusion has always been that it's 50 years away and holding. Well, it's now here. There are some 50 privately funded fusion companies that have raised about $6 billion.

2 US companies lead the pack: Helion, which we're going to talk about, and Commonwealth Fusion Systems. I had Bob Mumgaard, the CEO of Commonwealth Fusion Systems, on stage with me at the Abundance Summit. They're building a tokamak-like design, and they're expected to build their first 400-megawatt plant circa 2032.

The second story here is Helion. It's a Sam Altman-backed company. He was the largest early investor back in March 2012, and until just 2 months ago, he was the executive chairman of the company. Apparently, he's stepped down now so Helion can actually do some large-scale partnerships with OpenAI.

On June 16, the news here is that Helion cleared the required Washington State regulatory approvals for its Orion fusion power plant, which is intended to supply Microsoft with 50 megawatts of power starting in 2028. If successful, this is the first fusion plant coming online. It's relatively small. 50 megawatts is—you know, we talk about gigawatt-level plants. This is 50 megawatts.

They've raised about $1 billion at a $5.4 billion valuation, but it looks like fusion is finally here. I've got a video showing how Helion works because it's a unique design. I think it's worth discussing, but Alex, do you want to comment before I show the video?

Alex

Yeah, maybe just a comment. Fusion—or the lack thereof—has long, in futurist circles, been the whipping boy for why long-promised technologies never happen.

But if you look at one of the figures of merit for fusion, the so-called triple product, which is the product of the density of the plasma, the confinement time of the plasma, and the temperature of the plasma, there has been steady progress for the past half-century toward self-sustaining and net-positive, in terms of power production, fusion reactions over the past 50 years.

This has been sort of—not just—it's not the case that there was suddenly some recent unlock, although arguably, economically, there has been in the form of high-Tc, high-temperature superconducting tape that's very helpful for certain architectures of fusion reactors. There has been continuous progress this entire time.

So I think there's an interesting parallel that one can draw between fusion, which is arguably achieved by compressing enough matter into 1 volume that you achieve net power output, and AI/ASI, which is arguably achieved by taking enough human knowledge and compressing it into a small enough information-theoretic footprint until you achieve really a phase transition that produces prompt engineering and large language model behavior.

All of that has strong parallels. I think they're both inevitable, but they're both inevitable as—I'll make a stronger analogy—which is, if you were watching the right metric or the right figure of merit over the long term, you could see both of these from 50 years away. You could see—or maybe 30 years, at a minimum—

Peter Diamandis

Slow linear growth over time.

Alex

You just watch the compression over time. Arguably, with large language models and AI, if you were, say, watching the Hutter Prize—if you're Marcus Hutter and it's the late '90s—and you're watching the ability to compress the English Wikipedia over time, you could see LLM and AGI happening from decades away.

Similarly, with Helion and all of its competitors, if you're watching the triple product, you could predict when this is going to happen, and it's imminent.

Peter Diamandis

Yeah, I think there’s something incredible here because this is such a foundational technology for abundance, right? This is the abundance thesis, for sure. That’s the foundational technology for it because once you have clean, cheap, and dense energy, the cost of computation, desalination, transportation, manufacturing, agriculture—I mean, everything becomes the cost of just the materials at that point. So this is such a big deal, and it’s one of the hardest conversations I have with CEOs and companies, especially with the public sector: energy is becoming abundant over the next few years. And when energy becomes abundant, all sorts of other dominoes fall.

Alex

Energy is the number-one correlate to GDP, to health, to education. The more energy a nation has, the better it is across the board. This is something that Europe needs to learn.

Interestingly enough, the challenge here is the fission plants, right? The small modular reactors and the Gen III plants are still not going to come online really until the early to mid-2030s. And the fusion plants—getting up to 400-megawatt plants, like Commonwealth Fusion Systems, or getting Helion up to that level—again, those are not going to be coming online until the early to mid-2030s.

And so the question is, where do we get the energy from? Now, I had that conversation with Ramez, and he says it’s from the grid. It’s going to be from the grid, and we just need to make better use of the grid. He’s got a company, Alex and Dave called Aentic [?], that basically is sucking down energy to batteries in the middle of the night, between 1:00 a.m. and 6:00 a.m., and then pumping that energy out during peak hours. So there’s plenty of energy on the grid if you can time-shift it. I think that was fascinating.

Peter Diamandis

I think one of the questions that I don’t hear enough people discussing is: What is the killer app of fusion going to be? It seems obvious we’re going to get it, barring some surprise that we haven’t anticipated. But will fusion arrive in time to be transformative for terrestrial data centers? Maybe, maybe not. Will it be helpful for orbital data centers? Maybe. But there’s also a lot of solar.

Alex

There’s a 93-million-mile-away fusion plant that works really well in space.

Peter Diamandis

That’s right. Sorry. Go ahead, Alex.

Alex

I think space propulsion is actually one of the killer apps. If we get compact fusion reactors, that’s a wonderful application.

Peter Diamandis

My 9-year-old science-fiction self loves that.

Alex

Yeah. Hand in hand with that, if any materials scientists or chemical engineers want to work on this, if we have fusion, then any storage mechanism—even if it’s inefficient, as long as it’s clean—is suddenly viable. So if you have cheap, cheap, cheap, cheap, virtually free fusion energy, and you can put it into a car in a cheaper way than a lithium battery, right now you have to have some degree of efficiency. You don’t want to throw away electricity. But post-fusion, you won’t care about the efficiency of the reversible reaction. So anything is good.

And that’s true for launching rockets, too. Once you’ve got fusion energy, you can create any reversible reaction very efficiently. Then you can port it out to your space station or to your moon base, have it do whatever it’s going to do, come back, and recharge it. You don’t care if it’s only 10% efficient.

Peter Diamandis

If you remember Bob Mumgaard, the CEO of Commonwealth Fusion Systems, when he was on stage, his goal, once he gets his unit working, is to pump them out—to create the machine that builds the machines. The same thing here for Helion. I’ve got a short video that explains how Helion works, and given the fact that it may be the first fusion plant coming online, and it’s unique in how it works—using magnetically propelled plasma and then magnets to pull electricity out of the plasma—let’s take a listen to this. I think it’s valuable for our listeners to hear about Helion.

Narrator

Helion’s pulsed fusion device directly recovers energy, which is used to generate zero-carbon electricity from fusion. It starts with Helion’s fusion fuel: deuterium and helium-3. These fuels are injected as a gas into Helion’s formation chamber, where they are superheated into an ionized gas called a plasma. The machine’s capacitors are charged and send electricity to magnets that wrap around Helion’s device. The magnets invert the plasma’s magnetic field on itself into a toroid, or donut.

The device’s magnets fire sequentially, accelerating the plasmas toward each other at a velocity greater than 1 million mph. They collide in the fusion chamber and merge to become 1 hot, dense plasma. In the center of the device, the machine’s magnetic field is rapidly increased, compressing the plasma with a powerful force over 10 tesla.

