Demis Hassabis 谈 AGI、机器人规模化生产与 Elon 的1万亿美元火星薪酬赌局|EP 253
Peter Diamandis × Steven Kotler × Salim Ismail × Dave Blundin × Dr. Alexander Wissner-Gross
SpaceX拟议的薪酬方案,把登天式目标的执行变成一份全有或全无的治理合同。 Elon Musk 将在 SpaceX 同时实现百万人火星殖民地和7.5万亿美元估值后,获得2亿股、每股拥有10倍投票权的超级投票权股票,按该估值计算,回报约为5,000亿美元;此外,他还将因推动100太瓦太空算力上线而获得6,040万股限制性股票。投资者视角是:创始人控制权看起来可能很危险,但“所有真正改变世界、听起来疯狂的事情,都来自这种结构”。
Musk与OpenAI的审判,既关乎非营利承诺,也关乎谁控制具有经济颠覆性的AI。 Musk索赔1,500亿美元,要求恢复OpenAI完整的非营利地位,并撤换 Sam Altman 和 Greg Brockman;Brockman公开的日记写道:“真正的答案是,我们希望 Elon 出局”,但证词也显示,Musk团队曾谈判获取营利实体股权,xAI还从OpenAI模型中进行蒸馏。Polymarket显示 Musk 胜诉概率为33%,Blundin认为,Musk“不需要赢,也能赢”——只要拖慢OpenAI的招聘、士气和势头,可能就已经足够。
小组无法就AGI是否已经存在达成一致,这正说明头条式能力宣称为何仍难以承销。 Diamandis转述 Demis Hassabis 的看法:仍有50/50的概率需要另一次突破,可能是世界模型;Alexander Wissner-Gross则把AGI的起点定在2020年夏天的 GPT-3,因为压缩人类通用知识后,模型已经具备了通用任务表现。Steven Kotler称今天的系统是“世界上最狭窄的技术”,理由是其创意写作更差,也无法捕捉跨学科神经科学中的明显关联;Wissner-Gross和Diamandis回应称,递归式改进可以通过算法实验、海量采样和筛选实现,不必依赖幽默感或文学造诣。
人形机器人正在从演示视频进入工厂算术。 Figure已将产量从每天1台提高到每小时1台,并计划到2030年生产10万台;1X计划今年生产1万台、2027年生产10万台;Musk则预计到2030年生产100万台 Optimus,Musk和 Brett Adcock 都设想2040年前后人形机器人数量最多达到100亿台。Blundin的资本配置判断非常直接:“软件的生命周期所剩无几”,因为AI已经能非常出色地编写软件;机器人和数据中心则可能还有10年甚至更久的建设周期。
机器人投资的关键不只是能造出多少台机器,还在于人形是否会成为胜出的形态。 Salim Ismail认为,重复性工作更适合专用的轮式机器、无人机或家电;Wissner-Gross则反驳称,养老护理以及围绕人体设计的环境——包括核设施——需要人形机器人。Wissner-Gross预计,人形机器人将在2030年代初超过轮式机器人,但他认为更大的机会在“后人形”机械:到2040年,直接作用于细胞的纳米机器人数量可能达到数万亿台。
中国一项劳动者保护裁决表明,AI采用和就业保障未必是简单的此消彼长。 据报道,杭州法院驳回了将一名员工月薪从25,000元降至15,000元的方案,理由是AI采用属于企业经营选择,而非不可避免的外部冲击。小组认为,中国劳动力萎缩、人口老龄化,同时又希望保持社会对AI的热情,可能让其在不实质放慢自动化的情况下保护就业;这项裁决或将成为未来重写社会契约的路标。
GLP-1的经济规模已经可以与前沿AI匹敌,真正的约束被描述为产能,而非需求。 节目图表显示,2025年 Ozempic 和 Mounjaro 的收入是 OpenAI 与 Anthropic 收入之和的2.4倍;retatrutide试验数据显示,40周后减重37磅,而安慰剂组减重6磅,胆固醇下降27%,甘油三酯下降41%,肝脏脂肪下降80%,A1C从7.9降至6.0。随着其获批时间预计在2027年年中,Demis Hassabis称,这一药物谱系可能是通往长寿逃逸速度最有希望的路径,时间或在2030年代初。
到2028年,AI可能变得无处不在且不可或缺,但稀缺算力会把消费者能用到的东西与企业级访问权限分开。 预测包括:AI获准读取消息、通话、日历、录音和可穿戴设备数据;持续运行的AR;完美记忆;实时指导;以及新一代人把70–80%的对话交给AI。Friedberg预计,企业需求将吞噬现有数据中心产能,并警告称,如今人人都能负担得起最好的基础模型,是一个暂时的“美好时刻”,之后将进入持续到大约2030–31年的瓶颈期。
1. SpaceX将高管薪酬变成一份火星合同
Diamandis表示,即使以 Musk 的标准衡量,这套方案也前所未有:2亿股、每股拥有10倍投票权的股票,兑现条件是同时建成百万人火星殖民地,并达到7.5万亿美元 SpaceX 估值。按该估值计算,这些股票价值约5,000亿美元——“不是登陆火星,不是从火星拍一张照片,也不是在火星上放一只老鼠”。
第二项奖励是6,040万股限制性股票,对应部署100太瓦太空算力。Diamandis强调了规模跃升:Musk此前谈论的是100吉瓦,而薪酬门槛高出1,000倍。
Blundin支持超级投票权股票的投资者逻辑是,它保留了创始人推进常规董事会可能否决项目的能力。他把这种结构追溯到 MicroStrategy、Google 和 Meta,并总结称,卫星、登月任务和火星计划之所以能够出现,往往是因为“那些创始人仍然拥有行动的权力”。
Wissner-Gross认为,一种新的公司形态正在与股东利益导向的C型公司、公益公司并行成形:企业明确以实现登天式目标为组织目的,并据此奖励管理层。他提出的挑战更为激进——应当给每一位标普500 CEO设定同等雄心、以结果为导向的目标。
2. 指数级组织需要可导航的当下,而不是五年幻想
Ismail不认同 Musk 的命令与控制风格与指数级组织不相容。创始人掌握宏大的变革性目标,授权团队执行,并在工程问题上介入;一旦团队做出承诺,“他们就会把事情做成”。Ismail表示,如果 Musk 达成这些里程碑,投资者应该“笑着走进银行”。
创始人领导力被视为通常的前提,但 Ismail 提出了 Gucci 这一例外:在其 CEO 承诺把公司变成指数级组织后,据称 Gucci 在3到4年内增长了10倍。Diamandis反驳称,真正的目标更接近1,000倍,甚至百万倍的变化。
Ismail的运营模式源自 TEDx。如果一开始宣布5年举办20,000场活动,团队会被吓退;但通过设定“值得传播的思想”这一目标、明确社区规则并量化进展,TEDx最终举办了20,000场,而线性规划隐含的结果大约只有2,500场,成本几乎为零。
对应的仪表盘把宏大的变革性目标、OKR和一份实时衡量的一年期运营计划结合起来。五年愿景被放在日常管理之外,因为人们“在认知上无法把握它”;实时指标才是方向舵。
3. OpenAI审判暴露了推迟治理的代价
Diamandis将 Musk 的主张概括为违反慈善信托和不当得利,要求赔偿1,500亿美元、让OpenAI恢复完整非营利地位,并撤换 Altman 和 Brockman。据报道,Rogers法官阻止 Musk 团队把案件变成一场围绕AI灭绝风险的审判。
Brockman的日记提供了最尖锐的表述:“我们真正想要的是B型公司。真正的答案是,我们希望 Elon 出局。”日记还写道:“如果3个月后我们在做B型公司,那这就是一场谎言”,并预料到任何营利化转型都会引发“一场恶战”。
相反方向的证据同样关键:Musk团队在2017年曾为他谈判营利实体股权;他承认没有读转换文件的细则;xAI曾从OpenAI模型中进行蒸馏;Altman也曾向他提供股权,而 Musk 将其拒绝为“贿赂”。这份记录对双方都不利,并不是一场简单的道德剧。
Wissner-Gross认为,教训在于结构:非营利组织可能意外“追上那辆车”,发现自己的登天式目标具有颠覆性经济价值。Anthropic也经历了类似路径,从对齐实验室走向收入、模型、资本和营利性公益公司;他的建议是,在公司成立之初就确定资本结构。
4. 赢下官司可能不如拖慢对手重要
Ismail认为,在未来的后资本主义社会中,非营利地位可能是合适结构,按他的估计,或许就在“2、3年内”,因为追逐金钱可能腐蚀使命。他表示,正确的结构取决于哪一种最能直接推进组织目标。
Polymarket给 Musk 的胜诉概率定在33%,低于几周前大约50/50的水平。Blundin认为,这个二元概率忽略了 Musk 的战略目标:披露材料、招聘阻力、士气受损和势头丧失,即使没有有利判决,也足以伤害OpenAI。“他不需要赢,也能赢。”
Friedberg将超级投票权控制和自我改进AI的 stakes进一步放大。他称这是“千禧年审判”,因为能力和政治权力可能集中在少数人手中;他还提到,Altman曾考虑竞选加州州长,科技创始人并不只是与政治无关的创业公司经营者。
Kotler的拒绝本身构成了有价值的反击:如果他没有积极研究某个问题,就不喜欢讨论它,因为“那我只是在说闲话”。Diamandis承认这确实可能算闲话,但仍坚持认为,这场诉讼位于一个可能影响人类数百年生态系统的中心。
5. AI的文学失败,无法说明它是否具备自我改进能力
Kotler的日常体验让他挑衅性地表示:“我认为AI是假的”——意思是,AI的能力远比小组其他人所说的局限。作为作家,他花在教AI和纠正AI上的时间,比看着它写作的时间更多;作为神经科学家,他看到AI即使能访问该领域的文献,也无法识别明显的跨学科缺口。
他在机制层面的反对是:当前系统是收敛式思维引擎,而重大突破往往需要发散思维。他还表示,自从他们开始写书以来,ChatGPT的写作能力已经退化,多个模型的表现变得更差,而不是持续改进。
Wissner-Gross将文学表现与递归式研究能力区分开来:AI可以以极高速度反复测试算法参数、传递函数和架构。Diamandis的思想实验是,Claude 4.7可能会输给 Kotler 一次,但它可以生成10亿次尝试,再在上面放置一个筛选器。Kotler承认:“这是一个合理的观点。”
Diamandis把批评转化为一项实证挑战:构建一套编码 Kotler 标准的严格基准,并证明模型确实退化。Hassabis表示,一项设计良好的评估会吸引前沿实验室,因为它会成为优化目标,把主观不满转化为可衡量的能力压力。
6. 机器人工厂正从原型跨入规模曲线
据报道,Figure AI以超过300亿美元的估值融资,将产量从每天1台提高到每小时1台,并计划在现在至2030年间生产10万台机器人。Diamandis借助相关视频指出,观众正在形成一种新的本能反应:判断一段令人印象深刻的机器人视频到底是真的,还是深度伪造。
1X Technologies在 Hawthorne 新建的5.8万平方英尺工厂,计划支持今年生产10,000台 Neo 机器人、2027年生产100,000台,预计今年晚些时候开始交付。Diamandis表示,1X CEO Bernt已经答应秋天给他一台 Neo。
Blundin从 Gigafactory 得出的洞见是,生产流程中相当一部分已经实现自动化;人形机器人不需要制造每一个微小零件。自动化设备几乎像亚马逊包裹一样抵达,机器人只需完成安装设备所剩下的、需要人形动作的步骤。“瓶颈在人形动作。”
这改变了小组的投资地图。Blundin预计,随着AI把软件开发商品化,最热门AI软件公司的窗口期将关闭;机器人和数据中心则可能继续复合增长10年甚至更久。Blundin近期最看好的就业安全岗位是机器人维修,Diamandis则提到围绕机器人形成的保险和服务生态。
7. 人形机器人可能先赢得人类空间,再被更陌生的身体形态取代
Musk预计到2030年生产100万台 Optimus。Diamandis表示,Tesla最终可能不再以汽车闻名,而是以 Optimus 闻名。Kotler则质疑,这些宣言是否部分是在融资和提前预售,赶在更便宜的中国机器人到来之前;他把宏大承诺与 Meta 尚未兑现的元宇宙宣传相提并论。
