中国正在能源上碾压美国。这是否意味着他们会赢得AGI?— Casey Handmer
- 核心判断:2027年破土动工的数据中心将以太阳能为主。 Handmer 说,在 Scale Microgrids 的论文按90%太阳能、10%燃气建模后,“你听说过的几乎所有大公司”都打电话来问他;他的答案是:“完全可以做到100%太阳能。”关键在于,超大规模云厂商“对电价不敏感,对电力可用性敏感”,而在给定问题下,太阳能显然是“用消防水带式供能”最好的选择。
- 燃气今天赢,规模化后输。 约2030年前的每一台涡轮机都“已有买家”,仅 Brayton 循环中高速旋转的 Inconel 部件,摊销后就要$35/MWh;而 GE 扩产的融资模型要靠25年回本,对手却是每累计产量翻倍成本下降43%的太阳能(产量每2-2.5年翻倍,需求弹性约为边际产能增量的6倍)。“你赢不了。”Dwarkesh 关于 HBM/CoWoS 的反驳是,“我们不会做”其实意味着“给我开张支票”,而他们确实做了——这代表看涨的一面:支票可以解锁供给。
- 谈中国:不要把太阳能制造领先20倍,外推成AGI胜利。 中国周边是15个大多敌对的国家,进口自己无法保护的石油;而且“永远不要低估一个专制独裁政权把自己绊倒的能力”。但 Handmer 也承认,他自己的 Terraform 合成燃料技术“绝对会不对称地帮助中国”,因为它能把中国的电力过剩转化为电力目前无法覆盖的三分之二终端能源用途。
- 美国两年或更短就能把太阳能本土化,从泥土做到成品组件——美国落后中国约5年,不是一代人的差距;即便对中国组件征收200%关税,对数据中心经济学“完全无关紧要”。真正的约束是监管:NEPA 的4年审查周期让 Texas 的部署速度达到 California 的10倍;杠杆最高的政策,是对太阳能部署设置类别豁免。
- 按四个9的供电可靠性计算,土地成本低得近乎可以忽略:每兆瓦约10英亩(1 MW 机架+6台 Tesla Megapacks+2.5倍太阳能超配),因此5 GW只需50,000英亩——与 Oak Ridge 或 Hanford 相当;相较于2,500亿美元 GPU、约占资本开支0.1%,土地只要几亿美元。组件未加关税时为每瓦8美分,真正昂贵的是周边所有东西。
- 结构性做空电网,结构性做多电池: 电池进行时间套利,电线进行空间套利;人均电池重量已经跨越4-5个数量级(10g手机→100kg Tesla),而表后储能正在蚕食公用事业收费最高的峰值资产,同时推高其运营开支——PG&E 是 Baumol 成本病的典型案例。Handmer 标记这是他“最价外的押注”;所有他认为可靠的预测人士都不同意。
- AGI估值框架:全球工资总额60万亿美元是下限。 OpenAI 100-200亿美元 ARR 放在 McDonald's 旁边“太寒酸”,而今天的价值链是10美分电费→约$1,000用户价值,因此 Anthropic 完全可以把电力成本提高100倍,再加收$10。长期看,随着 AI 让认知成本通缩,GDP 可能在名义上收缩;衡量“文明规模”,更好的指标是我们实际消耗的原始能源。
1. 中国的能源领先是真实的,但别急着把AGI奖杯交给它
- Dwarkesh 开场提出挑战:如果 AI 变成一场工业竞赛——太阳能板、电池、GPU、变压器——那正是“中国最擅长的领域”,中国每年太阳能制造能力达到美国的20x,SMIC 最终也会追上 TSMC。Dwarkesh 说,拿高铁炫耀“说明你的资本配置能力真的很差”;而这场对话指出,中国或许在最重要的事情上“意外地做对了”:太阳能产能过剩。
- Handmer 的地缘政治判断是,美国是“全世界他妈最幸运的国家”(有海洋、有友好邻国);中国则被15个大多敌对的国家包围,还要用海运进口中东石油,而自己的海军无法在印度洋保护这些油轮。Dwarkesh 随后说:“永远不要低估一个专制独裁政权把自己绊倒的能力。”Handmer 的反驳是,不要拿整个中国比较,而要拿 Shanghai 和 Guangdong 对比美国:“中国可以有一个规模、财富、创新能力都和美国相当的部分”,这和印度那种规模很大但中产阶级贫困的国家不同。
- 令人不舒服的让步是:Terraform 的合成燃料技术——把电力(目前只占终端能源使用的三分之一)转化为覆盖100%终端能源用途的燃料——“绝对会不对称地帮助中国”。Handmer 没有与中国合作的打算,也不准备这么做,“但物理规律非常明显”,而且中国已经有合成燃料项目在运行。
2. 如果美国愿意,两年就能重建太阳能产业链
- Handmer 认为“中国产业环境更友好”这一共识“完全疯了”:在中国,你得让 CCP 检查员坐进董事会,还要靠行贿才能继续经营;美国则有廉价天然气、深厚金融市场和“世界领先的自动化能力”。美国太阳能制造大概只落后中国5年,而把产业链从“泥土做到成品组件”——一共4个阶段——本可以“从今天开始,两年或更短就完成。现在是11点,所以我们会在中午前开始开支票”。
- Handmer 讲了一个来自乌克兰战争后的反事实伤疤:他当时预计欧洲会把太阳能产业本土化,但欧洲没有——“他们仍然每天向俄罗斯支付10亿美元,只为享受被入侵的待遇。”
- Dwarkesh 的元层面反驳值得保留:Handmer 的预测前提是“如果 Elon 像经营 SpaceX 那样经营政府”,而不是现实中最可能发生的情况。Handmer 部分承认,太阳能工厂可能永远不会成为关键路径;即便对中国太阳能征收200%关税,也‘完全无关紧要’,因为瓶颈在芯片,而不是电力成本。
3. 为什么聪明钱今天还在买燃气,以及规模化会在哪里击穿它
- Colossus 的打法解释了当前行为:xAI 在 Memphis 需要速度,于是买下一栋楼,接入燃气管道(管道的能源输送能力远高于架空电线),再把卡车上的涡轮机租过来。“这样的可用余量曾经有过1次,也许2次。”
- 但一旦进入规模化,所有环节都会断裂:燃气供应、涡轮机和变压器制造速度、电网容量,以及 AI 与传统用电用户的竞争——PJM 远期电力拍卖已经把家庭电价推到“不可持续的高位”。“如果我们每年要做100 gigawatts呢?整个局面可以直接被打穿。”
- Henry Kaiser 的类比指向终局:Henry Kaiser 的 Richmond 造船厂当时被钢材卡住,于是他不仅建了一座炼钢厂,还建了一座铁矿。“这就是同一种情况。”这也是为什么演讲者尤其看好 xAI:与这个世界上的 Googles 和 Metas 相比,Elon 的电影宇宙已经做了太多工业化的事情。
4. 涡轮机融资陷阱,对比太阳能的复合学习曲线
- 讨论中的主流火力发电路径是 Brayton 循环;“只要有一堆 Inconel 在高速旋转,就一定会花很多钱”——仅这些旋转部件的摊销成本就达到$35/MWh,还没算燃料、换热器和冷却。
- 融资链条是这样的:银行借钱给 GE 扩大涡轮机产能,看到的收益要在3-5年后才出现,也不知道 AI 泡沫会不会破裂、Taiwan 会不会被入侵,因此必须让电厂运行20年才能回本。“25年后,我们还能以一个在太阳能已经达到当前价格的世界里有意义的价格生产燃气涡轮机吗?这种概率有多大?你赢不了。”
- 太阳能的数字是:累计产量每翻倍,Wright's Law 系数为43%;翻倍周期为每2-2.5年一次,也就是价格每年下降约15-20%;需求增长速度约为边际产能增量的6倍。“太阳能的采用、产量和降价不仅在继续,而且在加速;而它们加速的速度还在加速。”他的判断是:“我们仍处于太阳能的 Apple II 时代。”
- Dwarkesh 最有力的反驳来自 HBM:SK Hynix 和 Samsung 当初也对 HBM 发出同样的拒绝信号,但支票一开出来,产能就跟上了——“现在 Samsung 也要来美国,和 xAI 一起建设 AI6。”对此,这场对话的答案是:“他们最终都到了。”支票可以解锁供给。
5. 带日期的判断:2027年破土的数据中心将以太阳能为主
- 如今美国数据中心电力的43%来自天然气;从长期极限看,新负载将接近100%由太阳能供给,而燃煤电厂的运行成本已经高于建设新太阳能的成本。
- 近期判断是:“到2027年,新建数据中心中绝大多数——届时开始破土动工的那些——将以太阳能为主。”由于2027年破土的项目现在已经开始规划,“所以他们才会打电话给我。我的咨询费极其便宜。”在 Scale Microgrids 那篇90/10论文中,演讲者是少数主张100%太阳能的人。
- 用 AI 2027 的算力预测做量级校验:今天约有10M 个 H100 等效算力,到2028年约100M个,每个约1kW,合计约100 GW——“听起来大致正确”。他指出,过渡期可以利用美国境内“少数几个”拥有废弃冶炼厂电网容量的地点,再付钱让闲置老电厂多发电,同时由数据中心承诺在需要时限电;这在功能上就是“一座巨大的自备电池厂”。
6. 每兆瓦10英亩,土地只是四舍五入误差
- 单位化建设方案是:1个1-MW机架、6台 Tesla Megapacks(每台约4 MWh——可储存24小时电量,连续应对“两个糟糕的夜晚”),按 Texas 25%的利用率配置4 MW额定功率太阳能,再做2.5倍超配,把可靠性从一个9推到四个9,最终得到每兆瓦约10英亩。5 GW需要50,000英亩;作为参照,Oak Ridge 和 Hanford 各自约有100,000英亩被划出。
- 针对 Dwarkesh “为什么不直接买50台燃气涡轮机”的问题,答案是:50,000英亩 Texas 土地的成本“也许就是几亿美元”,而 GPU 投资约为$250B——约占项目成本0.1%。组件未加关税时每瓦8美分;安装后每瓦1美元的成本,几乎全部来自其他环节,“这才是 Terraform 让我想不通的地方。”
- 超配不是浪费。Brian Potter 的类比是:你买了一台1TB的 MacBook,却只用100GB,因为“它足够便宜”。99.9%的时间,阵列发出的电力都会超过需求,因此附近城镇只需“把一根电缆甩过墙来”,就能以接近零的边际成本用电。天气预报还允许项目提前3天主动限掉5%的电,而不是危机时被迫限掉50%。并网几乎不重要:这是离网项目,外接的只是“一根可以架在电线杆上的光纤”。
7. 美国的瓶颈是 NEPA,不是物理学
- 监管荒谬之处在于:一次4年的环境影响审查会产生大量纸张,以至于“仅仅为了制作这份报告所造成的环境影响,就超过了直接部署太阳能的环境影响。这太离谱了。”真正让他崩溃的是:一个拿$10,000报酬的生物学家,发现“有一簇草,我们认为它可能是这种蜜蜂有时会吃的20种植物之一”——地点明明是无限制工业用地,夹在火箭试验台和化工厂之间。“我快要变成Joker了。”
- 更荒谬的是,沙漠太阳能“可以说是有益的”(遮阴、保持土壤水分,甚至可能逆转荒漠化),却比把土地推平、铺满混凝土还要接受更严格的审查。政策诉求是:对太阳能部署设置类别豁免——这就是为什么Texas 的部署速度达到 California 的10比1。
