In Case You Missed It ...

✨ The long-term impact of L’affaire Anthropic (Monday, 731 words)

🎆 A serious paper about the path to superintelligence (Wednesday, 1146)

🚘 Why Waymo is stuck in Big Apple traffic (Friday, 933 words)

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

The Waymo experience is pretty awesome. Sure, the first left turn at a busy intersection might cause a fleeting moment of apprehension, but that’s pretty much it. All in all, it’s an affordable, pleasant drive, as robotaxi passengers in California, Arizona (I rode Waymo in Phoenix last March while attending some MLB spring training games), Texas, and Florida can attest.

It’s a vibe backed by data. A new JPMorgan analysis points out that Waymo is already doing roughly a half million paid rides a week, while its next-generation Ojai robotaxi is expected to cut vehicle capital costs by about half.1 And Waymo isn’t alone. Tesla appears to be “transitioning from a testing posture to a production cadence,” while Rivian has laid out a roadmap that could put tens of thousands of R2 robotaxis on Uber’s platform starting in 2028.

The remaining headaches are real—edge cases, remote assistance, rain, construction zones—but they increasingly look less like proof that the technology doesn’t work than like the operational pains of scaling it. The problems plaguing Waymo’s national expansion push—including New York, Illinois, and Washington, D.C.—have little to do with its actual value and safety proposition.2

An unhelpful New York state of mind

So what’s the Down Wing hitch? Not-so-big shock: Labor opposition, mostly. Driver and labor groups representing taxi, limousine, Uber, Lyft, and truck drivers see driverless cars as a threat to their jobs. These groups have stalled or killed legislation even after Alphabet-owned Waymo offered displacement funds to affected workers. In New York, Waymo offered the state $20 million for displaced taxi drivers as part of talks with Governor Kathy Hochul. She briefly backed a budget proposal in January to legalize Waymo’s cars across much of the state, other than New York City, then dropped it a month later under vociferous union pressure. A second not-so-big shock: Mayor Zohran Mamdani has signaled he will side with the taxi drivers.

Also: In the absence of a clear federal framework, Waymo has to win these fights one city and state at a time. Safety incidents, whether Waymo’s fault or not, keep giving opponents ammunition. Yet the company—and I would assume, the investors participating in a $16 billion investment round last February—is betting that visible demand in cities where it already operates will build support among residents of holdout cities, who will then pressure their own officials to approve it.3 Time might be on its side.

Robotaxi roadblocks

Just how many economic concepts can a single newspaper story illustrate without meaning to? “Why Waymo’s Driverless Taxis Won’t Be on Your Streets Anytime Soon,” reported by the New York Times’s David McCabe, may not set a record on that score, but it comes close. This thematically Down Wing piece, from which I gleaned the above details about Waymo’s troubles, would make a fine teaching aid for a basic economics course. Here are a few of the lessons buried in it, especially ones likely to irritate anyone interested in how government often stymies progress and in the broader AI revolution.

• The classic collective-action problem. Driverless cars offer massive, dispersed benefits to millions of future passengers, but they impose immediate, concentrated losses on a highly organized group: taxi and truck drivers. Mancur Olson nailed this dynamic decades ago. Groups with a lot to lose per person organize instantly and fiercely. The general public, where individual benefits are small, stays home. Waymo’s lobbying didn’t match the unions’ “fierce campaign,” McCabe reports, citing Hochul’s office.

• The carbon-based bottleneck. A technology can be technically flawless and still get choked out by local politics. Waymo already has driverless taxis operating smoothly in lots of cities—necessary, of course, but obviously not sufficient in some places where its expansion is being slowed by union opposition and local politics. JPMorgan puts the political economy point plainly: “Regulation remains the binding constraint outside select U.S. states and China.”

• Visible risks and hidden trade-offs. Waymos are far safer than human drivers on serious-injury crashes, but activists can still exploit vivid or viral accidents—“Waymo confirms its car killed KitKat, the Mission bodega cat”—whatever the cause.4 Don’t expect a nuanced view informed by a balanced cost-benefit analysis. Opponents intentionally weaponize our cognitive biases: how easily we’re moved by scary examples (salience bias), and how readily we stick with what we already know (status quo bias).

It doesn't take some preternatural flash of insight to see how these concepts are also at play with the diffusion of large language models across the American economy. These robotaxi battles are, as McCabe rightly notes, “one of the first political fights over A.I.’s real-world ability to replace human workers.”