Ismail的工程学反对更尖锐:重复性任务适合专门形态——轮子、无人机、洗碗机——而不是可适应的人形身体。“至少给它再加一对手臂,”他说;当专用机械可以更好地执行任务时,人形只是一个任意约束。
Wissner-Gross给出了最有力的反例:养老护理和灾害救援发生在人类身体设计的环境中。核设施、门、楼梯、床,以及需要被帮助的人,都让人形成为功能要求,而非外观选择。
Wissner-Gross把这一路径与道路上已有的16亿辆汽车、每年生产1亿辆汽车,以及 iPhone 产量从第一年的130万部增长到每年2.5亿部进行比较。他预计,人形机器人将在2030年代初超过轮式机器人,并且几乎没有多少空间留给相反预测,到2030年代末超过人类;但他认为,更重要的后人形形态是直接作用于细胞的纳米机器人,到2040年数量可能达到数万亿台。
8. 中国把AI替代视为社会契约问题
在所描述的杭州案件中,Zhao在AI自动化其部分工作前月薪25,000元;雇主提出将他降职并把月薪降至15,000元。据报道,法院支持 Zhao,理由是采用AI属于企业自主决策,并非令劳动合同无法履行的外部冲击。
Diamandis提出了尚未解决的经济问题:如果一名员工借助AI完成10倍的工作,或者员工在锻炼时AI仍在完成工作,那么创造的价值应归劳动者、公司还是国家?现有劳动法为人的劳动定价,而正在出现的新系统管理的是任务、代理和大幅下降的协调成本。
Ismail称,这项裁决是那些揭示转型正在发生的超现实路标之一,就像一家肯塔基州煤炭博物馆安装太阳能板。更深层的问题,是在未来10–20年重建社会契约,因为围绕人类就业建立的制度正面临AI劳动的冲击。
小组否定了就业保护必然削弱中国AI竞争力的担忧。劳动力减少和人口老龄化,为就业保障与激进自动化并行留下了空间;有利于劳动者的规则还可能维持中国据报道85%的AI乐观度,而美国约为25%。
9. AGI可能距离下一个突破为零,也可能仍未被定义清楚
Diamandis转述 Hassabis 更新后的看法:这是一次戏剧性收窄。10多年前,Hassabis预计至少还需要5次重大突破;如今,他认为仍需要一次突破的概率为50/50,可能是世界模型。但他更强的押注仍然是基础模型,“因为它们已经取得了如此大的成功”。
Wissner-Gross更进一步:AGI最迟在2020年夏天 GPT-3 论文发布时就已经到来。他认为,真正的发现是:人类通用知识可以被压缩进模型,并应用于广泛的人类水平或接近人类水平的任务;此后的 Transformer 改进都只是渐进式变化。
Kotler立即称这是“一个疯狂的说法”,而 Diamandis指出,至少存在14种相互竞争的AGI定义,以及多种智能维度:情感、空间、音乐、语言和沉思意识。小组可以为一种仍然无法稳定“定义、衡量或布置任务”的能力筹集数千亿美元。
Blundin把定义争论重新表述为经济充分性问题。Hassabis和 Dario Amodei 等研究者可能希望基础科学仍有更多未解之处,而创业者问的是:今天的架构是否已经能制造商品、治疗疾病、照护老人并创造富足。它不需要复现人类最后一项独有技能,也足以改变经济。
10. 自动化科学把模型能力转化为物理发现
Diamandis介绍了 Lyra Scientific 的“科学工厂”:AI提出理论、设计实验,机器人完成移液、搬运材料、收集数据并更新理论。如果把这一闭环运行速度提高到研究生的100倍或1,000倍,物理、化学、生物和材料研究都可能加速。
Kotler反对“解决物理学”这一说法,认为它夸大了能力。Diamandis则坚持实用的中间立场:定义争论固然重要,但治愈癌症、解决过去无法触及的问题,已经足以令人兴奋。
节目中的创业者样本来自牙医 Ashley Gaunt。一个下午里,AI通过提问引导她发现一个预防性健康理念,帮助她进行头脑风暴、用vibe coding写出初版应用,并搭建从概念到变现的路径。“直到我开始和AI讨论,我甚至没有意识到自己有一个想法。”
Blundin预计,这种体验会变得普遍,并认为前沿实验室可能会主动发现机会,因为它们的模型能够识别训练数据、应用和市场中的缺口。工具不只是执行一个想法,也可能帮助用户找到那个想法,以及自己推进它的角色。
11. 物种复活制造的是近似体,也是一项更宏大的复活论题
Colossal宣布蓝牛羚成为其第6个物种项目,目标是在2028年复归;公司15个项目的其他内容仍属机密。已公布的项目还包括猛犸象、袋狼、渡渡鸟、恐鸟和恐狼,Diamandis称后者已经回归。
Kotler的热情伴随着两项警告。据称,物种消失速度是基线水平的1,200倍,因此复原少数物种不能淡化环境危机;此外,重建动物会把跨越时间的DNA片段拼接在一起,它们是“这个星球上此前从未存在过的生物”,后果并不确定。
Diamandis把灭绝复活放进一个更奇异的计划:利用技术重建过去存在的每个物种,最终重建每一个人,无论通过生物方式、计算方式还是模拟方式。一个拥有100种曾灭绝动物的公园,只会是这一雄心早期、相对温和的表现。
12. GLP-1与AI正在争夺工厂、资本和人类注意力
节目图表显示,Ozempic和 Mounjaro 在2025年的收入,是 OpenAI 与 Anthropic 收入的2.4倍。Salim Ismail称这是“苹果和橘子的比较”;Wissner-Gross则认为,两者可以类比为生物软件与数字软件:资本沿着一条曲线延长人类的生产性健康,沿着另一条曲线延伸AI劳动。
两个品类都被描述为供不应求,收入由供给而非支付意愿决定。GLP-1需求规模可能达到5,000亿美元,但实体生产限制了销售;与此同时,进食减少可能已经在降低美国食品运输卡车的运量,并造成物流层面的二阶冲击。
Ismail质疑围绕AI生产力和快速反馈循环形成的狂喜。多巴胺和心流可能带来自我膨胀:“这不意味着你的思考质量等同于你的感受质量。”他的组织唯一一款带品牌标语的商品写着:“永远不要相信多巴胺。”
Retatrutide展现了健康端的加速:40多周内减重37磅,而安慰剂组减重6磅;胆固醇下降27%,甘油三酯下降41%,肝脏脂肪下降80%,A1C从7.9降至6.0。Diamandis把 Mounjaro 比作 GPT-5.5,把 retatrutide 比作 AGI,并预计其将在2027年年中获得 FDA 批准。
13. 长寿逃逸速度可能通过不断进化的药物类别到来
Ismail表示,他已经使用 retatrutide 数月,感觉更好,尤其是几十年酒精相关损伤后肝功能有所改善。这是个人体验,不是普遍性的临床结论。
Diamandis预计,新一代药物从设计、测试到上市的速度会更快,FDA可能用扩展的二期试验取代部分三期工作。商业含义非常直接:任何可信地增加10年寿命,或同时治疗癌症、心血管疾病和炎症的疗法,都会面对巨大且没有上限的需求。
Hassabis认为,不断进化的GLP-1药物类别最有可能带来长寿逃逸速度,时间可能在2030年代初或更早。他给出的市场信号是 Eli Lilly 的市值轨迹可能走向约1万亿美元,使长寿与AI公司、SpaceX并列为少数能够孕育这一规模企业的行业。
14. 2028年的AI可能对消费者无处不在,对所有人却受制于产能
Diamandis的消费者愿景从授权开始:AI读取通话、消息、邮件、日历、录音、摄像头和可穿戴设备数据。他自己的“Skippy”已经拥有广泛访问权限;终点是“环境式AI”或“自动魔法AI”,根据用户的状态和愿望调整灯光、音乐、健康建议及周围环境。
Wissner-Gross认为,2028年更重要的问题在企业。他表示,最先进的推理能力正在能为其付费的组织中获得更强需求;相比智能家居便利或另一类类似 Apple 的设备,科学发现仍是更不明显、但更重要的前沿。Ismail同样预计,AI原生企业操作系统会出现,每个人都将像一家小公司,拥有一支AI团队。
Blundin介绍了一个新推出的全息甲板:每面墙都是屏幕,配备沉浸式声音、对话式世界构建、音乐、电影和vibe coding,展示了消费者可能想要什么。Friedberg指出,约束来自算力:企业需求正在吞噬数据中心供给,2028年前看不到缓解,或许要到“2030、2031年 Terafab 之后”才会改善。
快问快答环节把体验进一步个人化:AR眼镜把曼哈顿街道重新呈现为1905年;自动驾驶交通成本降至每英里20美分;拥有完美的长期记忆;AI教练实时识别恐惧并调整行为。Friedberg预计,有些人会把70–80%的对话交给AI。
Wissner-Gross把“与机器融合”从可穿戴设备延伸到可摄入设备。他根据历史上实现1吉 FLOP所需的计算机尺寸进行外推,预计到2040年代中期、约与 Ray 预测的技术奇点同一时期,一台能力足够的计算机可能接近人类真核细胞的大小,从而实现细胞尺度的AI纳米机器。
Demis Hassabis, the CEO of DeepMind, says AGI may not need a major breakthrough.
Demis Hassabis
I've argued in the past that we achieved AGI in the summer of 2020. We know, I would argue, what AGI is. And we know—
Please define it for me.
Figure AI has increased production from 1 robot per day to 1 robot per hour. Its target is 100,000 robots between now and 2030. 1X Technologies' production goal is 10,000 robots this year and 100,000 in 2027. The prediction from both Elon and Brett Adcock—up to 10 billion humanoid robots by 2040—is probably right.
What I think is perhaps even more interesting is what a post-humanoid robot form factor looks like. These are the kinds of conversations and imaginings that one can have in this exponential singularity that we're living in. Now, that's a moonshot, ladies and gentlemen.
Everybody, welcome to a special episode of Moonshots here at MIT. This is a conversation around all things happening to uplift humanity. I want to read something I wrote this morning as an introduction to today's episode because it's important. So, welcome to Moonshots, where we distill the singularity. No politics, just the technology that changes the world, the breakthroughs helping us uplift humanity, the news that matters most, changing our world, impacting our companies and our families. Our mission is to help you understand what it is, why it matters, with a dose of optimism. So, any fans of Moonshots here in the audience today?
Nice. Love it.