- 按他的说法,未来10-20年如果不能摆脱化石燃料,“我们会像英国当年耗尽煤炭那样变穷”;与此同时,沿海城市会被洪水淹没,因此还需要太阳能合成燃料,以及“硫注入和另外几项措施”。
8. 电池接管电网的工作:他最逆向的押注
- 核心概念是:电网执行空间套利,电池执行时间套利。太阳每天升起,因此电池每年大约有300天可以套利;而电网最昂贵的峰值资产几乎从未达到峰值利用率。演讲者特别标记这一点:“这是最价外的那一个押注……我认为这个领域所有值得尊重的预测人士都不同意我。”
- 公用事业正在进入死亡螺旋:运营商无法控制的表后电池,正在蚕食它们收费最高的那些资产;与此同时,工会化维护、征用权诉讼和野火不断推高运营开支。PG&E“永远处于破产边缘”,是“Baumol 成本病的典型案例”。他预计,电网会被大规模削减,大负载则会采用自备电厂,就像过去的铝冶炼厂一样。
- 规模化的事实是:人均锂离子电池重量已经从约10g(一部手机)升至约100kg(一辆 Tesla)——4或5个数量级;“电子从发电到消费之间要走的平均距离,将会非常激进地缩短。”
9. AGI经济学:60万亿美元下限、GDP通缩,能源才是真指标
- 今天的价值链是:一项约$10的订阅,带来的价值更像$1,000;服务成本约为每百万 tokens $1,其中电力约占10%。因此,“10美分电费能产生$1,000的经济价值”,实验室完全可以承受电力成本上涨100倍,把它作为$10附加费,甚至可以买下“贵到让你瞠目结舌”的涡轮机。
- 奖池规模方面,OpenAI 的100-200亿美元 ARR,“太寒酸了,糟透了,他们晚上怎么睡得着?”这个数字甚至低于 McDonald's 或 Kohl's。但全球工资总额约为60万亿美元,而且这还只是下限:用工资总额估算 AGI,就像用“需要多少人和独轮车才能挖一条沟”来限制 Caterpillar 的价值。每次工业革命都会绕过一个瓶颈:第一次是代谢——“我们消耗的能量中99%都绕过了肠胃”;现在则是认知。
- Gwern 和 James Bradbury 提出了衡量问题:Dario 所说的“天才数据中心”在 GDP 中只会体现为芯片和 token 的流动,甚至“可能实际导致 GDP 名义下降”,同时大幅提高真实产出。石油按焦耳计算比食物便宜100倍,却只占 GDP 约1%;弹性比 GDP 占比更重要,因为石油冲击会造成两位数的 GDP 下滑。更好的长期指标,是“我们实际消耗的原始能源”,而不是 GDP。至于 AI 工资,实验室之间的竞争会把价格推向“这些 tokens 边际生产成本的一个小倍数”,而不是人类研究员的20万美元年薪。
10. 吸引子状态:每平方米硅片对应1个人类
- 把整个技术栈压缩到最基本的形态:“一大块相对便宜、用来制造电力的硅,外加一小块相对昂贵、用来进行思考的硅”;如果在太空中运行,连电池都不需要。H100 以约50倍的能耗匹敌人脑算力(1,000W对20W);如果达到人脑效率,1英亩土地可以容纳约50,000个 AI 灵魂,其隐含土地价值将超过人类历史上任何农田。
- 最终形态原话是:“一个人脑大致可以被模拟在漂浮于太空中的一平方米硅片上……这就是未来的人类形态。这就是我的最终形态。”太阳帆搭载 computronium 芯片,向更靠近太阳的位置飞行以获取更多能量,直到热力学极限。更大胆的推测是:4 billion 年的复杂化过程,可能正处在“坍缩回最简单的热力学—认知堆栈”的早期阶段——恒星、硅和激光;他对朋友说:“嘿,我刚编了个新梗。”
- 通往那里的工业路径,是从真正的泥土中提取硅(光伏只需20微米纯度),再用硅烷气体提纯;每座精炼厂需要约18个月。近乎免费的太阳能让人们可以“重新审视传统工业流程……如果我们只是多用一倍电,把它们做得更快、更便宜呢?”Terraform 的设想包括用阳光和空气合成天然气、甲醇、氨、钢和水泥——“我永远不会雇用不会做数学的人。”
Today I'm interviewing Casey Handmer. Casey has worked on a bunch of cool things: a Caltech PhD on gravitational-wave and black-hole-mimicker stuff, then Hyperloop, then the Jet Propulsion Laboratory at NASA. Now he is founder and CEO of Terraform Industries. Casey, welcome.
Thank you. It's great to be here, finally.
Big-picture question I'm interested in: to the extent that AI just ends up being this big industrial race—who can build the most solar panels, batteries, GPUs, transmission lines, and transformers? This is not what the US is known for, at least in recent decades. This is exactly what China is known for.
They have 20x the amount of annual solar manufacturing that the US has. Obviously, we have export controls right now, but over time, SMIC will catch up to TSMC's leading edge. What is the story of how the United States wins this? Why does China not just win by default?
Do you think that China is better at capital allocation than the United States? Do you think the Chinese business environment is better for business than in the United States? I feel you can make these first-principles arguments about these other industries where they're killing it, but it doesn't seem to have hampered BYD or CATL.
People say they're so much better at building high-speed trains than the United States. I would never hold up a flag saying, "I'm really good at building high-speed trains." That is just a sign that you're really bad at capital allocation. Why would you devote, in 2025, so much industrial effort and money to this?
They're devoting a lot to solar overcapacity, which, in your opinion, is the key to future industrial growth.
I think they might be accidentally correct. They called the most important thing correctly, right? Which should count for something. Well, they're in a similar situation to Europe, but unlike the United States. The United States is the luckiest goddamn country on Earth because it's surrounded on 2 sides by oceans and, on the other 2 sides, by friendly allies.
China is surrounded by 15 countries that are mostly hostile to it, with no good mountain ranges or rivers or anything to really separate them. They get almost all their oil from the Middle East, from countries that they don't control and don't have strong diplomatic relationships with, on fleets of oil tankers that they can't defend because their navy doesn't have the ability to operate effectively in the Indian Ocean.
But you're working on this, right? If you get synthetic fuels working at Terraform, doesn't that asymmetrically help China? Which might be fine.
It does. It absolutely asymmetrically helps China. We're not currently working with China, and we don't plan to, but the physics is very obvious.
Synthetic fuels have been around for 100 years. There are projects in China right now working on synthetic fuels. It would not surprise me if they were thinking pretty seriously about this.
