第 278 期·中文精读
社会主义者横扫纽约、中国编程能力追平、AI 内存紧缺、美光业绩爆表
Socialists Sweep NYC, China Catches Up in Coding, AI Memory Crunch, Micron's Blowout Quarter
特拉维斯·卡兰尼克与加文·贝克做客，聊纽约初选结果与民主党走向、中国开源AI追赶、美光财报与AI内存紧缺。
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- 0:00加文·贝克与特拉维斯·卡兰尼克做客节目！
- 1:05马姆达尼背书的社会主义者横扫纽约市国会初选
- 22:51民主党的未来、以色列议题与社交媒体禁令
- 45:12中国开源 AI 追赶、蒸馏与 OpenAI 新芯片
- 1:01:46美光业绩爆表，AI 内存紧缺冲击苹果与消费硬件
- 1:10:17分布式计算与太空数据中心的数学逻辑
- 1:27:22IPO 动态：Anthropic 估值 3 万亿美元、SpaceX 上市、Cerebras 跌破发行价
中文精读由 AI 基于原始节目改写，非官方翻译，可能存在偏差或错误；观点归属与表述以原音频与官方文稿为准。说明
纽约市市长佐兰·马姆达尼（Zohran Mamdani）这周二赢了三场。他背书的三个国会候选人全部拿下民主党初选，而 Polymarket 在选举日前给这个「横扫」开出的赔率只有 26%。
三个选区一个比一个有指标意义。纽约第 10 选区是全市最富的选区之一，涵盖西村、华尔街、Dumbo、Cobble Hill、Carroll Gardens、Park Slope 这一片。两届现任议员丹·戈德曼（Dan Goldman）输给了布拉德·兰德（Brad Lander）。戈德曼领导过对特朗普的弹劾努力，进步派履历一条不缺，常年在左翼有线频道露脸，赛前没人觉得他会输。
第 13 选区是另一个极端，哈莱姆加南布朗克斯，全市最穷的地方之一。一个 32 岁的民主社会主义者掀翻了连任五届的现任议员，此人还是国会西语裔党团主席、众议院议长哈基姆·杰弗里斯（Hakeem Jeffries）的盟友。杰森说，这场胜利之后，社会主义者下一个目标就是杰弗里斯本人。
第 7 选区是 DSA 的老巢，Bushwick、Williamsburg、Long Island City、Greenpoint 一带。克莱尔·瓦尔德斯（Claire Valdez）拿下了这个空缺席位，击败的是现任议员钦点的接班人。
把三场放在一起看，规律很清楚：这些候选人跟马姆达尼一样，在年轻、受过大学教育、高收入的人群里表现最好。杰森在节目里给了个说法，这些是「负担得起社会主义的人」。查马斯接了一句，说这是「富穷人」，有钱，但装作没钱。
关键是这三个都是安全的民主党席位。也就是说，DSA 大概率会真的把这几个位子拿进国会。
查马斯：AI 本来是最强的平等器，硅谷自己把叙事搞砸了
查马斯没有从选举本身切入。他说，我们正在失去话语权，而且是自己作的。
「AI 是我们这辈子能找到的最伟大的经济平等器。它能把地球上每个人的起跑线拉平。但我们在呈现它、把它推向市场、谈论它的方式上做得太差了。我们把自己的挣扎、不安全感和争斗全都摊在了台面上。结果硅谷在大众眼里的信誉又掉了一截。」（查马斯）
他给的例子是搜索。过去二十五年，Google 把全世界的知识和信息采集起来，通过搜索开放给所有人，但它没解决下一步：怎么把知识和信息转化成专业能力和判断力。AI 干的就是这件事。它让你身边随时有一个特拉维斯·卡拉尼克（Travis Kalanick）级别的超级联合创始人，能替你想清楚问题、在工程上压过别人、在思考上压过别人，而且没有任何守门人能拦住你获得它。
那问题出在哪？查马斯的说法是，硅谷把话题让给了另一套叙事：AI 会让大量人失业、会喝光水，这些说法「全是谎言，全是彻头彻尾的编造」。他声称这些叙事是被 AI 竞赛里某一小撮玩家专门制造出来的，由他们出钱喂养。在这个真空里，别人就能画出另一幅图，而且看起来比现状更有吸引力，因为现状这边「品牌大使太差」。
杰森接了一句，犹他和纽约有几场关键选战，本质上是「Anthropic 资助的反 AI 团体」对上「OpenAI 资助的亲 AI 团体」，结果亲 AI 那方赢了。查马斯补充，这些关键国会选战某种意义上是关于 AI 的公投，好消息是守住了，但只是险胜。
萨克斯：把 DSA 的纲领逐条念出来，看的是一整套宪制改造
萨克斯没有停留在情绪层面。他直接把 DSA 候选人的纲领一条条摆出来。
废除参议院。废除「监禁国家」，也就是警察和监狱。废除 ICE，给所有人特赦，不支持任何形式的驱逐出境。用从属于国会的行政和司法机构取代总统和最高法院。废除选举人团，用多党制取代两党制，扩大众议院规模，在所有选举里推行比例代表制和排序投票。解放巴勒斯坦。大公司公有化。砍掉战争部预算。
萨克斯的判断是，这是对美国宪政体制的一次彻底改造。这些提案单看有些像笑话，但现在笑不出来了，因为这个组织正在接管民主党。他说民主党建制派现在处于全面恐慌，因为他们已经失去了对党机器的控制，控制权落到了马姆达尼和他的盟友手里。
「DSA 联合主席乔什·布洛赫（Josh Bloch）说过，我们把民主党当作选票通行证，这跟我们是否认同它的目标无关。我们自己建组织，挂着民主党的标签当选，有用的时候跟民主党人一起进党团，然后从内部推我们自己的议程。我们把民主党建制派看作障碍，不是家。」（萨克斯引述）
他接着把矛头指向民主党自己的政策。开放边境带来的大规模移民潮，构成了这支新 DSA 力量的重要票基。他的判断是，如果纽约市长选举只有本土出生的纽约人投票，马姆达尼赢不了，是移民票把他送上去的。加上那批「受教育过度」的白人进步派，念完大学进学术界或 NGO，向前流动的通道却越来越窄，这批人构成了先锋队，两者合起来正在接管民主党。
他还补了一句，说民主党把「大熔炉」打碎了。过去美国用多元文化主义和觉醒主义取代了同化移民的长期政策，于是现在会出现公开把自己定位成「后美国」人的候选人，他们对美国的宪政秩序和自由企业制度没有任何敬意，想引进一套完全不同的东西。
杰森注意到一个相似之处：那位第 13 选区的新科候选人要「删除」一堆机构，而特朗普当年也要删掉国税局、美国国际开发署、教育部、环保署，用的是同一套剧本。萨克斯马上纠正，说「特朗普不想删掉美国宪法，差别还是有的」。
萨克斯顺手给了个论据：南美最近有七场选举集体右转，一个很大原因是美国国际开发署消失了，那些左翼的政权更迭操作没了资金来源，激励结构跟着变了。
特拉维斯的两条格言：真相与正义是社会的免疫系统，共产主义在每个人血液里
杰森提到特拉维斯曾在推特上把安·兰德的《源泉》当了很久的头像。特拉维斯纠正说没那么久，他读一本书就换一次头像，《汉密尔顿》也挂过，《安德的游戏》也挂过。
然后他给了两条自己的判断方式。
「真相和正义是社会的免疫系统。免疫系统被压制的时候，所有的社会病都会一起发作。你在社交媒体、主流媒体上看到真相在流失，那就是社会要出事的早期指标。正义那边一样，有人犯罪却没有后果，也是个早期指标。你只要盯着这两件事看：今天真相在赢还是输？今天正义在赢还是输？方向会告诉你我们是要变好还是变坏。」（特拉维斯）
杰森把这个框架套到 COVID 和福奇案上，说五年之后真相才慢慢多起来，正义可能更晚，但这是个完美的例子。
第二条格言更狠。
「共产主义在我们每个人血液里。你问别人，你这辈子懒过吗？所有人都说懒过。你想要过不劳而获的东西吗？想要过。区别在于，你会不会把这两件事变成生活方式。当你有生态系统让人可以同时做这两件事而不用承担后果，这个系统就会达到临界规模，开始扎下根来。我觉得我们正在看到这个。」（特拉维斯）
加文：DSA 的票基是一群正在向下流动的富裕白人
杰森请加文从经济角度解释。加文先自我定位，说他大半辈子是民主党人，那个党一度是工人阶级的党，想做的是创造机会、拉平起点、帮黑人、帮西语裔，方法可以争论，但目标本身是体面的。
而 DSA 里这些目标一条都不剩。
他看投票数据，DSA 的票基是相对富裕、正在向下流动的白人自由派。这个群体在失去工人阶级的票，在失去穷人的票，在失去黑人的票，在失去西语裔的票。而这些恰恰是民主党过去长期试图代表的人群。加文说，DSA 对他们没有兴趣。
他抛出「柯里效应」（Curley effect），波士顿那位市长的玩法：推行明知会损害自己选民的政策，但这些政策会赶走政敌，然后你就能把年薪六十万美元、什么也不生产的 NGO 岗位发给自己人。这是有组织的腐败，而且是超大规模的。加州和纽约的无家可归者人均支出翻了一倍以上，钱全流向 NGO，结果反而更糟；加州涨了大概四倍，结果也更糟。
加文说他不担心 DSA 的理念，因为理念只对那一小撮向下流动的富裕白人自由派有吸引力。他真正担心的是一个人。
「我认为马姆达尼是我这辈子见过最有天赋的政客之一。演讲好、访谈好、能接住所有情绪，像个变色龙一样会切换。DSA 能崛起，原因既不在他们的理念，也跟对 AI 的不满无关，就在于他这个人。民主党里没有第二个这样的人。我以前以为 AOC 是民主党里天赋最高的，现在看，马姆达尼在政治天赋上明显高出一个量级。」（加文）
杰森顺着说，这一代年轻人已经是「f2 一代」，两代人过得都不如父母。房价、学贷、医保，他们觉得自己进不了这个系统，觉得系统被操纵了。这时有人出来替他们说话，而他们对社会主义、对德国发生过什么、对红色恐慌一无所知。杰森给了个很好记的说法：他们卖的是「可乐零度的社会主义」，包装很好看，本质还是共产主义。他们要的是拿走一半公司股票、拿走别人的财富。
杰森承认，这边也没做任何事去改变这些人的想法。房子没多建，大学没变便宜，医保一团糟，通胀一团糟，还在打没有意义的仗。
查马斯：先走社会主义的三国，验证出来的是一地鸡毛
查马斯说他前一天在梅根·凯利（Megyn Kelly）节目上讲过一个正在琢磨的理论，想在节目里听听大家反应。
把修辞拿掉，只看结果。有三个国家比美国更早、更深地转向社会主义：加拿大、英国、澳大利亚。用任何合理的进步指标衡量，这三个国家的表现都是一场彻底的灾难。在社会议题上、在移民和开放边境上、在气候变化上的所有「道德表演」，留给这三个国家的是失修、内斗、政局高度不稳定，一个个都是火药桶。
但查马斯看到了一个转机，而且他认为这个转机印证了加文说的那点。这三个国家现在都禁止 16 岁以下使用社交媒体。
「这有点像确保小孩别太早对毒品上瘾。像马姆达尼这样的人，加文说得对，我还要更进一步：AOC、刚赢的那位，他们全都长得好看、有魅力、抓得住当下的集体情绪、知道怎么用社交媒体，本质上是在经营一支军队。如果你把这条腿砍掉，让年轻人真正长大成年之后再接触社交媒体，我怀疑最重要的信息摄入渠道被拿走之后，会给他们和我们所有人一个机会，看到均衡饮食能让人后半辈子更健康。」（查马斯）
他的推论是，这三个国家会迎来一代不那么激进的年轻选民进入投票年龄；如果加拿大、英国、澳大利亚之后出现政治稳定和可预测性，可以直接把功劳归给这道禁令。佛罗里达已经在美国先做了，查马斯认为值得在全美认真考虑。
特拉维斯立刻反打。
「我完全反着查马斯来。我们都同意社交媒体对孩子和成年人都坏，刷太多真的会让脑子烂掉，比香烟还糟。但禁到 16 岁的真正目的，是逼成年人验证身份、去匿名化，从而建立一套完整的审查体制，英国正在琢磨这个。审查打击的对象，从来都跟『有害内容』无关，它真正清理的是掌权者不想让你看到、跟他们意见相左的内容。跟掌权者一致的东西，没人会叫它有害。所以这套做法的实质，是把『不同意他们』定成犯罪。这就是那套年龄门槛的底牌，它针对的是成年人，跟孩子没多大关系。」（特拉维斯）
加文说他强烈同意 16 岁以下禁用会很好，但代价很高，就是特拉维斯说的那套。真正在发生的事，是想限制 X 上的匿名账号，尤其是那些说了欧盟当权者不爱听的话的账号。如果能同时保住匿名和言论自由，他完全支持这道禁令。他还说了一句：如果没有言论自由和 X，今天的世界会完全不同，而且会糟得多。
加文：每一代人都得自己试一遍共产主义，但这次赌注更大
加文把话题拉远。他说人类最大的悲剧之一，是我们无法从别人的经历里学到东西。共产主义在各种文化、各种机制下都彻底失败过，终点都是死亡和苦难，但每一代人都要自己再试一遍。
他接着列了几组他认为「可测量地坏」的政策结果。关心黑人生命？有一份没有争议的研究显示，只要选出一个共和党地区检察官，该市年轻黑人男性的全因死亡率就下降 7%。关心环境？进步派搞出的监管多到连太阳能都建不起来，而世界最终是要靠阳光运转的。关心教育？他们的做法是取消精英学校，那本来是低收入家庭孩子的真实上升通道，加州还把数学课取消了，这对弱势群体是极大的伤害。至于犯罪，大约 0.1% 的人犯下 70% 的罪，只要处理掉这 0.1%，几乎就没有犯罪了。
加文说他第一次开始为美国担心。作为读过历史的人，美国长期是一个地理上稳定、政治经济上稳定的实体，这本身就很难得，二战之后美国本来有能力真正接管世界，但没那么做。可是一旦 DSA 完全控制几个大城市，把有生产能力的人全部赶走，他不知道怎么才能回来。
萨克斯补充说，这不只是纽约。洛杉矶市长那场选举，一位候选人靠投票日之后的「选票收割」翻盘赢了斯宾塞·普拉特（Spencer Pratt）。DSA 现在大概已经拿下洛杉矶一半的市议会席位，还在扩张。他们特别擅长低投票率的选举。纽约这次是民主党初选，深蓝州，投票率大概只有 17%，这正是 DSA 最擅长的战场：支持者极度热情、组织度极高、懂得怎么利用规则。排序投票这类制度，他们知道怎么玩。
他还给了一个判断：无论最后有多少 DSA 候选人真的当选，党的其余部分都会向这个方向倾斜，因为没人想在自己的初选里重演丹·戈德曼的遭遇。他甚至认为，AOC 和伯尼在这些人眼里已经是「叛徒」，他们比那两位激进得多。
以色列议题成了民主党初选里的单点投票
萨克斯专门讲了戈德曼为什么输。戈德曼领导过弹劾特朗普，进步派履历全齐，常年在正确的有线频道露脸，赛前没人预期他会输。他和兰德都是犹太裔、都是纽约长期从政的白人，纸面上高度相似。唯一的实质分歧就是以色列。戈德曼过去几年基本在为以色列的行动辩护，兰德则去了清真寺，谴责他所说的加沙「种族灭绝」。这场初选几乎是关于这一个议题的单点投票，兰德赢得相当轻松。
背后的数据是：现在 80% 的民主党人不赞成以色列。以色列过去在民主、共和两党里都享有很高的支持率，是共识议题，如今这个共识在民主党一侧已经瓦解。
萨克斯强调他只是在描述，不站队。他说共和党这边其实是分裂的，分裂线是年龄。年长、建制派、看福克斯新闻的那批人，对以色列的支持率仍然很高；50 岁以下、更多转向播客的人，不赞成率已经到了 57%。年轻人不分党派，都对以色列的所作所为有严重意见。
查马斯补了一段他自己在梅根·凯利节目上讲过的类比，把 10 月 7 日和 9 月 11 日放在一起看。当一个国家被入侵、人民被屠杀，会造成巨大的情感、身体、心理创伤，而这个国家通常会授权当时的领导人去把事情拨正。9/11 之后发生了很多在别的任何情况下都不可能发生的事，排第一的就是《爱国者法案》，没有 9/11 它绝无可能通过。他理解这种时刻，也理解领导人代表国家去纠正错误的冲动。
但现在的问题是，人们无法在逻辑上把犹太人、以色列人、比比·内塔尼亚胡这三者区分开。查马斯说这非常不幸，因为一切都容易被混为一谈，这件事已经变成政治上的第三条 rail。他认为对 Netanyahu 有意见、认为该换以色列领导层、该重置以色列在全球舞台上的位置，这本身是非常合理的立场。以色列人民很了不起，犹太人很了不起，但把一个人和整个国家、整个宗教捆在一起，是疯狂的。
加文补了两点。第一，以色列有严重的公关问题，他们需要一个三十出头的美国以色列裔、英文流利、熟悉社交媒体的人来当面向美国的发言人，法国、德国、每个国家都需要这样的人，而他们没有。他说 10 月 7 日之后有个年轻的以色列美国裔做得很好，据说是 Netanyahu 的夫人不喜欢他，就把他撤了，之后一直没找到替代。以色列在持续挨打却几乎不回应，偶尔推出来的人是六十多岁的战争英雄，英文技术性精确但带口音，是了不起的人但不适合站到话筒前。
第二，回到查马斯关于 9/11 的评论，加文认为特朗普能当选，一个很大原因是 COVID 期间很多家长第一次听清了孩子在学校被教的是什么，这让他们激进化了。他说美国的整个教育系统里，不该有公开反美的内容。美国犯过错，不完美，但已经差不多是最好的了，这个故事需要在每个年级被一致地讲。奴隶制在全世界普遍存在，除了东亚少数国家，它不是美国独有的问题。很多孩子之所以易受社交媒体宣传影响，是因为他们从小被教育为自己是美国人而羞耻、为自己的身份羞耻、被告诉美国是邪恶的。这一点需要被扭转，因为美国是了不起的，是地球上唯一一个大致成功的多元文化社会。
杰森接上说，现在你说「大熔炉是美好的」，就会被取消，理由是「你在消灭别人的文化」。他说不对，保留你的文化，然后加入这个文化，大家凑成一桌丰盛的自助餐。查马斯被问到他的文化是什么，他答：「赢。学习。进步。冒险。」加文接梗，引了《塔拉迪加之夜》里那句「我撒的都是卓越」。几个人笑作一团。
杰森：他们学的是特朗普的剧本，马姆达尼是这套剧本最强执行者