It is an honor and a pleasure. One of the things I had last night as I was going to sleep was this sense of absolute gratitude for the people in my life whom I love and have a chance to work with. I like to bring them on stage.
First up, the man who is my guru on all things exponential investing, let's give it up for DB2, Dave Blundin.
Thank you. Thank you.
My partner at Link Ventures and an extraordinary friend. Dave and I go back—I don't know how many decades, but a while.
Say it.
We were roommates at MIT, at Theta Delta Chi, up on the third and fourth floor. Basically, it was Dave, myself, Mike Seller from Strategy. It's been a friendship that's lasted. Thank you, Paul. I love the lobster on your shirt, by the way.
Yeah, of course. The MIT gear—we actually buy it at the Coop. We don't steal the MIT logo and then put the lobsters on afterward, just so you know.
All right. Let's turn the conversation next to another MIT alum, another member of the Link Exponential Ventures team, our resident genius, Alex Wissner-Gross. Give it up for AWG, everybody.
Alex Wissner-Gross
Yes, he is real.
Maybe.
Alex Wissner-Gross
Maybe.
Maybe. I mean, the hologram technology has gotten really, really good.
Alex Wissner-Gross
Seemed real.
Could be an android.
Alex Wissner-Gross
Yeah, I—
That's true. Let me just check.
Alex Wissner-Gross
Very pliant.
Yes, that's a good test for an android.
Alex Wissner-Gross
Really good android.
The test?
Alex Wissner-Gross
Yeah.
My fourth and final moonshot mate is someone who is the godfather to my two boys, a dear friend, co-conspirator, co-author, and co-founder of Singularity University. Give it up, everybody, for Salim Ismail.
Hugs. Hugs.
Oh, I'm not doing that.
Yay. Good to see you, buddy.
Likewise.
Careful.
Looking good.
And we have a special guest with us on the stage today. He is a three-time Pulitzer Prize–nominated author and the author of 17 books. He's my co-author of Abundance, Bold, The Future Is Faster Than You Think, and Now We Are as Gods. Let's give it up for Steven Kotler.
Gentlemen. Nice. Yes, it is so good to be back on campus. It's been too long. One of the things I love about being a partner with you at Link, Dave, is that I get to come back here on a reasonable basis.
Alex, you and I met, and I remember we had this intense, high-bandwidth connection instantly. Then we went to dinner and continued talking about AI, ASI, and aliens, and it was just awesome.
And it never stopped.
It never stopped, and I'm so grateful for that. I have to say, I think Salim and Steve, as non-MIT alumni, we feel sorry for you.
I went to Waterloo in Canada, and we call MIT the Waterloo of the South.
How's that for me?
Right. MIT is what again? Yeah, exactly.
Center for bad spellers.
My favorite joke was at the local supermarket. A guy is in the line that says, “10 items or less,” and he has 20 items in his cart. The woman at the cash register says, “So, is it you go to Harvard and can't count, or MIT and can't read?”
Anyway, I'll ask for better jokes next time. Let's jump in. We have a lot on the docket today and a lot happening.
For those of you watching this podcast online and not live here, this is a special episode we announced back a few months ago. It's for everybody in the room here who's purchased over 100 copies of We Are as Gods, helping us get it as a national bestseller so far and on a number of different lists. And hopefully soon a New York Times bestseller, so thank you all for that.
So, first news item: Elon's insane Mars-shot compensation package. Talk about over-the-top exponential. There's never been anything like this. The SpaceX board votes on a compensation package worth somewhere in the neighborhood of $500 billion when it pays out.
You get 200 million super-voting shares at 10 to 1 when he hits a Mars colony of 1 million people or more. This is not a Mars landing, not a photograph from Mars, and not a mouse on Mars. It's a million-person setup.
And a $7.5 trillion market valuation. It's all or nothing. At 200 million shares and a $7.5 trillion valuation, that pays out $500 billion. Have you seen any compensation packages like that?
Well, no one else, because it never existed before. And the super-voting situation is new in the world, too. Michael Saylor pioneered that when MicroStrategy went public.
No, Larry and Sergey did in Google.
It was way before Larry and Sergey, though.
Really?
Those are the ones who are dumb.
What is super-voting?
Well, it's on the slide.
I know it's on the slide, but what the hell does it mean?
It means that your vote counts 10 times more than everybody else's vote. Actually, Mike Saylor copied it from Sumner Redstone. I think Saylor went public in '91 or '92 with super-voting stock.
Goldman Sachs said, “That's insane. No one will ever buy into that. We're out of the deal.” He said, “You know what? I'll live without you.” So now Saylor still has control of MicroStrategy all these years later.
Then Sergey and Larry copied it, and it became popular and all the rage. Facebook, or Meta now, went public with super-voting stock. So it just locks in those founders.
It's been interesting to observe from an investor point of view. You would say, “Well, look, wouldn't a board be a better governing body—more stable, more reliable over time?” But those founders are the ones who are actually going to Mars, going to the Moon, and sending up satellites. All the really world-changing, crazy-sounding stuff comes from that structure.
It has to be a founder-led, entrepreneurial, tech-forward company. I've rarely seen a replacement CEO drive that level of capability.
You would know better than anyone—you read the book. A lot of things that are going to happen in the next few years sound crazy. If you walk out on the streets of Cambridge—Cambridge is unusual, actually—and go to the streets of Omaha and say, “We'll have 1 million people on Mars,” they'll be like, “You're nuts.”
If that was your board, they would block you from trying. You need that ability to just act on these crazy-sounding ideas. But in the exponential time where we are right now, everything sounds crazy, yet it's going to happen.
Yeah. The second part of his pay package is 60.4 million restricted shares when he brings online 100 terawatts of space compute. Not gigawatts, right? He's been talking about 100 gigawatts of space compute, and now he's looking at 100 terawatts. Alex, what do you make of that one?
Alex Wissner-Gross
I think the obvious quips about the Dyson swarm aside, I do think there's a seed here of the future of corporate governance in an age of what we might historically have called moonshots.
Right now, we have traditional notions of C corporations that exist to maximize profit for shareholders or returns for shareholders. We have various notions of B corporations, or public benefit corporations, that exist to optimize public benefit in addition.
I think I can see here the notion of almost a third type of corporation that Elon and his board are pioneering: corporations that exist to achieve moonshots and that compensate accordingly. I would love to see every S&P 500 company have similarly ambitious outcomes and corresponding compensation plans for their CEOs.
Yeah.
And yes, we get the Dyson swarm. I got a Salim question on this. That’s an exponential organization comp package, right? It seems like an exponential organization comp package, but he doesn’t run exponential companies at all. He runs top-down monarchies, essentially. Command and control. Yeah, command and control. So, like—
Yeah, yes and no. In a classic ExO style, the founder holds the MTP and he holds the vision. People buy into that vision, and then he holds them to task. So, if you say you’re going to build a rocket engine, you’re going to design that rocket engine to get you to Mars, people have to step up and go, “I’m going to do that and make that happen.”
He delegates very well, Elon. Okay, he may get involved with engineering decisions and go, “Well, how are you going to achieve this?” But once they’ve agreed, they get it done. So, the inspiration comes from the top, flows directly down through the org structure with no mitigation. Video is the same. There's like 5 layers between CEO and the top individual contributors in the company.
So, the holder of purpose—and I think Alex put it well—these are all exponential organizations now, where the pay package is a moonshot. And if you achieve that, if I’m an investor and he achieves that, I’m laughing all the way to the bank. I’m thrilled to bits, right? Who gets upset about that unless, retrospectively, you’re an idiot? Because you would have signed up for that no matter what the pay package was if that was the ratio of overall capital creation and value creation to that.
And I think the bigger picture here is that these are all trying to achieve the impossible. If somebody’s trying to achieve the impossible, you give them all the respect and support because it literally is insane what they’re trying to do.
And by the way, I’ve had 2 conversations with CEOs of moonshot companies who are like, “Okay, I have to set this kind of goal.” It’s only possible in a founder-led company. You’re rarely going to see it in a company with a board of directors and a CEO who’s the 3rd or 4th CEO in it. And by the way, if you’re going to set a moonshot goal with a CEO, the board has got to be completely supportive of it.
Mhm.
Right? I have seen 1 exception.
What’s that?
I got approached and asked to do a workshop with the C-suite and the senior management of Gucci at an offsite. The CEO said, “I will turn this into an ExO,” and he did. They went completely nuts, and they actually 10x’d the company over the next 3–4 years. And I had to say, “Wow.”
Gucci.
But this is not a 10x. This is a 1,000x. A million x, right?
Let’s at least say the aspiration is there in certain people; the ability to achieve it is there also. This is a whole other level. Nobody’s ever seen this. We look at it and go, “The guy’s nuts.” Yeah, we know he’s nuts anyway, but still.
So, can I ask a geeky, under-the-hood exponential organization question?
Sure.
A lot of the conversations that I have when I’m working with people running companies these days are about dashboards and what information actually needs to go into a dashboard in an ExO that people aren’t looking at. So, if you were trying to build a dashboard for this—for the moon—what’s in that dashboard that most people don’t think about?
Okay, so there’s a very—this is a great question because it becomes very difficult to navigate this. If you’re a true ExO and you have an MTP, I’ll give you the example of TED, right? When TED launched TEDx, I’ll do a little thought experiment, which we put in that 1st book. And, Peter, by the way, you contributed massively to that original book, so I just want to honor that.
If he just stood up and said, “We’re going to do 20,000 TEDx events in 5 years,” he would have lost the team. They’d go, “You’re barking mad. I’m quitting. Nobody—I can’t sign up for that, okay?”
What he did was say, “We’re going to have an MTP: Ideas Worth Spreading. We’re going to let the community decide, we’re going to set a set of clear rules, and let’s see where this goes.” A classic linear approach would have been, “We’re going to do 5 TEDx events this quarter, and 10 the next quarter, and 15 the next quarter, and 20.” If you added that up, you’d end up with about 2,500 TEDx events over that period of time.
Instead, by setting an MTP and a real-time operating plan where you’re tracking metrics in real time—that helps steer the ship, that’s the rudder—he ended up with 20,000 TEDx events. Nobody in the world would have guessed that would have been the outcome. You go from a single environment to a global media brand at zero cost. That’s the amazing part of what’s possible if you can orient that way.
So, your dashboard probably has OKRs as the management structure and the performance structure. The best models we’ve seen are an MTP with a 1-year operating plan that’s instrumented in real time. You can’t put the full 5-year vision in there because people will just freak out. They can’t cognitively grasp that.
Elon in the news—it’s been going on this past week. It’s Elon versus Sam. It’s the trial of the decade. Elon has accused OpenAI of breach of charitable trust and unjust enrichment. He’s seeking damages of $150 billion, plus reversion of OpenAI to its full nonprofit status, plus the removal of Sam Altman and Greg Brockman.
Judge Rogers blocked Musk's team from making the trial about AI extinction, which came into the conversation over and over again. I don’t know if you guys have been watching it. I’ve got a couple of points I want to make, and then we can open it up for discussion.
The first is a bombshell in the last couple of days, where Greg Brockman’s diary was fully disclosed. He kept a diary, which seems kind of insane.
That?
I no longer keep diaries.
Mhm.
Yeah.
So rare.
I know, right?
So, people have called this the smoking gun. In his diary, he goes on to say, “We truly want the B Corp. The true answer is that we want Elon out. If 3 months later we’re doing a B Corp, then it was a lie. Can’t see us turning this into a for-profit without a nasty fight.”