Just to spell it out for the audience, China has all this electricity production, and the bottleneck is that only a third of final energy use in a modern economy comes from electricity. The rest, you need gas and whatever to transport things—or coal. They use a lot of coal in China.
Right. What Casey is inventing is a technology to turn that electricity, which can only supply a third of end uses right now, into synthetic fuels, which can supply 100% of the electricity your civilization needs.
This technology levels the playing field. It levels the playing field a lot. But at the end of the day, China still contains the poorest Chinese people anywhere on Earth.
Never underestimate the capacity for an autocratic dictatorship to shoot itself in the foot.
I don't know. I agree that they've obviously made bad decisions, but even if you have the poorest Chinese people anywhere in the world, they can still be quite rich. Singapore is richer.
Also, there are parts of China that actually contain quite rich Chinese people. You have to compare not all of China against the US, but Shanghai and Guangdong against the United States. You can have a part of China that is as big as America, as wealthy as America, and as innovative as America.
The Indian middle class is larger than the US middle class.
But also, it's nowhere near as wealthy. Whereas there are parts of China that are humongous, actually as wealthy as the United States, and in many cases as innovative, et cetera.
Yeah. I'm saying don't underestimate it, but at the same time, we want to find the truth here.
The truth is we should not count the United States out of the battle and just give up. We're very much still in the race now, provided we don't take extra effort to shoot ourselves in the foot.
Right now, we are export-controlling chips for the purpose of keeping our AI lead, and we recognize this is a key input in our ability to compete in AI. So we are going to export-control China's ability to have these chips.
Energy is also a key input in this AI race, and if China wanted to do the converse of what we're doing to them with these cheap imports, what they would do to us is export-control solar and batteries.
It would be asymmetrical. It would hurt them worse than us.
If they did tariffs?
China obviously depends upon the US export market for its economic dynamism. It's going to hurt both parties to sever the link.
But if you sever the link completely, China's ability to make advanced chips right now is basically not there, whereas the United States can make them. The United States' ability to make solar arrays is embryonic, but it's actually not that far behind China's. It's maybe 5 years behind.
If we decided we wanted to produce 100 gigawatts of solar capacity every single year—
We're already on track to do that.
Is it going to be as cheap as it is to do in China?
My views on this are somewhat different from the mainstream, which is great because this is a podcast.
The mainstream view would say China has cheaper labor, which is no longer true because they compare it to Mexico. It has lower environmental regulations, which is true, and that it is more business-friendly, which is absolutely crazy.
There's no way you could justify that your company having to have an inspector from the CCP on its board, who harasses you about Xi Jinping every day, helps you do your business. Also, the rule of law is not great, so you're constantly having to pay bribes to people in order to stay in business.
The idea that the United States cannot compete against that with mostly or fully automated solar-panel manufacturing in the United States—which has cheaper natural gas by far, abundant oil, abundant human resources, great financial capacity, world-leading automation, et cetera—is crazy. We could literally copy-paste solar-manufacturing factories.
How much additional solar-power capacity do you think we could be putting on by 2028 that's manufactured in the US?
This is a good question. When Russia invaded Ukraine, I thought, finally, the Europeans will see sense and they'll pull the trigger on, "We need to localize production of solar panels from dirt to the finished module," which is roughly a 4-stage process.
They didn't. They're still paying Russia $1 billion a day for the privilege of being invaded.
But at the time, I thought they could probably do that in about 2 years. I think the United States could probably do that in 2 years or less if you started today.
It's currently 11 o'clock, so we're going to start cutting checks by noon. You could ramp up pretty quickly. A lot of technology already exists here. It's not like it has to be invented from scratch.
It's mostly a case of putting in a phone call to all the different manufacturers here, in Germany, and so on, and saying, "We need you to 10x the size of your factory, starting today. Blank check. Go."
A lot of your predictions seem to be not predictions, but more like, "If we had World War II levels of motivation, if we had Manhattan Project-level intensity around doing a specific thing, how fast could we do it? If Elon was running the government, how fast could it happen?"
He was, for a brief period.
Maybe then we should put it like, "If Elon ran the government like he ran SpaceX," as opposed to the question of, "What is actually practically likely to happen, given that we are not treating it with World War II-level intensity?"
If you look at xAI, which Elon is involved in, obviously, what are they actually focused on right now?
They're focused on the chips because they understand the key bottleneck is the chips, not the solar power.
Even if Trump puts in a 200% tariff on Chinese solar and we're not able to bypass it via Vietnam or something, it's still a bargain.
[Speaker?]
It doesn't matter. If you need solar to run your data center, it doesn't hurt in terms of the overall cost picture. It doesn't matter at all. What matters is having the chips at competitive capabilities per chip, and enough of them installed in your PCBs, in your data centers, hooked up to your liquid cooling, ready to go.
That's actually something that Elon and his companies are great at. It's figuring out this mass production, semi-automated mass production. They've got this facility in Texas which is making the Starlink receivers, completely automated. Dwarkesh Patel
At what point does “Oh, we don't have a solar panel factory” become on the critical path?
[Speaker?]
I very much doubt it's ever going to be on the critical path. There are dozens and dozens of manufacturers of solar panels worldwide that are all competing against each other.
So you're a big solar bull.
[Speaker?]
Yeah.
1. Why hyperscalers choose natural gas over solar
Right now, the hyperscalers are making decisions about the data centers that they're building. They're going to be 1–2 gigawatts, 5 gigawatts in Meta's case. They're making decisions about how they're going to be actually powered. The people with actual money on the line are choosing natural gas. It's not like they can't see the learning rate. They're building things which will be online in 2028 or 2030. Why are they wrong and you're right?
[Speaker?]
It's their job. They probably know more about it than I do. But in all seriousness, if you're like xAI right now trying to build the Colossus data center in downtown Memphis, you want to get it done super fast. “What are all the different things we need? What are the factors of production to build this? We need a building. We don't have time to build a building, so we'll buy a building. Okay, we'll adapt it. We need power, we need thermal cooling.”
That stuff you can deliver on a truck, so that's what they did. You need access to gas. They had access to gas there. They could tap into a local gas line. If you can tap into a gas line, generally speaking, you can get enough power. The energy transmission capacity of your regular gas delivery pipelines is way, way higher than electricity overhead lines, and it's easy to upgrade.
So if you're in this situation right now, you say, “Are we constrained by our ability to go and rent gas turbines?” No, they're not, because there was enough available once, maybe twice. But at a certain point, you realize as you grow, you start to touch all these additional constraints. Some of those constraints include gas availability.
There's a lot of chat about doing this in Pennsylvania, where there's quite a lot of stranded gas, and in parts of Texas. But at the same time, the United States is gearing up in its ability to export natural gas overseas, so the price will not be infinitely low forever.
You start to run into constraints around turbine manufacturing rate, around transformer production rate, around grid capacity, and also running into problems where the AIs and the humans who depend on legacy electricity production and delivery utilities are competing with each other. We just saw this recent forward auction in PJM result in very high, unsustainably high prices for consumers who depend on cheap electricity to heat and cool their houses and have general prosperity.
If you look far enough in the future, you can just turn up the dial arbitrarily high. You can say we're going to put in a gigawatt a year. Well, we can meet that constraint with gas turbines. We're not going to run out of natural gas at 1 gigawatt per year indefinitely. What if we're doing 5 gigawatts per year? What if we're doing 50 gigawatts per year? What if we're doing 100 gigawatts per year? You can just break the situation.
Not to reach prematurely for analogies, but Henry Kaiser set up the shipyard in Richmond, just down the road here in San Francisco near Berkeley. He was initially making ships for the British, and by the end of the war he had 4 separate shipyards operating in parallel, to the point where he was bottlenecked on his supply of steel.
Steel was rare enough in the war, because everyone was using it for different things, that Kaiser Industries went off and built not only a steel mill, but also a steel mine. They went and started digging rocks out of the ground to turn into ships. That's the same sort of situation you have here, where you have these massive industrial verticals.
Here I'm quite bullish on xAI in particular because the Elon cinematic universe has just done so much industrial stuff compared to the Googles and Metas of this world. They can reach all the way down into primary material supply if they need to.
PJM has all kinds of different sources of power. They have nuclear as well, they have gas, they have coal, all kinds of stuff. This price here is probably driven more by the delivery cost growth than by the generation cost growth, if that makes sense.
When you pay your utility bill, the cost is sometimes broken down into a delivery cost and a generation cost, sometimes importation costs and other things. The delivery cost is what it costs the utility to build and maintain all the power lines that connect all the houses to all the power plants in some gigantic area divided by your marginal usage, with all kinds of other complicated rules designed to make it fairer.
The problem that we see—and the reason that PG&E here in California, for example, is perpetually on the brink of bankruptcy—is that even though the cost of an additional solar panel or additional wind turbine or additional gas turbine or whatever is relatively cheap, getting that power to your house is really expensive.
Why? Because you've got generally unionized labor that has to build and maintain power lines in areas that already have built-up infrastructure. You have multiple collisions, whether this is a power pole on your own street or building a new transmission line, which requires you to use eminent domain on land.