These fusion reactions within the plasma convert matter into new energy, which strengthens the plasma’s magnetic field. As the plasma’s magnetic field gets stronger, it pushes back on the magnetic field of the machine, causing a change in the machine’s magnetic flux. In accordance with Faraday’s law, this change in flux induces current in the machine’s coils, which is directly recaptured as electricity and returned to the capacitors that originally charged the magnets around the machine.

Peter Diamandis

You know, we really are living in the future. When I see that, it’s extraordinary. And their goal was to mass-manufacture those Helion plants.

Well, if I had to call out 2, it’s that Helion raised $1 billion, and so did Commonwealth Fusion. Remember, we had dinner with him in Riyadh in March, and he had just raised $1 billion. When we were at MIT, the budgets for this were in the tens of millions.

Alex Wissner-Gross

Research budget. Yeah.

Peter Diamandis

Research budgets. Now, suddenly, we’ve said this on the pod many times, but we’re actually truly investing in the commercial sector in hard science for the first time in my lifetime. Something great will come out of those 2 $1 billion investments, for sure.

I mean, Alex, look, to bookend this, once you make energy abundant, every other scarcity becomes negotiable. It’s probably also worth pointing out what the so-what of that explainer video is. Unlike many other fusion architectures, the whole point of Helion’s architecture is direct recovery of energy from the fusion plasma.

In a more conventional, say, tokamak-style or other fusion reactor, there’s a bucket brigade of energy production. You create the plasma through inertial confinement or through magnetic confinement. Then the plasma will be used to heat something, maybe water, and that produces vapor. Then the vapor goes into a turbine, and you turn the turbine, and you recover electricity from the turbine, inductively inducing, via magnets, currents in wires. It’s like a 10-step process.

The whole point—and what’s potentially quite seductively attractive—about the Helion architecture is that you’re just directly recovering from magnetic fields that are being induced by the plasma, and then currents induced by those magnetic fields. You’re almost directly recovering free energy from the plasma. So you’re skipping a whole bunch of steps, and it’s potentially a lot more efficient.

I was going to say a moment ago, if I had to pattern-match to a Mr. Fusion from the Back to the Future Part II architecture and identify the archetype of any one of the now many fusion startups that are out there, I think Helion is the closest to being a Mr. Fusion startup. All of those extra steps that are being skipped could lead to potentially radical compactification of the ultimate fusion implementation. So it’s very exciting.

Alex Wissner-Gross

Yeah, it is. It’s a beautiful design, and again, something Helion can mass-manufacture. Where does it go? It goes into every township, depending on the size; every city; every place that you need baseload energy production. Compact fusion is going to be a thing.

Peter Diamandis

Well, if you told me I’d be listening to a little chipmunk voice explain Faraday’s law…

Alex Wissner-Gross

I know. It was like, “Am I running this? Am I running this at 1.5?” No. That’s the voice they chose.

Peter Diamandis

All right, let’s jump into AI and a really fun story to kick us off. There’s a $1.8 million incentive prize founded by Nat Friedman, former CEO of GitHub, and Daniel Gross. Matt, I know Nat is your friend and roommate.

Matt Welsh

He was my first roommate at MIT. Fun stories.

Peter Diamandis

He was on stage in March 2023 at the Abundance360 Summit, and he announced the Vesuvius Challenge. Here it is being won some 3 years later.

The challenge was this: There are these scrolls that were basically buried and burned under Mount Vesuvius back in 79 AD. The scrolls are fully carbonized. You can’t open them and read them without destroying them. So they asked, can we use technology? Can we use CT scans to gather the data and then use AI to read them?

For almost 2,000 years, they’ve been unreadable, and the challenge has just been won. You can see here in the image these scrolls of ancient Greek that have been linearized and laid out by the AI: 22 columns of ancient Greek text. And there are still hundreds of scrolls that can be read. I mean, this is using AI to basically look back in time. Alex, this must be a favorite one for you—

Alex Wissner-Gross

And not just because of the Nat connection. Objectively, I think computational archaeology powered by AI is going to be utterly transformative in the future.

I've argued from time to time before.

Peter Diamandis

Sure.

Alex Wissner-Gross

Yeah. The killer app of the singularity is superpowering computational archaeology. I'll inevitably cite Nikolai Fyodorov, one of the fathers of the strain of philosophy called cosmism—the idea that humankind's common task is to essentially resurrect every human who's ever lived using technology.

I see in the Vesuvius Challenge the very beginning of a larger arc of technological progress that may require the singularity we're in to fully run its course. But imagine, just as a thought experiment, if we could do what the Vesuvius Challenge did—not just perform high-resolution scans of the positions of ink, or X-ray analysis of small blotches of ink, in order to recover scrolls that were otherwise preserved by the eruption of Vesuvius—but do this at a planetary scale.

Imagine that somehow—we're not going to say specifically what the mechanism of action would be—we're able to scan the Earth and gain fine spatial and temporal precision, or position, momentum, canonical coordinates, if you like, for every atom on Earth. Imagine if we fed the entire state of the Earth into an AI and what we might be able to recover about Earth's history. I think the answers would be quite transformative.

One of my favorite anecdotes is environmental DNA. If you go for a walk outside, you may or may not realize this, but you're just drowning in DNA that's been aerosolized from animals, alive and dead. If you dig into the soil—say, soil near a cemetery where human bodies have been buried—DNA has a surprisingly long half-life, even under environmental conditions.

There's a lot of state left over from Earth's past, not just in these scrolls that were preserved by volcanic eruptions, but in general. I think, again, an idiosyncratic position here, that with strong enough AI in combination with strong enough scanning technology, at some point in the future we will be able to recreate large fractions of our past light cone.

Peter Diamandis

Well, you know, this is what Colossal is doing in a way, right? Going and extracting DNA from fossils, bringing back the dire wolf, bringing back the woolly mammoth in a very limited slice—and this is taking that to extremes.

Alex Wissner-Gross

Yeah.

Salim Ismail

Yeah. There's another angle to this story, too. If you're watching this podcast live and you look at the image and really zoom in on it, AI is very, very good at interpolating these fragments, these little pieces. If you look at the characters, no human being could ever reverse-engineer what that original character was, but the AI is really good at filling in those blanks.

It's not regular LLM AI. It's not your Anthropic or your OpenAI transformer. And this is where, Peter, you know David Siegel, right?

Peter Diamandis

Sure.

Salim Ismail

He's on the board of MIT. He has a project called Project Open Athena, which he's funding heavily. It's designed to give AI compute resources to people who have alternative versions of AI that are not necessarily transformers, but are very, very good at these types of problems.

There are many, many, many of these. As Alex was describing, if you wanted to look at fragments of DNA that are lying around and reverse-engineer what happened in that room, that's a really good use case. All of these world events and historical events leave a little trace that's scattered around.