杰森读了纽约 DSA 联合主席古斯塔沃·瓜迪略（Gustavo Guardillo）的一段话，大意是：我们在民主党党团里，但我们不认同民主党的运作方式，所以我们靠志愿者驱动的运动来建立自己的独立性。他接着说，民主党的问题是靠亿万富翁捐款，同时又想代表工人阶级，在这两者之间必须选一个。
杰森认为他们在用特朗普的剧本接管民主党。特朗普当年接管了共和党，党内试过把他踢出去，但他的信息和沟通方式太精准，他知道人们想听什么，也知道怎么送出去。杰森形容他：「在非喜剧演员里，他是世界头号喜剧演员；在真正的喜剧演员里，他也能排进前二十。」马姆达尼做的事一模一样：靠沟通接管。杰森说他是个死忠尼克斯球迷，看到马姆达尼那段关于尼克斯的演讲时，被彻底震住了，甚至有点生气，因为讲得太好了，有奥巴马和特朗普那种魅力。
萨克斯的回应是调侃：你知道马姆达尼是共产主义者，他代表的是邪恶，结果就因为他讲了一段尼克斯，你现在爱上他了。杰森辩解说爱的是那段演讲。萨克斯说，就这？就这就能拿下你？我们完蛋了。杰森说自己像被催眠了，硬把自己拔了出来。萨克斯说，我们得给你做去编程处理了。
GLM 5.2：开源权重模型第一次站到前沿门口
第二个话题，杰森起头：中国的开源模型看起来正在追上美国的前沿模型。他先介绍 Z.ai 发布的 GLM 5.2，前沿级别的开源模型，免费下载，744 亿参数，100 万 token 上下文，MIT 许可证。MIT 是最开放的开源许可，你可以随便用、可以 fork、可以拿它开公司，没有地域限制，可以完全自托管，不需要 API。
成绩单：在 Artificial Analysis 智能指数上拿了 51 分，是历来做过的开源权重模型里最高分。在 SWE 编码基准上，落后 Claude Opus 4.8 不到一个百分点，和 GPT 5.5 基本持平。API 使用成本比 GPT 5.5 便宜 85%。Z.ai 创始人告诉马斯克，开源权重达到前沿能力的时间会早于 2027 年第一季度。
杰森的问题是：如果明年第一季度就能有这种模型，那这六个月在 AI 的漫长弧线里还有意义吗？对所有自我施加的法律限制意味着什么？
加文承认，GLM 5.2 好到这个程度，动摇了他的一些信念。他先解释了一个关键机制。
「蒸馏就是，你们见过那些中国 iPhone 农场，成千上万台手机、iPad、电脑，用马甲账号去问云端 API 非常具体的问题，然后把所谓的推理轨迹收集下来。如果你在 API 上，你能看到每一个 token。这些推理轨迹再被喂回模型，用于强化学习过程，很可能也用于预训练。这就是你能用极低成本极其接近前沿的办法。这件事肯定在发生，而且已经发生了很久。」（加文）
特拉维斯给了个通俗版：这就像你把能想到的所有问题都去问 Google，拿到所有结果，然后拼出自己的搜索引擎。加文说，但现在不一样了，这个模型已经好到能做自己的强化学习，猫可能已经从袋子里跑出来了。不过他提醒，没人知道 Mythos 有多强，没人知道 OpenAI 下一代有多强，下一代 SpaceX 模型也没见过，所以差距也可能重新拉开。
加文抛出了他认为的未来形态：可组合模型。每家企业的架构里都会有一个路由器，把任务先发给自己的开源权重模型，一半以上、可能 85% 的查询由它处理，只有最难的再交给前沿模型校验或补充。他引了卡帕西（Andrej Karpathy）的说法，叫「LLM 议会」，你会有 Grok、Anthropic、OpenAI、Google 里至少两家，并且他主张 Grok 应该始终占一席，因为它对真相的坚持，会告诉你一些作为企业主需要知道、但政治上不方便听的真相。
加文还纠正了一个常见误解：开源模型对 AI 整体是好事，尤其对 AI 基础设施提供商。它只是把经济价值从边缘实验室的毛利转移到基础设施。目前前沿 token 大概拿走了 90% 的经济价值，而开源 token 占了 80% 以上的处理量，这两个比例可能还会维持下去。
萨克斯：我们现在真正的对手是时间，不是审查
杰森请萨克斯谈中国开源的上升，以及美国为什么还没有自己的开源旗手。加文插了一句，说 NVIDIA 就是美国的开源旗手，他们随时可以放出一个比 GLM 5.2 更强的东西。杰森追问那为什么没放，加文说原因很多，说到底是谁也不知道。
萨克斯接着说，中国擅长开源早就不是什么新闻了，但 GLM 5.2 有几件事值得注意。它现在是编码、软件工程和长上下文 agent 任务里最好的开源权重模型，比 Opus 4.8 只差一点，和 GPT 5.5 齐平。也就是说，一个中国开源权重模型，已经和 OpenAI、Anthropic 当前能用的模型一样好了。而 Fable 和 GPT 5.6 现在因为监管原因卡在「炼狱」里。
萨克斯说他从加入政府第一天起就在讲，我们跟中国处在一个竞争极其激烈的局面。整套 AI 战略从一开始就是把这场竞赛定义为全球竞争，我们不能做那些不必要地拖慢自己企业的事。
加文直接问了一个尖锐问题：Dario 是不是正好得到了他想要的？这看起来像是一个精心计算的策略，激美国政府做出刚做的事，因为这样他就有了监管护城河，可以把未来的模型藏在这道墙后面，甚至只发给 Glasswing 之类的伙伴，用来蒸馏和自用。
萨克斯的回答是：某种程度上确实如此，因为他们一直在鼓吹要设一个联邦监管机构，Dario 几周前还发博客说要给 AI 建一个「FAA」。他们想要的就是政府审批流程。从这个角度说，他们确实得到了想要的。但他不认为他们乐见 Fable 被下架，这可以说是「搬起石头砸自己的脚」，或者叫 FAFO（自己作的自己受）。
「我的看法是，我们不该奖励 Dario，不该给他那个他一直在渴望的东西，也就是一套迷宫般的政府审批流程，那实质上是在奖励监管俘获。我希望很快，只要 Anthropic 解决了越狱问题，就应该允许他们回到市场。OpenAI 同理，不该没必要地拖延他们。这场竞赛里我们没有几个月可以白白送掉。」（萨克斯）
萨克斯把网络安全风险的处理逻辑讲清楚：网络攻击确实是风险，但正确的回应只能是让白帽先去把所有漏洞找出来，做一次大规模升级周期，在漏洞被利用之前把补丁铺开。如果只是收紧到连模型都不让用，中国反正马上也会有这些能力。他说中国一直稳定落后美国模型大约九个月，上下浮动三个月，看具体能力；但一旦他们知道某个方向（比如网络安全）出现了突破，就会把更多资源堆到那个具体问题上，追得更快。他的结论是，我们头上有一个计时器，已经说了好几个月了，不能让一切都慢下来，因为那不会让中国慢下来，他们不在我们的管辖范围内。
查马斯把这事总结得更直接：他们在模型上落后六个月，在芯片上落后二十四个月，结果总体上只落后几个月。那我们到底在玩什么游戏？继续这样对自己下手，我们会输。
萨克斯补充了中国本土化的进展。DeepSeek v4 声称用华为芯片训练，Z.ai 声称 GLM5 全系用华为昇腾 910B 集群训练。他说这些说法可以打折扣，也许他们走私了 NVIDIA 芯片，但官方口径是全部用国产芯片完成。中国正在强力推本土化，要把华为捧成国家冠军，要让所有公司都用华为芯片，产能还需要扩，但会扩得很快。然后他们会把华为芯片加上为华为优化的模型打包，GLM 5.2 的推理就是为华为芯片优化的，打包成所谓「AI 装进盒子里」，以极低成本卖到全球。
杰森接上，说这就是他们对待每一项技术的做法：更好、更便宜、更快，或者差不多好就行。萨克斯把话拉回出口管制：他自这届政府开始就一直在说，我们必须支持出口，因为中国一两年内就会到那一步，我们会后悔当初给自己发明了那么多理由，不把产品卖给朋友和伙伴。
杰森也做了实测。他用 Z.ai 的托管版问台湾，没得到满意的回答；问天安门，没回答。问巴黎有什么可玩的地方，答得非常好，可一旦让它把想法做成信息图、排一个三天行程，它就说「这个模型太忙了，你换一个模型」。萨克斯补充说，中国模型确实出厂就带审查和政治偏见，但美国公司已经证明这不是致命问题，把开源模型拿过来 fork、定制，就能把天安门之类的回答补回来，Perplexity 很早就这么干过。
美光业绩爆表：内存成了整个 AI 最硬的瓶颈
杰森转到第三个话题。全球只有三家公司能造高带宽内存（HBM），美光是其中之一。这类专用芯片坐在 NVIDIA GPU 上面。美光 2026 年全年产能已经售罄，而且售罄很久了。SK 海力士和三星也做 HBM。
数字：营收从 90 亿美元涨到 420 亿美元，同比四倍，超出预期 16%。第四季度指引从 430 亿上调到 500 亿。股价涨了十倍。杰森还特别点名加文，说他在 2025 年预测节目里就押注 HBM 制造商，是最佳表现资产，从那之后美光涨了 14 倍。加文回了一句，说自己碗里的汤还没凉。
然后是最直接的消费者冲击：苹果开始涨价。苹果一直是本地模型运动的大赢家，人们买 128G、256G 的 MacBook Pro 和 Mac Studio。但对冲的成本涨得太多，苹果一直没转嫁给消费者，现在撑不住了。那台 699 美元、对标 Chromebook 的笔记本涨到 799，涨了 14%，Mac Studio 涨了 25%。杰森的原话是，通胀来到了桌面上。
加文给了一个框架：DRAM 是当下最重要的瓶颈。X 上有一批专门盯瓶颈的人，他管他们叫「瓶颈兄弟」，会拿 Claude 去找一些冷门的日本公司。但别人盯着激光器、电容、电源、半导体、NAND flash、硬盘，加文说真正要盯的只有一样：DRAM 和 HBM DRAM。原因是内存容量和带宽是所有 AI 模型性能的地基。马斯克把 TeraFab 的重心放在内存上，也是因为它是最重要的瓶颈。这个瓶颈会伴随我们很久。
这一季真正有意思的东西是美光的 SDAs，也就是供应链协议。这些协议给价格设了上下限，覆盖的客户群越来越大，大约 50% 的营收被四家大客户锁定，而这些新合同的价格下限，从毛利率角度看已经高于上一轮周期的峰值。加文认为这可能会改变整个行业的结构。
他顺手做了个类比：半导体供应链的其他环节早就重估过了，Lam Research、晶圆制造设备商，相对 DRAM 长期给高溢价，商业模式也改善了。DRAM 这边，行业结构和商业模式同样在改善，因为 HBM 越来越像定制芯片。
至于别人能不能进来，加文说 CXMT 正在中国上市，它可能会解决苹果消费级 DRAM 的部分问题，会向市场大量投放便宜的消费级 DRAM。但 AI 服务器需要的那种 DRAM，全球只有三家公司能做，这是科学能达到的最接近魔法的东西。TeraFab 会是解决方案的一部分。加文还抛出一个数字：明年 DRAM 可能占所有超大规模厂商资本开支的 30% 到 40%，每一分花出去的钱、几千亿美元，直接流进 DRAM。
但他给了个反直觉的解读：这可能对社会非常有价值，因为把建一个千兆瓦数据中心的成本推高到连超大规模厂商也要认真算经济账的程度，而他们又陷在囚徒困境里。这或许能给社会争取时间，去适应我们那位朋友布拉德·基尔希纳（Brad Kirchner）所说的「社会契约」。
萨克斯补充了 HBM 的技术细节：把 DRAM 晶圆或裸片叠起来，HBM3 大概是八层裸片堆叠，现在往 12 层、16 层走，堆叠之后再整体封装，本身就是高阶技术，所以只有三家公司能做。他提到纽约那座美光工厂，刚破土动工当天就因为有环保争议被叫停，说明在美国扩产不容易。加文补了一句更狠的：建 fab 的难度取决于选哪个州，问题出在深蓝州，那里才是真难。也许那家美光工厂最后会建到他的家乡得州。杰森吐槽说，现在激励游戏反过来了，以前是各州抢工厂，现在是工厂挑州，问哪个州真能把东西建起来，钱不是问题，你说把信封寄到哪都行。
加文提到微软上调了 Xbox 价格，Switch、PlayStation 也在路上，消费者端因为价格出现需求破坏，而 AI 需求对价格相对不敏感。萨克斯把这一切命名为「AI 通胀」。
太空数据中心：把 250 亿美元的地面成本换成 50 亿美元的发射成本
萨克斯提了一个假设，说人们默认随着时间推移，新建数据中心会越来越便宜、越来越容易，但按加文说的，其实可能越来越贵、越来越难，因为零部件有竞争，内存变贵，GPU 也没变便宜，许可越来越难拿，政治环境越来越难，能建数据中心的地方越来越少。
加文说百分之百如此。他给了这套账的骨架：建一个千兆瓦的数据中心，350 亿美元花在半导体，也就是 NVIDIA 的芯片上，250 亿美元花在电力和冷却设备上。那 250 亿里有很大一块是安装所需的人力，所以明显是通胀的。轨道计算要做的比较就是：太空和地面的硅片都是 350 亿，但如果你能把发射成本压到远低于 250 亿，这笔账就成立了。当 Starship 可复用时，把一个千兆瓦的算力送上太空大概花 50 亿美元。
也就是说，太空 400 亿，地面 600 亿，而那 250 亿的电力和算力明显在通胀。三四年后可能是 700 亿对 400 亿，而那个 50 亿随着 Starship 快速复用很可能是通缩的。他还纠正了一个常见想象：别把它想成五角大楼那么大的数据中心，太空里实际是用激光连起来的一排排机架，本质是一个虚拟的太空数据中心。运行阶段，大概一年十亿美元付电力和冷却。
查马斯从他的数据中心项目经验出发，给了一个更宏观的判断。2021 年以来大约有 40 个数据中心项目遭遇抗议，这个数字会往上走。他怀疑现在所有对 AI 能源消耗的预测都严重失衡：供给极度稀缺，需求几乎无限。这会把去太空的经济账提前。而一旦如此，SpaceX 和他们那套算力栈会优于超大规模厂商和其他所有人，地面超大规模厂商每输出一个 token 的成本，相对 SpaceX 规模化之后会显得经济上不那么对劲。但留在地面上的东西会极其珍贵，他形容为钻石：十千瓦的钻石是没人要的小石子，但几百兆瓦到千兆瓦规模的，就是希望之钻，应该锁死。
杰森提了个新商标。6 月 18 日提交的「Megapod」，描述里是一堆模块化数据中心硬件：服务器网络、AI 处理硬件、网络硬件、配电单元、冷却系统，作为自成一体的模块化算力系统出售。市场传闻是，这会是超级充电站里的巨型电池组加 GPU，而超级充电站已经获批。
查马斯解释了这个需求的来源。地面上要通电算力，地不难，前提是能拿到许可，这个就没那么直接了；电力非常难。然后是一个关键设计选择：所有这些公司都会发布「设计基础」文件，也就是 BOD，告诉你 Anthropic 的规格、OpenAI 的规格、CoreWeave 的规格、AWS 的规格、GCP 的规格，这些文档能有 50 页到 500 页。他说，如果你最近用过 OpenAI 或 Anthropic，一定见过「稍后再来」，那个「稍后再来」完全不可接受，说明他们根本没有算力。
为了找解决方案，这些设计基础里的限制和特异性正在被放宽。一个关键约束是，Google 和 NVIDIA 的架构要求这些机架必须液冷，是又大又粗的超级计算机机架。现在大家在往回走，说也许那些老一点、用途少一点但能风冷的设备也有用，能用上的都用上。在第二类里，一些很聪明的人在做的就是把一个集装箱放到某块水泥地上，接上电就开跑。戴尔做这种机架，Vertiv 做这种模块。如果特斯拉能供货，他的数据中心项目会大批量采购，因为可以在仓库里预制、装芯片、卡车运到现场、吊装、通电，90 天建成，快得闻所未闻。他只希望这些 Megapod 不会被特斯拉和 SpaceX 内部全部吃掉。
杰森说传闻就是马斯克会把它们放到超级充电网络，那里有地、有电、有些地方还利用率不高。查马斯泼了冷水，说超级充电站这类场所有很多其他要求：访问控制、信息安全、液冷要求，很多工作负载在那里根本跑不起来，因为会有随便的人在旁边晃悠。
特拉维斯说他手上有 500 处地产，有能源、有机械冷却系统、有已经接进来的天然气，所以他在做的机器人、AI、物理 AI 这些事，正在认真考虑把一部分算力放进自家厨房里。查马斯坚持没那么简单，说如果要把算力贡献给算力池，就得签违约金条款和 SLA，那不是你会想签的东西。特拉维斯说那些条款和他无关，他只是自用，够不上超大规模厂商。杰森问机架堆叠，两人一来一回，查马斯说自用当然可以。
特拉维斯点出了真正的难点：在非数据中心类型的物业里，安全是最大的问题。数据中心的架构里有「人阱」，你按指纹进第一道门，门在身后关上，再按指纹进下一道，只有前一道关上了才能进。加文追问，一个人阱要多少钱，为什么不能在厨房里也装几个。杰森接梗说，你是真想搞人阱来「阱」人吗。特拉维斯说，公共充电站那种物理可达性，如果是要转售算力，确实还有很多要做，但自用就没问题。
查马斯把话题引向真正让他兴奋的方向：如果能把算力贡献给一个 SLA 更低、更像社区协作的分布式训练或推理池，那才是价值所在。他点了几个项目，BitTensor、Venice、Plurals。特拉维斯提醒分布式训练的效率问题：如果节点彼此离得远，效率会大幅下降，你要的是物理上紧挨着，至少差一个数量级。哪怕用自家光纤连，隔两公里就完蛋。加文同意，说所有不利于训练的因素，对推理反而有利，延迟对推理很重要，分布式推理云正在到来。