So you're in court for years and years and years, spending public money litigating against other people who are also spending public money to litigate against you on behalf of other interest groups, and so on and so forth. Then you've got wildfires. It's just the poster child for Baumol cost disease.
One of the reasons that we're going to see large-scale pruning of these grids is that we just can't afford, under our current regulatory regime, to maintain them.
When you say pruning, will everything just go off-grid?
It's fairly clear to me that for really large captive loads, like AI data centers or aluminum refineries or whatever, you're going to have to build your own power plant for them, which is how it used to work. If you had an aluminum plant back in the day, you would be building your own power plant for it as well.
It seems inefficient to have redundant power plants at every single industrial site. Let me paint a grand vision for you. It would seem inefficient, but if you are sensitive to the cost of power expressed in supply elasticity or something like that, you just have to do it. There's no two ways about it. Is it inefficient for the xAI Colossus data center to have its own captive power plant, which it does on the backs of a bunch of trucks in the parking lot?
No, it's not inefficient. It's the cheapest way for them to get power.
Okay, AI might be a special case. But big-picture question: across different kinds of ISOs, from Texas to Pennsylvania to whatever, people are building data centers which will not be online for many years. They're choosing natural gas. What's going on? We haven't completely exhausted the supply of turbines relative to GPUs. Do you have some estimate of when we'll run out of them? Because we can also make more.
[Speaker?]
Everything before about 2030 is spoken for at this point.
Yeah, you could make more turbines.
[Speaker?]
The funny thing is that it's actually relatively expensive to spool up additional production of these turbines. Here's one thing you have to grapple with sooner or later. Conventional power generation is a steam engine. You have some kind of chemical that you find inside the Earth that is out of chemical equilibrium with the atmosphere, and you burn it and it makes heat. It could be coal, could be gas, oil.
You're giving me the true birds and bees here.
Yeah, exactly. And it makes heat and you boil water. The water goes through some kind of mechanical contrivance that creates motion. That motion twists a magnet and generates an electrical field, which then pushes electrons down wires, which then push electrons through a series of gates that then approximate thinking. It's kind of complicated.
[Speaker?]
But the key step in this is converting heat into electricity in the most efficient way. The most common way is the same for a nuclear plant, a gas plant, a combined-cycle plant, a coal plant, or whatever. It’s called a Brayton cycle. The jet engine on an aircraft is a Brayton cycle as well.
Anytime you have a Brayton cycle with a bunch of Inconel spinning at high speed, it’s just going to cost you a bunch of money. It’s inherently expensive to build.
Because it’s inherently inefficient, or what? GE makes these 100-megawatt gas turbines, right?
[Speaker?]
I don’t actually know what the retail price is. I would suspect that, if their price is flexible, it would have gone up a lot. But if I recall correctly, $35 a megawatt-hour is just the floor cost.
How much, sorry?
$35 a megawatt-hour just for the Rankine cycle. We’re not talking about the fuel, the heat exchangers, the cooling ponds, or anything like that. Just the amortized cost of the high-speed, high-temperature spinning components is $35 a megawatt-hour.
Do you think the hyperscalers are being irrational, or do they have some reason?
[Speaker?]
To be clear, they don’t care about the cost of power. This is very counterintuitive. For Grandma Kettle in Pennsylvania, she’s very sensitive to electricity costs. We don’t really want her to suffer in her retirement from unaffordable electricity costs and have to sit there shivering. That’s not the image that we want.
At the same time, what is the economic value to you of using Claude or Grok, or whatever you use, on a monthly basis?
A lot. It’s obviously much more than the subscription, but is it maybe 10 times more than the subscription?
Yeah, easily. Let’s say the subscription is on the order of $10. The value is on the order of $100.
No, it’s probably more like $100 and $1,000.
How much does it cost xAI or Anthropic, or whatever, to serve your usage? The marginal variable cost of serving it, in electricity, is less than 10% of the actual cost. Their cost of serving it is maybe a buck per million tokens or something like that. The cost of electricity is about 10% of that.
So 10 cents of electricity is generating $1,000 worth of economic value. It’s very obvious that Anthropic could be like, “Our electricity cost basis has increased by a factor of 100. Now instead of paying 10 cents on your $100 bill for power, you’re paying $10. So we’re putting your subscription up to $110 for an electricity capacity charge.”
Then they could go out and buy turbines for prices that would make your eyes water.
2. Solar's astonishing learning rates
Okay, so then why are we going to get the solar future? In 2032, we’re going to have hundreds of gigawatts of extra demand for data centers, and at that point, most of it is coming from solar? Why is that?
[Speaker?]
There aren’t enough turbines being manufactured.
We can probably overlay the graph of how many turbines were being manufactured. Right now, we’re at historical—
They’ve ramped up basically to the early 2000s rate again.
But you have to make more solar panels as well, right? There will be supply elasticities for both solar and natural gas. Is there some reason to think that it’s worse for the supply chain involved in having a natural-gas-powered data center than a solar one?
[Speaker?]
Yeah, I do. The learning rate for natural gas is nowhere near as steep as solar. It just tells you that it’s easy to make solar panels—much easier to make solar panels. There are very few manufactured products that are easier to make. The Wright’s Law coefficient is 43%, so every time we double cumulative production, we get a 43% reduction in cost.
What is the basis of that? Why are we finding 43% worth of things that can be made cheaper or more efficient every single year?
[Speaker?]
Roughly speaking, there are 10,000 manufacturing-process engineers working on this full-time.
That could be true of any process, but no other process sees the kinds of learning rates that solar is seeing.
[Speaker?]
That’s not strictly true. In order to sustain this over a long period of time, you obviously need to have demand elasticity that exceeds your learning rate. Otherwise, after a couple of OOMs, you would saturate your market at the current price and have no additional growth.
But in this case, roughly every 2 years, we’re doubling production. Every 2–2.5 years, we’re doubling production and the price is coming down by a factor of roughly 40%. So it’s roughly 15–20% per year. Then, just as a result of that price reduction, demand skyrockets by probably 6 times more than that additional marginal production-capacity increase.
This is one point where I’ll say the so-called pros are definitely wrong. Conventional wisdom is that solar demand is going to saturate this year. It’s going to saturate. We’ve got a graph here somewhere that’s like, “This year is it; it’s never going to grow anymore.”
Instead, it’s just blasting out the top of the graph. This conventional wisdom is wrong. Not only are solar adoption, production, and price decreases continuing, they’re accelerating. The rate at which they’re accelerating is still accelerating.
The rate at which it’s accelerating is accelerating?
Yes, as measured in the total fraction of energy that’s coming from solar?
In the sense that its fitness for the markets that it’s being produced for is increasing over time. So it’s still extremely early. We’re still in the Apple II computer era of solar.
Backing up, if the story is that the reason solar is getting cheaper is because there’s a lot of demand for more solar, and that demand can sustain economies of scale or whatever is going on—then shouldn’t that also be true of gas turbines, transformers, power stations, and whatever else is required for the non-solar future?
We’re expecting AI to drive up demand for power regardless of the source. To the extent that the story for solar becoming cheaper over time is just that demand will go up and that will drive efficiencies, why isn’t that true for gas turbines and the other infrastructure?
[Speaker?]
I’m going to go out on a limb here and agree with Elon Musk on this.
Let’s say you’re a bank, and you’re trying to decide whether to lend GE a bunch of money to expand production of its gas turbines. You can write them the check today. They’ll start scaling up their factories. They’ll start to see the benefits of that in 3 or 4 or 5 years. You don’t know if the AI bubble will have burst by then.
You don’t know if China will have invaded Taiwan by then. You don’t know if Siemens or Mitsubishi or someone will have outcompeted you. You don’t know if GE’s major looming structural problems will cause it to be unable to compete, as it has in the past.
[Speaker?]
In order to make that money back, you also have to then operate that plant at that capacity for 20 years. If I were looking at the same charts as they’re looking at right now, I’d say, “What are the odds that, in 25 years’ time, we can produce gas turbines at a price that is relevant in a world where solar is already at its current price and batteries are at the price where they already are?”
You cannot win.
I feel like there was actually a similar discussion a year back when AI people were like, “No, AI is real. This is going to happen.” Then SK Hynix, Samsung, and others were like, “We’re not ramping up HBM production because HBM is used largely for AI workloads, and if this demand doesn’t continue, then our additional manufacturing capacity for HBM will not have been worth it.”
Then there was another bottleneck with CoWoS. What happened after that? Did they end up indeed ramping up their production?
I think so. When someone says, “We can’t do it, we won’t do it, no way, no how,” what they’re saying is, “Write me a check.” And they did. Now Samsung’s coming on board in the States to build AI6 with xAI, I think. So they all got there in the end.
Maybe it’s worth going into the numbers. Right now, 43% of US data-center power consumption is from natural gas. Basically, you think asymptotically that it will be 100% solar if you go to 2040?
[Speaker?]
Yeah. Obviously, legacy production—coal and stuff—is going to retire over time. If a gas plant is still making money, people will keep operating it. It is the case right now that operating a coal plant costs more than building a new solar plant, so it’s just cheaper to turn it off.