There's usually only one interpretation of history that could have created that trace. It's impossible for humans to glue those fragments together, but it's not LLM AI. It's core neural-network AI that's built from the ground up to solve that problem.

Peter Diamandis

Let me give a shout-out to the non-technical founders out there. If you have an idea for a technology or a company, but you're not a technologist and it's your dream to make it happen, imagine being able to use an incentive prize like this to aggregate the best experts in the world to come help you solve your problem.

In this case, a $1.8 million prize probably brought, on the order of tens of millions of dollars, if not more, of genius to apply and solve the problem. Think about this: This is the basic principle of XPRIZE—to get people from around the world to focus on solving a problem. We get 30 times the prize money spent cumulatively to solve a challenge like this. Salim—

Salim Ismail

I wanted to stress that the prize model is incredibly powerful. What really strikes me in this is the before and after. The image of the before, and getting real data and information out of it, is so mind-boggling.

But there's an audacity in thinking that you can do that, and I think this is the abundance thesis again: Challenges we never thought were solvable fall as a result of the technologies that we're building.

Peter Diamandis

All right. Let's move to the SpaceX universe. Grok 4.5 is coming out based on a 1.5-trillion-parameter V9 foundation model. Interestingly enough, Elon has made the claim that he's going to iterate a new model and release it every month for the rest of the year.

Alex, let's go to you on this one. He said something even spicier, if I understood his announcement correctly: that he was going to start pretraining every month—not just distillation cycles, or not just post-training or fine-tuning cycles per month, but start a new pretraining run every single month. That's—

Alex

Completely a new model from scratch.

Peter Diamandis

From scratch, which means pretraining, which is, I mean, it's audacious. It's brute force. It's exactly, I think, what the world expects of Elon: a brute-force attack.

Alex

I've had a number of folks, since we first discussed in an earlier episode my comments about Grok being put on life support in favor of SpaceX's hyperscaler resources being handed over.

Peter Diamandis

You got a lot of hate mail on that one.

Alex

I got some spicy comments. I had people saying, "Okay, well, Elon's announcing this, Elon's announcing that. Are you retracting your comments about Grok being put on life support?"

I think, again, my comments may have been misconstrued. I want the frontier to be competitive. Right now, we are arguably in a duopoly between OpenAI and Anthropic. They're just running away with the race, with Chinese open-weight models a few months on their heels.

I want there to be a competitive frontier, and I think Grok is one of the possible competitors, along with Gemini. Maybe Meta will come up with something eventually. I want it to be competitive, and Elon's strategy historically vis-à-vis xAI has been brute force.

Hopefully, as SpaceX brings more and more compute online, this sort of brute-force approach—where he eventually has more compute than everyone else, in combination with off-the-shelf algorithms—maybe this will work. I see the beginnings of that with Grok 4.5 in combination with Cursor.

Right now, the Cursor acquisition is taking the form of post-training models that he already had. In the near future, Elon has promised that Cursor is going to be part of the pretraining recipe. If he can make that work, I think Grok has a fighting chance to join the frontier through brute-force compute efforts.

Peter Diamandis

There are a few things he's doing. First of all, he's got tens of billions of dollars of dry powder now to focus on this. The second thing is, he's announced that he's bringing in his smartest players from SpaceX and Tesla to work on xAI.

He is by no means giving up the ghost here. He wants to be number one. He wants to beat OpenAI. He wants to create Grok as the ultimate, greatest seeker of truth. And again, I would never bet against him.

Alex

Yeah. I think the best bet here is that he will brute-force his way back to the frontier. That's what I'm hoping will happen.

Peter Diamandis

Yeah. Well, he also doesn't see it as a two-horse race.

Salim Ismail

Yeah. What you're describing as a two-horse race, he doesn't perceive that at all. He thinks it's still a race against Google, specifically because training directly toward a customized chip is a 10-to-100-times unlock, and he doesn't perceive Anthropic to be near there.

OpenAI has some activity there, but it's nowhere near it. Google, however, has already got its whole vertical monopoly stuck together. He doesn't think he's going to lose because he thinks he's going to be the first to have a reasonably good model with custom silicon that supports the model instantaneously, with the design of the chip being AI.

Peter Diamandis

You know, we're seeing verticalization win every race here. We'll see it in the space industry. We're seeing it with Google, and we're seeing it with xAI. I mean, it's fascinating. Salim, please.

Salim Ismail

Yeah, there's an idea here that could allow him to leapfrog even faster. We're moving from models that were built on human artifacts toward models being trained on the actual process of human-machine work, which is where the Cursor data becomes really useful.

That creates a flywheel where you have a better model, more usage, a richer workflow, and then a better model. I think that's going to serve him very well in the future.

Alex

I’ll comment on that point narrowly. I think it’s an interesting debate one could have. The Cursor acquisition—I think I viewed this at the time and commented on this on the pod previously—I viewed it as a brain transplant for the future trajectory of Grok, given that ChatGPT is also going through the same brain transplant, making Codex essentially a model—or class of models together with scaffolding—that were optimized for code generation and recursive self-improvement. That’s becoming the new mainline ChatGPT; by analogy, xAI and SpaceX acquiring Cursor post-IPO to make Cursor essentially the new mainline Grok, I view as an analogous move.

However, the dataset from Cursor, which, in my understanding, consists in part of lots of reasoning traces driven by developers who wanted more code generation, I think buys Elon sort of a leap to the near frontier in terms of code generation. But it will still be incumbent on Elon, xAI, and SpaceX to achieve their own recursive self-improvement loop. You can only get so far by post-training on developer or user traces. At some point, the models need to start developing better models. That’s been, historically, I think, a strength of Anthropic—probably a weakness of xAI—but maybe he can brute-force himself to the front of the recursive self-improvement loop.

Peter Diamandis

Let’s jump into a few Anthropic stories. Anthropic’s flagship model, Fable 5, has been offline for 15 days because the US government pulled it for national security fears, and hopefully we’ve talked about this ad nauseam. Now Axios reports it may be back within days. Secretary Lutnick credited Anthropic for working on the risks through the Pentagon and NSA. They still haven’t signed off on that.

Interestingly enough, Stripe recently reported that they ran a test using Fable 5 to overhaul 50 million lines of code in a single day, work that would have taken engineers many months. The government is treating Opus 5 as a commercial AI model, like a controlled munition, taking it offline and re-permitting it for users. We’re going to have to see how this evolves in the coming days. So let’s talk about Opus 5 coming back online, and Anthropic is another story. Alex, if you want to cover that one too.