加文还举了个例子：有家创业公司在把四块 GPU 加一块电池装到居民家里，给住户电费打折，然后就能为那个社区提供推理，设备密封锁死，没人能进去。他还讲了推理正在发生的拆分：prefill 负责理解问题和已有的回答，受内存容量约束，记得越多越好；decode 负责生成下一个 token，受内存带宽约束，说得越快越好。这两类推理正在被拆开。把 Grok 或 Cerebras 这类为 decode 优化的芯片，放在 H100、A100 这类旧 NVIDIA GPU 前面，就能把老卡从旧数据中心里捞出来，装进集装箱机架，组出一套相当有竞争力的方案。这样 GPU 能用七年、十年、十二年，降低了融资成本，让这场 AI 革命更可融资。
杰森补了 Targon 和 BitTensor 的机制，说 H200 按小时租只要三四美元，无需许可，任何人都能贡献，BitTensor 的妙处是有验证者确保你贡献的东西跟宣称的一致。他抛了个设想：如果特斯拉说从今往后每个 Powerwall 都内置 GPU，不装 GPU 不能买，你不用的时候我们付钱租你的电池，屋顶再配个 Starlink，于是马斯克就凭空造出无数个家庭备用电源，用户免费拿到电池，他拿到二十年独家。查马斯最后说，他在这块没有投资，但在跟中国竞争、要有充满活力的美国开源社区、要有为言论自由等服务的一堆分布式模型这个交叉点上，分布式推理在美国生态里确实有位置，只是他还不确定具体形态和房主怎么拿到钱，谁想明白这个泛美式的主意，谁就真抓到了东西。
Cerebras 破发：为什么跌破发行价会引来一波不惜代价的卖盘
加文主动把 Cerebras 拎出来讲，说它上市后表现很棒，但这两天跌破了发行价，值得说清楚。
「有一整代基金经理，很多人在鼓吹要把 IPO 定价里的水分榨干。但反过来，也有很多基金经理，只要股价跌破发行价，不管什么理由都卖。他们把这当成一个被打破的承诺。这两天 Cerebras 在某种程度上就是这样。这看起来不理性，但我认识的一些管理巨型基金的人，只要破发就卖，没有例外。所以一旦股价接近发行价，做空者就会做空，因为他们想把它打穿，然后快速赚个 10% 到 20%。」（加文）
杰森总结说，于是就形成踩踏。加文说，你会有这种对价格不敏感的卖盘被触发。他给所有要上市的公司一条建议：告诉你的投行，定价要保证我们上市头九个月不破发，他一直这么建议所有人。
他也说，公司需要时间来学会怎么向公开市场讲自己的故事，这跟面对 VC 是很不一样的听众。他给出了他会怎么讲 Cerebras：公司在去年 12 月和 OpenAI 签了一份变革性的合同，签完立刻向台积电追加晶圆订单；从下单到台积电答应、再到芯片造出来要四个月；再把芯片变成服务器要两个多月；如果运气好还能找到电力，通电开始产 token 还要一个月。所以这份 OpenAI 合同最早能在劳动节前后见到效果，第三季度会看到一点，之后才开始真正累积。
他给了个粗略算法：按 NVIDIA 的数字，350 亿美元带来一个千兆瓦，一个千兆瓦能产生 150 亿美元的 token 收入和云收入。如果他们在 2027 年能每月新增 50 兆瓦，年底云业务年化收入大约 90 亿美元，而当前市值不到 400 亿。他说这非常难做到，他们从没做过这么大的事。作为投资者，他真正盯着的是他们能以多快速度把电力接进来，至于竞争位置、能带来多少新需求，他没花太多心思。超大规模厂商之外，能把一千兆瓦以上接进来的公司，只有 CoreWeave、Crusoe 和 SpaceX AI；把 600 兆瓦接进来都极难。
杰森提到 Rivian，以及查马斯那家公司在上市第一年就跌破发行价的历史，说这不必然意味着公司差，只意味着热度太高，或者 IPO 定价定到了完美。定价可以大幅低估，也可以大幅高估，很难拿准，所以才有拍卖这种方式。特拉维斯说拍卖才是正道，定价本身不难，只要你按该有的流程走；真难的地方在于你心里已经先有了一个想要的数字。查马斯补了一句，而且有很多张嘴要喂，这会影响定价。加文说他不认为这次是这样，Cerebras 的定价是一场善意的、经过深思的努力，只是这单 IPO 需求太旺，很难定价。
IPO 市场能不能吃下这一波
最后一个话题，杰森把数字堆起来：四千亿美元的在途发行，包括 OpenAI 和 Anthropic，加上 Cerebras，问市场怎么消化这么多新供给。钱从哪来，散户，还是有人卖比特币换过来？
加文的回答先给了一个估值判断。
「我认为 Anthropic 今天就值 3 万亿美元，这大概是它作为上市公司会交易的位置。他们今年结束时的收入会远超 1000 亿。28 年的数字是多少？2000 亿还是 3000 亿？它大概不会以那个数字的十倍交易。而那个规模上它会非常赚钱，因为收入会由推理主导，而大家报的是推理有 85% 的毛利率。」（加文）
特拉维斯听到「3 万亿」和「远超 1000 亿」时连爆了几句粗口。杰森追问，你真的说 Anthropic 值 3 万亿？加文确认。
至于市场能不能吸收，加文说市场其实已经在吸收了，这只是从私募市场转到公开市场，而公开市场本身更大。在 3 万亿里只发行一小部分，那部分是很容易被吸收的，全球资本市场吸收 500 亿的发行量不难。查马斯补了个数字：5% 的流通盘就是 1500 亿，够用了。
关于 SpaceX，加文说一件重要的事：所有 SpaceX 的投资人和员工，过去十年每六个月都有机会卖一次，所以他们可能不构成很多人想象的那种流动性墙。他提到读过一份纽约对冲基金的空头报告，说可以趁解禁做空 SpaceX，因为要卖的人太多。但几乎所有在册股东都有过卖出的机会，而且近一半 SpaceX 员工在 IPO 时买了股票。特拉维斯说他 2018 年就持有 SpaceX，每年有小的流动性窗口，去年的估值是 350 亿，一年涨了 8 倍，这种涨幅确实可能引发大量卖出。加文承认有这种可能，但员工是在新价格上买入的，而且很多人是通过 SPV 持有的，那些份额短期内不会解锁或分发。他也不认为马斯克会卖他那 50%。
聊到最后，特拉维斯开始感慨：还记得 150 亿美元曾经是多大一笔钱吗？这钱到底是从哪来的，之前都藏在哪？加文回忆当年在 Fidelity，他和同事给 Uber 定价 140 亿，被媒体骂得狗血淋头，说他们不懂行，结果半年后那一轮的估值到了 420 亿左右。特拉维斯纠正说其实是 170 亿。加文说他当时想要 140，双方大谈判。特拉维斯讲了具体做法：想要参与的投资人每人填一张表，写清楚在 100 亿、110 亿、120 亿一直到 200 亿各愿意投多少，然后做荷兰式拍卖，先说要融 15 亿，拍完告诉没拿到的人还有一次机会，大家改一改表，价格往上抬一点，就关掉了。那一轮从大概 90 亿或 100 亿起，最后停在 170 亿。几个人越聊越像在怀旧，说以前连融 15 亿都难，最后自嘲已经像两个老头了。
萨克斯在旁边插了一句调侃：还记得以前融 50 亿很难吗。加文最后提起他身后那件艺术品，说自己正住在一栋爱瑟顿的租来的房子里。节目收尾，互道再见。
这一期真正该带走的几件事
把三个话题串起来看，这期节目其实讲的是同一件事的三个侧面：制度、模型、算力，都在从「看起来稳固」变成「随时可能重排」。
- 别只看全国政治，去看初选和低投票率选举。纽约三个安全民主党席位、17% 的投票率，被一个组织度极高的少数派全部拿下。如果你关心政策走向，盯住地方初选、市议会、学校董事会这些低关注度战场，那里才是结构性变化真正发生的地方。
- 开源模型的追赶速度要按「几个月」来重估，别再用「几年」这个尺度。GLM 5.2 已经和当前可用的前沿模型齐平，成本低 85%。如果你的产品架构还没考虑「路由器 + 自家微调开源模型 + 前沿模型兜底」这套可组合结构，现在就是评估窗口。这件事只是让价值从实验室毛利转移到基础设施一侧，对 AI 整体是重新分配，谈不上灾难。
- 把 DRAM 当作未来两年最硬的约束来规划。内存占超大规模厂商明年资本开支的 30% 到 40%，消费电子的涨价已经开始。任何涉及硬件采购、自建算力、边缘推理的预算，都要把内存价格上行的预期算进去，并且把供应链协议当成风险对冲工具来谈。
- 拖慢美国 AI 的，其实是我们自己的审批时钟。萨克斯那套「白帽先找漏洞、快速升级周期」的逻辑，比封锁更值得记住。对从业者来说，凡是会拖慢部署的合规流程，都值得提前准备应对方案，因为监管的钟摆只会在两个极端之间摆。
- 关于分布式算力，分清训练和推理。训练要物理聚集，隔两公里就废；推理可以拆成 prefill 和 decode，分布式推理才是真正有空间的方向。如果要做，先想清楚房主、贡献者、验证者三方怎么分钱，这道算力题的经济账还没人解出来，谁解出来谁拿到一个泛美式市场。
文稿来自 All-In 官网（allin.com）发布的官方 Transcript，说话人按官网分轨数据标注，个别段落可能张冠李戴。
Jason Calacanis (00:00:00): Alright, everybody. Welcome back. Welcome back to the number one podcast in the world, the All In Podcast, episode 278. And, Freiberg, he took a mental health day today after the socialist sweep in New York City. So we invited two guests. They both said yes. Travis Kalanick is here from Adams. How are doing, brother?
Travis Kalanick (00:00:20): I'm good. I'm good. Good to see you.
Jason Calacanis (00:00:22): Good to see you. Good to see you. And after a triumphant week at Starbase, the one, the only, everybody's favorite, Gavin Baker of Atretes. Management, how are you doing, Gavin?
Gavin Baker (00:00:35): Great, man. Thanks for having me.
Jason Calacanis (00:00:37): You're still floating on Cloud 9 after the SpaceX IPO?
Gavin Baker (00:00:41): Yeah. That was a very special moment, and it was a culmination of, you know, decades decades of hard work. But, man, to quote, Bill Belichick on to Cincinnati.
Chamath Palihapitiya (00:00:52): Yeah. Yeah. Exactly right.
Jason Calacanis (00:00:54): Yeah. Zero zero is, the how the Knicks talked about the next game in every series. They're like, it's zero zero. We come into this as if it's like the first game of the series even if we're up two games or three games. The socialists have swept New York in the congressional democratic primaries. On Tuesday, New York City mayor Mondami went three for three in the candidates, which he endorsed, and they all won their primaries. 10th district leader Brad Lander defeated two term incumbent Dan Goldman. 10th is one of New York's richest districts, includes the West Village, all those townhouses, Wall Street, Dumbo, Cobble Hill, Carroll Gardens, Park Slope. That's some weird geography put together there. In New York's thirteenth, Chevalier beat a five term incumbent who's backed by house speaker Hakim Jeffries, and apparently, the socialists are coming for him. Thirteen is one of the poorest districts, Harlem and the West Bronx, the boogie down Bronx. She's a 32 year old democrat socialist with a history of spicy remarks. New York's 7th District, Claire Valdez, won the open seat over the handpicked successor, the incumbent. 7 is a DSA stronghold, Bushwick, Williamsburg, Long Island City, Greenpoint, known as the Kami Corridor. Lot of hipsters and baristas with suspenders in that neighborhood. According to our partners, Polymarket, this was a pretty big upset. The Mondami sweep. Chances were just 26 before election day. Yeah. That would be like the trifecta there if you were gambling. These candidates, just like Mondami, did a lot better with younger, college educated, and high income folks, the folks who can afford to be socialists. And these are all safe Democratic seats. The DSA will very likely win. So the DSA caucus
Chamath Palihapitiya (00:02:44): That's the best way you just said. People who can afford to be socialists.
Jason Calacanis (00:02:46): It's always
Chamath Palihapitiya (00:02:48): It's always the rich poors, you know, they're rich, but they pretend to be poor. It's perfect.
Jason Calacanis (00:02:52): I mean, this is the history of our country from the thirties, the fifties, Red Scare, Black Panthers, I mean, we'll get into it some up. But basically, if you're intelligent and you get into business, you become a capitalist. If you're super intelligent and you go into academia, eventually, you have the luxury of belief that socialism is awesome. What's your take here, Chamath? And then I'll go to you, Saxypoo, because I know I can see you're chomping on something over there. You're just ready
Gavin Baker (00:03:16): to go.