Also, capacity is going to increase a lot, so that helps to dilute the existing production. The amount of energy used by data centers will just be exponentially higher. The amount of data-center energy use will increase by a lot, so the new stock matters a lot compared to the existing stock.
Anyway, I want to know: in 2027, what fraction is natural gas? In 2030, what fraction is natural gas versus solar?
For new load?
Let’s say new load.
For new load, 2035, etc. If eventually you're right that we'll pave the earth in solar panels to sustain quadrillions of AI souls, what is the pace of that? The question to ask is, what is the major constraint on that ramp-up? Then everything else will just draft in behind.
I suspect that the hardest thing to make will always be the silicon, like the GPUs. So the question is really, “How quickly does TSMC ramp up its production of GPUs?”
That's a question for you, not for me. I'll use some numbers that AI 2027 used for their compute forecast. Even if you don't buy their singularity thing, I think they did a reasonably good job with crunching the numbers on their compute forecast. I think they said there's on the order of 10 million H100 equivalents in the world today.
I think they said by 2028 there'd be 100 million, so basically 10× more H100 equivalents in the world. About a kilowatt each, something like that. Okay, so that's like 100 gigawatts. That sounds roughly right.
You're not the first person to give me a call and ask me about this. I'll put it that way. I'm not going to name names. Pretty much all the names you've heard of have given me a call and said, “We know that you're a minority voice on the paper that came out recently with Scale Microgrids talking about how you could do 90% solar, 10% gas.” I said, “You can go all the way 100% solar.” I wrote a blog post about it.
So they always call me up and say, “What about this?” They're all talking like 5 gigawatts in the next few years. That's just like 90+% solar for just those. So within a few years, we'll probably see that the majority of new data centers that are going in will be mostly solar.
Within how long? Let's say by 2027, the majority of new data centers going in at that point would be mostly solar. Going in as in…?
Groundbreaking at that point.
But if you're groundbreaking in 2027, you're probably planning it now, right?
That's why they're calling me. My consulting fees are extremely affordable. But I don't have deep visibility—because I'm not in the same room with the Meta people—as to when we're going to hit the wall on transformers and when we're going to hit the wall on just how much municipal peak load we can shave off, which is the latest thing that's been doing the rounds.
It turns out there's a handful of places in the United States—and by handful, I mean literally a handful—where there might have used to be an aluminum smelter. There's a bunch of latent capacity in the grid. And there's also a bunch of generators on the grid that are notionally turned down.
They operate at, say, 40–50% capacity factor, but they max out at about 80% capacity factor because you've got to bring them down for maintenance pretty often, especially if they're old. So they're saying, “Well, you know, we could pay you just to operate this old coal plant or something at higher capacity. It'll go down this power line to this place where the smelter used to be. We'll set up there, and then we promise to curtail when you need the power.”
That basically means they just have a massive captive battery plant as well. Which is fine, you just buy that and it arrives on a truck. The major advantage to doing that over the pure solar play is that the power is already there, so there's no risk there. And you don't need a massive amount of land.
The problem with the solar approach is that there's no two ways about it. It's a farming operation. You need a huge amount of land. Of the total amount of land that you're using, less than 1% is under batteries, under roads, under data center structures, et cetera. It's mostly solar.
3. How to build 50,000 acre solar-powered data centers
Let's get into what this looks like. If you've got a 5-gigawatt plant you want to build, break down the numbers for me in how much land in terms of solar you need to farm this out.
I was talking to somebody in this space and they said, “Obviously, the cost of energy for these data centers is a small fraction of the total cost. Most of the cost is going towards chips. So then the issue is just, can you make the energy available?”
They were saying that even though solar panels themselves you can acquire, the issue is getting that much contiguous land and getting the permitting to interconnect it. That's apparently a big hassle. It's kind of a nightmare. So they're like, “Well, at that point, is it actually easier than just getting on the grid or…?”
Anyway, if you need tens of thousands of acres of solar, where can you do that?
Basically in Texas. There's this very popular misconception that there's not enough land to do solar. This is garbage. If you've ever flown in an aircraft in the United States and you've ever looked out the window, you'd be like, “Oh, wow, look, there's a lot of land you could put solar on.” Especially west of 110°.
Does it need to be flat, or no?
No. Doesn't matter. Do trees grow on mountain slopes? So it doesn't matter. For reference, Nevada is something like 80 million acres. Just Nevada, which is like 90% federal land, is 80 million acres.
I would never say that we should sacrifice Nevada to the AI and pave the entirety of Nevada from one wall to the other.
But I just saw a bunch of things in my feed the last couple of days that Vegas is falling apart. The boomers are retiring. No one goes there anymore. People would go to see the 100 million acres of solar. Even if you did it in Nevada—
We can do it anywhere. You can do it anywhere you can find the land. People say that you can't do this in Europe because Europe doesn't have solar power. Europe has solar power. I've been to Europe in the summer. It's sunny for 20 hours of the day. It's a bit seasonal. But that's not a big deal.
But I mean it is. Because energy is a small fraction of the cost, you care more about making sure the chips are running all the time, right?
In practice, what happens is… Let's say Europe hypothetically awakens from its slumber and decides it wants to participate in AI. I hope it does. They say, “Well, we're going to have to put 100 gigawatts of solar down at some point to build these data centers.”
It will most likely be in southern Europe. Spain is not particularly heavily populated. That's a great place to start. So we put in 100 gigawatts of solar data centers in Spain.
Basically, if you're spending AI hyperscaling money on your GPUs, you want to have four nines of uptime in order to maximize your tokens per dollar spent on the entire project, not just on that. This is a very subtle point. I can go into vast detail on it later on, maybe. Let's just say you need four nines of uptime.
In order to achieve four nines of uptime in the middle of winter, you need to have a lot of solar overbuilt. Is solar overbuilt a bad thing? No. Is the fact that we produce 40% more food than we need a bad thing? No. It's much better than producing 40% less than we need.
It just means that effectively, you have a giant captive power plant attached to a data center that 99.9% of the time produces more power than it needs. 99% of the time it produces much more power than it needs.
That can now actually be the source of power for the local utility, which, instead of being like, “Naughty, naughty data center, you must disconnect when we tell you to,” they say, “Hey, data center, I noticed you've got a bunch of power you're not using 360 days of the year. Would you mind ever so much if we threw a power cable over the wall and we powered our entire town off your spare power at essentially zero marginal cost, plus whatever residential batteries that we need in addition to local power supply?”
Brian Potter had a good analogy in his blog post about this. He's like, “My MacBook has a terabyte of storage and I use 100 gigabytes. I just got the terabyte version because it's cheap enough and I might need it at some point, and it's worth it.”
You're saying solar gets so cheap that it's the way we'll treat hard-drive space. We get a bunch of excess.
Also, the market will be made at the new marginal consumption and production. All the people who are working in the space right now are like, “Oh, I'm in the business of delivering power or storing power. I'm going to serve the AI market because that's where all the growth is occurring.” That's where all of US GDP growth is occurring right now.
I guess you didn't answer the question of, yes, theoretically we could do this, but is it going to be possible to get the permitting to have tens of thousands of acres of contiguous land?
It doesn't need to be contiguous. It helps if it's contiguous. It doesn't need to be convex. You can have a bit over here and a bit over there and you can wire them together relatively easily. In fact, in the limit, you have fields upon fields of solar arrays with…
Tell me your dream, Casey.
Fields, just solar arrays as far as the eye can see. Then, within the solar arrays, roughly in the middle of them, you have your batteries and your data centers. I’ve played Factorio. I remember this optimal layout of batteries and solar.
You’ve got your batteries and your data centers. In terms of ground-floor area, it’s roughly 10% racks, 10% access to the racks, maybe 50% batteries stacked up on top of each other, and there’s also cooling, something like that. That’s in terms of what sits in the centralized node.
That could be 100 megawatts, or it could be 10 gigawatts, depending on how you want to scale this. But then all you need to connect that to the outside world is an optical fiber cable, which you can string up on poles or run underground. You could even use microwave links if you really wanted to. You could use Starlink if you really wanted to.
I don’t know if Starlink would be fast enough. I’m not sure if its capacity is high enough. You could use laser links if you really needed to. That’s it. It’s this completely self-contained world of computation.
Because it’s off-grid.
Yeah, it occurs off-grid, on private land somewhere in the backwoods of Texas where no one lives and no one will ever live because it’s completely inhospitable to humans.
In terms of the ratios, one trend that was impressed upon me is that the power density of racks is increasing a lot as the FLOPs per GPU are increasing. A megawatt per rack is what they’re heading to now, which just seems bananas to me. I think it was even more than that.
Let’s get concrete here for a second. Let’s say you’ve got 1 rack and it’s 1 megawatt. I’ll leave the cooling to someone who specializes in air conditioners, but it’s basically throwing air conditioners at the problem.
Then you have batteries. So, in order to get 4 nines of uptime on this—in South Texas, you actually need less than this—but let’s just say it’s 24 hours’ worth of battery storage. That means it’ll get you through 2 bad nights in a row, basically.