Alex

Sure. I think there are a couple of interesting notes coming out of this if Fable 5, as I expect, eventually becomes available again. One of the more interesting takes, I think, is that this will have been a period of a few weeks when allegedly Chinese organizations that were leveraging access to Anthropic’s frontier models or near-frontier models for reasoning-trace distillation will have been denied that access. So we talk on the pod all the time about how the US maybe has a 3-month lead or a 6-month lead or an 8-month lead, depending on how you count. There’s a certain sense in which this 1-month-ish shutdown—future perfect tense—may have, or will have, denied China at least a month of catch-up time. That’s a generous interpretation.

A less generous interpretation is that historians will look back and say this period marked the period toward the middle or the endgame of recursive self-improvement, when months counted and the permitting of frontier intelligence became almost a Zone of Thought, to borrow from Vernor Vinge, or a bloc system, to borrow from the Cold War. Before, anyone could access frontier intelligence; after, you have to be a US person, there are strict export controls for capabilities, and there’s a nonproliferation regime where, if you’re a non-US person, you gain access to models that are maybe a few months behind the frontier.

But I also think a few years from now, when we look back on this time, I think this will have been—yes, there was a phase change in terms of the diffusion of frontier models—but I do think sometime in the next few years we’re going to get to the end of the recursive self-improvement rainbow, and there’s going to be a perfect model. We’ll look back and say this was just a period of months—a delay—but ultimately everyone is going to figure out what the perfect model looks like.

Peter Diamandis

Was this 1-month period also a chance for a lot of critical systems to safeguard themselves against Fable 5—the most essential ones, maybe?

Alex

By and large, yes. There was a stand-up, both within the US government, of vulnerability scanning, and outside the US government, we saw 3 or 4 independent nonprofit or for-profit organizations stand themselves up to do bulk vulnerability scanning using Fable 5. But I think, to the extent pause-ism has had its day in the sun, I don’t think this actually decelerated AI at all. I think this is a net accelerant.

Peter Diamandis

I’m not thinking about decelerating AI. I’m thinking about decelerating black hats from being able to get in there and penetrate.

Alex

I don’t think so. I think black-hat capabilities are proportional to capabilities overall. And I think what we saw during this time is that Chinese models like GLM-5.2 began to give anyone who wants near-frontier capabilities the ability to do essentially whatever they want with them. They may not be as capable as Opus 5, but this creates enormous pressure on Chinese organizations and the Chinese frontier labs to catch up.

And so I think, as with the original PauseAI movement, it had the net effect of accelerating capabilities globally. Same idea here.

Peter Diamandis

Two quick implications from this slowdown. I just want to point out one for investors: regulatory risk is now one of the first-order variables when you’re looking at companies, because it’s real. And the second, for technical founders, is don’t build your product or your company on a single model. You have to make sure you’re able to swap out models, because you have no guarantees as we’re going forward. And Dave, you saw that. Dave and Alex, do you want to talk about the Sonnet announcement that came an hour ago? Dave, you first.

Dave

Well, it’s really obvious that AI is sold out, and that when Fable 5 came out, they doubled the price on us, but you had to use it because it’s just so good. So it’s pretty clear that Sonnet 5 is now a way to kind of fill this gap until Fable 5 is back out. But the price point is very high, given the amount of compute that they have to use to deliver it. People will still buy it because, again, AI is sold out.

So you see the revenues at Anthropic going through the roof, and it’s because the demand for AI way outstrips the underlying chip supply. The byproduct of that is a lot of things. Only the very top-of-the-mountain use cases are going to get access, and then after Fable 5 comes back out, I agree with what Alex was saying a minute ago. This moment in time will be remembered in history. This is the intersection of AI and the government that’s never going to go away now.

But not every person on the planet and not every company on the planet is going to be able to access the models, and it’s supply-constrained at the same time. So then there’s going to be preferential routing. Sonnet 5 is a kind of mediocre capability at a high price point, but people will still need to buy it. And then Fable 5 will come out at its extremely high price point. That’s my read on Sonnet.

Peter Diamandis

Alex, any addition?

Alex

I think this is a bizarre announcement. Admittedly, this is a hasty analysis, since Sonnet 5 was released right before we went to air here. But I’ve been trained—as I think the majority of sophisticated users have been trained—to expect that the Sonnet series from Anthropic would represent some distillation of the Opus series. Similarly, the Haiku series represents a distillation of the Sonnet series.

As you go down toward smaller, lower-parameter-count, more-distilled models, you see some optimal frontier emerge in price-performance space where performance—at least throughput—goes up, price per token goes down, and performance goes down. Maybe I’m missing something, and maybe the answer will reveal itself in the next few hours. But just looking at the cost-versus-performance-at-agentic-tasks curves that Anthropic released with Sonnet 5, it’s a little bizarre.

On the one hand, Sonnet 5 is an optimal frontier, sort of a Pareto improvement over the last version of Sonnet, Sonnet 4.6. But Opus 4.8, which has been out for what, in these singularity times, passes for an eternity, is better. It’s superior on a cost-performance basis. So I’m not 100% certain I understand what Anthropic is hoping to achieve with Sonnet 5.

Peter Diamandis

I can tell you, Alex, everybody’s working on these frameworks where you can bounce from model to model while keeping the context intact, and all of the work that’s piling up—the prompt history and the intellectual property—is piling up like crazy now. You have a choice between working in an open framework, but Claude Code and Claude Cowork are super compelling, with all the MCP wrappers and connectors already built in. So the easy choice—the Apple-like, “I’m going to pay more, but it all works” choice—

Alex

—is to go with an all-Claude stack. And then, when you’re working in Opus 4.8, if you have a simpler question, you go to Sonnet—or it automatically goes to Sonnet—and if it’s an even simpler question, it just goes down to Haiku. So that’s the easy way to go. But the more cost-effective way to go would be to bounce over to a different model, but then you have to use a third-party context-management platform. So that’s the tension. But this is kind of like Anthropic becoming the Apple of AI, where you’re overpaying by some insane amount.

Peter Diamandis

I feel like there’s some branding going on behind the scenes that we’re just missing. My intuition is—there’s something there we’re not seeing.

Alex

Maybe, in the sense that Fable and Mythos are the new high-end models. Maybe there's some sense in which Sonnet is the new low end. Sonnet is the new Haiku, and viewing it through the branding of Sonnet is maybe incorrect. Maybe we should be thinking of it as the Haiku level, and it's just that Fable 5 isn't accessible. There's some weird Pareto-optimal frontier, I think, that's missing in order to explain why we've seen a reversion to this optimum.

Peter Diamandis

We will find out, and we will get to the bottom of it.

All right, mates. Let's jump into data centers and space. For that, we're pleased to bring a friend on. Philip Johnston is the co-founder and CEO of Starcloud, a startup building space-based data centers. Starcloud has raised about $200 million, with its last round over $1 billion. Famously, Philip's company launched Starcloud-1, the first NVIDIA H100 GPU in orbit. Apparently, Philip, you've trained your first LLM in space. Starcloud launched in November 2025 on Falcon 9. Welcome, Philip. It's a pleasure to have you.