Chamath Palihapitiya (00:03:17): Honestly, I think that we are losing the script, and part of it is because we've been our own worst enemy. I'll just keep saying this that I think AI is a very good prism into this problem. I think AI is the greatest economic leveler we'll ever find in our lifetime. I think it's the thing that can create the greatest amount of equality. I think that it can even the starting line for every single person on earth. But we've done such a poor job in representing it, in bringing it to market, in talking about it. We've let all of our own personal trials and tribulations and insecurities and fights spill out into the open. As a result, Silicon Valley has lost even more credibility with the people at large. And in that vacuum, what other people can paint is a picture of how anything other than what capitalism looks like today is a better version of what they see. And this is why you're seeing, I think, a lot of these people get a lot of momentum. I think if you look at some of the key congressional races, they were a referendum on AI. And the good news is we were able to hold the line in some of these key places, but just barely. In Utah and in New York, there was a couple of very important races where it was essentially anthropic funded anti AI groups, which is, again, insane, against, in some ways, open AI funded pro AI groups, and the pro AI groups won.
Jason Calacanis (00:04:48): You just explained that it's a a great leveler. Can you give a couple of examples and just expand on that briefly? How is it a great leveler? I mean, I know, but, for the audience's sake, you've said this a couple of weeks now, so I think unpack it a bit.
Chamath Palihapitiya (00:05:01): The best way to explain it is I think that the first real major unlock of economic productivity was when the internet and specifically Google went and harvested and collected all the world's knowledge and all the world's information. And they made it available via search. What we figure out though twenty five years later, despite the fact that they built a great business, is what was missing was then being able to take that knowledge and information and transform it into expertise and intelligence. And that's effectively what AI does. It takes that world's knowledge and it allows you to act upon it so that every single man, woman, and child has an equivalent Travis Kalanick as his co founder, a super founder, this brilliant person that can think through all your problems, can out engineer people, can out think people. And they sit beside you and you have that. And there is no gatekeeping that can prevent you from having that. And so now you're only as good as your ability to direct that energy into something productive that you value. That is an incredibly powerful thing. And instead, we've gotten caught up in doomerism and jobs being lost and water being consumed, all of which are lies, all of which are complete fabrications and misinformation. And these have been created in order to specifically help one small set of actors inside the AI race, and it's been fed and funded by those folks. So in in this vacuum, Jason, we've allowed all these other people to paint the other version. And right now, the other version looks way more compelling than the current version because the current version has very poor brand ambassadors. Sachs,
Jason Calacanis (00:06:49): what's your take on this? I guess some people are looking at this as the left's version of the populist takeover that Trump did over the last ten plus years. What's your take on what we're seeing here with socialism and its amazing appeal, and it's winning at the election box.
David Sacks (00:07:09): I think there is some truth to that. I mean, I think the choices of the future are gonna be communism or if you wanna call it socialism of the Democrat party or nationalism in the Republican party. I mean, that is where we're headed. Those are the two populist directions. But let's look at what these DSA candidates stand for. So let's look at what their platform is. They actually say they want to abolish the Senate. They want to abolish the carceral state, that means basically police forces and prisons. They want to abolish ICE and grant amnesty for all. They do not support any deportations whatsoever. They want to replace the president and supreme court with an executive and judiciary that is chosen by and subordinate to Congress, which basically now, I guess, this means this House. And with respect to House elections, they wanna abolish the electoral college, they wanna replace the two party system with a multiparty democracy, and they wanna expand the house of representatives, implement proportionate representation, and ranked choice voting in all elections. So this would be a total makeover of our constitutional system. They want to free Palestine. They want public ownership of major corporations. They want to defund the Department of War. This is a very radical organization. And you would laugh at a lot of these types of proposals, but you can't really laugh at it anymore because these guys are taking over the Democratic Party. And you can see the Democratic establishment is in complete panic right now because they have lost control of the party, to Zoram Mamdani and his his allies. So, Jason, like you said, I mean, let's take this one race here, New York 13. You've got this ally of Hakim Jeffries, longtime incumbent congressman, Espalat, I guess is his name. He is the chair of the Congressional Hispanic Caucus, and he was defeated by an unemployed 32 year old PhD candidate. She's never had a job. She's been in college for ten years, I guess writing this PhD thesis. And I think even by DSA standards, she might be kind of a lunatic.
David Sacks (00:09:17): So she has declared that she wants to end Western civilization. She wants to eradicate Western civilization.
Jason Calacanis (00:09:24): Wait a second, what? We're soaking in it.
David Sacks (00:09:28): Yeah. She actually said she used the American flag as a napkin to clean her hands. Oh. She attended a rally one day after October 7 celebrating the slaughter of Israeli civilians. I mean, she's very pro Palestine, but even to the point of celebrating Israeli civilian deaths. She calls white women ugly colonizers. She's called for the complete defunding of the police and abolishing all prisons and borders, doesn't want a single deportation, hates the police, openly calls them pigs, or has on social media before, calls US service members war criminals, and says The US is a disgrace of a country. She's written favorably about communism and seizing the means of production and on and on and on. So this is basically the new Democratic Party. It's gonna be even if the Democrats do take the house in November and Hakim Jeffries becomes speaker, this is gonna prove to be a huge headache for him managing all these new DSA members. Because they do not actually see the traditional establishment wing of the Democratic Party as an ally. They see it as an obstacle. This is the DSA co chair Josh Bloch said, we're using the Democratic Party as a ballot access vehicle
Jason Calacanis (00:10:42): Oh my god.
David Sacks (00:10:43): Not because we share its goals. We build our own organization, get elected under the Democratic label, caucus with Democrats when it's useful, and push our own agenda from the inside. We see the Democratic establishment as an obstacle, not a home. So the DSA is coming from the Democratic Party. It controls the base now. It's where all the energy is. I think this takeover will continue. I think the DSA will gradually take over more and more of the Democratic Party. And all I can say to these establishment Democrats is play stupid games, win stupid prizes. You supported this open border policy that brought in this wave of mass migration. That is a huge part of the base of this new DSA wing. Ma'am Donnie would not have won the mayoral election in New York if it had just been native born New Yorkers voting. It was the mass migrant vote in New York that swung it to Mam Donnie. It's not exclusively the DSA base, it's the migrants plus these overeducated white progressives who, I say overeducated because they're more downwardly mobile, they end up going to work in academia or NGOs, that kind of thing. They're hard left wing, They're kind of the vanguard, and it's this combination of these, you know, recent college graduates who are kind of the organizers and this migrant movement who are really taking over the Democratic Party. But again, this all goes back to Democratic Party policies. They may not have intended for the staff, and they may not have intended for them to lose control, but it was their open border policy. It was also the fact that they have cracked the melting pot, and the policy we had for many years in America of assimilating migrants, right, immigrants. Yep. That all got cracked by multiculturalism and wokeism. We don't really do that anymore. So now you've got these candidates like Chevalier openly declaring they're not just anti American, they're post American. They don't have any respect for the American system, our constitutional order, our free enterprise system. They want to introduce something in much different, and it's gonna look a lot like the countries where these migrants are coming from. Yeah.
David Sacks (00:12:52): So, again, you know, if you import massive numbers of migrants, don't assimilate them into our system, and then you have these Marxist leaders, you're gonna end up with the American system coming to resemble the countries from which
Jason Calacanis (00:13:05): It's really interesting. Migration. Mentioned, like, how she wants to get rid of all of these, delete all of these units. It's very similar to Trump's, he wanted to delete a separate set of things, the IRS and USAID, Department of Education, EPA, they each use that playbook as well, like, hey, we're gonna delete some of this stuff. Travis, you famously had the fountainhead?
David Sacks (00:13:28): Trump didn't wanna delete the US constitution.
Jason Calacanis (00:13:31): No, definitely not. Travis, you're used to
David Sacks (00:13:34): Slight difference.
Jason Calacanis (00:13:34): Slight difference, I agree. He didn't wanna delete western culture.
David Sacks (00:13:38): I don't think he wants to delete Western culture. No. You might wanna delete USAID because it was a festering, it was basically a front for all these
Jason Calacanis (00:13:47): N CIA.
David Sacks (00:13:49): Yeah. By the way, you may you may have noticed that in South America, we've had seven elections where the countries have swung to the right. And I think a big part of the reason why might be you don't have the USAID there conducting all these left wing regime change operations.
Chamath Palihapitiya (00:14:06): Payola's Payola disappeared. Yeah. And the incentives disappeared with it.
Jason Calacanis (00:14:12): Travis, you famously had The Fountainhead, Ayn Rand's novel as your Twitter avatar for a decade or two.
Travis Kalanick (00:14:20): Don't if that's your take No. They've been writing about it for a decade or two. This is like a six month thing where I would read a book and then rotate at my avatar.
Jason Calacanis (00:14:29): Yeah.
Travis Kalanick (00:14:29): Yeah. I had Hamilton for a while. I had Ender's Game for a while, but, yeah, it became And mean, you Yeah.
Jason Calacanis (00:14:35): Having known you for a while, I think, believe in the individual and their exceptionalism and and trying to Sure. Have a little ruggedness there. This is obviously the the exact opposite. What's your take on what's happening in these pockets? Because it's not national yet, but it's definitely notable.
Travis Kalanick (00:14:55): Alright. I've I've got I've got sort of two aphorisms for us. Okay? First is truth and justice is the immune system for society. When the immune system is suppressed, all the social ills flare up, Okay? So if you're seeing us losing truth like social media, mainstream media, whatever you call it, that's an early indicator for bad things happening in society. Okay? And it's not just like social media mainstream media, it's just everything around us. And the same on the justice side too. If people commit crimes and there's no consequences, it's a nice early indicator. So you can kind of watch you can watch these things and say, is truth winning today or is it losing? Is justice winning today or is it losing? And what is the trajectory will tell you, are we gonna get worse or are we gonna get better?
Jason Calacanis (00:15:58): Right. COVID makes and and the Fauci case, now we're seeing a lot more information come out. We have a really hard time getting the truth, and maybe we'll get justice eventually. It seems like we're getting a little more truth five years later, but it's like a perfect example of what you're discussing. Yeah.
Travis Kalanick (00:16:11): There's a lot packed into that, but you can unpack it. If we had a lot of time, we could unpack it. But those become the sort of atomic things that you look at. And then the other thing I'd say, and and some people get a little surprised when I say this, which is communism is in is in all of us. Communism is in is in our blood as humans, And people go, what the hell are you talking about? You're crazy. What do you mean? Well, I'm like, well, have you have you ever in your life been lazy? And everybody's like, yes. I've been lazy in my life before. I said, have you ever in your life wanted something for nothing? Yeah. The difference is do you make that a way of life? And when you have ecosystems that essentially allow you to do both of those things without consequence, those ecosystems get a critical mass and start taking hold. And I think that's what we're seeing.
Jason Calacanis (00:17:10): Well said. Yeah. I think it's well said. Gavin, I I know you I don't know you to talk too much about politics, but talk about markets, but these two things do relate, I think. So give us the economic perspective here on why this is happening because, obviously, different generations have had different economic experiences. So I don't wanna lead the witness here, but I have had conversations with you about this before.
Gavin Baker (00:17:34): Yeah. Well, so I do think, I risk obviously, AI is, think, going to be the defining political issue in the midterms and for sure the the next presidential election. But I feel like what is going on with the DSA is really a fusion of two things. So the Democratic party I I I was a Democrat for most of my life, and it was the party of the working class people that was trying to create opportunities, you know, maybe level out, equality, you know, help black Americans, help Hispanic Americans. And, you know, you can agree or disagree with their methods, but I think those are all noble goals. And to a large extent, none of those are really present in the DSA. None of them. If you look at who voted for which candidate, the p the voting base of the DSA are relatively wealthy white liberals who are downwardly mobile. They're losing votes with working class people. They're losing votes with poor people. They're losing votes with black Americans. They're losing votes with Hispanic Americans. And those you know, the the the people that the Democratic party, I think, for a long time tried, and whether they failed or succeeded is up to tried to represent and give a voice to. They are not of interest to the DSA. And I think the DSA is is dangerous. It's tragic that we are electing profoundly anti American candidates who, in some cases, have called for violence, to eradicate America. And I just think there's there's a whole class of people who went to an elite school. They grew up in really nice circumstances. And, instead of going into industry, they went into this kind of giant NGO nonprofit machine, and their outcomes have been very different from people who did productive things for the world. You know, I've said on the show many times, Elon has done more to decarbonize the planet than every activist combined.
Jason Calacanis (00:19:57): Yeah. Time's 10.
Gavin Baker (00:19:59): Yeah. Time's 10. And I think these NGOs and the fact that the government is increasingly outsourcing a lot of funding to them is a really big part of this problem. And they are pursuing policies. You know, I think we talked maybe we talked about it last time, but the curly effect, a mayor of Boston, you pursue policies that you know are going to be disastrous for this your constituents, but they drive out your rivals. And then you can give jobs, $600,000 a year jobs, running an NGO that does nothing productive to your friends and allies, and it's really organized corruption happening at a massive scale. You know, the one thing whatever whatever you wanna say about the Trump administration, a lot of people are up in arms about this, you know, new plane he's getting from Qatar. Well, one, sounds like we needed a new plane, but two, it's right there for you to see. I think there are tens of billions, maybe hundreds of billions of these payments flowing to these NGOs. And if you look in California and New York, it's like, I think the per capita spending on homelessness has more than doubled, and it's all gone to NGOs, and outcomes have gotten worse. In California, it's, like, quadrupled, and outcomes have gotten worse. So I think this is this is dangerous, and I hope that the mainstream democrats can find a compelling candidate. Because I think the reason that the DSA is increasingly ascendant is not because of their ideas. I think their ideas appear to this appeal to this very narrow subset of doubly mobile, rich white people who, you know, increasingly maybe live in, you know, quasi genteel poverty because they they're not doing productive things. They may be well intentioned, but they're not doing productive things and can find a compelling candidate because I think the reason they're ascendant is Zoram Mamdani.
Gavin Baker (00:22:08): I think he is one of the most talented politicians I've ever seen in my lifetime. You know, he can give a great speech. He's good in an interview. He can tap into all of this. He's kind of a chameleon who can shift. But I think he is a singularly talented politician, and he is the reason that the DSA is ascendant. Not their ideas or not dissatisfaction with AI, but it's him. And there is no one else in the democratic party. I used to think AOC was by far the most talented democratic politician.
Jason Calacanis (00:22:44): That was the warm up.
Gavin Baker (00:22:45): Yeah. She was talented. She's
Jason Calacanis (00:22:47): Yes. Clearly.
Gavin Baker (00:22:48): Like Zuran from a political
Jason Calacanis (00:22:49): experience. Is clearly talented and if you combine his charisma and ability to communicate with generations, like we're now like f two of these lost generations that feel like they're gonna do worse than their parents. And if you look at housing and college debt, healthcare, they don't believe that they can participate in the system. They feel the system's rigged. And if somebody comes along who speaks to them and they have no conception of socialism and what happened you know, in Germany or during the Red Scare. They have no idea what socialism or communism is. They have this incredible wrapper they put around this, which is, you know, they're democratic socialists. It's like it's it's the Coke light. It's a Coke Zero of socialism. It's actually just communism. They want to literally seize people's assets. They wanna seize half of these company stock, they wanna seize their wealth. They just want to take from the people who have made stuff as we talked about last week, and we've done nothing to change their mind. We haven't made more houses. We haven't made college more affordable. Health care is a disaster. Inflation's a disaster and starting pointless wars. Obviously, the support of Israel is somewhere in here as part of
Chamath Palihapitiya (00:24:02): all something?
Jason Calacanis (00:24:02): Yeah. Short course.
Chamath Palihapitiya (00:24:04): I was on Megyn Kelly yesterday, and I had this theory that I've been kind of working through. And I'll just share it with you guys because I'd love your reaction. If you look at the scourge of socialism, if you take the rhetoric away and you actually look at the outcomes, there are three countries that I think have veered far towards socialism well before The United States, Canada, The UK, and Australia. And I think when you look at any sort of reasonable measure of their progress, it's been an unmitigated disaster. So all of the virtue signaling on social issues, all of the virtue signaling on immigration and open borders, all of the virtue signaling on climate change has left each of those three countries in some state of disrepair with enormous amounts of infighting, tremendous political instability, they are all sort of powder kegs. And there's an interesting thing that happened in each of those three countries that I think has the potential to turn the tide. And it speaks to what Gavin said. Each of those three countries now have banned social media when you're 16 and under. And I think it's sort of like making sure the kid doesn't get addicted to the drug too early. And when you look at somebody like Zoran Mamdani, I think Gavin is right. I'll go even further. AOC, the lady that just won
David Sacks (00:25:35): Chevalier.