Actually, it turns out that you can significantly decrease power consumption with a very small reduction in overall compute. So, if you’ve got 3 really bad days in a row or something, you can dial back your power usage quite a lot without compromising your inference or training.
Okay, so you’ve got, say, a Tesla Megapack, something like 4 megawatt-hours. So, 1 megawatt rack, and then 6 Tesla Megapacks, each of which is roughly 1 truckload worth of stuff. So, 1 truckload worth of rack, and then 6 truckloads’ worth of batteries.
Then, in order to operate this at an average power of 1 megawatt, your solar arrays in Texas will be something like 25% utilization. So, on average, if the sun came up every day and the day was the same length all the time, you would need 4 megawatts of solar arrays, which is about 4 acres of land.
But in practice, because you’re aiming for 4 nines instead of 1 nine, you need an overbuild of about 2.5 times. So, you’ve got about 10 acres of solar. So, 10 acres of solar, 6 truckloads of batteries, 1 truckload of data center, and some cooling stuff.
For how big of a data center?
1 megawatt. That’s just for 1 megawatt. So, 10 acres, 1-megawatt kind of situation at 4 nines. If you want 5 gigawatts, then that’s 5,000 times 10. So, 50,000 acres.
At a larger scale, you can probably cut all those numbers down by 10–20%, but it’s on that order.
And 50,000 acres sounds like a lot. It does sound like a lot. Is it not?
The amount of land put aside for Oak Ridge was 100,000 acres. The amount of land put aside for Hanford was about 100,000 acres.
What’s Hanford? But I don’t know how big that was. Is it like, “Oh, this is so small,” and then you’re like, “Oh, but it’s 100,000 acres,” or…?
Hanford was where they made the plutonium in the Manhattan Project. It’s still largely unpopulated now because it’s a national laboratory. The reason they did that was they thought, “Oh, we’re going to need 4 piles to produce plutonium.”
These are not nuclear reactors that produce exothermic energy, so you can’t actually make nuclear power with them, but you’re making plutonium with them. In the end, they only needed 2. They wanted them spaced out because they thought they might just spontaneously explode, and there were a bunch of other facilities and plants and stuff as well.
Austin Vernon had an interesting blog post where he said that if you have diesel generators or something which can take over 10% of the generation during winter, then you can have a 60% reduction in the amount of solar panels you need to install because you don’t need to plan for that contingency.
Yeah, there’s a balance here. This is not a very complicated optimization problem. For people who do optimization problems for fun, this is how you do it.
You start off with a bunch of NREL data on what your solar abundance is in this particular part of the world, and then you just start throwing solar panels and batteries at it over the course of a 1-year simulation until you hit the number of nines you want.
To an extent, you can trade the amount of panels and the amount of batteries you’ve got back and forth, and there’s a very broad optimum. Or you can throw in a third thing, like a diesel backup or a gas turbine.
The issue here is, if Meta or Microsoft or whoever just wants to get something off the ground, this might be low opex to have this huge solar farm, but it’s high capex, where you need to hire 30,000 people to go into the middle of a desert and install 50,000 acres’ worth of solar panels. They’re like, “Why would I not just buy 50 gas turbines instead?”
Why not just outbid Microsoft, or have Meta outbid Google or something, for the last gas turbine that’s available that year?
Totally. The thing that Meta has realized is that Zuck is running out of time to spend his money to win. The capex is not crazy high, just to be clear. The capex is still dominated by just the GPUs.
How much does 5 gigawatts’ worth of GPUs cost?
I don’t know if my numbers will be wrong, but $250 billion or something.
$250 billion sounds about right. Is 50,000 acres going to cost $250 billion in Texas? That’s so much money. Wait, I did the math in my head, and that’s a lot of money.
We’re talking maybe hundreds of millions of dollars, something like that. So, it’s like 0.1% of the cost is land.
How much does a megawatt of solar cost?
If you go and ask the usual suspects, they’ll tell you a million dollars. But this is one of the things that breaks my brain at Terraform, which is my day job. The modules themselves, without tariffs, would be 8 cents a watt, so that’s $80,000—
8 cents a watt? But they’re like a dollar a watt, including installation and everything.
Including installation and everything. But the panels are the magic part. They’re the thing that turns sunlight into pure electrical energy at 25% efficiency. Everything else should be less than that.
The central takeaway is that the hyperscalers are not power-cost-sensitive. They are power-availability-sensitive. For all these things, you just run into this supply-elasticity wall at the rates of increase that we’re talking about.
Solar is by far the best option for firehosing energy at a given problem because it rains down from the sky.
4. Environmental regulations blocking clean energy
Between the fact that maybe solar prices will go down and the fact that demand is going to go up, do you think electricity prices are likely to rise?
Yes, but electricity prices at this point are a reflection of a regulatory irrationality. This is the same situation in Europe and Australia, for that matter. Your prices will rise until you’ve had enough and you say, “No, we demand that you allow us to take advantage of power technology that’s been invented in the last 50 years.”
In terms of things that are causing us to lose to China, tariffs are neither here nor there because, as we’ve discussed, we’re not sensitive to cost on power. But the environmental regulations that are actively preventing us from deploying renewable energy in the United States—this is the reason Texas is winning.
Texas is out-deploying California 10 to 1. The regulatory environment around solar is just insane. It’s insane.
In the United States, part of the reason that solar has not been deployed at massive scale yet is that a bunch of laws went into action in the early 1970s that were intended to protect our environment. And that makes a lot of sense. Our environment’s a great thing we should protect.
I think people will be familiar with NEPA and whatever, but how is it especially impacting solar?
Let’s say you’ve got a bunch of private land out in the middle of nowhere, and you want to build solar on it. You’ll probably end up triggering NEPA, at which point you now have to do what is not in the law but considered necessary under current regulations.
That’s your 4-year environmental impact review, which generates so much paper that just the environmental impact of producing the report—because you have to cut down trees to make paper—is more than the environmental impact of just deploying the solar.
[Speaker?]
This is bonkers. It is crazy town. The thing that drives me particularly crazy in Southern California is that just because solar is new, and off-grid solar is very new, unless you're very, very careful, you end up getting regulated as though you're trying to build a chemical plant, even though it's a solar array.
The impact of solar arrays on the desert is arguably positive because they shade the ground and improve soil moisture retention. If you wanted to reverse desertification, you would basically just deploy solar panels on it, and that would pay for the process.
But you end up having to go through a more stringent environmental review process than if you just wanted to grade the whole thing and cover it in concrete, or if you grade it and then park a bunch of old rusting cars that are dropping oil into the aquifer, which in many cases you don't need a permit for at all. But to build solar, you have to go through this whole process.
If there's one thing that anyone listening to this can do, it would be to have a categorical exemption for solar deployment. Or if I put money in an escrow account that says, after 20 years, we have to pull this out—we'll pull all the solar out of the desert and it goes back to being desert—I will do that in a heartbeat.
But if I have to hire another biologist for $10,000 to be like, “Well, on that 40-acre plot, we found a tuft of grass which we believe might be one of the 20 species that this particular species of bee sometimes eats, and this species of bee is not technically endangered, but it might be at some point in the future. Therefore, you can't deploy there.”
Even though it's zoned unrestricted industrial and it's sandwiched between a rocket test stand and a chemical plant, for example, in an industrial part of the desert, I'm going to become the Joker. It is insane.
We need to be a bit balanced about this. I don't want to drive species into extinction. But the meta-problem here is that if we don't move our industrial stack off fossil fuels in 10 or 20 years, first of all, we'll get poor the same way the UK did, because they ran out of coal, basically.
The second thing is we'll get poor because we'll flood our coastal cities and put Florida underwater with climate change. We need solar synthetics for that part. We also need to do sulfur injection and a couple of other things.
5. Batteries replacing the grid
People will point out that transmission-line growth has been stuck in a rut for decades. We have all these bottlenecks in terms of substations and transformers, et cetera. Why will this not hamper this abundant solar future?
[Speaker?]
That's a really great question. You and I had a conversation along these lines almost 2 years ago when we first met. It caused me to go and write a blog post.
This is a good way of thinking about it. There's another blog post you wrote, which was also related to a conversation we had, which is “How to Feed the AIs.” That's much more recent. That was after dinner, I think.
To be fair, I usually am fairly clear in my blog posts if I'm shitposting or if I'm serious, but I'm actually dead serious on this one. It's actually the most out-of-the-money bet as well. Everyone else that I consider to be a respectable forecaster in this area disagrees with me on it. That aside, we know why the grid is expensive.
It's a lot of wires strung up in hard-to-reach places that are hard to maintain, especially as the workforce ages, with regulations and all the rest, eminent domain, and so on and so forth. So the grid's not going to get cheaper anytime soon or easier to build.
If you look at the projections of how much grid the DOE would have us build in the next 10 years versus how much is actually being built, it's not even in the same order of magnitude. You say, “Are we totally screwed?” The answer is, “No, we're not totally screwed,” because batteries actually do the same job that the grid does.