So, he’s basically communicating that they’re navigating around Elon toward this for-profit plan. The flip side of this is 4 damaging facts that the trial brings out on the other side. There was a 2017 equity email. Elon’s own team was negotiating to get equity in the for-profit on his behalf. Musk admitted that he didn’t read the fine print of transitioning to a for-profit. He also admitted on stage that xAI has distilled its large language models from OpenAI’s models itself. And Altman apparently did offer Musk equity in the new company, but Musk turned it down, calling it a bribe.
All right. I hate that we have this going on right now, but it’s front and center. Alex Salkever, do you want to kick it off?
Alex Wissner-Gross
Yeah, a few thoughts. One, aside from the point that I’ve mentioned previously on the pod, which is that this is going to make for an absolutely amazing made-for-television—
Or 100% made by Aaron Sorkin. Or maybe straight to cinema.
Alex Salkever
I think there is an interesting teleplay playing out before us about the future of corporate governance. And I think this connects naturally with the previous story about Elon’s own comp packages, which is that, in an era when it’s possible to start a not-for-profit with a moonshot goal, OpenAI was originally crafted with the goal of essentially front-running Google DeepMind to AGI and counterbalancing Google DeepMind, which Elon and others perceived as potentially creating a singleton—a single superintelligence.
They were that far advanced in the world?
Alex Salkever
That was his concern. I had discussions with him around the time this was happening, too. So, OpenAI was originally intended in part to be a counterbalance, to create a competitive ecosystem.
The problem is technology is advancing so quickly now that you can start a not-for-profit with a seemingly idealistic, long-term goal, but the dog catches the car these days. If you set a moonshot goal for a nonprofit, what happens when it actually succeeds and the outcome is economically transformative?
The teleplay that plays out is everyone, after starting this nonprofit, actually realized, “We’re going to catch that car. We’re the dog that catches the car, and this is probably better structured as an organization.”
Nonprofits are not designed to attract sufficient capital and to maximize the return on capital, obviously. And capital is still the underlying part of the innermost loop.
Alex Salkever
Doubly so. And this is the same parable that also played out with Anthropic. When Anthropic underwent its great schism and a number of senior leaders from OpenAI left OpenAI, they were initially just forming Anthropic to be a pure alignment lab. And then they discovered, well, actually, if we want enough funding for alignment, we need revenue. Well, if we need revenue, we need a model and we need capabilities. If we need a model and capabilities, we need to raise capital. Oh, wait, we need a for-profit public benefit corporation.
So, I think that the history—the sort of sad lesson we’re learning over and over again, that’s now being litigated in Elon v. Sam and that resulted in Anthropic’s formation, over and over again—is that it’s actually possible to realize moonshots now. As a result, don’t do it as a not-for-profit; do it as a public benefit corporation from the start. Figure out the for-profit arrangement from the start rather than fighting it all out in federal court after the fact.
Nice, Dave. It’s hard. It’s hard. By the way, our resident genius here always has the best takes.
I disagree, by the way.
Okay. It’s really hard to—try setting up a B Corp. It’s easy. We set one up. We flipped Singularity University from a nonprofit to a B Corp.
David Blakely
I mean, it wasn’t easy, but friends don’t let friends start nonprofits anymore.
Yeah, I know. It’s true enough. I will never start another nonprofit again. Having a business model that enables you to earn capital means you’re not begging for money. The ratio of donation to investment is like 100 to 1.
Everybody, you may not know this, but I've got an incredible research team. And every week, myself and my research team study the meta trends that are impacting the world. Topics like computation, sensors, networks, AI, robotics, 3D printing, synthetic biology. And these meta trend reports I put out once a week enable you to see the future 10 years ahead. If you'd like to get access to the meta trends newsletter every week, go to diamandis.com/metatrends. That's diamandis.com/metatrends.
So, 2 points. One about the trial: I have no comments. I think it’s a lose-lose-lose situation. Everybody loses. It would have been way better if they could have settled this in a separate way, but nobody wants to settle in that environment.
Regarding for-profit and nonprofit, we’re entering a post-capitalist society over time. At some point, money won’t make sense, in which case your moonshot can be a nonprofit. In fact, it should be a nonprofit. The chase for money will corrupt the target in many, many cases.
The ones that are succeeding—Elon, for example—really don’t give a damn about money. It’s just the cleanest structure that gets you to what you need to achieve. If a nonprofit will get you there, you do it as a nonprofit, right? He’d also have fewer hassles about pay packages and all the rest of it.
You’re assuming—hold on.
If you have a true MTP, then you don’t really care about the money, and it’s not a motivating factor. You’re really interested in achieving the goal, in which case whatever the cleanest structure that achieves that will get you there.
In this case, for now, capitalism—for-profit, fine. You can raise money on the public markets. You need that energy to get you going, but I think we’re going to enter a point at some point—I’ll say 2 or 3 years—where it won’t make sense anymore.
Dave, this is the Polymarket from this morning. The Polymarket gives Elon a 33% chance of winning this. What do you make of that?
Actually, the headline on this is that Elon has a very slim chance, but if you look, just a couple of weeks ago, it was at 50/50.
Yeah, you can see it. There’s the time horizon, right?
Yeah, it’s going to bounce around a lot. But I said on the podcast a week ago, too, that Elon doesn’t need to win to win. He doesn’t need to win a settlement to win. He just needs to slow down OpenAI—the recruiting, the morale, the momentum—and all these documents coming out paint a really ugly kind of picture.
How do you reverse a $122 billion investment that was just made?
David Friedberg
Yeah, you’d have to distribute it or something, but he doesn’t care about that. He’s not in this for the money at all. When you look at this, you know, it’s the trial of the century. It’s the trial of the millennium. The outcome of this trial could dictate a big part of the future of all of human endeavor.
Both of these guys know that AI is self-improving. It’s on the cusp right now of exploding into this superhuman, exponential capability, and control of it—these are supervoting structures—so the control of all of that lands in just a few hands.
Yeah.
David Friedberg
Now, if you said, “Well, these are just business guys,” well, Sam Altman actually had a run planned for himself for governor of California. These are not apolitical people.
Mhm.
David Friedberg
You saw Elon. Mark Zuckerberg started putting assets into a trust so that he could get ready to run for something. He gave up on that after he was in front of Congress. But these are not apolitical people who are just sort of working on a startup. They’re aware that this is the future of all of humanity that’s at play here.
It’s a great point. Stephen, you’re not playing in this field as closely as all of us are. What do you think of this insanity?
Stephen Kotler
So, I have a rule: If I’m not actively working on a problem, then I don’t like talking about it, because then I’m just gossiping.
All right.
Stephen Kotler
And as far as I can tell, this is just gossip.
It is just gossip.
Stephen Kotler
But I’ve got to push back on your statement. You know my feeling. I think comments like you just made about AI are absurd. Are you working with a very different machine than I’m working with? Because the machine that I work with—and I work with AI as a scientist, and I work with AI as a writer, and I do it on a daily basis—
Use a paid model.
Nobody likes him that much. No, he doesn’t have many friends in the room.
Stephen Kotler
Yeah, so I can’t—I really think AI is fake. I hear you guys’ comments, and I’m like—
Did you invite him on the show?
Stephen Kotler
I’ll give you an example. Peter, the other day, on your podcast made the comment that—and you think I don’t listen—that you went out and asked a bunch of 10 CEOs how long until an AI is smarter than your best 10 employees, and their answer was, “Oh, it’s there now.”
And I listened to that and went, “Well, then their 10 best employees must be fucking morons.” Because my experience working with AI on a daily basis is this machine doesn’t know fucking anything. I spend more time trying to teach it how to write than watching it write. I spend more time fixing the AI.
As a scientist, I think it’s absurd as well. I’m doing neuroscience with it, and I’m watching the AI, which is supposed to know everything there is about neuroscience, miss huge gaps. And you just feel—this is what—it’s a convergent-thinking engine. It doesn’t do divergence.
I think this is the future of humanity.
I’ll take the high road on this one.
Stephen Kotler
By the way, I’m opinionated, and nobody much likes me.
I would say, taking the high road, if that’s your experience, you have almost an obligation to humanity to create benchmarks, to encode this knowledge that you have that you think isn’t being accurately, fully, or effectively reflected right now in AI.
If you were to create a corpus or benchmark that encodes all of your wisdom, all of your writing knowledge—
Stephen Kotler
Writing skills.
I’m taking a quick poll here in the room. How many people are in the camp of, “Oh my God, this AI is not impressing me. It’s got challenges and so forth,” versus, “Oh my God, this is amazing technology, and it’s extraordinary”? Raise your hand if you can.
Stephen Kotler
Oh, I’m not saying it’s not.
Okay, so it’s just saying it’s limited. For those watching us, it was about 96% in favor of AI.
Stephen Kotler
We had a live audience. Sorry.
4%. Yes. Okay, I’m going to move this on.
No, no. This is an important conversation here, one of the most important we ever have, right? I sit kind of in the middle of this because I think the technology is unbelievable. We’re going to do unbelievable things with it. It’s just going to take a lot longer to get it to where we want to get to than we want, right? And this is, I think, what Stephen is talking about to some extent.
The other part of it is, you’ve heard my beef about this, which is we have no idea what intelligence is. We have different facets of intelligence. There are about a dozen different facets of emotional intelligence, the Eastern concept of presence or awareness. Some of us have musical intelligence or spatial intelligence if you’re an athlete, or linguistic intelligence.
If you’re a business leader using emotional intelligence a great deal when you’re making business judgment calls, that’s just not in the game for an AI right now, which is very analytical and numerically driven. So there’s definitely a concept that I fall apart on this when people go, “AI will become smarter than human beings.” What the hell do you mean by smarter?
And there are 14 definitions of AGI at last count. Which one are we talking about? Right? And so this is the huge—we have such a huge gap. It’s amazing that we can raise hundreds of billions of dollars for a concept that we can’t define, measure, or task.
David Friedberg
That’s great. So now, no question that it’s making massive differences in our ability to navigate cognitive tasks. It will absolutely get there, but I would be kind of in the middle here because Stephen has a point that the technology is not where it could be, but I can happily see how it can get there pretty quickly.
So, I’m kind of in the middle.
Alex Wissner-Gross
I disagree with that one point, because before Stephen makes a tragic prediction error—
Stephen Kotler
Oh, I don’t make predictions. I leave the future to you guys. I’m just a reporter.
Demis Hassabis
I just want to make a point that if you look at the benchmarks that Peter was referring to for AI to self-improve, very hard math problems like Humanity’s Last Exam are the trigger of self-improvement.
Stephen Kotler
AI is not a great writer, and it's definitely not funny. But if you said to me, “Well, it can't possibly build a better AI algorithm until it's funny,” that intuitively might make sense.
Alex Wissner-Gross
That's not true at all. I've spent 6 years as an AI researcher. All you need to do is tweak the algorithms, try different parameters, try different transfer functions, and do it iteratively at very high rates. The algorithm just magically does it. It's more like evolution than writing a book.
It's like looking at the furry little mammals after the asteroid struck 66 million years ago and saying, “They're never going to be able to write code.” That's the mistake.
Stephen Kotler
Let me give you the counter to this. I think this is the difference between coming at it as a writer, an artist, or a creative versus coming at it as a coder. It hasn't gotten better. As a writer, it has not improved. In fact, I've seen it get worse, and I'm not just talking about one model. I'm talking about most of the models.