Chamath Palihapitiya (00:25:36): Chevalier. Let's just break it down. They're all good looking. They're all charismatic. They have their pulse on the gestalt of the moment. They know how to use social media, and they are essentially curating an army. Now, if you cut the legs off by saying young people should actually age into social media, I suspect that the most important channel of information consumption being taken away from them actually starts to give them the opportunity and the rest of us, quite honestly, because we have to deal with kids who are just really stupid constantly asking for this stuff, the chance to actually show you how a balanced diet actually allows you to be much healthier in your later life. And I think as it relates to information consumption, I think you are going to see, I suspect, a far less radicalized youth aging into the voting roles in those three countries. And I suspect if you start to see political stability and predictability in Canada, The UK, and Australia, you can put your finger right on this ban as the reason why. And Florida's already done it in The United States, and I think we need to deeply consider it across the rest of The United States.
David Sacks (00:26:49): Can I
Jason Calacanis (00:26:49): Social media ban is now starting at 16, Canada has it? It may come to The US. Go ahead, Travis.
Travis Kalanick (00:26:56): I'm a full counter to Chamath on this one. I I think we all agree social media is bad for the kids and for the adults. Like, too much of that stuff is very bad. It's brain rot for real, and it's gonna be worse than cigarettes. It's all the things. But the real point of banning 16 is so that you can force adults to identify themselves and de anonymize themselves so you can set up a full scale censorship regime, which they're sort of contemplating in The UK. And what censorship is really about is not about harmful content. It's about content that the people in power don't want you to see, that disagrees with them. If it agreed with them, it's not harmful. It's the stuff that doesn't agree with them. And so what they're doing is they're criminalizing disagreeing with them. And so there's a derivative of this age based
Jason Calacanis (00:27:53): stuff Age gating.
Travis Kalanick (00:27:55): Which is really about the adults, not the kids.
Jason Calacanis (00:27:58): That is the downside to it. Gavin, you wanted to add?
Gavin Baker (00:28:00): No. I super agree that I think that a social media ban under 16 would be great, but I think it comes at a really high cost outlined by Travis. And that's what's really going on is they want to restrict anonymous accounts on x who say things that particularly the powers that be in the EU do not like. And if there's a way to do that while preserving anonymity and free speech, I'm all for it. But I think if if it were not for free speech and and x, like, I think we'd be living in a very different world today that would be a lot worse. And just to riff on a few things that that all of you have said, you know, on communism, it is communism and the great tragedy of human experiences we can't learn from the experiences of others. And it may not matter that communism has failed utterly and ended in death and misery wherever it has been tried in a variety of different cultures with a variety of different mechanisms, and every generation may need to experiment with it. I think the the saving grace and the importance of preserving free speech is that the DSA's policies, and I would say, in particular, super progressive democratic policies, are measurably bad. They lead to bad outcomes. If you care about black lives, there's a study that is uncontested that when you elect a Republican DA, all cause mortality for young black men in that city drops by seven percent. That's all it takes. Yeah. You care about the environment? Well, progressives, there's so many regulations that you can't build solar, which is really the only thing that matters and, like, the world is gonna run on sunlight. You care about education? Their approach to education of getting rid of these elite schools that allows low income people to have a real chance, you know, getting rid of math in California, It is profoundly disadvantageous to people. It leads to terrible outcomes. And we all know what happens with crime. It turns out that there's a certain percentage of people who, you know, are I think it's, like, 60 over 60% of the violence or 75% of the violence comes from people who have, like, 10 or more convictions.
Chamath Palihapitiya (00:30:24): Yeah. I think the specifics that is, like, point 1% commits 70% of the crimes. And if you just dealt with the point 1%, you Yeah. Effectively no crime.
Gavin Baker (00:30:33): And so I just think the scary thing is and I do worry for the first time, like, a student of history, The United States has been, like, a very stable political economic entity, geographically stable for a long time. And that's to its credit because we could have literally taken over the world after World War two. But, man, if they get total control of some of these cities and drive out everyone who is productive, I don't know how you come back. And so that's that is a little worrisome to me in terms of the future of of The United States.
David Sacks (00:31:11): Well, and by the way, I I I don't think it's just New York. I mean, that race for mayor in LA where was it Rahman somehow beat Spencer Pratt, thanks to ballot harvesting after voting day? Or I should say votes that were found and counted after election day. I mean, that will be a test of the DSA because they are highly organized and they have learned how to take advantage of all these rules, these ballot harvesting rules and all these types of things. The DSA, I think they've got something like half the city council seats now in LA, and they're growing. So especially in these low turnout elections and look, this was a Democratic primary in New York, which is a strongly blue state, so I think maybe 17% turned out. So it was very low. But this is where the DSA really thrives and excels because they care passionately and they're highly organized and they know how to take advantage. This is why they want all these like ranked choice voting and all these types of things. They know how to manipulate and take advantage of those kinds of systems. So I think that you're gonna see this in lots of other jurisdictions. Wherever they're organized, I think LA will be a really interesting test. So I don't think we can just chalk this up to Zoran's popularity, you know? This is a national movement, and we're gonna see it in a lot of places, but there's no question that Mamdani is now kind of the spiritual leader. I mean, all of these people don't, they think AOC is a sellout, you know, or Bernie is a sellout. You know, they are way more radical than even those types.
Jason Calacanis (00:32:41): To add to that, Saks, they did learn something from Trump, which is builds a big tent. So you're seeing Bernie, Mundamy, Ro Khanna. They're all kinda like, yeah, we're different, but there's enough room in this tent.
David Sacks (00:32:52): Well, what's happening is that these sort of more established progressive leaders, they wanna tap into this energy. And even the establishment wing of the Democratic Party is now bending the knee. And so what you're going to see is, regardless of how many DSA candidates actually get elected, the rest of the party is now responding to this, and they're going to bend, and they're going to blow in this direction because they don't wanna get challenged in a primary. I mean, think about this. You had three major congressional races where the Mamdani candidate won. Two of them unseated, you know, really strong incumbents. These were big upsets. So you gotta think now that every congressional race in a pretty blue district, those members are now gonna have to take into account that they could get primaried, and they're gonna have to tilt their voting and their views and their rhetoric in this DSA direction because they don't wanna have happen to them what just happened to Dan Goldman in the New York 10th District. And just to make one last point on that. So, J. Cal, you mentioned the the Israel issue, and I actually think that is a hugely important and salient issue now in the Democratic party, in Democratic primaries. Obviously, you saw that as part of the DSA platform, one of the legs is free Palestine. This defeat of Dan Goldman, two time congressman, he led the the impeachment effort against Trump. He had all the right progressive credentials. He checked the box in all the left wing policies. He was on the right cable news channels all the time. No one expected him to lose. He lost to Brad Lander really just over this issue of Israel. Dan Goldman is is very pro Israel. He basically defended Israel's actions over the past few years, whereas Lander, who, like Goldman, is also Jewish.
David Sacks (00:34:38): So this was, again, you know, white Jewish congressman against white Jewish longtime New York politician. So on paper, they're very similar. It was just in this issue of Israel where they disagreed, and Lander went to a mosque in order to denounce what he called the genocide in Gaza. So this was really as close as you can get to a straight up vote on that one issue in this primary, and Lander won pretty handily. Now the reason for this is if you look at polling, 80% of Democrats now say they disapprove of Israel. So, know, the approval disapproval rating. Israel used to have high approval ratings pretty much across the board. I mean, it was sort of a consensus, both Democrats and Republicans. Now 80% of Democrats say they disapprove. You really can't underestimate how much of a motivator this is for young Democrats. Believe Well, we
Jason Calacanis (00:35:30): that thought they were all over campuses, Saks. We see it. I mean, it it draws people out, and it has been quite polarizing, just to call balls and strikes here, inside the Republican party as well. You have Tucker leaving the party over this. You have Mac and Kelly going mental over this, and you have, you know, a lot of civil war inside this administration, according to the report. So this is Well, the
David Sacks (00:35:50): let me let me let me look. I mean, I'm not taking a side in this. I'm just trying
Gavin Baker (00:35:53): to describe
David Sacks (00:35:53): what's what's going on.
Jason Calacanis (00:35:55): Absolutely. Same as me.
David Sacks (00:35:56): I think the Republican Party is a little bit more mixed on this issue, and it really comes down to age. So if you're part of the older, more establishment Republicans, let's say you're a Fox News viewer, you still have high approval ratings for Israel. But if you're under 50, which means you're probably not watching Fox that much anymore, you're probably onto the podcast, I think the the disapproval rating for Israel is now 57%.
Jason Calacanis (00:36:20): Interesting.
David Sacks (00:36:20): So it really comes down to age. Young people across the board have serious problems with what Israel is doing, and then, you know, as you get into older age groups, that's where you see a big difference between And to
Jason Calacanis (00:36:31): be Democrats clear, and I think Chamathi did a wonderful job of explaining this on Meg and Kelly. There's Jewish people, there's the state of Israel, there's Israelis who live in the state of Israel who are also Jewish, and then there's Bibi Netanyahu. And I think there's a lot of concern on Bibi Netanyahu is just absolutely out of control is the consensus. I think amongst many people across many religions and and political parties.
Chamath Palihapitiya (00:36:55): Not to reash this whole thing, but there are a lot of parallels from what happened in 10/07 and what happened in 09/11 in the following ways. When you invade a country and you slaughter their people, it creates an enormous injury, an enormous emotional, physical, psychological injury. And what that country typically does is respond by giving the authority to the leader at that time to set the table right. And you have to remember, there was a lot of things that happened post nine eleven that under any other circumstance would never have happened. At the top of the list would have been the Patriot Act, which in any other world would never have gotten past and would have seen the light of day, but not for nine eleven. So there are moments where leaders are put in a position and they essentially act on behalf of their country and their people to right a wrong. I understand that. I think everybody understands that. What's happened now, though, is that people cannot logically disambiguate Jews, Israelis, and Bibi. And I think that's very unfortunate because we're at a point in time where everything gets conflated, and this thing has become this third rail issue, and I find it absolutely shocking. It's completely reasonable for people to have a point of view on Bibi and say, hey. You know what? It's enough, or it's gotten too far, or whatever it is. And I think that there's a very reasonable claim to make that it's time to find different leadership, new leadership inside of Israel, and have an opportunity to reset their standing on the global stage. They deserve that. The Israeli people are incredible. Jews are incredible. But the idea that you fold it all together and you look at one person and then you apply it to an entire country and an entire religion is insane.
Gavin Baker (00:38:47): May I add one thing?
Chamath Palihapitiya (00:38:49): May I
Gavin Baker (00:38:49): add one Yeah. Is I think there's well well, two things really, and I'll be quick. One, Israel has a giant PR problem. They need a young sub 33 year 35 year old American Israeli who's super fluent in English, conversant in social media, and is their kind of spokesperson to America. And they need that in France, in Germany, in every country. And they do not have that. There was a young I think his name I forget his name, but there was a young Israeli who was doing a really good job, Israeli American representing Israel after October 7, and, evidently, Bibi Netanyahu's wife didn't like him, so they canned him. And they've never really found a a replacement. And I do think this is an urgent issue for Israel because it's like they are taking body blows every second, and they're not even responding. And what I think they do what they tend to do is they'll sometimes roll out someone who's a great man or woman in Israel and is in their sixties and a hero of a war, but isn't that fluent in social media. Maybe the command of English is, you know, technically precise, but there there's an accent. And those are great people, but they're not great spokespeople spokespersons, and this is an urgent issue. As far as the antidote, going back to Jamas' comment, I do think a big reason Trump got elected, every democrat many of the democrats I know who voted for Trump, a big part of it was that during COVID, they heard what their children were being taught.
Chamath Palihapitiya (00:40:25): It was the first time.
Jason Calacanis (00:40:26): And it
Gavin Baker (00:40:26): was radicalizing for them.
Chamath Palihapitiya (00:40:28): Yeah.
Gavin Baker (00:40:28): And I think it's just really important that, like, as part of the American educational system, just they're not be overtly anti American things. Listen. We've made mistakes as a country. We're not perfect. We're about as good as it gets, and we need to tell that story in every grade consistently. And we can have a debate. We've done so many things wrong. Let's learn from them. But just, you know, slavery was endemic to the world apart from some countries in East Asia. Like, it's not a uniquely American problem. And we need to tell those stories because I think a lot of kids, the reason they're so susceptible to this social media propaganda is they've been brought out being ashamed to be American, ashamed of various things in their identity, and being told that America is evil. And we need to unwind that because America is awesome, and we're the only vaguely successful multicultural society on planet Earth.
Jason Calacanis (00:41:29): Yeah. The melting pot. And if you say that, Gavin, if you say the melting pot is a beautiful thing, you're gonna get canceled because, oh my god, you're getting rid of people's culture. It's like, no. No. Keep your culture and then join this culture, and we can all have this great smorgasbord. Yeah.
Chamath Palihapitiya (00:41:44): You you know my culture is? You know what my culture is?
Travis Kalanick (00:41:46): I don't know.
Jason Calacanis (00:41:47): It's no longer Laura Piana. I know that. I know you're off the train. Winning. Winning. The culture of winning. I love it.
Chamath Palihapitiya (00:41:54): Learn it. Learning. Progress. Adventure.
Gavin Baker (00:41:57): Jamal, do you piss excellence to quote
Chamath Palihapitiya (00:41:59): quote Ricky Bobby? Oftentimes. I piss excellence. Just sometimes it burns, but oftentimes.
Travis Kalanick (00:42:06): Just to warn funny too.
Jason Calacanis (00:42:07): Just to warn the dopey democrats who have been unable to get anything done, the socialists are using your party and this guy went viral. They're just a host. Like they literally want to infect the oh yeah, good image. They wanna infect the Democratic Party and then, like, just literally get the voting base. And this guy, Gustavo Guardillo, don't know if you guys saw this, he's a DSA co chair in New York City, and he just said it outright. I was gonna read you the quote. We're part of the Democratic Party caucus, but we don't agree with the way the Democratic Party runs its apparatus. So we're trying to build our own independence by focusing on volunteer led movement. We think everyone should be able to be trained and become someone who can participate the in political process, and we don't think the Democratic Party is run that way. In terms of the agenda, there's a problem in the Democratic Party. They are funded by billionaire donors, and at the same time, they're trying to represent the working class. In our opinion, you have to choose between the billionaire class and the working class. They are just taking over the party. And again, back to the playbook. This worked really well for Trump. He took the Republican Party over, and he owned them. And they tried to get him out. They tried to get him out. But his message and his communication style was just too on point. He knew exactly what people wanted to hear, and he knew exactly how to deliver it. He is a all time comedic performer. Like, of non of non comedians, he's the number one comedian in the world, and of actual comedians, he's in the top 20. So he communicates perfectly, and that's exactly what Mondami's done. He's taken the Trump playbook, and he has applied it here. He is taking over with this communication. You guys know I'm a diehard Nick fan my whole life. Cried. It was at game five when they won the finals. And then Mondami gave this speech that somebody wrote for him about the Knicks, and I was just absolutely flabbergasted and upset that it was so great. He's got that Obama Trump charisma, and he is going to destroy your party from the inside out.
Jason Calacanis (00:44:01): Socialism is communism, and it is the road to suffering and pain, as Gavin said. No good will come out of it.
David Sacks (00:44:07): Isn't it amazing?
Jason Calacanis (00:44:09): Here we go.
David Sacks (00:44:10): You know you know Mam Donnie is a communist, and what he represents is Of course. Evil. And yet, because he just gave a speech about the Knicks, you love him now.
Jason Calacanis (00:44:20): No. I love the speech. I'm like, why do the speech?
David Sacks (00:44:23): That's it takes. We're screwed. That's all it takes.
Jason Calacanis (00:44:26): It's true, though. If something's a good
David Sacks (00:44:29): this guy, he's a total phony. I mean, he doesn't stop smiling. He's got this crocodile smile all the time. He's talking about eating you, and it's totally fake. Absolutely. I mean, come on.
Jason Calacanis (00:44:40): To be able to see this. He making Nicks references, and it was the most get out of your seat, standing ovation, cheer speech I've ever heard about the Knicks, and I was infuriated. This guy is such a good orator.
David Sacks (00:44:54): You got programmed.
Jason Calacanis (00:44:55): I hate him.
David Sacks (00:44:55): We're gonna have to deprogram you now.
Jason Calacanis (00:44:57): No, no, no. It was like getting hypnotized and I just pulled myself out. Got pulled in Never. For a
David Sacks (00:45:04): Next topic.
Jason Calacanis (00:45:05): Next topic, for sure. My God, great, good, strong first topic. I didn't know you guys were gonna go all in, so to speak. Topic two, Chinese open source models appear to be catching up with The US frontier models. Let's start with a GLM 5.2 released by China Z dot ai. This is a frontier class, open source free to download anywhere model, seven forty four billion parameters, 1,000,000 token context window, and it's under the MIT license. If you don't know what that is, open source licenses have
Travis Kalanick (00:45:36): very Super open source.
Jason Calacanis (00:45:37): It's super open source. Thank you.