Philip Johnston

Thanks so much for having me. It's a huge honor. I've been a longtime fan, so I'm very privileged to be here.

Peter Diamandis

Awesome. It's mutual.

I have a lot of stories we want to talk about in data centers and space to wrap up today's episode, but let's start with a little bit about Starcloud. Tell us about the company and your vision. Where are you guys, what have you done with the H100, and—yeah, let's go there.

Philip Johnston

Yeah, for sure. We started about 2.5 years ago, in January 2024. We're a team of about 20 engineers based in Redmond, Washington—actually, right down the road from the Starlink manufacturing facility. About half our team came from SpaceX, and the rest are from the data center companies up here, so AWS, Azure, and the others.

Then, yeah, we launched our first spacecraft, Starcloud-1, in November last year. It had 5 GPUs—2 from AMD and 3 from NVIDIA—but the most important one, as you mentioned, was the NVIDIA H100. With that, we were the first to train a model in space. We trained nanoGPT from Karpathy, which is a very tiny model, but it still counts.

Peter Diamandis

Totally counts.

Philip Johnston

We were actually the first to run a version of Gemini in space. We ran Gemma, which is DeepMind's cut-down version of Gemini. We've done a few other things. Now we're doing much more useful workloads. We've just been doing high-power inference on SAR data—synthetic aperture radar data—in collaboration with various DoD entities. We also actually played Doom. We ran Doom on Starcloud-1.

Peter Diamandis

As one does. A little bit of lag there, probably.

Philip Johnston

Before we get into it, I just want to say you guys have been ahead of this trend more than most. Thank you for your support. I know Alex is often vocal about his support, and Dave gave me a shout-out early on. Peter, I know, in the interview with Elon, you were also very supportive, so I really appreciate it.

Peter Diamandis

Yeah. Well, you're building the Dyson swarm, and this is important for our great-great-grandchildren—for all of us. Philip, speaking for myself, I want there to be multiple Dyson swarms. We can't have a solar-system-scale monopoly.

Philip Johnston

Agreed. Maybe a Matrioshka brain, so we can have swarms inside swarms inside swarms.

Peter Diamandis

So there's Jupiter and Saturn—plenty of atoms left to disassemble.

Philip, you gave us a sense of where you are right now in terms of Starcloud-1, but where do you go next?

Philip Johnston

Yeah. We've got 3 launches booked next year. We're launching Starcloud-2, booked for January. It's about 100 times the power generation of Starcloud-1. We'll have, by far, the largest commercial deployable radiator in space. That's going to have a whole bunch of H100s, also the Blackwell chip from NVIDIA, and some other interesting things, like some Bitcoin-mining ASICs. It will also have an AWS Outpost, which is an on-premises server blade, so we can run an instance of EC2 in orbit, which is useful for DoD customers.

As soon as possible, we'll be launching a much larger spacecraft, what we're calling Starcloud-3. It's a 200-kilowatt, 3-ton spacecraft, which will fit on the Starship rideshare dispenser form factor. Actually, if you guys can see this, I can even show you. We've got a version of it welded up on the ceiling—the chassis. With this, we'll have huge 100-meter deployables hanging off the side of that.

Peter Diamandis

How much power are you generating to power that?

Philip Johnston

That's 200 kW.

Peter Diamandis

3 tons, you said?

Philip Johnston

3 tons, yeah.

Peter Diamandis

3 tons. Okay.

Philip Johnston

Yeah, and we can fit about 50 of them per Starship. So we're talking about about 10 megawatts of new compute capacity per Starship launch. We're hoping to be launching very frequently on Starship. They're building absolutely enormous capacity, as I'm sure you're all aware: 2 Starship gigafactories are designed to produce something like 3 Starships per day. Hopefully, there'll be capacity for us to launch. Obviously, we're looking at some other launch providers as well, but that's the primary one.

Peter Diamandis

You have to ask the elephant in the room: When you're pitching investors and they say, “But there's Elon and his mega plans, and Google's far behind. Are you picking a niche in this area that you're going to be competitive in?”

Philip Johnston

Yeah, it's a great question. The main niche we're going after is to be more like an energy and infrastructure play than like our own cloud. For example, we've got an agreement with Crusoe where we essentially say to them, “Hey, we have a box, and that box has power, cooling, and connectivity. We'll work with you on whatever chip architecture you like, and you can sell to whichever customers you like, for whatever price you like. You just pay us a fee.” In the same way that you would pay a rental fee to somebody like Equinix, you pay that kind of rental fee to us, and you finance the chips. That's the approach we're thinking about.

I think, in the early days at least, it looks like SpaceX is primarily going to be serving their own Grok and xAI workloads. In the medium term, we'll be providing a cloud service to folks like Anthropic. I think it's probably a bit further out that they're looking at being just a pure infrastructure provider, though I think Elon did mention something about that relatively recently. But that's the idea.

In general, it's a good point because, of course, we're going to have a higher cost base than SpaceX because they own the launch. As long as we have a lower cost base than all of the other hyperscalers, I think we're in a reasonable position. If we have a lower cost base than OpenAI, for example, they're going to need to figure out a space solution. Either they pay xAI to run workloads on xAI or on SpaceX's satellites—in OpenAI's case, I think that sounds unlikely—or they start building their own satellites, and it's possible, but I mean, they're going to be way, way far behind.

Or the last option is they'll look around in 2 or 3 years, as Starship cadence ramps up, and they'll be like, “Okay, we're going to get left behind if we don't get on top of this.” They'll be like, “Okay, who's the most advanced in the market? Maybe besides SpaceX.” At that point, I think we'll have a very significant lead over anybody, perhaps besides SpaceX.

Peter Diamandis

Interesting. Dave, Alex, you want to jump in?

Alex

I've got 2 questions.

Peter Diamandis

Okay.

Dave

Okay. One was, 2 years ago, we didn't have data centers in space on our bingo cards at all. What had you do that? Some of us did, and definitely the mainstream did not. I know, Alex, you've been talking about Dyson swarms since you were probably 5 years old. But what made you jump to that and say, “We're going to do that?”

Philip Johnston

Yeah. We actually started off by looking at space-based solar. So, in mid-2023, I randomly took a trip down to Starbase, Texas, on a weekend, even before the first launch. Not as many people were looking at it back then, and I was just blown away by the scale of what they were building.

In my head, I was like, “Okay, all of the concepts from sci-fi that I remember reading about—Asimov was talking about space-based solar in the ’40s, even—are going to come true. It's just a matter of timeline now.”

Peter Diamandis

Philip, if I could clarify: space-based solar power satellites for beaming energy down to the ground?

Philip Johnston

Yes, exactly. Huge solar panels in space, and then either using infrared or microwave to beam power down.

The main problem—and we spent several months on the math, essentially, on the break-even—was that we wanted to know what the break-even launch cost was at which space-based solar makes sense. We came to a number around $50 a kilo, where that would make sense. Initially, we thought, “Okay, that's good enough. Starship will get there at some point,” and we started working on that.