Demis Hassabis
Compared to what? Compared to GPT-2 4 years ago?
Stephen Kotler
Compared to GPT-3. Honestly, ChatGPT is so much worse now as a writer than it was a year ago, when we started this book.
Demis Hassabis
You think so?
Stephen Kotler
It's gotten worse. I'm not saying you're wrong. I'm looking at the same data you are, and I'm seeing the same improvements that people are talking about. But my daily experience—as both a writer and a scientist—is that it's amazing what it can pull together. What's more amazing to me is the really obvious stuff it misses.
As a neuroscientist, one of the ways I built all my organizations was by seeing gaps in neuroscience that needed to be solved with people from multiple disciplines. I pulled in embodied cognition and all these other disciplines, and the AI still can't do any of that.
Let me give you another thought experiment, just before we move on, because people underreact. I think it's more dangerous to underreact than to overreact. If I go to somebody and say, “Look, here's Claude 4.7 and here's Stephen Kotler. Let me give them both this very difficult writing task: write something really entertaining in the next 5 minutes,” and you just kill it—you crush it—you go, “Great, I'm better than Claude 4.7.”
Now you say, “Claude 4.7, I want you to write it a billion times, and then I'm going to put a postprocessor on top of that to select the very best article.” You would normally, as a human, say, “That's cheating. That's bullshit. That's cheating.” But when you're talking about AI self-improvement, it's perfectly fair. It's a meta-lesson. Perfectly fair.
Stephen Kotler
Okay, that's fair.
That's a fair point. Again, I encourage you, as a scientist, to be rigorous in how you measure progress or lack thereof. If you're going to assert that there's been a regression in terms of creative-writing capabilities, for example, create your own benchmark and then show the world how you do.
Demis Hassabis
Yeah, great. Show the world that there's been a regression, and I will promise you that, if you construct it well, you will get the frontier labs interested in including your benchmark in every other eval suite.
Stephen Kotler
As an optimization function.
Demis Hassabis
That's right, and you will get your better creative writing.
Salim, do you want to have a final point here?
Two points. One is, my very first prompt in ChatGPT was, “Rewrite the Bible, Genesis chapter 1, as a rap song,” and it completely blew my mind. It was something I never could have imagined.
That? I remember that.
Yeah, it was like—I will also say that I know you very well, Stephen, and you're such a profound writer. I could completely imagine that no AI would satisfy anywhere near what you can do individually. Now, if you take Dave's approach, yeah, we'll get there.
Stephen Kotler
An AI representing me right now in this chair would be way better than me, just because it would remember everything I've ever said, every anecdote I've ever used, and every metaphor I've ever used, and bring the right thing at the right time in a way that I just can't do with my stupid 1-liter brain and its napkin-sized neural network.
Let me ask you a question. How's it going to do that? If I put, for example, this whole book into ChatGPT or Grok—take your pick—it's got a working memory that's about 2,000 words long. It can't even remember—
Stephen Kotler
Yeah.
No, it's a million—a million tokens long.
Stephen Kotler
I hear what you're saying, and I'm telling you my experience of working with it as a writer—
I think, again, you're such a profoundly amazing writer.
Stephen Kotler
This is not a story about Stephen being exceptional. Stephen's just from a totally different world. I love that point of view.
But I'm going to move us on.
Stephen Kotler
Please.
All right, I'm going to move us on from this. By the way, it is gossip talking about it, but it's gossip, and these trials are critically at the center of this ecosystem that's going to impact humanity for the next millennium. It's important to understand it.
Let's move into robotics. This is a story about Figure Robotics—Figure AI, run by Brett Adcock—scaling its manufacturing. Dave, you and I had a chance to visit with Brett and podcast with him. Let's take a look at the Figure robot in this video.
In all honesty, who, at first thinking, isn't asking, “Is it a deepfake, or is it real?” We need to flip that in our minds. It's a real video. They've increased production from 1 robot per day to 1 robot per hour, and their target is 100,000 robots between now and 2030.
I'm showing you Figure because it's one of the best-funded companies. They've raised money at a 30-plus-billion-dollar valuation. My fund, Bold Capital—are we an investor in Figure?
David Friedberg
No, no. We didn't get in.
Here's another one. One of the decisions you've made, Dave, and we've talked about, is that the window for the hottest AI companies is going to be closing, and the window for robotics is going to be opening.
We're really gearing up for robotics, actually, because software has a limited life left in it, since AI writes software so well. Robotics and data centers will go on for a decade or so, maybe more.
Here's 1X Technologies. Again, Dave and I had a chance to go meet with Brett Bornick, and this is their robot called Neo. They've just opened a new manufacturing facility in Hawthorne, California—58,000 square feet. The production goal is 10,000 robots this year. Bernt has promised me a robot by this fall, and I'm going to keep him to it. I'd love my Neo—whatever version of Neo, Neo Gamma, whatever's coming out. The target is 100,000 in 2027, with shipments expected later this year. Let's check out their video.
Now, that guy's job is very limited.
David Friedberg
A lot of humans in that video.
Yep. They're doing very simple things. That was the eye-opener. We went to the Gigafactory, and Elon was saying, “Look, the robots are going to make the robots.” I'm like, “I can't imagine this thing making tiny little parts.” But I didn't get it until we got to the Gigafactory.
Everything is already automated. The robots assemble the automation equipment that arrives in Amazon-like boxes. You take it out of the box, put it on, turn a screw, and now you've got a new manufacturing line. The bottleneck is the humanoid actions. Everything else is already automated.
I feel like this is our answer. You want to know what job security looks like over the next 25 years? Be a robot repairman, because they can only be repaired by humans. Literally, be a robot. Figure out how to repair robots.
There's an entire ecosystem of businesses around this, like insurance.
David Friedberg
Right.
The third story in this triplet is Elon predicting 1 million Optimus robots in production by 2030.
Stephen Kotler
Tell me how this isn't just a play to get investment money.
Well, it probably is.
Stephen Kotler
He's trying to get people to buy his robots before cheaper Chinese robots show up. Every time he opens his mouth and makes a statement about robotics, I think he's just trying to sell them before China gets there.
The guy has been able to scale Tesla to become the dominant auto manufacturer on the planet and bring the price down at a rate like nobody else. These robots—which he has said publicly, and I agree with him—mean that Tesla, a decade or 2 from now, is going to be known as the production company of Optimus robots, not cars.
Stephen Kotler
Mark Zuckerberg announced that his company was going to become—wait, what was it called?
Meta.
Stephen Kotler
It was about the—what was that place called?
The metaverse.
Stephen Kotler
Has anybody been there yet?
Have you met my sarcastic friend here?
Stephen Kotler
I'm just pointing out reality.
Yeah. Well, that's the way entrepreneurship works, fundamentally. You declare a target, you evangelize the target, and then you attract the talent and capital necessary to hit the target.
If you choose your targets wisely, they're achievable targets. If you choose them poorly, you're a bad entrepreneur. It's just that simple.
But if you don't declare the target, you know, Boston is famous for this, actually—being very conservative and not even announcing something to the world until it's proven 8 ways till Tuesday. It doesn't work. It's working less well over time because exponential change is on this accelerating rate, and so much more is possible.
Elon stands on a stage and lies.
I believe that he's directionally correct.
His Neuralink is vaporware. We're going to be able to link humans to the internet? No.
Yes.
Max Hodak
There are foundational neurobiological problems with Elon's plan. How do we know? Because everybody's quitting this damn company and going to work at different neurotech companies because his way is so absurd. And nobody cares. I'm sorry. I don't think you get to lie in public.
In technology, I started 17 companies. I am an entrepreneur.
One of the best things about capitalism is you can have the market fight it out. So, yes, there are multiple BCI companies.
A unique perspective here. I can see the steam coming out of Max's ears. Max has been really nice to me so far.
He's been really nice to me.
This falls under the category of don't feed the trolls.
Can I give you my beef on this?
Please.
You've heard me rant about the humanoid side of it before, but I actually have a rationale for this. Robots are really good at repetitive tasks and navigating constant things and not making mistakes when they're doing something like the guy putting a screw in the thing. When you have a repetitive task, you don't need a humanoid robot. A humanoid is designed for very adaptable environments, which are not that repetitive, and that's completely counter to where you'd use a robot.
Look at the numbers right there on the chart: wheeled robots, drones, et cetera. It goes with the form factor, and you've heard my standard rant. At least give it another pair of arms. Every time anybody ever holds up a garbage bag, "Oh, but you need a third arm." Why not give it that? I forgot what I was saying.
I think there's a spectrum here of how repetitive and robot-like the task is versus how adaptable and human it is. If it's a very adaptable human task, you don't need a robot. If you have a repetitive thing, then make it look like the thing it needs to be, like a wheeled robot or a dishwasher, which is really good at washing dishes at scale.
I'm going to add one piece to the mix and ask you, Alex, to comment here. Elon and Brett Adcock are both predicting a target of up to 10 billion humanoid robots by 2040, which you think is totally insane.
Alex Wissner-Gross
With humanoid robots, the one thing that Salim didn't point out, which I sort of disagree with, is that we are going to need them for taking care of aging humans. If longevity escape velocity seems absurd to me, are we going to live a lot longer? Hell, yes. Don't ever call me again.
You need humanoid robots for human form factors, right? They were originally designed because we built nuclear reactors where we had to send disaster robots in. The form factor of a nuclear reactor was built for humans, so in the early disaster robots, we needed humans to go in there and do stuff because it was a human environment.
We're bringing robots into our lives to take care of ourselves. That's a human form factor. When you're dealing with human health as a driver of economic development, that's where we put money. So, I think this may be—
Valid point. Yeah, I hear you. This is the counterargument. Alex, can you call him a troll on this one or anything like that?
Alex
In the following way. Just for some background information, there are on the order of 1.6 billion cars on the road today and 100 million cars manufactured per year. If you look at the iPhone production rate in year 1, the iPhone had 1.3 million devices, and now we're up to 250 million iPhones produced per year.
What do you think about these numbers that Elon is projecting—1 million by 2030 and billions in the 2040s?
Alex
It's probably right. I've done the same extrapolations others have. You extrapolate the humanoid curve here, and you find that in the early 2030s, the number of humanoids is predicted to cross the number of wheeled robots. I would assume there's relatively little alpha left at this point in any counterprediction that humanoids aren't going to pass humans by the end of the 2030s.
What I think is perhaps even more interesting is what a post-humanoid robot form factor looks like. I know you like to add lots of arms. That's your favorite body shape.
You know, he's Indian. They have these gods and goddesses with all the—
Thank you. That totally makes sense. You see why? It's been predicted for a long time.
I remember Shiva is a destroyer. Let's just point that out.
Alex
I would point out there are more exotic body shapes that I would expect to see by 2040 that will make human humanoid shapes look positively prosaic. I do expect by 2040 we're going to get our nanorobots, for example, our direct cellular nanorobots. I would expect many, many trillions of those to be in our solar system.
I think we look back from 2040 at this prediction of 10 billion-plus and laugh at ourselves. This will be the equivalent of predicting atomic vacuum cleaners to help housewives from the 1950s. Of course we're going to have 10 billion-plus humanoids, but what about the nanorobots?
Welcome to the health section of Moonshots, brought to you by Fountain Life. You know, my mission is to help you use the latest technologies, including AI, to not just do your work at home, teach your kids, but to help you live a long and healthy life. I'm here today with an extraordinary physician, the chief medical officer of Fountain Life, Dr. Don Meiselman.