David Sacks (00:45:39): The most open source.
Jason Calacanis (00:45:40): The most open source of all open source. If you open it up, you can use it however you like. You can fork it. You can build your own company based on that. No regional restrictions. No API. Fully self hostable. No Dario.
Travis Kalanick (00:45:55): It's just yours.
Chamath Palihapitiya (00:45:56): It's just yours.
Jason Calacanis (00:45:56): It's yours.
Travis Kalanick (00:45:57): It's just yours. And you just gotta reference the license. That's it.
Jason Calacanis (00:46:03): Yeah. You shout out the license and you're good. Scored 51 points on the artificial analysis intelligence index. That's the highest score of any open weight model ever. Stacks up nicely next to the Frontier models, BGPT 5.5 on the Frontier SWE coding benchmark, that's a software one. Trails Clawd Opus 4.8 by less than one percentage point. API usage cost, obviously much cheaper, 85% cheaper, in fact, than GPT 5.5 for comparable performance. Z dot AI founder told Elon Musk, open weight fable capabilities will be here sooner than q one twenty twenty seven. Gavin, in other words, all this hand wringing, all of these legal restrictions, self imposed restrictions are now completely or close to completely moot if they're going to have a model in q one. Does this six months even matter? Does six months in the grand arc of AI matter or not? And what does this mean for frontier models?
Gavin Baker (00:47:01): I do think how good GLM 5.2 is has challenged some of my beliefs. And there was a great post from a TPU engineer that for sure, distillation has happened. There's been an immense amount of distillation. No question.
Chamath Palihapitiya (00:47:16): No. Please explain to the audience what that means.
Gavin Baker (00:47:18): Distillation is when you have, you know, a a like, you know, we all have seen videos of these Chinese iPhone farms. Just picture a farm like that, tens of thousands of phones, iPads, and computers that are asking the Cloud API through masked accounts very specific questions, and then these what's called reasoning traces are being harvested. Because if you're on the API, you know, you get to see every token. And those reasoning traces are then fed back into the model during the reinforcement learning process and probably during the pretraining process. And that is a way that you can get really, really close to the frontier at a fraction of the cost. And this is for sure going on and has gone on for a long time. I do think It's
Chamath Palihapitiya (00:48:09): a cheat sheet. It's a cheat sheet for other models to catch up.
Travis Kalanick (00:48:12): It would be like asking Google every question you could ever imagine, every search imaginable, getting all the results, and then putting your own search engines together to make it very simple.
Gavin Baker (00:48:21): Exactly. But now that this model is so good, it is good enough to do its own RL. And, you know, the kind of cat may be out of the bag. Now I don't think we really know how good Mythos is. We don't really know how good the no Next OpenAI model is. We haven't seen the next SpaceX model. So maybe that gap opens up again. But either way, I profoundly believe the future is composable models. And you're going to every enterprise. You're gonna have what Andre Karpathy called the council of LLMs. You're gonna have you're gonna have Grok. You're gonna have Anthropic. You're gonna have OpenAI, Google. You're gonna have at least two of those. I would argue Grok should always be one of the two because of its dedication to the truth, and it will tell you as a business owner a politically inconvenient truth that you need to know for your data. But you're also going to have your own open weights model that URLed on your data, and you're gonna put those two together, the frontier models in your own model, and you are going to get, you know, real Pareto dominant outcomes. And, you know, half the queries are gonna be go to the open source model, maybe 85%. And only the hardest ones are then maybe they all go to open source first, and only the hardest ones are then checked by the frontier models. So I think this is the future. It's coming. And a misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure. And that's not bad for AI.
Chamath Palihapitiya (00:49:59): That's great for them.
Gavin Baker (00:50:00): It's great for them.
Chamath Palihapitiya (00:50:02): Great But for
Gavin Baker (00:50:03): I do think there's still a role for these frontier models. And it may be true to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed. And those ratios may be here to stay, but I just think composable models are the future.
Travis Kalanick (00:50:22): What does that mean composable model?
Gavin Baker (00:50:25): A composable model where you have if you're a corporation, if you're is there is there a new name for your super secret, startup, Travis? What's the new name?
Travis Kalanick (00:50:37): The name is called Adams. It's not super secret. It's super awesome.
Gavin Baker (00:50:42): Super awesome. Super awesome. For your super awesome startup, Adams, which man, lots people have been calling me to say how, like, they've been in the, you know, they've they've spoken to you and Yeah. Investor the, your your dog is hunting with investors, Travis.
Travis Kalanick (00:50:59): Alright. Fair enough. Fair enough.
Gavin Baker (00:51:00): Okay. You're going to have a router, and every query that somebody comes in, task that needs to be done at your company, that router is gonna send it to, you know, your RLSFT version of yours, 5.2 or Demotron.
Travis Kalanick (00:51:16): Yes.
Gavin Baker (00:51:16): Then at some point in the workflow, a frontier model may or may not come in to kind of check it, add to it. And that's what I mean by a composable model when you have kind of, you know, kind of a symphony of models working together with kind of the frontier models being, you know, maybe the. But that's what I mean when I say composable.
Travis Kalanick (00:51:37): Yeah. Understood. Thank you.
Jason Calacanis (00:51:39): Sachs, formerly AI czar, and now running PCAST, what are your thoughts on China's ascension in open source? And we're still looking for our open source champion, obviously, here in The US, but feels
Gavin Baker (00:51:53): like Hold me. Can I just say one thing? NVIDIA is the American open source champion.
Jason Calacanis (00:51:57): Thank you. Yeah.
Gavin Baker (00:51:58): They can release GLM 5.2 or better whenever they want.
Jason Calacanis (00:52:02): Okay. But why haven't they done that? They don't wanna screw their customers too much of a conflict to be, like, pushing it out there too often?
Gavin Baker (00:52:11): All of the above. Who knows? We'll see.
Jason Calacanis (00:52:14): Okay. Yeah. And you you gotta be delicate there. I see. Okay. So I'll say it, not you. Jensen, does it yeah. I mean, it's it's a it's a classic channel conflict. Right? You're you you don't wanna compete with your customers, and he is competing with Elon on self driving now, and Elon's making his own chips. So
Gavin Baker (00:52:30): I think these frontier model companies should think very, very carefully about ASICs and the incentive that creates for NVIDIA. On the model perspective
Jason Calacanis (00:52:40): If OpenAI, which launched their jalapeno chip this week and announced it being built by, I believe, Broadcom, And they are saying, hey, f you to Jensen and NVIDIA, and they already were full contact with him. Don't be surprised if NVIDIA says, you know what? We kind of like the area you're operating in now that you're gonna make chips and maybe OpenAI sells those chips to other people. Don't be surprised if NVIDIA starts an OpenAI competitor. You heard it here first on all in. Saks, did you wanna jump in there?
David Sacks (00:53:12): Sure. I mean, look, I think that China's been good at open source for a while here. There's nothing new about that. But there are a few things that are significant about GLM 5.2. So the first one is it is now, like you said, the best open weight model for coding, software engineering, and long context agent work. And you gave a couple of the SWE bench scores. I mean, it was just a tick below Opus 4.8, and it was right up there with GPT 5.5. So if you compare this to, again, the state of the art, the frontier models for Anthropic and OpenAI, it is right there with the previous model. But you have to remember now that the current model, Fable for Anthropic and 5.6 for OpenAI, is now in a little bit of a purgatory because of all the reasons we covered last week. Now look, I like I said last week, I ultimately blame Dario and the way he communicated and the way that he primed officials to be on a hair trigger with respect to these models. And when the government got a credible report about a jailbreak from, you know, one of Anthropoc's most trusted partners, you're gonna say roll that back. But that is the situation we're in right now is that Fable has been rolled back and GBT 5.6 is trying to navigate these new approval hoops. So we now have a Chinese open weight model that is as good as the currently available models from OpenAI and Anthropic. And look, this is a point I've been making really since I joined the administration is that we are in a very competitive situation with China. I've been saying this from the beginning. Our whole AI strategy from the get go was about winning this AI race, defining it as a race, as being globally competitive, and we cannot afford to do things unnecessarily that slow our companies down. I hate that either.
Gavin Baker (00:55:16): David, can I ask? Do you think Dario got exactly what he wanted? It seems to me there's some chance, this has been a very calculated strategy, to provoke the US government into doing what they just did, and this is what he wants. He has a regulatory moat now. He can keep his future models behind this. You know, give it out to Glasswing, use it to distill it for him for themselves. Do you think this is what they wanted?
David Sacks (00:55:40): I think that on a certain level, it is what they wanted because they've been advocating to have a federal regulator, basically a new agency. In fact, Dario posted a blog just a few weeks ago saying he wants an FAA for AI. They wanted government approval, a government approval process for AI models. And so in a sense, they've gotten exactly what they wanted. Now, that being said, I don't think they're happy about the fact that Fable has been rolled back. So in a sense, you could say that Dario got hoisted on his own petard here, or it could be a FAFO situation. But look, my view on it is we should not reward Dario by giving him exactly what he's always craved, which is some sort of labyrinthine government approval process that does reward regulatory capture. So I hope that very soon now, I do think that as long as Anthropic has resolved the jailbreak issue, then I do think they should be allowed to come back to market. And similarly for OpenAI, I don't think we should be delaying them unnecessarily. We do not have months to give away in this race. And let me just say one other thing, which again, is something I've been saying for months, which is with respect to risks like cyber, it is undoubtedly a risk. But what is the response to that? The only thing you can do is go out and find all the vulnerabilities first yourself, the white hats. Have the white hats find all the vulnerabilities and do a big upgrade cycle, roll out the patches before they can be exploited. The reality is that if you just clamp down in a way that doesn't even allow these models to be used, the Chinese are gonna have these capabilities imminently anyway. You know, they're already at OPUS 4.8 level. And the founder of Z dot ai, he said that before Q1, they'll have Fable level capability. I believe them because, look, the Chinese have been, I'd say, nine months behind our models, plus or minus three months depending on capability. But it's when they know there's been a breakthrough around something like cyber, they can deploy more resources against that particular problem and catch up faster. Yeah.
David Sacks (00:57:50): There are like I said, we're on a shot clock here. I've been saying for months that we're on a shot clock. We have to do smart things. We can't just slow everything down because that will not slow down the Chinese. They're not under our jurisdiction. We have to basically get these tools in the hands of our cybersecurity industry. They're the force multiplier. They're the enabler. We have to basically go out and do this big upgrade cycle quickly, because we only have a few months left.
Chamath Palihapitiya (00:58:16): They're six months behind on the model, and they're twenty four months behind on the silicon, yet they're only a few months behind in total. So what game are we playing? This is insane. We are gonna lose if we keep doing this stuff to ourselves.
David Sacks (00:58:29): Let me make a point about that. So on the silicon, there's been a huge push in China by the government to push their AI labs to develop and train on Huawei chips. And look, you can take these claims with a grain of salt, maybe they're not true, but it was claimed that DeepSeek v4 was trained on Huawei chips, and now Z dot ai, they are saying that the GLM5 family was trained entirely on clusters of Huawei Ascend 910b chips. So now look, maybe they're lying. Maybe they smuggled in some NVIDIA chips, but the claim is that this was all done on indigenous chips. And what I believe is that China is engaged in a strong indigenization push right now. They want to prop up Huawei as the national champion. They want all their companies using Huawei chips. They still need to scale some of the manufacturing, but they're gonna do that pretty quickly. And then what they're gonna do is they're gonna take these Huawei chips, they're gonna take these Huawei optimized models. Remember that GLM 5.2, the inference is optimized for the Huawei chips. Okay. We know that. And they are basically gonna package these things up. They call it AI in a box. They're gonna sell it at a fraction of the cost globally.
Jason Calacanis (00:59:47): Which is what they do with every technology, right? Better, cheaper, faster, or almost as good, yeah.
David Sacks (00:59:52): And that's another thing, as I've been saying since the beginning of this administration, we have to be pro export because China is gonna be there within one or two years, as I said, we're gonna be kicking ourselves because we could add the whole global market to ourselves. We invented reasons not to sell abroad to our friends and partners, and now China is gonna be there imminently.
Jason Calacanis (01:00:12): Yeah. And with that lower price tag, when you play with this new GL, you you get some really interesting responses. It I asked it about the country of Taiwan. Was not pleased and didn't give me an answer. I asked it about Tiananmen Square. No answer as well. I'm using the hosted version at z.ai. But when I asked it places to visit in Paris, it did an exceptional job except when I said make these ideas into an infographic and make me, like, a three day agenda. It was like, hey. We don't have enough time to do that. And it said use the other model because this model's too busy, But you can go play with it at z.ai.
David Sacks (01:00:49): Just on a point about the censorship. So there's no question that these Chinese models have, you could say, censorship and, you know, there's political bias in there out of the box. But American companies have taken Chinese models and then essentially worked around and basically fixed the censorship inside their own forked version. So for example, Perplexity did this very early on with Chinese models. They showed that you could sort of put back the content on Tiananmen Square and things like that. So I think, J. Cal, you're absolutely right about the censorship, but it's not a fatal problem. It's something that American companies can fix when they take an open source model and fork it and customize it.
Jason Calacanis (01:01:31): Yeah. In the hosted version, you're not gonna get a great answer of what agenda you should use for tourism in the great country of Taiwan or your visit to Tiananmen Square. Alright. Let's keep moving here on the docket. Micron smashed their earnings. If you don't know Micron, they are one of only three companies on earth that make high bandwidth memory. These are specialized chips. They sit on top of the NVIDIA GPU, and their entire twenty twenty six supply is sold out and has been for some time. SK Hynix and Samsung also make HBM. Micron smashed earnings, revenue up four x four x year over year, 9,000,000,000 to 42,000,000,000, beat expectations by 16%. Big jump in guidance for q four, 50,000,000,000 versus 43,000,000,000. Their stock is up 10 x. Shout out to Gavin in our 2025 prediction show. He gave a call on HBM makers like Micron as the best performing asset. Since that time, Micron up 14 x.
Gavin Baker (01:02:34): I'm not crying in my soup.
Jason Calacanis (01:02:35): You're not crying in your soup. We got a ton of information here. I think this well, just end on the Apple price increases. Everybody knows Apple has been really been a beneficiary of the run local models movement that I'm part of, and and people are buying 128 gig, 256 gig MacBook Pros, Mac Studios. But the gig is up apparently because now Apple, which had not passed on those costs to customers, is having to pass those increases on. So everything from, you know, the new MacBook Neo, which is their $6.99 laptop, you know, kinda competing with Chromebooks, is now $7.99, up 50 14%, and Mac Studio up 25%. The costs are just gonna be very significant. Inflation has come to the desktop. Your thoughts, Gavin, on Micron and the impact on the industry, and is this a temporary bottleneck, or does this mean everybody has to get into this business quickly?
Gavin Baker (01:03:35): No. Well, one, DRAM is the most important bottleneck. But there's a whole segment of people on X who are very focused on bottleneck. I cut bottlenecks. I call them the bottleneck bros. You know, they'll they'll do some work with Claude, find some esoteric Japanese company. The bottleneck that matters is DRAM. And DRAM and HBM DRAM, this is the most important bottleneck simply because memory capacity and bandwidth are foundational to the performance of every AI model. So this is the most important bottleneck. Elon is focusing the TeraFab on memory because he sees it as the most important bottleneck. You know, not lasers, not capacitors, not power power supplies, semiconductors, not NAND flash, not HDDs, DRAM. And I think this bottleneck is gonna be with us for a while. And it is kind of astonishing. So I think so a few thoughts. Like, what was important about the quarter? They announced that they have these SDAs, these supply chain agreements that have a floor and a ceiling for prices with increasingly large group of large customers. And this covers essentially 50% of their revenue, I think, with just four customers. And the floor pricing in these new contracts is ahead of prior cycle peaks from a gross margin perspective. And so this is really, I think, pretty maybe end up being very transformational for the industry. Most other parts of the semiconductor supply chain have rerated. You know, Lam Research, you know, the the wafer fab equipment suppliers, you know, they all trade at huge premiums to DRAM relative to prior cycles, and their business models have improved. But, you know, so has the industry structure and business models of DRAM because HP and DRAM is increasingly a customized chip. But as far as other people being able to do this, look. CXMT is going public in China. They're going to they may be the cure for Apple's ills.