At this point, I have little doubt about the economic usefulness of LLMs. The deployment risk isn’t technical nearly as much as it’s a matter of how concentrated losses, regulatory bottlenecks, anti-growth activists, and easily exploitable fears can slow adoption. From that perspective, data-center opposition is merely a convenient vector for attacking AI, one that can riff off these concepts and biases to the detriment of American progress.

Frustrating? You bet.

Now get more frustrated. Let me end with this gaggle of graphs that show the percent difference between the Waymo and human benchmark crash rates by location:

A negative number means the Waymo Driver reduced crashes compared to the human driver. Confidence intervals that do not cross 0% mean the percent difference is statistically significant. The percent reductions and confidence intervals show that the Waymo Driver has a large, statistically significant, reduction in crash rates compared to the human benchmark across many outcomes and locations.

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Goldman Sachs’s safety data also show why raw incident counts can mislead: Waymo’s accidents, regardless of fault, came roughly every 150,000 to 175,000 miles, but NHTSA reports can include minor incidents, non-AV-caused crashes, and apples-to-oranges comparisons across cities and operating models.

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On sale everywhere by James Pethokoukis The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

It was Nobel Prize–winning physicist Niels Bohr, or maybe science-fiction author Arthur C. Clarke, or even possibly New York Yankees catcher Yogi Berra—or perhaps all of them, in one way or another—who neatly observed that predictions are difficult, especially about the future. That paradoxical witticism, for lack of a more elegant term, lies at the heart of the new Google DeepMind paper “From AGI to ASI.”

Like those other guys (maybe?), the fourteen authors—including Shane Legg, the company’s cofounder and chief AGI scientist—concede that “the future is unpredictable.”

But there's more to the story, which is why the paper is so valuable. Because the pace and nature of AI progress are unpredictable and because the stakes are massive, the researchers think it's a good idea right now to map out the possibilities of "how AI itself might continue to develop in a post-AGI world along the continuum of machine intelligence."

Lots of uncertainty, although the researchers claim they are pretty sure about one thing. As they explain:

Perhaps, reaching human-level AGI will take longer than a few years. What can be said with certainty is that even if AI progress continues far beyond human-level AGI, this does not mean that ASI will be omnipotent, and that ASI will certainly be able to “cure” ageing, reshape matter arbitrarily with nanobots, upload human brains, build Dyson spheres, or restore the planet’s climate and bio-diversity to pre-industrial levels. Either way, predictions when AI progress plateaus, and at what capability level, will remain difficult and uncertain.

I dunno. That passage being included actually kind of makes me think these folks may well consider artificial superintelligence, or ASI,1 as being quite capable of all that science fictional stuff. After all, Google DeepMind CEO Demis Hassabis thinks advanced AI will be able to perform some absolute techno-marvels, as documented in The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence by Sebastian Mallaby.

From the book:

The way Hassabis saw things, true general intelligence would make almost anything possible, surpassing the internet, the printing press, or even the Industrial Revolution in importance. It would usher in a post-scarcity world of radical abundance, resembling the future described in the science fiction he had read as a teenager. “People aren’t thinking ambitiously enough about what a post-AGI world will look like,” Hassabis once told me. “I still hear people talking about the limits to our resources. Like, will we have enough to pay for government programs to deal with the fallout from AI, such as a universal basic income? Or for the electricity to power the data centers? But it’s going to be like Iain Banks’s Culture series. We’re going to be mining asteroids. We’re going to solve nuclear fusion. We will have ways of extracting hydrogen fuel from seawater. People are not understanding the magnitude of the change.

Talking timelines

OK, so that's the dream. But when?

Earlier this month Hassabis said AGI was a sooner-rather-than-later thing, “maybe 2030, plus or minus a year, which is astounding to think, really. I think that will be such an enormous transformative technology; it’s gonna effectively be a new human era.”2

And that’s assuming, by the way, we can science our way through various remaining problems, ones Hassabis typically clusters together as the need for “one or two more big breakthroughs,” which he expanded upon thusly during the Big Technology podcast back in January:

“I’m definitely a subscriber to the idea that maybe we need one or two more big breakthroughs before we’ll get to AGI. And I think they’re along the lines of things like continual learning, better memory, longer context windows—or perhaps more efficient context windows would be the right way to say it—so, don’t store everything, just store the important things. That would be a lot more efficient. That’s what the brain does. And better long-term reasoning and planning.”

But remember, we're talking about getting to ASI, which is even harder but hardly impossible. As touted in its title, the paper highlights four possible routes—which could work in unison—from AGI to something far beyond it.