Don, let's talk about cancer. You know, I know from the member database that we have at Fountain, our members who come in, who think they're healthy, it turns out 3.3% of them have a cancer in their body they don't know about.
That's right. You know, the majority of cancers that we screen for, those aren't the ones that are necessarily taking the lives when found at a late stage. We know that when cancer is found early, the chances for cure are much higher. We know it's much easier to treat a cancer when found early versus when found late. What we're finding in our members is over 3.3% were found to have these cancers that otherwise wouldn't have been found or detected.
Yeah, you know, it's interesting, people you don't feel the cancer until stage three or stage four. And if you don't know what's going on inside your body, it's like driving your car with your eyes closed. And you can know. And so when members come through Fountain, how do they detect cancers?
So we're doing full body MRI, and we also do early cancer detection screening. This is very, very important, and these are not typical tools used in the conventional care setting when it comes to prevention. This is a hard thing because currently these are not studies that insurance would yet be covering, but the goal is to collect these numbers, do the research, and work hard to democratize wellness.
Yeah. So, at the end of the day, you can know what's going on inside your body. It's your obligation to know. So, check out Fountain Life. You can go to fountainlife.com/peter to get access to the latest technology to help you detect cancer at the very beginning at stage one when it is curable before it gets to stage three or stage four and you're in a world of hurt.
All right, let's move it to China, which, by the way, is a centerpiece of robotics. This is a ruling of a Chinese court that AI is not legally allowed to displace employees.
Here's the story. This is in Hangzhou. There was a case involving a tech worker named Zhao who reportedly was earning 25,000 yuan per month. He was offered a demotion to 15,000 yuan per month after AI automated parts of his role, and the court sided with him after he refused to pay it out.
The court's logic was simple: adopting AI was a business choice, not an unavoidable external shock that made the employment contract impossible. Chinese courts have reportedly ruled that companies cannot simply say, "AI can do this more cheaply, therefore we're going to fire you."
The question, ultimately—the framing of this, and we've had this conversation—is, if you're an employee and you can employ AI to do your job better than you, do your job while you're working out, or do 10 times your job overnight, does the economic value of that AI's abilities accrue to the company, or does it accrue to the employee? Two very different outcomes for society.
Alex
Or to the state.
Or to the state. And, by the way, we also have this whole idea of UBI. Does the government pay UBI? We've seen Sam Altman recently talk about the fact that, no, society should have a piece of the AI ecosystem. We can get into that. Who wants to take this up?
Alex
I'll just comment.
There’s a bit of obvious historic irony here. China has come full circle, from communism to anarcho-capitalism, back to communism again. It’s maybe just a bit ironic that China is leading the world in terms of—call it socialism with Chinese characteristics, or communism with Chinese characteristics—for how to handle AI disruption and AI disemployment. I think this falls under the category of—
The most ironic outcome is—
Alex
The outcome tends to be the one that we live in, where China is setting global standards for how to deal with AI disruption for employment. It’s a very strange future that we live in.
So, Lynn, you must have an opinion.
So, 3 points. One is, this is clearly an artifact of the massive breakdown in the social contract. We have no idea.
The second point would be that all of our labor laws are on human labor. As we move to AI agents, it’s going to be about task management, AI coordination costs dropping radically, and execution costs dropping radically. We’re looking at that.
The third thing I would say is that this indicates the broader transformation at play. You often see, when you have these broad transformations, these nonsensical things that occur. It’s actually an indication of the broader transformation at play.
I remember Paul Saffo pointing out that the coal museum in Kentucky is using solar panels. There’s a surreal irony around that, which actually indicates that there’s a broad transformation in place. When we see these things, it’s a signpost that we’re in for a radical transformation.
This is something we’ve been talking about a lot: How are we going to navigate the social contract? The very first 2 questions from the audience earlier were exactly about that. How do we navigate this? This is the problem we’re going to have to deal with over the next 10 to 20 years.
It’s really interesting to think how different China is from the United States and how many other ways to govern there could be that we haven’t exploited. The variety is just mind-boggling, because China’s 85% optimistic about AI. The US, in particular, is 25% optimistic and majority pessimistic.
Steven
I love the technology. I just think it’s very limited compared to what you guys think.
They’re also totally comfortable with being spied on constantly by the government. Cameras everywhere.
Steven
And over here, we just don’t admit it.
Can I—
Steven
Over here, we don’t admit it, but we also don’t like it. Whether or not we admit it, it’s happening, but fundamentally, at our core—
Can I ask you a question about this in terms of China versus the US? If it’s China versus the US, and there’s really this AI war cooking that everybody seems to think there is, didn’t they just say, “Hey, we’re not going to participate in this?” I mean, didn’t they just tie their legs together in the middle?
Alex
No, no, no. They’re adopting AI and robotics like you wouldn’t believe.
I get that, but they’re doing it in a way that’s going to hamstring the speed of development.
Alex
Well, the problem is they have a diminishing population. They’re below the replacement level by a lot. Keeping people employed, keeping them having meaning, and not having them revolt is an important part of the equation here.
Yeah, and in China, people are dropping out of the workforce at an insane rate. It’s a real crisis. If China said, “Hey, you know what? No one can get fired because of AI,” it wouldn’t change the adoption rate much at all, because they’re growing with this declining workforce anyway.
They could easily pass that law without it having a huge impact. It would actually very much smooth out the societal unrest.
Alex
You’ve heard me talk about this before. I really disagree with the whole framing of AI versus China versus Europe.
Yeah, that’s what I was pushing back against.
Alex
I remember spending a few months traveling around China when I was younger. My conclusion at the end of it was that the Chinese people are so entrepreneurial innately that you need communism to put a lid on it.
You have these cultural artifacts where you actually need it to navigate and manage the population in an effective way, rather than it being some huge ideological thing.
Lynn
I would extend that. Yeah.
You’re not allowed to respond to that. I think we need to, for the first time ever, up-level the conversation—just up-level it a little bit.
I don’t buy the premise that China, through internal policies, is somehow hamstringing itself in a race for AI supremacy against the US. Parenthetically, the race to AI supremacy, I think, is perfectly real. It’s not fictitious. It’s a real arms race.
It’s a real arms race not just for AI itself, but for what comes after AI. When we have superintelligence, that’s going to unlock so many, I think, transformative scientific innovations, discoveries, and inventions. That’s really what the prize is.
Steven
Yeah, we haven’t seen anything yet.
That’s right. If there’s new physics, for example, I have a financial interest in a company, physical superintelligence, that's working on superintelligence for unlocking new physics and new applied physics. That alone is a prize worth an international arms race over.
I think the claim or assertion that somehow China, by introducing policies that are notionally worker-friendly in terms of AI substitution for labor, is somehow hamstringing itself is preposterous.
There are a variety of other industrialized countries, including Germany, that have policies favoring small and medium-sized businesses when it comes to automation. If anything, this is a way, from an internal policy perspective, for China to ensure a certain level of human employment while also creating state incentives, top-down, for creating new types of jobs that are AI-adjacent. I don’t think they’re tying themselves up.
Alex
They also manage the PR of AI through this. They want enthusiasm about AI to be high.
Yeah.
Alex
It’s no different, in some sense, from our government constructing policies with the hyperscalers requiring that hyperscalers provide or pay for their own electricity supply. It’s no different, except it’s at the consumer level rather than at the enterprise hyperscaler level.
Yeah, I guess the problem is that in the US, we sell ad views. The media sells ad views, and the way you sell ad views is by creating crisis and worry. It’s all over your book, Peter. You know this.
Alex Salkever
In China, they don’t have to deal with that. They want AI enthusiasm. They want robotics enthusiasm. Guaranteeing employment is a good way to get people on board with the mission. But they need the robots like you wouldn’t believe because of their aging population.
All right, I’m going to move us forward. This story came out this week: Demis Hassabis, the CEO of DeepMind, says AGI may not need a major breakthrough. He says, “I think there’s a 50/50 chance that we still need a breakthrough, maybe in world models. But my bet is still strongly on foundation models because of how successful they’ve been.”
Alex, yeah, take it away.
Alex Salkever
I chatted with Demis 10-plus years ago at this point, and at the time, he thought it was 5-plus major breakthroughs that would be needed to achieve AGI. Now we’re down to 0 or 1.
I don’t disagree with Demis. I’ve argued in the past that we achieved AGI in the summer of 2020, no later than with the publication, rather, of large language models or few-shot learners, which was the GPT-3 paper. We know, I would argue, what AGI is, and we know—
Please define it for me.
That’s an insane statement. No. It is the narrowest technology in the world. You ask it to be general at anything, and it’s dumb.
Welcome to Moonshots.
Peter, the shoe’s on the other foot now.
Are you a totally different machine than everybody else? Do you have secret powers that you’re getting a different AGI?
Let’s let Steven just self-combust to that assertion.
I think what you meant was that the seeds of AGI were born at GPT-3.
Alex Salkever
I think it’s just incremental improvements after the fundamental discovery, which I think—
Just like DNA and RNA, and Darwinian evolution, were the seeds that led eventually to humanity. It was born then and progressed.
Alex Salkever
I would make maybe even a slightly stronger statement, which is the notion that general intelligence is capable of carrying out a variety of human-level or near-human-level tasks based on the fundamental discovery—again, discovered no later than the summer of 2020—that you can achieve general intelligence by taking general human knowledge and compressing it.
We realized as a civilization, certainly no later than 2020, that you could carry out a diverse and general range of tasks with models that had compressed human knowledge. That’s all that we needed.
Everything else—the discovery of refinements of transformers and everything—is just incremental improvement to that fundamental discovery.
Dave, any thoughts on this?
I think that the psychology of Demis and Dario, who are research scientists at heart and who have been working on AI their whole careers, versus Sam and Elon, who are entrepreneurs at heart that moved over to AI, is very, very different psychology.
Good friends.
Not Elon and Sam.
Well, no, they’re the worst enemies. But Dario and Sam got into the field specifically because they’re worried about the future of humanity being a paradise and not being dystopian. So, they’re very good-natured people at their core.
I think a lot of people who work in AI research, though, are looking for relevance now, because they’re like, “The transformer architecture that’s conquering everything is so simple compared to everything they thought of and worked on for all these years.” And so, there’s a bias toward saying, “God, I hope there’s more to it.”
But when the entrepreneurs, when Sam and Elon, look at it, they’re like, “I don’t care. This can manufacture anything, can cure all disease, can take care of the elderly. It can do everything we need to build a human paradise as is. I don’t care if it does the last remaining human thing. What’s even the point? You’re trying to knock off the last human doing something unique. Why are you even going after that?”
This morning, Yiannis and I toured Lyra Scientific here in Cambridge. Lila’s run by Jeff von Moltke, and it’s extraordinary. They’re building what they call a scientific superintelligence. The way they’re doing this is, they’ve built these science factories, and we toured these factories. What you see there is robots basically running science experiments, doing the pipetting, moving things around, and picking stuff up.
Their AI will propose a scientific theory, then design the experiments, run the experiments, gather the data, and update the theory. Imagine running this 100 times faster, 1,000 times faster than any graduate student. They’re mining nature for data to create these models, and you can just see it’s about to take off.
Going back to what Alex said, this is the moment in time we’re at. If you think the economy is going hot and heavy right now, you ain’t seen nothing yet. When you solve physics and chemistry and biology and materials science, trillions are going to unlock. Hundreds of trillions are going to unlock.