Gavin Baker (01:05:38): They will flood the market with, to some degree, cheap consumer grade DRAM. But for the DRAM you need in these AI servers, there are three companies that can make it. It's really hard to do. This is as close to magic as science can get. And, you know, I think TerraFab TerraFab, you know, is gonna be an important part of this solution. But, you know, these stocks still trade are cross sectionally cheap relative to the rest of AI. Something I've been thinking about, memory is DRAM is probably going to be 30% to 40% of all hyperscaler CapEx next year. Every dollar, hundreds of billions of dollars that are spent, you know, going straight to DRAM. It's wild. But this may actually be very valuable for society because it is probably, you know, going to, you know, inflate the costs of building a gigawatt data center to the point where, you know, even for the hyperscalers, economics matter who are caught in this prisoner's dilemma. And this may give us as a society time to adapt, to adapt, you know, what our friend Brad Kirchner calls the social contract. So the high iPhone prices, you know, one, CXMT is coming for consumer grade DRAM. But two, this may be good for AI. It may be good for us as a society.
Jason Calacanis (01:06:59): And making it is just really pure silicon. Right? Like, making memory is just this incredibly refined silicon, and that might be the pre bottleneck?
Gavin Baker (01:07:11): Yeah. Yeah. Making that HBM DRAM, making what NVIDIA calls SOCAM, making LPDDR. These are the types of DRAM that are really hard to make, not consumer grade DRAM, and they are increasingly what you need in these AI data centers.
Jason Calacanis (01:07:26): Yeah. Semiconductor grade. Yeah.
David Sacks (01:07:29): Yeah. So my understanding of HBM stands for high bandwidth memory. Again, this is part of the, GPUs that go in the data center to run AI, is that you take the DRAM wafer or die, and you actually stack them. And so I think HBM three is like eight it's stacked eight dies high, but now they're increasing to 12 and even 16. And to basically stack them and then package them all together is that's an advanced technology in and of itself. So you're seeing now, like Gavin's saying, there's only three companies that can do it. But also, this is creating significant price pressure for all the consumer electronics businesses. Apple had huge news today where they announced massive price increases. And again, it's because DRAM now is less available because it's just being hoovered up by all the data centers. And if you're a data center and you need to buy GPUs, again, those chips, they're using immense amounts of DRAM because, again, one HBM chip is using multiple, like, stacks of DRAM. So it's just getting slurped up, and then it takes a couple of years to ramp up new capacity. So these companies are gonna do that, but that could take a while. We saw that in New York, remember, that was that Micron plant that had just broken ground and then got shut down the same day because of some crazy environmental issue. So it's not easy to ramp this stuff in The US, although Micron is the one provider that's in The US. SK Hynix in South Korea. Samsung's in South Korea too. But anyway, we're gonna see again more of this AI inflation they're calling it. You know? It's just another reason I hate AI is it is in this narrow area of consumer electronics where there's competition for DRAM. It is leading to price inflation now.
Gavin Baker (01:09:16): Microsoft raised the price of the Xbox. You know, it's coming for the Switch. It's coming for the PlayStation. You know, there's demand destruction because of prices and consumer, whereas AI demand is relatively price insensitive. David, I would modify one statement. It's hard to build a micron it's hard to build a new fab in a deep blue state. You can build fabs.
David Sacks (01:09:36): Why were they trying in New York? It's kinda crazy.
Gavin Baker (01:09:38): You know, New York gave them all these incentives, and but it doesn't no. Those incentives matter. It's a little bit like solar power. You can be as pro environmental as you want. But if you can't build and install solar because of regulations, it doesn't matter. So, you know, maybe that Micron plant ends up getting, you know, built in my home state of Texas.
Jason Calacanis (01:09:57): The incentive game has kind of flip flopped. It's like it used to be the states were courting the factories and the fabs. Now it's the fabs are like, which state can actually build this? We'll pay you whatever you want. Just tell us where to send the envelope. We'll we'll we'll drop a couple of envelopes off. It's not a problem.
David Sacks (01:10:15): Gavin, can you say how long it's gonna take to stand up the fab at TerraFab?
Gavin Baker (01:10:23): Well, I mean, if it was a normal fab, it would be a two, three, three and a half year process. But, you know, we we we've seen what Elon has done to other construction processes, and, you know, he's starting with some some advantages with the Intel partnership. So I don't think anyone knows, but based on past history, he's probably gonna stand up TeraFab faster than other fabs have been stood up. But it what? This is really hard. It's really hard. It's the intersection of magic and science. You can't believe how complicated this is. So it's gonna be hard, but, you know, he has a he has a track record of doing, you know, what Jensen called impossible superhuman. And so we'll see. We'll see how long it takes. You
David Sacks (01:11:08): know, one other point here that I guess is it might be relevant to SpaceX AI, although it's don't have to limit it to this, is, I think there's an assumption that over time, it would get cheaper and easier to stand up new data centers, right? But what you're saying is actually it might be getting harder. It might be getting more expensive, right? Because there's competition for these components. The memory's getting more expensive. I'm not sure that the GPUs are getting any cheaper. I guess some of
Chamath Palihapitiya (01:11:35): transformers, the switchgear
David Sacks (01:11:37): And some energy might be getting cheaper. And then the entitlements are getting harder, and the political situation is getting harder. There's very few places you can even stand up new data centers. So is it the case that actually it's gonna get more and more expensive to
Gavin Baker (01:11:52): 100%. So to stand up a one gigawatt data center, it's $35,000,000,000 in semiconductors, NVIDIA semiconductors, and it's $25,000,000,000 of power and cooling equipment. And that is clearly inflationary because a lot of that 25,000,000,000 is the human labor required to install it. So the calculation that needs to be done for orbital compute is it's 35,000,000,000 of silicon in each space and, you know, in in literally outer space in orbit and on ground. But if you can get the cost of launch significantly below that $25,000,000,000, then the math starts to really math. And when Starship is reusable, it's gonna cost $5,000,000,000 to put a gigawatt of compute into space. It's something that drives me crazy as people picture these pentagon sized data centers. No. It's racks in space linked with lasers. It's it's kind of a virtual data center in space.
David Sacks (01:12:43): Wait. 5,000,000,000. Is that 5,000,000,000 of launch cost? Or what
Gavin Baker (01:12:46): 5,000,000,000 of launch cost. Now you're at 40,000,000,000 to put the gig into space. You're at 60,000,000,000 terrestrially, and the 25,000,000,000 that is power and compute is clearly inflationary. And so it may be that in three or four years, it's 70,000,000,000 versus 40,000,000,000, and that five, as Starship becomes rapidly reusable, is likely deflationary. So this is the economics that underpin orbital compute from first principles. And then on an ongoing basis, you are you're maybe paying a billion dollars a year for the power to run those chips and cool it.
Chamath Palihapitiya (01:13:22): If I had to make a guess, I think what's gonna happen is that since 2021, about 40 of all data centers get contested. Right? I think that number is gonna go up. So, Saks, I suspect that whatever forecasted energy consumption that we are looking at in AI is grossly imbalanced. There is very, very meager supply, and there's effectively infinite demand. So that probably pulls forward the economic equation to wanna go to space. But then again, that's gonna prefer SpaceX and their compute stack and their compute decisions over the hyperscalers and over anybody else. And so you're gonna have a cost of an output token, I think, terrestrially, particularly from the hyperscalers, be a little economically lopsided versus SpaceX once they get it to scale. Now that's the key statement. Whatever's left on the ground, though, will be incredibly, incredibly valuable. It'll be a diamond. These are diamonds. And the thing is you have to find reasonable size. Right? You can't have a 10 kilowatt diamond. That's like a little pebble of Nobody cares. But if you're in the reasonable hundreds of megawatts to gigawatts, man, those are like hope diamonds. Those are just lock them down, which I own.
Jason Calacanis (01:14:44): Travis, there was a interesting trademark filed this week. So more in the investigator investor investigator of the Tesla plus SpaceX marriage that everyone seems to believe is gonna happen
Gavin Baker (01:15:01): shortly.
Chamath Palihapitiya (01:15:01): You can can say that that you can give me credit for
Jason Calacanis (01:15:04): Of course. Yes. As Shamath has architected in his in his high perch, but this trademark came
Travis Kalanick (01:15:12): out How cool would that be? How cool would it be for those two to together?
Chamath Palihapitiya (01:15:16): It's gonna happen. Be amazing. It'll be incredible. And if you're lucky enough to be an owner of both oh, everybody can be an
Jason Calacanis (01:15:24): owner of bottom. Shamafest top. Who's the bottom?
Travis Kalanick (01:15:26): Everybody can decide to be an owner of both.
Chamath Palihapitiya (01:15:28): Jason, I'll be I'll I'll be making love to myself when this happens.
Jason Calacanis (01:15:31): There'll be no So no difference than any other Thursday.
Travis Kalanick (01:15:35): So just another
Chamath Palihapitiya (01:15:36): day. On the top and the bottom.
Jason Calacanis (01:15:37): You're gonna be the top and the bottom? Just like any other Saturday night. Yeah. Here's the trademark for Megapod that came out. This is a filing date of sixeighteentwenty twenty six. So a very recent June 18. Modular data center hardware for artificial intelligence computing comprised of network of computer servers, computer hardware for artificial intelligence processing, computer network hardware, power distribution units, cooling systems sold as a unit, self contained modular computing hardware systems for artificial intelligent workloads, yada yada yada. Essentially Well,
Chamath Palihapitiya (01:16:09): just to explain what this is.
Gavin Baker (01:16:10): Well, you know,
Chamath Palihapitiya (01:16:10): let me just let me just By
Travis Kalanick (01:16:12): the way, that description makes I don't know what it I still don't know what
Chamath Palihapitiya (01:16:15): it is.
Jason Calacanis (01:16:15): Essentially, what people are saying is this is going to be a giant battery pack with GPUs at the supercharger stations, which have already been approved. That's the back channel. Chamath, go ahead. You have a
Chamath Palihapitiya (01:16:26): couple of issues right now to turn on compute terrestrially. So assume you have land, that's relatively straightforward. Assuming you can get it zoned, less straightforward. Assuming you can get power, very difficult. Then you have a very critical design decision. So all of these folks publish these things called the basis of design, and your your BODs essentially tell you, here's the Anthropic spec. Here's the OpenAI spec. Here's the CoreWeave spec. Here's the AWS spec. Here's GCP. And you get these 50 and up to upwards of 500 page documents of all these technical details. The issue that we have is I don't know if you guys have used OpenAI or Anthropic recently where you get the whole thing of, like, come back later. Right? Yes. That come back later is completely unacceptable. It just means that they have no compute. So in trying to find
Travis Kalanick (01:17:13): Search pricing is coming.
Chamath Palihapitiya (01:17:14): Yeah. Let's go. So in trying to find this solution, what is happening is these basis of design, the restrictions, the specificity is being relaxed. And one of the key constraints is we've moved to an architectural model from Google and Nvidia that has said, look, we have to liquid cool these racks. These are very complicated, big girth supercomputer racks essentially. And now we're also going back and saying, you know what? Maybe some of these older stuff that's a little bit less proficient and a little bit less useful, but we can air cool them is useful. And everybody's like, yeah, you know what? We should try to use everything that's available. In that second class, what some very smart people are doing, they're like, wow, well, here's a shipping container that you can just drop on a concrete pad somewhere, plug in the power and let it rip. And so, Jason, what you're seeing is that level of investment that's happening. So there are companies, like Dell makes these racks, companies like Vertiv makes these modules. And I think if Tesla can make them available, folks like us for my data center project, we would be enormous buyers of these things because we would just literally prefab them in a warehouse. Right?
David Sacks (01:18:27): Roll
Chamath Palihapitiya (01:18:27): them chips, prefab them, truck them to the place, crane them in, turn it on, off to the races you go. You have like a ninety day build cycle, which is unheard of. So that's where these megapods are coming from. I hope it's not entirely consumed by Tesla and SpaceX internally.
Jason Calacanis (01:18:46): Well, that's the rumor is that he's gonna put them at the supercharging network where he has a lot of land and he's got power there already, and those are lightly used in some cases, you know?
Chamath Palihapitiya (01:18:55): There are other requirements. The problem with some of these things is that you need to have certain levels of access. There are certain infosec requirements. There are certain liquid cooling requirements that make many of the workload applications unfeasible at a place like a supercharger center where random bumble are, like, traipsing around.
Jason Calacanis (01:19:11): Security guard. Put an optimist. Guys, I've
Travis Kalanick (01:19:15): got I've got 500 properties with lots of energy, lots of mechanical cooling systems, and lots of LNG access or sorry. Not LNG. Natural gas. Sorry. Already piped in. So on all the stuff I'm doing on robotics, AI, physical AI, we're literally looking at putting some of our compute Wow. Into our kitchens.
Jason Calacanis (01:19:43): Compute kitchens. You're
Chamath Palihapitiya (01:19:44): gonna be able to buy small modular. Let's put data center in a quote.
Travis Kalanick (01:19:51): But but it doesn't it doesn't matter. Like, I I just go buy the GPUs, and I'll just I just set it up at a kitchen. Right?
David Sacks (01:19:58): It's called it's like Bitcoin miner.
Chamath Palihapitiya (01:20:00): That know, hold on.
David Sacks (01:20:01): It's not like a Bitcoin miner.
Chamath Palihapitiya (01:20:02): No. No. Hold No. On. Hold on. Hold on. It's not that easy. Okay? Like, if you guys wanna build a cloud and contribute it to a pool, you're gonna have to sign up for liquidated damages, and you're not gonna sign up to these SLAs.
Travis Kalanick (01:20:13): I'm not a hyperscaler. I'm just using it for myself.
Jason Calacanis (01:20:15): Yeah. Rack and stack it?
Chamath Palihapitiya (01:20:16): Oh, okay. Sure. You can use it for yourself. I'm saying Yeah.
Travis Kalanick (01:20:19): The more interesting opportunity is when Whatever Travis says, let's talk about the interesting stuff.
Chamath Palihapitiya (01:20:25): No. No. I'm just saying, like, what I thought you were going with this, Travis, is, like, you could build a synthetic pool and contribute it to
Travis Kalanick (01:20:31): You can. Sure.
Chamath Palihapitiya (01:20:32): Neoscaler. And all I'm saying is
Jason Calacanis (01:20:34): to do
Chamath Palihapitiya (01:20:34): that is a leap of things that you'd have to do that you probably don't wanna do because it veers you away from
Travis Kalanick (01:20:39): what you're doing. I think the security thing is the main issue around non data center type real estate, to be honest. It's the big one. Look. You you gotta do liquid cooling. You gotta do mechanical systems per air cooling. You have energy. Like, there's a lot of things you gotta do. But assuming you even had all that, the architecture of a data center is set up like they have man traps, right, where you go into a room, the door closes behind you that you got into with your fingerprint, then you go into the next part of it against your fingerprint only when that door closes.
Gavin Baker (01:21:13): Well, just out of curiosity, how much does one of those man traps cost? Like, why can't you put some of those in your Yeah.
Travis Kalanick (01:21:18): Maybe you
Jason Calacanis (01:21:19): could. Are you really interested in bringing the man traps? To help trap some men.
Travis Kalanick (01:21:22): I'll try to interpret where Chamot's going a little bit. It's like a Megapod that's sitting at a chart, like a public charging situation because of the physical access of it. Like, there's probably some stuff you gotta do if you're going to resell it. But if you're gonna use it for yourself, you can use it for yourself.
Chamath Palihapitiya (01:21:40): The real value, I think, in the Travis example, which I find super exciting, is if you can contribute it to a distributed training pool or a distributed inference pool that has a lower SLA, which is more of how this community based oriented work. Jason, I think you've talked about BitTensor. I think Venice is a project. I think Plurals is another project. Travis, that's where I think it's super exciting. Where?
Travis Kalanick (01:22:03): But but the one thing I'll just throw out there, guys, the distributed training stuff, if these things are far away from each other, meaning not right next to each other, they're so less efficient. The efficiency drops dramatically. You want these things to be right next to each other physically. You get multiple orders of bag at least an order of magnitude type efficiency, maybe plus plus plus. I'd like it it's a big deal. Yeah. So, like, you could have two we have two of
Jason Calacanis (01:22:32): our facilities that jobs from one GPU to the other is super important. And if it's on a peer to peer network, it's gonna have lag. It's gonna take more time.
Travis Kalanick (01:22:40): Even if it's on your own fiber connected, like, two kilometers away, you're screwed. It's not a thing.
Gavin Baker (01:22:47): This is a 100% true. But everything that cuts against training works for inference.
Travis Kalanick (01:22:54): Respect. Respect.
Gavin Baker (01:22:56): Well, latency is super important, and I do think, you know, a distributed inference distributed inference clouds are coming.
Travis Kalanick (01:23:04): I get that. That's fair.