But then we were like, “Okay, well, the problem with space-based solar is you lose 90% or 95% of the energy in transmission from space to ground.” We were looking around and saying, “Okay, once we get the power down, what are we going to be using it for?” Even 2 years ago, most new energy projects being built, particularly in the US, were being built primarily to power data centers.

So the thinking was, “Okay, well, either directly or indirectly, that power is going to be going into data centers. If we instead can find a cheap way to get the data center to space, let's rerun all those calculations to know what the break-even launch cost would need to be for that business to break even—to make sense versus terrestrial.” So we reran those numbers. We came to a launch-cost break-even of around $500 a kilo if we had a cheap way to get the data center to space, and that became the basis of a white paper that we put out in summer 2024. Then that essentially became the basis of the company.

Peter Diamandis

Wow, that's great. That's a great story. It's an interesting entrepreneurial story for all the entrepreneurs listening, right? You're going down one road, and then all of a sudden you see a massive opportunity, especially when you can go deep enough to look at it, because the idea of space solar power satellites has been around since the ’70s.

Gerard K. O'Neill at Space Studies Institute looked at it. His solution was to build them on the Moon and then fly them to Earth orbit, where the launch costs obviously are minuscule.

Philip Johnston

I'm sure that would happen. I'm sure that will happen.

Dave

Yeah. Second question is, what are the couple of biggest bottlenecks you're facing right now?

Philip Johnston

We are actually very constrained on launch right now, as everybody is. We're so constrained that we're trying to book now on Relativity Space's first launch in—

Peter Diamandis

January. All right. I'm really excited about that. I think that would be super cool to have a launch on there.

For those of you who don't know, we covered Relativity Space in a podcast a while ago. This is Eric Schmidt's company, where he's CEO. He bought it from Tim and Jordan when it missed the financing, and Relativity Space is about the size of New Glenn, half the size of Starship.

Well, if you're building toward the Pez dispenser, actually, that's a problem. That's really interesting. How's that going to work out?

Philip Johnston

Yeah, it is a problem. I think we're going to have to have 2 form factors. The primary one we're working on right now is for Falcon 9, but I think we're going to need a form factor that will also fit on Stoke Space. Stoke Space is the only one that has a reasonable upper stage, or the only one that's seriously working on a reusable upper stage right now. So we're also looking at a Stoke launch-vehicle form factor.

To be frank, the Relativity one is—maybe just to take a step back—the business has 2 phases. The first phase is while launch cost is relatively high. We're launching on Falcon 9 and others, and we're primarily serving edge and cloud, providing edge and cloud services for other spacecraft, particularly DoD and Earth-observation constellations.

Then, on a sort of 3- to 4-year time frame, as Starship ramps up cadence and production, that's when we switch over to competing with all terrestrial data centers on energy cost. So, when I say we're launch-constrained right now, I'm even talking about the first business. We've got 3 launches booked for next year, but if you want to book anything for 2028 on Falcon 9, there's just nothing available.

Peter Diamandis

Wow.

Philip Johnston

The government's just plunked down 20 launches, which has bumped everything back. We're going through various channels to try to get some priority on that.

Peter Diamandis

So this is GPUs for processing in space?

Philip Johnston

Yes, correct. We will receive, for instance, raw imagery—hyperspectral or SAR, or other types of satellite-sensing data. Instead of having to wait for a ground station and downlink enormous amounts of data, we can process all of that on the edge.

Actually, one of the demonstrations we've just done is to process a whole bunch of SAR data, identify the coordinates of a tank, and then just downlink the coordinates of that tank. Rather than having to wait—it could take 3 days to get enough ground-station passes to get 100 gigabytes of SAR data off a satellite—we can receive all that data optically in space, process it on orbit, and then just downlink the insight. That's the use case we're building toward right now.

Peter Diamandis

I'm curious, Philip. The premise there is presumably bandwidth is scarce—scarcer, maybe, than launch. So you have to do a lot of edge inference in LEO or wherever you're doing this.

I'd love to ask you a similar question that I asked Will Marshall of Planet in a previous podcast episode. Let's project out 10 to 20 years, well past the current bottleneck in heavy-lift or heavy-launch capability. What do you think, as the founder and CEO of one of the incumbent Dyson swarms—plural—what do you think the Dyson swarm, or Dyson swarms, of, call it, 20 years from now look like?

Does it look like LEO? Does it look like sun-synchronous orbit? Does it look like the Moon? Does it look like a Dyson swarm around the Sun? Paint a picture for us of what, 20 years from now, the Dyson swarm or swarms look like.

Philip Johnston

That's a good question. I hope within 20 years we've started putting significant amounts of compute in a Sun orbit, probably starting with the Lagrange points, although you probably don't want to clog them up too much, but even just a distinct Sun orbit that trails Earth or is in front of Earth.

Certainly, you could fit about 10 terawatts of compute in the dawn-dusk sun-synchronous orbit, and then you're back to flying in orbits that have an eclipse—sort of 45 minutes of every 90-minute orbit. That then drives the cost up significantly because you need batteries and all these other things.

Peter Diamandis

Scarcity of real estate. SSO is going to get crowded. You're one of the few people, Philip, I hear talking—this is like overpopulation on Mars—about SSO getting crowded due to the SSO Dyson swarm and then overflowing back to other orbits. That's fascinating.

Philip Johnston

Yeah. Well, because there's only one SSO orbit that is—you know, it's a very rare and beautiful orbit—the dawn-dusk sun-synchronous orbit, which flies over the terminator line.

I mean, 10 terawatts is a lot of compute. That's like 20 times the entire US power grid. My expectation, roughly, is that in 10 years we might hit a point where most new compute capacity is being deployed in space.

If you ask me what the total percentage of compute in space is at that point, it's still probably less than 5%. In the same way, right now, in certain parts of the world at least—Norway or whatever—most new cars coming off the production line are electric. But if you want to know what percentage of the fleet is electric, it's still like 4%.

It just takes a long time to replace all of the capacity that we're building on Earth terrestrially right now. So, in 10 years, I would say most new compute capacity will be in space. In 20 years, it could be—I would be surprised if more than half of all compute were in space even in 20 years.

But beyond that, certainly there'll come a point, and it's probably more like a 50-year time frame, where 99% of all compute is in space.

Peter Diamandis

I also just have to ask: second elephant in an increasingly crowded room. If, over the next few years, heavy launch is the main bottleneck, is there some plan in a back room somewhere for you either to build or buy your own vertically integrated heavy-launch provider, if that's the main constraint?

Philip Johnston

We are in quite serious discussions to partner with various launch providers. Probably shouldn't go too much down that path. It's early days. If SpaceX can provide the capacity, we'll be very happy customers of SpaceX.