This is kind of weird. Hear me out. The grid transports power from one place to another. It transports almost instantaneously, at the speed of light, so it's actually performing a spatial arbitrage.
The idea is that right outside the local nuclear power plant, power is really cheap because they make a lot of it. And in your house, power is really expensive because you don't have a power plant in your house. You pay the intermediary a small fee, and they allow this trade to take place. That's basically how the grid works.
Until quite recently, the only way we had of meaningfully storing electricity on the grid was pumped hydro. That only works in a handful of places and with limited capacity. It doesn't work all that well either. The efficiency is not great.
Now we have batteries. Batteries store power at one time of day, and they release it at another time of day. Batteries are performing a temporal arbitrage—an arbitrage over time. But they can be local, or they can be more remote.
I think we'll end up seeing batteries next to the solar arrays, batteries in the middle of the grid at substations, batteries on the sites of existing power plants that get turned off, batteries in your house, and batteries everywhere in between.
One way of thinking of this is: What is your per-capita allocation of batteries in kilograms per head? When you and I were much younger, the lithium-ion battery was just in your cell phone. So let's say it's 10 grams per person or something.
Nowadays, half the people in this town drive Teslas, so your per-capita allocation of lithium-ion batteries is 100 kilograms or something like that. We're talking about a 4- or 5-OOM increase in total battery per person. That trend is only going to continue.
We've got batteries that are performing this temporal arbitrage. The sun comes up every day, right? So the power swings from midday—you're otherwise curtailing the solar array—to dusk, when everyone's watching TV and cooking dinner or running the air conditioners to cool off in the evening. It's very predictable.
Whereas, “Oh, we had really bad weather, so we had to use the power line that runs to the extra power plants over by Hoover Dam or something.” It doesn't get used nearly as much. Its peak utilization happens almost never, which means that the utilization of the batteries is, on average, let's say, 300 days a year.
The utilization of your most expensive, highest-voltage grid assets is much, much lower. That includes the substations, transformers, and stuff that serve them. So it's a really bad position to be in if you're a grid operator.
You've got this aging existing thing that the batteries are cannibalizing. The batteries are being installed behind the meter. You don't have a say in whether they're being installed or how they're being used. All you know is that your utilization of your asset, for which you get to charge top dollar, is just dropping year after year, at the same time as your operating costs are increasing year after year.
So it's just very clear that the average distance the electron is going to travel between generation and consumption is going to decrease in the future, pretty radically. It's already decreasing. It's going to continue to decrease.
It's especially helpful for solar, but solar is the one that's most intermittent. You can predict the amount of solar power you're going to get in 3 days pretty accurately because of weather prediction. But you can't change the amount of batteries you have.
Well, actually, in the limit, you can, because you can put them on trucks and drive them around. There could be a capacity market for batteries where you drive them around to people who need them.
In practice, it's going to be cheaper just to double the size of your battery because batteries are going to keep getting cheaper and cheaper. But what it does mean is you can say, “Well, I know that I'm going to have 3 low days, so I will start curtailing now by 5% so I don't have to curtail by 50% in 3 days.
“Then overall, for the whole year, I'll only curtail 5 hours, so I'm still at 4 nines instead of having to curtail 24 hours because I can't predict the weather.”
6. GDP is broken, AGI's true value must be measured in total energy use
Okay, let's assume you're right. I think at some point, you will be right. Maybe we disagree about—sorry, I'm not qualified to disagree. Maybe you and some other person disagree about what year it happens.
But it's hard to deny that in the asymptote, our civilization is headed toward lots of energy use for AI and a lot of that coming from solar. In that asymptote, I want to get to the crazy nerd sci-fi.
What does our civilization look like? What is happening? Kardashev Level 1.
[Speaker?]
Let's wait to get to turning the entire Earth into an AI factory. But let's say in the 2030s, where you've got multiple people building sites on the order of 5 gigawatts or 10 gigawatts, the value of the hardware is dependent on its complement, which is the software. Right now, AI models are fine. The hardware they're running on—and the economic value they can generate—is sort of bottlenecked by how good the software is.
But if you actually had AGI, if you had human-level intelligence or maybe even better, running on an H100, that H100 is worth a lot. We're paying a lot for humans to do work. Right now, I don't think AI is that valuable. The models themselves aren't super, super valuable in terms of just pure economic value.
OpenAI is generating on the order of $10–20 billion ARR. That sucks. It's terrible. How can they sleep at night? But for context, McDonald's and Kohl's generate more yearly revenue than that.
But the promise of AGI is to automate human labor. Human labor generates on the order of $60 trillion of economic value. That's how much is paid out in wages to labor around the world. So that's what AGI can do. Even if you curtail it to just white-collar work, that's still tens of trillions of dollars of value.
So once we have models that are actually human-level, they will be worth at least that, pending the fact that you can build them or you can run them. I don't think we should constrain ourselves to, "Oh, well, maybe it'll be some fraction of current payroll," because that's very contingent on humans being humans. That's a lower bound, to be clear.
Oh, yeah, lower bound for sure.
But if you think about someone trying to estimate the upper bound for the market cap of Caterpillar based on, "Well, it takes this many men and wheelbarrows to dig a trench, so it couldn't be more than that," that's obviously the wrong way to think about it.
One way to think about the industrial revolutions is that every time you figure out an industrial revolution, what you're doing is finding some way of bypassing a constraint or bypassing a bottleneck. The bottleneck prior to what we call the Industrial Revolution was metabolism. How many oats can a human or a horse physically digest and then convert into useful mechanical output for their peasant overlord or whatever?
Nowadays, we would giggle to think that the amount of food we produce is meaningful in the context of the economic power of a particular country. That's because 99% of the energy that we consume routes around our guts, through the gas tanks of our cars, through our aircraft, and in our grids and stuff like that.
Right now, the AI revolution is about routing around cognitive constraints that, in some ways, writing, the printing press, computers, and the Internet have already allowed us to do to some extent. A credit card is a good example of something that routes around a cognitive constraint of building a network of trust. It's a centralized trust.
That's interesting. I want to credit James Bradbury and Gwern with making this interesting point when I was talking with them a couple of days ago. If you measure it by GDP, AI's outputs might be underwhelming. One of the complaints that economists have about the Internet is that it's hard to measure the consumer surplus that's created by the Internet because a lot of the goods and services that are made available, you pay zero for them. They don't show up in GDP.
[Speaker?]
Well, it's the same with oil.
In the sense that energy's like only 1% of GDP?
Well, oil is like $8 trillion a year or something, right?
Yeah. But if you said, "One day we're going to consume 100 times more energy in the form of oil than in the form of food—and the per-joule cost of food is whatever it is, the cost of a Big Mac—then oil should be like $800 trillion a year." Per unit of energy, oil, like gasoline, is 100 times cheaper than the cheapest food that humans can digest. Does that mean that we've shot ourselves in the foot by using oil to run our economy because it's so cheap?
No.
Right. Also, its fraction of GDP doesn't correspond to how important it is. For example, oil is like 1% of GDP or something. But if you don't have oil, then you have these oil shocks, which cause double-digit decreases in GDP. So the elasticity of demand often matters more than its raw fraction of contribution to GDP.
Anyway, on the original point about AI, you're going to have this huge deflation. Gwern put it this way. He's like, "If you imagine Dario's data center of geniuses, how is that showing up in GDP? Well, it would be the inputs, which are the chips, the energy, et cetera, and the outputs, which are just the tokens. Neither of those is going to be that astronomical in comparison to the value that data center of geniuses is producing."
In terms of GDP numbers, if that data center of geniuses automates or complements a bunch of human work, it might actually cause a nominal decrease in GDP while at the same time contributing massively to what we might think of as the valuable stuff human civilization can produce. In the long run, it might make more sense to think of the size of our economy, or the size of our civilization, as the raw energy use that we do rather than GDP.
[Speaker?]
Again, GDP will see this huge deflation because the variable cost of running AI will just be pretty cheap as compared to paying humans' wages. At the point where you've got a mixed economy with an AI doing my job and also a human doing my job—
I love how this is the new way we use the phrase "mixed economy."
[Speaker?]
Obviously, I still have some pricing power relative to humans, and the AI thus has pricing power. But if it were the case that a new kind of job emerges that AI is really well adapted to, because it's not competing against humans for most of those roles, it'd be competing against the other labs. You'd actually see the cost pushed down to a small multiple of whatever the marginal production cost of those tokens is. That would be my guess.
It might be a mistake to assume that if we're going to pay a top AI researcher $200,000 a year—
Lol.
Let's say, for the sort of AI researcher that I could be, $200,000 a year—that if an AI comes along that's as good as me, even taking into account the fact that, realistically speaking, I only get maybe 10 hours of really top cognitive work done a week, that it would also be worth $200,000.
Obviously, it'd be worth much more than that in the sense that you can copy-paste its output, and much less than that in the sense of whatever the marginal additional cost of spooling up H100s is. If some kind of role comes along that the AIs are really well specialized at and outcompete the humans quickly, then we'd also expect to see that both the cost of providing that service would drop drastically, at the same time as the overall value generated in the economy by that service would increase a lot.