Gavin Baker (01:23:05): And to riff and to riff on, like, what Thomas said in all of this, like, one, I mean, there is actually a startup that is trying to put four GPU units with kind of a battery on people's houses and give them a discount on their power. And then you could do inference for that neighborhood, you know, from those four GPUs, and it's like locked sealed so nobody can get in. But there's there's another dynamic that I think we should talk about with all of this and could play into the mega pods and, you know, other people are kind of working on data centers. You know, Crusto is working on, you know, modularly assembling data centers, you know, kind of like a data center. And think of it as like an 18 wheeler. What do you call those things? The 18 wheeler, you know, shipping container, whatever it is. But that is the disaggregation of inference into prefill and decode. When you when a model is answering your question, it's doing two things. The prefill part is understanding the question and its answer thus far. And think of think of that as the more you can remember, the bigger your, you know, your memory capacity. Literally, the more words you can remember, the better. Decode is the process of generating the next token, and that is a memory bandwidth bound problem. And think of it as the faster you can speak, the better. And these two types of inference are increasingly being disaggregated. And Chamath was an investor in Grok, which NVIDIA bought, and they're gonna use this. Cerebras is the other solution today that is available. And you can put Grok or Cerebras, decode, optimized chips, they both say you can do more than decode on them, and that's true, in front of old NVIDIA GPUs like H100s. So you can lift H100s, A100s out of some old data center, put them in one of these mega mega pods, you know, a rack in a shipping container, put a Grok or a Siri bus in front of it, and you can get a very competitive solution. And so I do think the disaggregation of inference, we're gonna be using GPUs for seven years, ten years, twelve years, and that's great because it lowers the cost to finance them, which makes this AI revolution more financeable.
Gavin Baker (01:25:18): Jamath, you wanna riff on on Gronk? Should we should we should we
Chamath Palihapitiya (01:25:21): I really agree with everything. You're incredibly well steeped in this space. It's so exciting. I don't have any investments or anything in the distributed compute space, but at the intersection of competing against China, having a vibrant American open source community, having a bunch of distributed models for purposes of free speech and otherwise that Travis mentioned earlier, I do think this idea of distributed inference has a real place in the American ecosystem. I don't exactly know where and how and how homeowners would get paid, but whoever figures that out as a Pan American idea, I think, a is is really onto something.
Gavin Baker (01:25:56): It'd be awesome.
Jason Calacanis (01:25:57): And, yes, Travis, obviously slower, but people are contributing compute to this. That's like kinda surplus compute or or compute that's available.
Travis Kalanick (01:26:04): Recycling unused compute. Recycling unused compute.
Jason Calacanis (01:26:08): And then there's Targon, which is just straight up people are putting and you can rent h two hundreds by the hour for $3, $4, and it's permissionless. Anybody can contribute provided and this is kind of the magic of BitTensor is there are validators that make sure you're putting in what you're saying you're putting into the network. And so if somebody just had the hardware and Tesla said, from now on, every Powerwall, and I I I don't put it past him to do this, you buy a Powerwall, we give you a discount on it. Every Powerwall has our GPUs in it. Part of the offering is you can't buy a Powerwall without putting GPUs in it, and when you're not using it, we will pay you for your battery. And you put a Starlink on your roof, and now you've got a distributed system where you get a couple of these Powerwall's with their own silicon in it and a Starlink, and now Elon's created an infinite number of home battery backup systems. People get their battery system for free. He gets the exclusivities for twenty years.
Chamath Palihapitiya (01:27:09): You guys see that there's a rumor that Elon's gonna buy T Mobile?
Gavin Baker (01:27:12): Woah. By the way, we should just because Cerebras has blown up and bumped your deal price. We should talk about Cerebras a little.
Jason Calacanis (01:27:20): So Cerebras had an incredible IPO. Give us an update on where these IPOs are happening. Obviously, SpaceX had an incredible IPO, but has retreated from this, you know, otherworldly $200 share price. So to the extent you can talk about these two, as well as the two IPOs to come, $4,000,000,000,000 in backlog. We've obviously got OpenAI and Claude I'm sorry, and Thropic, which makes Claude. Both of those would be worth a billion plus. You put all this together, 4,000,000,000,000 of new offerings plus Cerebras in there in the mix. How does the market manage this much new inventory being put on the market? Obviously, the flow to SpaceX is notably small, but over time, people like yourselves and and other insiders, Founders Fund, etcetera, will be unlocked and have the ability to distribute to their LPs. So this is gonna be a moving target, I think, in terms of share price. And can the market absorb this? Where does the money come from? Retail? Or does it come from people selling their Bitcoin and moving it over to something more exciting? What's the dynamic here in the market? I know we're in uncharted territory, Gavin.
Gavin Baker (01:28:21): Well, for sure, there's no precedent for any of this, but a few things I would say, like, just in no particular order. I think Anthropic is worth $3,000,000,000,000 today. And it's very important.
Jason Calacanis (01:28:31): Did you say Anthropic is worth $3,000,000,000,000?
Gavin Baker (01:28:33): Yeah. I think that is roughly where it would probably trade as a public company. And Wow. Yeah. And pro I mean, look. They're gonna do they're gonna end this year
Travis Kalanick (01:28:44): well Oh, man.
Gavin Baker (01:28:45): They're gonna end this year well over 100,000,000,000.
Travis Kalanick (01:28:48): Holy shit.
Gavin Baker (01:28:49): What what's the '28 number? What's the 28 number? Is it 200? Is it 300,000,000,000? It's probably not gonna trade it 10 times that number. And it will be very profitable at that scale because it'll be inference dominated and people reporting they have 85% gross margins on inference. But in terms of the market absorbing this, like the market's already absorbed it. You know, it's it's just shifting from private to public. And so in the scale of global capital markets, these seem like really big numbers. You're just moving from the private markets to the public markets, which are even bigger. As far as SpaceX specifically, I think one of the more important things, is everybody who's a SpaceX investor or employee has had a chance to sell every six months for the last ten years. So they may not be the wall of liquidity that some people are thinking about. I read this New York hedge fund short short report that you could just short SpaceX on the lockup because so many people are gonna sell. Really? Well, everybody who's on the cap table, they had an opportunity to sell. And almost half the employees at SpaceX bought on the IPO. Now I do think Cerebrus.
Travis Kalanick (01:30:01): But, Gavin, one thing, though, I gotta say. So I I've had SpaceX since 2018. What? What? But their little their little liquidity thing every year, like last year, it was, like, $3.53 50,000,000,000 last year. So you got an 8x in one year. You could have a lot of people selling. Right?
Gavin Baker (01:30:21): For sure. They were
Travis Kalanick (01:30:22): doing little 20% up, 30% up clips for many years, and then an 8xer could create that liquidity.
Gavin Baker (01:30:30): Maybe. But we'll see. That's possible. But the employees are buying at the new price, and they're probably the you know, at some level, one of the biggest pools of, you know, ownership that's gonna unlock. Yeah. And then, you know, I do think a lot of people probably own SpaceX through SPVs, and those probably don't unlock or get distributed anytime soon. So I just, you know, I would be careful with assuming. I don't think Elon's a seller of his 50
Travis Kalanick (01:30:58): He's definitely not, obviously. Yeah. Yeah. So And a lot of us and a lot of us aren't sellers. You know? And that's great. Yeah.
Gavin Baker (01:31:04): Yeah. I mean, a lot of people who had large space expositions were large buyers on the IPO. On Cerebras, so Cerebras has had a tough two days since they reported their first quarter as a public company. And I think there there there are two things that are very that are worth discussing here. One is there is a whole generation of portfolio managers. There's a lot of people who are advocating for kinda squeezing the blood out of the stone on IPO prices. And the flip side of that is that there are a lot of portfolio managers who, if a stock breaks deal price, they sell it no matter what. They consider it a promise that was broken. And so this is what has happened with Cerebras to some degree over the last two days. And, you know, this may seem irrational, but there are people who run giant funds who I know personally where if a stock breaks deal price, they sell no matter what. And so if stock breaks deal price, it can sometimes, you know, go to places you wouldn't think it would go. And this means that shorts, if a stock gets close to deal price, they short it because they wanna break deal price, and then, you know, they make a quick 10 or 20%.
Jason Calacanis (01:32:22): So it becomes a pile on.
Gavin Baker (01:32:23): Because you have this price insensitive selling that can be triggered. And this is what has happened to Cerebras. You know, people talk about hate sale hate selling, but they broke deal price. And so just if you're going public and you're listening to this, tell your bankers, price this in such a way that we're not gonna break deal price in our first nine months as a public company. And that's what I always advise everyone to do, and I think it's important. But I also think, you know, it takes companies a while to learn how to tell their story and communicate to to public markets. It's a very different audience than VCs. And the way like, the way I would have respectfully told the Cerebras story because what happened to Cerebras is they reported a quarter, and and they're growing fast. But relative to the rest of AI, they're not growing that fast in the March quarter. So what I would have said is we signed this transformational, you know, $2,025,000,000,000 dollar, I don't know the exact number, contract with OpenAI in December. December 2025. We immediately ordered more wafers from Taiwan Semi. It takes a 100 it takes four months from when we make that order. Taiwan Semi, know, says yes. They start producing. Takes four months to make the chip. Then we then it takes us two months, plus or minus, to turn that chip into a server. And then if we're lucky and we can find the power, it takes us a month to energize that chip and start making tokens with it. So the first time you're going to see the impact of this OpenAI deal at the earliest is probably around Labor Day. So you'll see a little bit of it in the in the third quarter. But then it really it starts to build. And just, like, really simple math. So, like, let's just use some rough numbers. Let's say let's take some NVIDIA numbers. It takes some 35,000,000,000 to bring on a gigawatt and 15,000,000,000 that you can generate 15,000,000,000 in token revenue and cloud revenue out of that gigawatt.
Gavin Baker (01:34:29): And somebody on the call talked about adding 50 megawatts a month. If they could add 50 megawatts a month in 2027, forget '26, that means they exit the year at roughly a $9,000,000,000 cloud computing run rate. And, you know, we're at we're at less than 40,000,000,000 of market cap. Now that is gonna be really hard to do, and they've never done anything like that before. And but I would have I would I would focus, like, as an investor, I think what matters here is not where they sit competitively, not what new demand they can bring on, but just how quickly can they bring on power. And listen. Like, outside of the hyperscalers, the only companies that have ever brought on more than a gigawatt, I think, are Corweave, Crusoe, and and and SpaceX AI. To bring it on 600 megawatts, it's really hard. And that is what, like, I'm focused on as an investor. How many megawatts can they bring on? Because we know what they're gonna monetize at, and that is the question, and we'll see.
Chamath Palihapitiya (01:35:37): Yeah. I think that's well said.
Jason Calacanis (01:35:38): Yeah. The other companies that have had this happen of late, I guess, Rivian and famously, Chamath Facebook traded below IPO price in the first year, I think. And so this isn't necessarily mean a bad company, it just means a lot of hype or maybe going for it in the IPO and pricing it to perfection. It can go one of two ways. You can either grossly underprice, grossly overprice. And it's really hard to get right. And this is why doing auctions for, you know
Travis Kalanick (01:36:07): Auctions are the way. Auctions are the way. And so it's not hard to price if you just do it the way it's supposed to be done. It's hard to price when you, want it to be a certain number.
Chamath Palihapitiya (01:36:19): Yeah. And you have many mouths to feed, and that influences the price.
Gavin Baker (01:36:23): I don't think that happened here. I think there was a good faith effort to to price this thoughtfully. But just, you know, there was it was such an in demand IPO. I think it was a hard IPO to price.
Chamath Palihapitiya (01:36:35): Oh, you just auction it.
Travis Kalanick (01:36:37): Gavin, you just auction it. I think that's different than underwriting it. You're underwriting. But the bankers, like, I think they just need to get more in the mode of just doing the auction. You
Chamath Palihapitiya (01:36:48): know? Yeah.
Jason Calacanis (01:36:49): Final topic was this $3,000,000,000,000 or actually, now it's your $3,000,000,000,000 call on Anthropic would make it like 6,000,000,000,000 in offerings. What do we think broadly
Gavin Baker (01:37:04): It's not in offerings because it's they're gonna offer a small slice of that.
Jason Calacanis (01:37:08): Sure.
Gavin Baker (01:37:08): And that small slice is very easy to absorb in the context. I believe we have no precedent. We'll see. I might be wrong, but it's not hard for global capital markets to absorb
Jason Calacanis (01:37:19): Yes.
Gavin Baker (01:37:19): 50,000,000,000 of an offer. It's not like it's not like somebody has to come up.
Jason Calacanis (01:37:24): Yeah. It's a 5%
Chamath Palihapitiya (01:37:25): float is a 150,000,000,000. There's enough.
Travis Kalanick (01:37:28): Guys, remember remember when 15,000,000,000 used to be a whole lot of money? Yeah. How weird is what's going on? How weird Where this
Chamath Palihapitiya (01:37:37): is all
Jason Calacanis (01:37:37): this money coming? Oh, yeah. Where was it all this time?
Gavin Baker (01:37:40): Can we just reminisce, man? We got my when I was at Fidelity, my my colleagues and I, we got pilloried. I think we priced Uber at 14,000,000,000, and we got pilloried in the press for not knowing what we're doing. And it was seen as, you know, then then of course, like six months later, I think you guys did around at what, like 42,000,000,000 or something. But it's like, yeah, 14,000,000,000. That was groundbreaking for a private company back
Travis Kalanick (01:38:06): then. Yeah, for sure. It was 17, but that, know, no 17.
Gavin Baker (01:38:10): No. You're right. I wanted 14, and we had, like, a big negotiation.
Travis Kalanick (01:38:15): We ran we ran an auction. No. We just ran an auction.
Gavin Baker (01:38:18): Yeah. You wanted 20, and maybe we landed at 17.
Travis Kalanick (01:38:22): What we did what we did was every person who wanna be involved had to fill out a sheet of how much money they put it at ten, eleven, 12, thirteen, 4 all the way up to 20. And then we just did the Dutch auction. We said we wanna clear 1 and a half bill. We just did the auction and cleared it. Went back to people and said, hey, you're not gonna get it. You have another shot. They update their Excel sheet, and it just moves the number up a little bit, and then you you close it down. But, yeah, it started that round started at, I think it was nine or ten or something like that, ended up at 17.
Jason Calacanis (01:39:01): Thank you for your service.
Travis Kalanick (01:39:01): So it used to be that that was a lot of money, and that was unheard of at the time. And that was well, look. It was ten years ago when we used to walk to school uphill both ways.
Jason Calacanis (01:39:12): Yes. We used to have to. Yeah. We used to eat potatoes with no butter, just hot potatoes.
Travis Kalanick (01:39:18): Sometimes we
Jason Calacanis (01:39:19): were lucky that
David Sacks (01:39:19): they were cooked.
Travis Kalanick (01:39:20): I love that.
Jason Calacanis (01:39:20): Sometimes they were raw. That's right. No. My dad would tell me that story. There's some famous John the Bewd story. He'd say his mom would put like four potatoes in the oven. They'd wrap them in tinfoil, one in each pocket because they couldn't afford gloves. So you put your hands in your pocket with the hot potatoes. You get to school, eat one for breakfast, one for lunch. Him and his sister, Johanna, God rest for so, my aunt who died too young, and they would just go eat these potatoes. That was their life walking to school. Yeah. And our kids are trying
Travis Kalanick (01:39:52): to both ways.
Jason Calacanis (01:39:53): Yeah. They're trying to get the new iPhone 16 or 17. I don't know.
Travis Kalanick (01:39:56): Remember when remember when it used to be hard to raise $5,000,000,000?
Jason Calacanis (01:39:59): Oh my.
Travis Kalanick (01:40:00): Lord. Crazy. Remember when we're hard to crazy.
Jason Calacanis (01:40:02): Always hard to raise 1,500,000,000?
Travis Kalanick (01:40:04): Dude, I remember I yeah. I remember when it was hard to raise anyways, we don't have to do this. It's okay. We already sound like grandpas.
Jason Calacanis (01:40:10): It's fine. We do sound like
Travis Kalanick (01:40:12): move on.
Jason Calacanis (01:40:12): It was so hard to raise that first 1.5.
Travis Kalanick (01:40:16): It's we don't need to go there. It's so funny, though.
Gavin Baker (01:40:19): I hate be this art piece,
Jason Calacanis (01:40:20): Gavin, behind you. Is that, like, an art piece or you made it? Yeah.
Gavin Baker (01:40:24): No. This is I'm staying at a rented house in Atherton.
Jason Calacanis (01:40:28): Oh, okay. There you go. It's just a Arabian art. Alright, everybody. For the dictator, Jamal Paihapatia and for David Sacks, TK, GB. We'll see you next
Chamath Palihapitiya (01:40:40): time on the Wallin podcast.
Jason Calacanis (01:40:41): Bye bye. Great job, everybody.
Chamath Palihapitiya (01:41:14): We should all just get a room and just have one big huge orgy because they're all just useless. It's like it's like sexual tension that they just need to release somehow.
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