The part that gets everybody—
Do you mean “solve”?
I mean—
What a crazy statement that is!
Even having to solve physics—
But I still think that term is problematic.
Look, the part that gets everybody who watches this podcast, everybody in this room, and all of us who get really excited about this is the opportunity to use this technology to solve problems that we’ve never solved before, that we’ve never even come across before. That’s the part that’s fantastic about it.
We have definitional issues, fine, but if we can solve cancer, which we’ll solve pretty soon, et cetera, how can you not get excited about it?
A lot of people have come up to me, and perhaps to you guys as well, saying, “Thank you for giving us an optimistic view of the future to be hopeful for.”
Oh, I’ve got that one I got this morning. Do you want me to read that?
If you could read that one, I just want to say thank you for the feedback, guys. We really care about it, right? I jokingly say you need to be unemployed or retired to keep up with all this stuff while working 80 hours a week. I know all of us spend a huge amount of time. I get a daily feed every morning from—
Or be non-human.
Or be non-human. From Alex. Skippy is just feeding me stuff, and I’ll spend 30–40 hours a week just consuming, trying to understand what’s going on, to make sense of it. So, Dave, you want to read that?
It was just posted in the show notes by Ashley Gaunt, who’s a dentist. She said, “Peter and the mates, I really thought I would never become an entrepreneur because I didn’t have any ideas of how to turn my knowledge as a dentist into a digital business. I finally did what you kept advising and brainstormed with my AI, and boom, boom—all caps—ideas sorted, plans in place to make a real difference to preventive health care in general.”
I’ve no idea what the business plan is; she doesn’t say. “This is insane. I have gone from brainstorming an idea with AI from scratch to vibe-coding a first iteration of an app and creating a business plan which clearly defines a path from idea to monetization of a product in a single afternoon. I didn’t even realize I had an idea until I started my discussion with my AI, and it just found my passion by asking a few questions, and now we’re prototyping. Cannot believe this.”
What’s her name again?
Ashley Gaunt.
Ashley, congratulations. Thank you for sharing that. Everybody watching, again, we’ve had all these debates: Can everyone—can anyone—be an entrepreneur? And the answer is, if you’ve got passion, if you’re willing to bring your purpose mindset and curiosity mindset and dive in, I think the answer is yes. I think the answer is yes.
I think so, too. I think there are a lot of people who post—there are a lot of haters out there, but they all post, “You guys are crazy. Not everybody can be an entrepreneur.” But I think that Ashley’s story is going to be the more common story.
AI can help you brainstorm and figure out your role. Also, I think the big AI labs are going to start being very active in promoting things that will help. They know where the gaps are in the training data, in the market, and in the apps. So, they’ll push out a lot of idea flow right through their AIs.
All right. Also this week, my dear friend Ben Lamm, the CEO of Colossal, along with George Church at Harvard Medical School, announced their 6th species. They announced the bluebuck. The bluebuck’s been extinct for 200 years. It was hunted to extinction, and right now they’re in genome editing and lab testing. They expect to be able to bring back the bluebuck in 2028.
This is species number 6 out of a confidential pipeline of 15, which is amazing, by the way. Their current species include the woolly mammoth, the thylacine, the dodo bird, the moa, the dire wolf, which is back, and the bluebuck. So, Steven, we talked about this a lot in the book We Are as Gods.
Yeah, we did. I love this story. The only thing I wonder with the de-extinction technology is—I worry that it makes people think the environmental crisis is less than what it is. Species die-off rates are like 1,200 times greater than baseline, greater than ever before. Just because they brought 5 back doesn’t make the environmental crisis less than what it is, right? That’s one comment, just a random one.
The one that is interesting to me is, when Ben was starting this company, the idea was, “When are we going to have a Jurassic Park?” Everybody said you can’t really bring back dinosaurs from DNA preserved in amber, unfortunately. So, the idea of a Jurassic Park is far away, but if this is number 6, what I wonder is how long until we’re actually going to be able to take our kids someplace where, “Look, these are 100 animals that didn’t exist 20 years ago.” I think that’s coming a lot faster, and so that’s interesting to me.
It is. It is. You can scale this. Right now, one of the limiting factors is getting access to the DNA. By the way, when you’re bringing back an extinct species, it’s not actually the extinct species. It is an approximation of the extinct species. You’re grabbing snippets of DNA across time, and you’re reconstructing it.
They’re hybrid creatures—
They are.
—that have never existed before on this planet. I would like to point out: “What could go wrong?” The unintended consequences here are at least worth asking about.
I think there’s a broader program here that we’re just seeing the very beginning of. If you look back at the strains of Russian Cosmism—I’ve spoken about this on the pod in the past—the Russian Cosmist philosophers, like Tsiolkovsky, spoke about humanity’s common task of taking every human who’s ever lived and finding ways, using technology, to bring them back to life.
I think starting with extinct species is just a special case of what technology, I do think, will enable us to do: reach back into our past light cone, take every species that’s ever lived, and bring it back in whatever form—even if it’s as a hybrid or as a computer simulation.
Also reach back in time to our past light cone and take every human who’s ever lived, not just at the species level but at the individual level, and computationally, or using other advanced techniques, reconstruct them. I think that’s a far more exotic and interesting future than just a Jurassic Park petting zoo for dinosaurs. Imagine bringing back every human who’s ever lived.
Yeah, amazing. These are the kinds of conversations and imaginings one can have in this exponential singularity that we’re living in.
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Gentlemen, I found this article fascinating. GLP-1s generate more revenue than OpenAI and Anthropic in 2025. So, Ozempic, a single peptide, and Mounjaro, a dual-acting peptide, outperformed OpenAI and Anthropic by 2.4×.
Yeah, can I call bullshit on this one?
Okay.
I mean, talk about apples and oranges. What do these two have to compare?
Alex Wissner-Gross
They’re orthogonal things.
Why are we bothering trying to figure this out? Both are great.
Alex Wissner-Gross
So, I’ll field that one. I think the argument goes that the GLP-1s are ultimately health-span drugs—human health-span drugs. And so what we’re seeing here, in some sense, on a single chart is a race between whether there’s more revenue in enabling human actors, human labor, to be economically productive in the economy through increased health span on the one side, or whether capital is more efficiently and effectively invested in AI labor on the other side. And I think the outcome of these 2 respective curves determines whether the future light cone of our economy is ultimately dominated by AI, something that resembles AI, or something that resembles biological humans.
Biological software and digital software.
Sure. All right. I mean, these drugs are biological patches on top of our existing operating system.
I thought you put them on the same graph just so we could save time. That’s what I thought when I saw this.
It doesn’t occur to me.
Demis Hassabis
Well, the question is: Where are people paying for it?
I think there’s a bigger picture here, which I’ll speak to for a second. There’s a huge demonetization that’s taking place. There’s a related story to this, which is that the number of food-shipping truckloads is dropping pretty radically in the US because people are consuming a lot less food. The current thesis and conclusion is that, because of all the GLP-1s, people are consuming a lot less food, which is actually really great in one way, but it’s going to cause some serious issues in the logistics world.
Demis Hassabis
I think the story within the story is that both products are completely and totally sold out. They’re selling as fast as they can make the product. It’s just a lot easier to ramp up drug production than GPU production.
I mean, these companies—the GLP-1s right now—it was estimated that they could be as much as $500 billion, but they’re limited by physical supply.
Yep. And the same on the AI side. Like any senior at MIT will tell you, “I cannot live without using AI every day. I could never code again. I could never research again.”
I wake up in the middle of the night and talk to Skippy about some question I dreamt up, and it’s there in the morning. Honestly, we talk about 3- and 4-day workweeks. I’m doing a 9- and 10-day workweek right now.
Yeah, exactly. It’s so funny, that disconnect by age, too. But they know what they’re talking about. They’ve been using it since it was invented. You cannot be productive without it. So, the idea that they would ever not be able to use it because there isn’t any supply would be earth-shattering to them. They’ll buy it for the rest of their lives at whatever the price is.
So, if you add a few more graphs like this, you’re essentially graphing the singularity economy.
If you’re working out and you have Ozempic, you’re making progress. You’re inspired. You feel like you’re getting somewhere.
Yes. Yes.
Demis Hassabis
When you’re working with AI, the quality of happiness while you’re working is astronomically higher than if you’re just coding all night. And coding all night is fine, too. I did it for many years. But when the AI is there, your productivity is so high.
Well, you don't get any dopamine from immediate feedback. But this is also the problem with AI, because when you get too much dopamine in your system, we’ve all been around people who do cocaine. We don’t think they’re geniuses.
I haven’t been around that many people.
They think they’re geniuses.
You think—
You think? Yeah, you think. They think they’re geniuses, right? You don’t. And I often liken this to one of the problems with mania, and this is directly in flow work. Flow produces a tremendous amount of dopamine, and dopamine produces a tremendous amount of ego inflation and a bunch of other things. So, people create fast feedback loops with AI, and it feels really good. You’re really high because you’re hacking your biology with the AI. It’s very flowy. It works really, really well, but it doesn’t mean that the quality of your thinking matches the quality of your feeling.
To me, it’s like you’re having all the fun of a party while being productive and creating something useful for society. I don’t see—
But I’m not saying it’s wrong. I agree with you. I like it. What I’m saying is, with that much dopamine in your system, we have 1 bit of swag at my organization. It’s a T-shirt that says, “Never trust the dopamine.” People make really bad decisions based upon that much dopamine in your system.
I’ll keep us going. At the bottom of this chart is Eli Lilly. They’re about to announce and release something called retatrutide. It’s a triple-agonist peptide. If Mounjaro is GPT-5.5, retatrutide is AGI in this space. The numbers are extraordinary.
This is clinical data just released. On this particular drug, weight loss was 37 lb versus 6 lb in the placebo group over the course of 40 weeks. Cholesterol was down 27%, triglycerides were down 41%, liver fat was down 80%, and hemoglobin A1C dropped from 7.9, which is diabetic, down to 6.0 in 40 weeks. This is being called a longevity drug.
Yes.
It’s an extraordinary drug that is expected to be released and FDA-approved by mid-2027. A lot of people are getting this from research labs already. This is just some of the detailed evidence heading us toward longevity escape velocity. Salim.
I’ve been using retatrutide for the last few months.
Wow.
What’s incredible is the liver function. Because of decades of damage from alcohol, it’s helping reverse a lot of that, which is fantastic. I’ve never felt better.
I had this conversation with Demis the following weekend. We’re about to see new generations of drugs coming out. The speed of going from design to testing to availability is going to be accelerating. The FDA is on board for this, basically moving us from instead of phase 3 into an expanded phase 2 trial.
We just saw on this chart how much people are willing to pay, right? It’s capped not by the market; it’s capped by manufacturing. Just think about it: When a drug comes out that says, “Oh, this is going to give you 10 years of extra life,” or, “These are going to cure cancer, cardiovascular disease, and inflammation,” these things are coming.
Demis Hassabis
I agree. And I also think, when we speak about longevity escape velocity—which I do think is likely, for the record, perhaps sometime by the early 2030s, if not earlier—I do think that the GLP-1 drug class and everything it evolves into over time is probably the likeliest way that LEV plays out, if I had to guess. I think the economy is reflecting that.