If not, we’ll need to figure out something. If you ask me, do I think SpaceX has a monopoly on launch in 5 years? The answer is yes. In 10 years, the answer is no.

Peter Diamandis

I realize—and we’ll talk about Rocket Lab’s purchase of uranium in a moment. What I’d love to do is jump into a few stories, Philip, and have you comment alongside the other guests. The first story is a recent conversation by Elon about space-to-Earth telephony, so let’s jump into that.

I’m going to play a short video. This is a video clip of Elon speaking at the All-In Summit, and then we’ll talk about it afterward.

Elon Musk

The phones that are able to use the spectrum that was acquired probably start shipping in around 2 years. We also need to build the satellites that are going to communicate on those frequencies. In parallel, we’re building the satellites and working with the handset makers to add these frequencies to the phones.

Then the satellites and the phones will handshake very well to achieve high-bandwidth connectivity. The net effect is that you should be able to watch videos anywhere on your phone.

Peter Diamandis

Fascinating story—vertical integration again. SpaceX owns the whole stack: launch, satellites, spectrum, and increasingly compute. Direct-to-phone is an interesting product. It’s going to be space-based internet for everybody on the planet. Thoughts on this? For investors, we’re going to see the telecom industry getting disrupted.

Philip Johnston

Yeah. He didn’t mention it here.

Peter Diamandis

To a point on vertical integration, he didn’t mention it here, and I think he’s talking about working with phone providers. It would not surprise me at all if they either buy or start manufacturing their own phones as well. I don’t know—what was your read of that? My read was that he was talking about working with phone providers and not talking about building their own phone. At some point, I would be surprised if they don’t think about building their own phone.

It’s been rumored that Tesla phones have been coming for a long time. Elon famously does not work well with others. He tends to buy them or blow past them. Did you see the recent rumors about the possible acquisition of T-Mobile?

Philip Johnston

Yeah, the rumors are out there, and also with Charter Communications.

Peter Diamandis

Starlink is the most unbelievable business. Starlink is going to produce hundreds of billions of dollars of free cash flow in the next 5 to 10 years. They’re going to have direct sales and unbelievable bandwidth. Unless you’re really in the middle of Manhattan, I think Starlink will be the best option for most people.

I can’t see a world where, on Starlink revenues alone, SpaceX isn’t the most valuable company in the world. We’ve been projecting $10 trillion by 2030 in terms of valuation and scaling toward $100 trillion. I’d absolutely back that.

Dave

My question, actually, is: if we have direct satellite-phone connectivity, downloading videos, and that implies tens or even hundreds of thousands of satellites in low Earth orbit, and then data centers are going to want that same space, is that actually going to survive the escalating needs of AI?

If you figure, as you said, 5 to 10 years from now, almost all computing will be in space, that’s also a lot of very high-value use cases for that famous LEO.

Philip Johnston

The orbits are slightly different because the Starlink satellites fly around 460 kilometers, I think it is now, but they are in a 50-degree inclination. They aren’t going over the poles; they’re mainly going up to just midway through Canada. They’re flying as low as they can.

Actually, with the AI satellites, you want to fly them as high as you can, almost, because even in this dawn-dusk, sun-synchronous orbit, if you’re flying at 600 kilometers altitude, there’s about a month of the year when you have a 10% window that is blacked out. The ideal altitude to fly is actually 1,200 kilometers. That’s the lowest you can fly where you don’t have any blackout, even throughout the year.

Between 400 and 500 kilometers is going to get extremely crowded. I think where the AI satellites fly will get very crowded, but it’ll be for a different use case. I don’t think they’re going to be competing for the same real estate, essentially, because—

Dave

Are you going to run into Kessler effect problems if you go that high?

Philip Johnston

I mean, at scale, we’re talking—yeah. The main reason people don’t want to fly that high right now is actually radiation from the Van Allen radiation belt. Do you mean because there’s less drag, so if you have any collision there, the debris is going to stay up for longer in the—

Dave

Yeah, for millions of years.

Philip Johnston

Yeah. Well, even at 1,000 kilometers, most stuff will probably deorbit within about 50 years, which is not great. But it’s not as drastic as I think a lot of people sometimes think.

For example, I don’t know if you know about this, but in 1970, the U.S. government dispersed 400 million needles at about 3,000 kilometers altitude because they wanted to bounce radio frequency off them, which is insane to think about today.

Dave

It was like an artificial ionosphere.

Philip Johnston

Yeah, it was the most insane thing ever. You can’t imagine it being done today. But actually, every single one of those needles has now deorbited, which people don’t realize. People think that if you have quite a large satellite, it will stay up at 3,000 kilometers for quite a long time.

Things that are much smaller and don’t have their own propulsion, because of the way the Sun and Moon and all of the solar wind interact together, every so often they get closer to Earth and get dragged in and dragged in and dragged in. The Kessler effect is something we really need to pay attention to, but it’s not as drastic as I think a lot of people sometimes think.

Peter Diamandis

That’s good news. Sim, you got a question.

Dave

Wait, but what about cooling? I mean, cooling and radiation—oh, sorry. Go ahead, Sim.

Sim

No, go ahead. I was going to ask that exact question.

Peter Diamandis

Well, we were talking about this—I forget whether it was in Riyadh or at A360, Philip, but you had this all-aluminum cooling system, and I was like, “Wow, that’ll be incredible if that works.” But now it sounds like you’re going to move to liquid cooling or some kind of liquid-cycling process.

It’s a government project. What else do you expect?

Philip Johnston

Yeah, it’s liquid through aluminum. That design is the same as what we discussed in Riyadh, I think. Exactly. It’s a very large, low-cost, low-mass deployable radiator.

Radiators work because the International Space Station has been using them for 20 years. The problem with the ISS radiator is that it is both expensive and heavy.

Philip Johnston

Expensive, heavy, and late. The core IP of our company is making this radiator cheap and light. It’s not a new physics problem; it’s a manufacturing and engineering problem.

Our radiator design—and we’ve got it working; it’s been fabricated and gone through TVAC and everything—is 10 times less mass per watt of dissipation than the ISS radiator and about 100 times less cost.

Peter Diamandis

Yeah, about 100 times less cost per watt of dissipation than the ISS radiator. I’m excited that that will fly in January, and it will be a big milestone. It’ll be, by far, the largest commercial deployment.

I wanted to double-click on something you said. Did you say that, over time, 95% of the compute we use will be done in space?

Philip Johnston

Ninety-nine point nine percent, I think, over time.

Peter Diamandis

Wow.

Philip Johnston

But that’s on Alex’s Dyson-swarm-type time frame.

Peter Diamandis

That’s right. Masayoshi Son just came out with a statement saying he disagrees with the thesis of orbital compute because energy is only 7% of the cost compared to everything else. Where do you come out on that? What’s your answer to him?