Exactly. If we think that the value of cognition is going to be unbounded, and the way to derive cognition—to the extent you think solar will eventually win—you can derive it from how much land it takes to power an H100 using solar panels.
[Speaker?]
That is a very interesting derivation. At a minimum, we're going to just fill up all the land. At some point, you might have a declining marginal value of cognition or something. We discussed this earlier. If you have 10 acres of land feeding 1 megawatt of H100s or something, let's say a megawatt is 1,000 humans. So 1 acre is 1,000 humans' worth of cognition.
The implicit land value there is a lot higher than it is as undeveloped desert. It's also a lot higher than it is as the most productive farmland that humanity has ever had. At current hardware efficiencies, I don't know if it's worth spelling out, but basically, an H100 has the same amount of FLOPs as a human brain, but also uses way more energy than a human brain. It uses 50× more energy.
Is that right—20 watts versus 1,000 watts?
[Speaker?]
We know hardware can be at least as efficient as the human brain. The human brain can generate this many FLOPs on 20 watts.
If you do that calculation, that's 50 × 1,000, so 50,000 AI souls off of 1 acre?
[Speaker?]
It could easily be much more than that because neurons are much slower than transistors, obviously. Probably 10 years ago, one of my friends reminded me that the way your phone saves power is that it goes to sleep between you tapping out "hello." It takes a nap for, like, 10,000 cycles. It's kind of nuts. I think Elon Musk has talked about this in the context of self-driving cars as well. Anything humans do is glacially slow from the perspective of a computer.
7. Silicon wafers in space with one mind each
Let's go back to the original point. I was explaining why I think it's plausible that there could be more than hundreds of gigawatts of extra demand from AI in the 2030s.
I want to understand what that looks like in the real world.
At that point, it has become basically this industrial problem. Can you generate enough solar panels and solar modules and batteries, not to mention the chips themselves? That's the industrial point, and then there's a cultural point as well.
Let's start with the industrial point. I want to know what the year 2035 looks like if we've got AGI and we're just bottlenecked by the ability to deploy it. What do you need in order to run? What is the minimum amount of matter that you need in order to perform these calculations? Right now, we're talking about AI racking, the grid, transmission, and a bunch of ISOs and all the rest.
You don't need any of that stuff. Obviously, xAI is on top of this because the first thing that Elon will always ask is, “Delete anything you don't absolutely need.” What you actually need is a big slab of relatively cheap silicon to make the power, and then a small slab of relatively expensive silicon to do the thinking. If it's in space, that's all you need, because it's in the sun all the time, so you don't need a battery.
If you're on Earth, you need a battery as well, so you need some interconnects. You don't need a transformer. You don't even need a DC-to-DC converter. You can actually make do with a buck converter or with relays or whatever to match the current output of your solar array with the charge state of your batteries and the power consumption of your GPU or something.
But a solar array about the size of this desk, for example, will generate about 500 watts in full sun. So you can actually imagine aliens who have different silicon technology stacks building their systems as an integrated solar array with a bit of computronium in the middle, for example, on the same wafer. But that's basically all you need.
On the same wafer? Because it's all silicon?
It's all silicon all the way down. What's silicon made of? It's an element. It's chemically in the crust. There's no shortage of it.
This is a great prompt for a sci-fi exercise, because especially in space, you don't need batteries. The future TSMC just manufactures integrated solar dies. And they can fly around. They're solar sails, and they're relatively dense, so they don't fly crazy fast, but they don't need to because they're immortal.
Is this what the Dyson sphere will be made of, Casey? Is it just going to be computronium at the center of a solar cell?
They can fly closer to the sun to get more power, right up to the thermal limit, and they can fly farther from the sun to go and explore or fly to other planets or something. They can adjust the orientation of the solar sail with LCD panels that could be integrated into the wafer itself.
What's the post-human state? That's it. A solar sail with a silicon die in the middle for compute?
One human's worth of computation. One human brain can be simulated in roughly a square meter of silicon floating in space.
How much, sorry?
1 square meter of silicon, like the thickness of a sheet of paper, floating in space. That's the future human form. That's my final form. That's the attractor state. That's assuming a little bit of software improvement, but I don't think that's...
All that's assuming is software improvement. The Dyson sphere just needs a little bit of tweaking of the algorithm. The area of the panel is the variable there. What do you need in order to make the silicon?
Making solar arrays and making chips are multistage processes. You start off with silicates, which are rocks, ideally in a relatively pure form. You chemically reduce them. A couple of different processes can do that. Then you purify them into, ideally, 6 nines of purity for solar arrays, maybe 9 nines for really nice computers, and grow crystals, cut wafers, et cetera.
So then the constraint is, well, how quickly can you convert the crust into enough silicon to support silicon thought? What does the silicon ecosystem look like? Any thoughts?
Well, it's pretty quick. You have 1 kilowatt per square meter, and then you use that just to rip oxygens off the underlying dirt; it doesn't take all that long. You only need about 20 microns of silicon to make a solar PV array.
You mean actual dirt?
Yeah. Actual dirt has plenty of silicon in it. For example, setting up a brand-new silicon refinery takes about 18 months. But that's just with the current technology. I actually think we may find new ways.
One of the nice things about having infinite free solar power—approximately free solar power—is that you can revisit a bunch of legacy industrial processes that have been optimized for efficiency and say, “Well, what if we just use twice as much power and we just want to do them faster and cheaper?” Less capex, less lead time, more power. Well, you can start solving problems.
It turns out that if you want to chemically reduce silicon, you can do it electrolytically with less efficiency and under a hydrogen-rich atmosphere or something. One of the ways that silicon can be refined is by turning it into silane, which is silicon tetrahydride. I'm not really a chemist, but I think that's right. So, SiH₄, which is a gas, is actually like methane, but one down on the periodic table. Don't breathe it, though.
Once it's a gas, you can filter it from all the contaminants which don't form gases or can be separated by density, much like how uranium is sometimes enriched, but much, much less difficult. You then heat it up to separate it back into pure silicon, where you can then precipitate out a crystal.
The reason I think this is interesting is because whenever people are talking about the AI singularity, often their expertise is not in energy or physics or whatever. They focus only on the cognitive elements of the singularity: How much faster can we make AI smarter, et cetera? I think this is really interesting.
If we have unbounded cognition, which sets up both the ability to supply and to demand more energy, I'm very curious: What does the energy singularity look like? We're just trying to saturate as much of the energy that the Earth receives and turn it into cognition.
That is an interesting concept. For 4 billion years, we've been increasing the variance in complexity of creatures, and then you might see this big collapse.
I hadn't thought about that before, but there's this idea that evolution resulted in this continual ramification and complexification of the thermodynamic gradient. You start with very simple RNA-based organisms. Now you get this industrial economy.
But it may be the case—I don't have a strong reason to suspect one way or the other—that what we're seeing is the beginning stages of a collapse back towards the simplest possible thermodynamic-to-cognition stack.
We have fusion in stars and the inky blackness of space, and that provides our temperature gradient. Then the most efficient way to convert that into usable cognition is silicon. Literally, electrons being pushed across the band gap in a solar array and then taking the return path through some set of gates, making decisions about things and then beaming lasers to their friends, saying, “Hey, I just made up a new meme.”
Should I give you the opportunity to plug why people should work for Terraform?
Just to give you an introduction, Terraform is my day job. It's a company I founded almost four years ago. We are making synthetic natural gas from sunlight and air. We are also working on other core primary materials stuff. We also have a methanol process. Methanol and methane together are precursors to every hydrocarbon you could possibly want. Another chemical, ammonia, processed steel, desalination. We can also make cement and a few other things. Basically everything that the primary industry does, except for glass and paper. We are hiring. Our jobs are available at terraformindustries.com. Yes, the website's meant to look like that because we're very cool. We are some very special people. I know a lot of smart people and I'm privileged to work with some of the smartest people I know. We are mostly mechanical engineers. I will never hire anyone who can't do math. I will never have the problem at Astronomer because we don't have a head of HR. Also the CEO is not having an affair.
Yeah, step one. I think that was a more crucial issue, Casey. Heads of HR can get into trouble.
I'm just saying, everyone does math. It's very important to me that Terraform is the place that ambitious hardware people go to become the best they can be. That is really important. It's not here to check in and get your paycheck and optimize some shiny widget. It's still a small team. It's still like a one project per person kind of situation. And I will level you up—maybe not quite like a Jensen "torture you into greatness" kind of situation, but at times it's going to feel that way. You get to work with the best people that there are, at least on the West Coast of the United States, on this sort of thing. It's also a unique company. I thought years ago, by now we'd have competition. We don't. No one else is doing this except for a small startup in the UK. So you get in on the ground floor, and it's going to be super cool technology. Eventually, we get to go and build it all on Mars as well and help our robot overlords make more of themselves out of dirt. It's pretty cool.
Nice. Come work for us. Casey, thank you so much for coming on the podcast.
Thanks for having me. This was fun.
Yeah.