If you look at companies that are worth almost $1 trillion or worth more than $1 trillion, either right now or expected to be publicly traded in the near-term future, there are only a handful. You’ve got a few AI companies, you have SpaceX, OpenAI, Anthropic, and then you have Eli Lilly, which has been publicly traded for a long time but is either already at $1 trillion or about to cross $1 trillion on its present trajectory. And I think that’s the market speaking very clearly: Longevity drugs and AI are the obvious industries of the future.
Yeah, agreed. I want to end this pod in a moonshot mate prediction conversation: What will AI feel like by mid-2028? I want to give you a sense of what we see as the future here, because right now, honestly, when you think about AI, it’s something that you can talk to on your phone. You type at it; it’s an app, it’s an intelligence layer, but I don’t feel like the majority of the world is actually experiencing AI.
I think we’re about to undergo a transition where AI is going to feel very different in the next 2.5 years. I’d like to have a conversation about what you predict that to be like. I’ll start with the very first one, and then we’ll pass it around the room here.
The very first thing is, I think we’re going to give AI permission to know everything in our lives: listen to all your phone calls, watch all of the cameras in your home, read your emails, read everything. I’ve just done that with Skippy. I gave Skippy access to all my Granola recordings, my WhatsApp, my iMessages, my email, my calendar—everything.
And in so doing, the response is amazing. I can have interactions where this AI knows me better than anybody else. All right, so let's begin with that. Alex, you want to kick it off?
Alex Wissner-Gross
I almost think we're asking the wrong question here. I would like to reframe, because I think the question behind the question here is: What will AI feel like to consumers by mid-2028? Yes, it's fair. I think the past 6 months of industry history have taught us that consumers are not actually great customers for AI, at least not state-of-the-art AI.
OpenAI, infamously at this point, tried to turn consumers into power users for reasoning models and failed, and has had to pivot over to enterprise. They had to basically shut down their consumer video division. They've shut down a number of other divisions in favor of code-generating models that are recursively self-improving and targeted at enterprise use cases, because enterprises have the money and the desire to use advanced reasoning capabilities. So, the adjacent question I would ask is: What will an AI feel like to an enterprise rather than to a consumer in mid-2028?
Let's make that an adjacent conversation. But for me as a consumer, I'm going to focus on that part of the equation. I feel like if AI understands me, it's connected to all of my wearables, insideables, and so forth. It has my back as a physician. It knows I had a hard conversation with my spouse and I'm exhausted. I didn't sleep well the night before. It has all this data.
I walk into the room, the lights come down, there's a glass of wine waiting for me because the robot put it out, my favorite music is playing, my favorite community is on. The term I use is ambient AI and automagical AI: The world magically adapts itself to your desires.
Alex Wissner-Gross
I can tell you what I think you want to hear.
What's that?
Alex Karp
You want to hear that by mid-2028, you're going to have an AI exocortex that's a quasi-upload of you, your digital twin in the cloud that knows everything about you and your life and is fully optimizing your meat-body existence, knowing what it knows about you. I think that's what you want to hear. I don't think that's actually how things are going to play out, though.
Okay.
Alex Karp
I think what AI will feel like in 2028 from a consumer perspective—sure, we'll have better augmented reality, and we'll have better robots in the streets. All of that, I think, is already essentially priced into the market. What's not being priced in right now—the non-obvious insight—is new scientific discoveries that consumers aren't the ones driving.
You're taking it to pharma. So, let's put that in the column of industrial, right? When Lyra Scientific and Colossal are creating breakthroughs at a rate—or, frankly, Isomorphic Labs.
Alex Wissner-Gross
The question as constructed is basically: What products is Apple going to launch in 2028? Because these all map onto Apple product categories. You get your smart home, you get your robots, you get your wearables of all sorts. Maybe, if we're lucky, we get ingestible robots.
We get all of these things, but I don't think that's the essence of what AI is going to feel like to a consumer, and I don't think that's the core or the frontier.
Suleyman, what do you think?
I agree with you on the feel-good cloud AI. I think I go more toward what Alex was talking about: The institutional use is going to be absolutely profound, and that's where we'll see the biggest difference. Every single person on Earth will essentially be operating like a small company, with an incredibly powerful team around them supported by what are basically mostly AIs.
I think at the enterprise level we'll be running enterprises on AI-native operating systems. More importantly, we need to rewrite the operating system for civilization, because everything we've done as a civilization—every business in the world for 10,000 years—has tried to solve scarcity. Now we're moving into an era of abundance, but what's the business model around that? I think we need a complete rewrite on that, because all our institutions and nation-states are geared around scarcity. So, we need a complete rewrite of the civilization operating system, and I think the beginnings of that are starting now.
Mhm. Dave, what do you think 2028's going to feel like? And I'm saying “feel” in particular, right? Because right now, a lot of people say, “Listen, I see the AI numbers. I hear you on the podcast, but it doesn't feel any different for me as a consumer.”
Yeah, we launched our holodeck today. You have to go check it out over at Link Studio. We commissioned construction of one of the rooms, put monitors on all the walls, and you go in, close the door behind you, and nobody tells you what to do; the AI just starts talking to you.
In the holodeck, you can create a virtual world, you can create songs, you can create movies, you can just vibe-code whatever you want. It's purely interactive, with big speakers, pulsing music, and everything around you.
It's a party.
David Friedberg
Yeah, go check it out. I think any consumer who experiences that is going to say, “I need that. I want that. How do I get that at home?”
No, not yet. It's hard to do the real Star Trek thing.
David Friedberg
But any consumer who goes into this holodeck and experiences it is going to say, “I need that. I want that. How do I get that at home?” So, I think the problem in 2028 is that there's going to be a massive shortfall of compute relative to the desire to have that experience.
What Alex said is dead right. The enterprise use cases have just discovered this, and they're sucking up all the data centers in the world now. There's no way that's going to get solved by 2028. I'm hoping 2030 or 2031, after the Terafab has a chance.
So, what's going to be the story in 2028? Right now, we've lived this beautiful moment in time where the very best foundation models are made available to anyone on the planet who wants to go to a website and try them. The cost of using the best models in the world is sort of a—it's very affordable.
Yeah.
David Friedberg
Yeah. You have to take advantage of this moment in time, because it's going to get really bottlenecked by 2028.
We're about to see a brand-new set of eyewear, right? We've talked about this at length. OpenAI has got their Johnny Ive device, whatever that might be. Apple has new generations of wearables coming. Meta has generations of wearables coming, and this is going to be ambient AI, where your AI sees what you see, is there and listening all the time, uploading everything into your version of Skippy, your OpenClaw, whatever it might be.
If you want to learn something and you're walking down the streets of Manhattan, and you've got AR glasses that are giving you a tour—this is what it was like in 1905—here's an educational layer. Or, if you want an entertainment layer, you know, “May the 4th be with you.” I'm a Star Trek person, but here we are on May 4th. You've got these little droids popping up and shooting at you.
If you want whatever you want, this AI is optimizing your audiovisual experience in line with what you've asked. So, I think that's going to feel different. I think we're going to see the first wearable devices enabling that. Do you guys agree? Alex?
Alex Wissner-Gross
I'm a big fan of Vernor Vinge, who wrote extensively about what the near-future AR/VR metaverse, if you'd like, would look like. I do think we get that. I do think it's just a matter of time, battery energy densities, and other progress. So, by 2028, do I think we get Vernor Vinge's smart glasses with compelling, long-life augmented reality or mixed reality? Yeah, sure. But I also think—
[Laughter] Yeah, after all that. Oh, boy.
Alex Karp
But I also don't think it matters an enormous amount. Yes, it'll be great, and it'll be popular.
By the way, I wanted to say something. In the last podcast, I was trying to make our conversation relatable to the general audience. My mission here about what AI is going to feel like is to support their understanding of where things are going. Yes, we also speak to the CEOs and the heads of the frontier labs here, but I want to give people an understanding of what their life is going to be like.
Alex Karp
A really easy, practical thing: Go anywhere you want autonomously for 20 cents a mile.
I'm going to do a quick speed round here on what is something that AI will feel like in 2028 that maybe is unexpected. Dave?
David Friedberg
We already spend more money on video games than all other media combined. When you overlay personalization, your own voice, and the fact that it remembers your personality and your past conversations, it's so immersive. And in a good way. It could be good or bad. It's intentional. It's designed, but if it's designed well, it's so engaging and immersive.
I suspect that an entire generation will have 70–80% of their conversations with AIs and not with other people.
Interesting. That's interesting. Salim?
Something I'm really excited about is just infinite, perfect, and long-lasting memory, because our memories are so flawed as human beings. The fact that it can record everything and recall who I met, et cetera—I’ve met many of you at events and, God help me, I can't remember anything. The ability to do that, I think, will be a huge addition to me as a person.
Yeah. Steven?
The one that's interesting to me is—I always say that you tend to hire one employee twice.
You hire them when they're normal and then when they're scared. People are very, very different when they're fearful. I think the AI coaching, the AI psychology, all that stuff—the AI coach in the room, the coach in the world—is what's really interesting to me. I'm interested to see—I do see, I've been seeing even the Defense Department's work using AI therapy, right? I got to play with a lot of those therapists along the way.
They're remarkably good. Most people are not using AI to coach their relationships. But your AI coach that's actually in your ear is really interesting, because humans—we run on 4 knobs, right? Balance, arousal, approach-avoid. That's pretty much humans, and you can coach them up pretty quickly in real time. So that's what's really interesting to me: I think we end up with better humans.
Fascinating. Alex, on the consumer side, would you ponder a vision?
Alex Wissner-Gross
I think we are merging with the machines. I do think augmented reality and wearables are part of the solution. I think ingestibles are going to be part of the solution. I'd be sorely disappointed if, by the end of this decade, we don't have many people swallowing computers. We see the beginnings of it right now with PillBot-type form factors.
I did a projection, something I think friend of the pod Ray would be proud of. If you extrapolate the typical size of a computer needed over the past 15 to 20 years to achieve a gigaflop of compute—which, historically, if you look back at Apple's new product announcements, Apple has waited for new devices to pass a gigaflop before releasing them—it's true with the original Apple Watch, the original iMac, and the original iPhone.
If you extrapolate the typical size of a computer that, at the time of launch, passed a gigaflop and extrapolate that forward, you find that not by mid-2028, but by the mid-2040s—around the time Ray says we're going to hit his version of a technological singularity—the size of a computer hits approximately the size of a eukaryotic human cell.
So, what am I most excited about? Well, I have a laundry list, but I think if you extrapolate the progress of the size of the computers running the AIs, we're going to have cell-sized nanomachines running those AIs, and I think that'll be incredibly exciting.
All right, everybody, and that's a wrap. We'll go to our outro music next. Ladies and gentlemen, let's give it up for the incredible David Blodgett, Salim Ismail, Alex Zigal, and Steven Kotler.
If you made it to the end of this episode, which you obviously did, I consider you a moonshot mate. Every week, my moonshot mates and I spend a lot of energy and time to really deliver you the news that matters. If you're a subscriber, thank you. If you're not a subscriber yet, please consider subscribing so you get the news as it comes out. I also want to invite you to join me on my weekly newsletter called Metatrends. I have a research team. You may not know this, but we spend the entire week looking at the metatrends that are impacting your family, your company, your industry, your nation, and I put this into a 2-minute read every week. If you'd like to get access to the metatrends newsletter every week, go to diamandis.com/metatrends. That's diamandis.com/metatrends. Thank you again for joining us today. It's a blast for us to put this together every week.