Philip Johnston

I did a post about this this morning because people kept tweeting it at me, so I was like, “Okay, well, he also sold all of his Nvidia stock in 2019, so he’s not always right.”

He is right that energy is a very small proportion. Energy and infrastructure, though, are actually quite significant. It depends: right now, chip cost is very high, so that is by far the dominant cost. But if you include energy and infrastructure, you’re talking about at least 30% of the cost.

The main problem is that, even to build a new energy project terrestrially, you’re looking at a 5- to 10-year lead time just for the permitting.

Peter Diamandis

Yeah.

Philip Johnston

The main advantage is that we can deploy this stuff extremely rapidly. So even if we were breaking even on energy and infrastructure, it would still make sense to do this. But we’re looking at doing this about 10 times cheaper on both energy and infrastructure.

When I say infrastructure, what I mean is that we don’t need batteries, cooling towers, big chillers, or backup power. All we need is a dirt-cheap radiator. Our radiator is really dirt cheap, and a lot of the other infrastructure costs are gone.

It's only then that the launch cost is the additional piece we have. But as I say, that is very rapidly trending toward a much lower launch cost.

Peter Diamandis

Philip, if I might, please just pull the thread a little bit on launch. Projecting conservatively 20 to 30 years out, where do you think launch is going to come from? Will we be using railguns to launch from the lunar surface? Will we have, optimistically, self-replicating von Neumann probes that are disassembling our solar system to build more compute? Where is all the matter, energy, and launch coming from 20 to 30-plus years out, in your mind?

I mean, Elon has this great quote, something like, “Optimus is the von Neumann probe,” and I kind of agree with him. If you can get 100,000 Optimus robots to the lunar surface and get them to build an Optimus factory on the lunar surface, then we're off to the races. Then you have this insane exponential curve in terms of development and pace of development.

Philip Johnston

Hyperexponential.

Peter Diamandis

Yeah. Absolutely hyperexponential.

Philip Johnston

So, I do think we'll have mass drivers on the Moon, and I think they'll probably come sooner than most people. If it was less than 20 years, that would be maybe surprising to me. If it was more than 20 years, I'd also be a bit surprised. I think, yeah, around that time frame.

Dave

All right, I apologize. I have one of the senior executives from State Street Bank waiting for me outside the door here. I'm going to love watching this podcast because all of my questions are in Alex and Sem's heads, but I can't wait to hear your answers. I'm super excited about what you're doing, though. Congratulations.

Peter Diamandis

All right, Dave.

Philip Johnston

Thanks so much, Dave. Appreciate it.

Peter Diamandis

See you very soon again on our next pod recording. But let's move to our last story on the docket here.

Rocket Lab is acquiring Iridium, creating yet another fully integrated space powerhouse. Rocket Lab, for those of you who don't know, is a company started by Peter Beck—actually, Sir Peter Beck. It's a $6.4 billion company now. Kudos to them. Peter had no background in launch, and he built arguably the second-tier provider for launch after SpaceX.

They have their Electron launcher. It's a smaller-sized launcher, but it's launched 91 times and has very high reliability at this point. They're building their next vehicle, called Neutron, and it's planned for a first launch by the end of this year. Like Falcon 9, it's got a first stage that's reusable.

I know Iridium well. I was playing in the big LEOs in the early '90s when it got its license and started commercial service in November 1997. It's a 66-satellite constellation orbiting at about 780 kilometers.

A fun story—I don't know if you know this, Alex—it was originally called Iridium because it originally had 77 satellites, which is the atomic number for iridium. When they changed it to 66 satellites, they did not change the name to dysprosium, which is atomic number 66. Good marketing move there.

Alex

Also, iridium, I think, is a little bit more stable as a nuclide.

Peter Diamandis

Yeah, and it sounds a lot better than dysprosium.

So, what makes Iridium interesting is that it's got 10.5 megahertz of bandwidth at L-band that's globally coordinated. They go through the ITU and get it. Importantly for our viewers here, you can get 10.5 megahertz in the U.S., but can you get it in every country around the world? That's what makes it a prize.

Spectrum is the prize, and vertical integration here is becoming the winning structure for the new space economy. Owning launch and manufacturing—they build their own satellites at Rocket Lab as well—and getting spectrum and operations is a winning combination. They're playing on the SpaceX handbook. Pretty extraordinary.

Philip, thoughts for you?

Philip Johnston

Yeah, I mean, it's a very smart move, I think. It's particularly smart because I think there's been quite a bit of commentary—people saying, “He's not trying to compete directly with SpaceX with this.” If he was, it probably wouldn't be as smart a move. He's really carving out a niche.

The other thing is his share price has gone to an insane multiple of his revenue, and he's capitalizing on that because I'm pretty sure all of this is going to be in Rocket Lab stock. It makes sense to start paying for cash-generative, profitable companies in Rocket Lab stock when you're trading at a however-many-hundred-times-revenue multiple, which is what they're trading at.

Peter Diamandis

I have to ask Philip a question just about the spectrum side. There are a bunch of obvious questions I could be asking about vertical integration, and whether spectrum and LEO compute want to inevitably own, or be owned by, heavy-launch capability, but I just want to focus on spectrum.

To the extent that part of the Iridium–Rocket Lab story is the acquisition of RF spectrum, do you think radio has a future, or will we find ourselves 5 to 10 years from now with it all being optical-frequency direct laser links and radio having approximately no future?

Philip Johnston

It's a great question. I would lean more toward the second of those 2 options. I wouldn't say radio really has no future. It's useful because it's cheaper, because you don't need gimbals and things, but laser is where everything's going.

We've got 3 laser terminals on our second satellite, launching in January, with gimbal lasers. We've actually just signed a contract with SpaceX for the next 25 of our satellites. We'll have 2 Starlink—they call it PPL, plug-and-play laser terminals—on our satellites, and then 1 SDA-compliant laser that can connect with the government satellites.

So, yeah, lasers are the future for space comms, and it's also unregulated, which makes it amazing.

Peter Diamandis

All right, guys. I apologize. I've got a hard out here as well. Philip, a pleasure, and I'm excited to watch StarCloud 2 and StarCloud 3 make it to orbit. Thank you for joining us, Sem. Are you coming home eventually?

Sem

I am. I'll be here for a few more days, and then I'll be back.

Peter Diamandis

All right. And Alex, how about you? What's your travel schedule looking like?

Alex

Well, I don't know. I'd love to visit LEO or sun-synchronous orbit sometime soon. Philip, we should chat.

Philip Johnston

We should. We should. And Peter, I think you're going to be in Paris in a week, so I might see you there. I think I may be there virtually. Oh, no, I see.

Peter Diamandis

Wait, where am I? I know. I'm in Calgary.

Alex

Calling the kettle black.

Peter Diamandis

Yeah. Calgary, Germany, and Greece. Yes. Okay, okay. All right. Love you guys. Again, thank you, buddy. Thank you, Alex. Thanks. Take care, guys.