First, “effective compute” may keep rising extremely fast—perhaps roughly tenfold a year—thanks to better chips and bigger chip budgets, plus software that squeezes more out of each one. Second, there’s the wisdom of AI crowds. Even if individual models stall around human-level intelligence, running vast numbers of them—superfast, 24/7/365—and coordinating them could create something far more capable. (The Borg knew what they were doing.) Third, a flywheel of progress. AI could begin helping build better AI, creating a self-reinforcing loop that could tip into an intelligence explosion. Finally, some significant breakthrough could change the game. It could be a new architecture or training method, not just a bigger version of today’s systems.

The good news: “Taking all of this together, we believe that the possibility of cruising past AGI and into ASI territory within the next decade or two cannot easily be dismissed.”

Looking at limits

None of this is guaranteed, though. Doing something that has never been done before will no doubt have problems both foreseeable and impossible to foresee. Scaling could hit the wall of economics and physics—only so many chips, so much electricity, so much money. Did I mention electricity? AI-making-smarter-AI still has to work properly in the real world, and maybe the self-improving feedback loop fades as easy gains run out. There’s no rule flywheels have to keep spinning. Perhaps Team Agents gets bogged down in a bureaucratic quagmire. Also: Counting on big breakthroughs isn’t much of a strategy, really.

And some of the most plausible friction isn’t technological at all: Governments—nudged by a spooked, Down Wing public—could simply decide to slow the whole thing down.

Further, getting to ASI may require something extra, a truly miraculous bit of technological sparkle: the ability to look at today's reality and pull out a genuinely new idea. Such cognitive leaps are what power scientific revolutions. Rearranging known concepts, no matter how cleverly done, is insufficient.

Think of the paper's thought experiment. Take an AI and train it on everything humanity knew about physics before Newton, then ask it to produce general relativity like a techno-Einstein. The authors are skeptical: "It seems highly improbable that the system could reason its way to the laws of general relativity, let alone quantum mechanics, while lacking the conceptual primitives of calculus, universal gravitation, or electromagnetism."

Today's models inherit their concepts from us. Whether a machine can extract brilliant new ones from the world remains, the authors suspect, unsolved.

Which leads us to a robust research agenda, from mapping the bottlenecks more precisely (think Google Street View) to pinning down how self-improvement loops actually behave and what superintelligence would theoretically require. From the conclusion: “And while we can only see a short distance ahead, we can see plenty there that needs to be done.”

Faster, please!

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It’s my recollection that the typical Hassabis speculation has been that AGI could emerge over the next five to ten years. Indeed, he used that exact framing, for instance, in March 2025 when speaking to CNBC (where I am an official contributor): “AI that can match humans at any task will be here in five to 10 years, Google DeepMind CEO says.”

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On sale everywhere by James Pethokoukis The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

True revolutions are tumultuous affairs, and the AI Revolution will be no different—as the past few days have once again reminded. L'affaire Anthropic (the latest version) might well be over by the time you read this, with the government's export controls on the Fable and Mythos models lifted, and so too Anthropic's suspension of those same systems. Still, I think the conflict makes for an important marker of where we are.

Market-loving champions of applying little more than the lightest of regulatory reins on generative artificial intelligence—perhaps agreeing to some voluntary model auditing if pushed—have spent three years betting that Washington would mostly agree.

It’s been a totally reasonable view. Too much Silicon Valley investment, too little appetite for comprehensive new rules that risk all that investment and the upsides of what might come after. And don’t forget about competition with China.

Yet that wager now looks shaky, at best.

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In Case You Missed It ...

🛗 How to finance a space elevator (Tuesday, 1685 words)

✨🧚 What story is Fable telling about the state of AI? (Wednesday, 1383 words)

☀️ Star power, almost within reach (Thursday, 830 words)

🚀 Elon Musk is a trillionaire. Why that’s good news for all of us (Friday, 917 words)

⤴️⤵️ Up Wing/Down Wing

A selection of pro-progress and anti-progress news items from the past week.

⤴ Up Wing Things

SpaceX, the IPO & the Trillionaire Debate

• SpaceX, Now Worth $2.1 Trillion, Pulls Off Goldilocks Debut - WSJ

• Elon Musk is the world’s first trillionaire (on paper) thanks to the SpaceX IPO - The Washington Post

• Musk should go more boldly with fantastical SpaceX projections - FT

• In Defense of Trillionaires - WSJ

• Who Wants to Be a Trillionaire? - WSJ

Frontier AI Labs & Models

• Anthropic Releases Fable 5, a ‘Mythos-Class’ AI Model With Guardrails - WSJ

• Anthropic Releases ‘Safe’ Version of Its Mythos A.I. Technology - NYT

• Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude - WIRED

• Google’s latest DiffusionGemma open AI model comes with a 4x speed boost - Ars Technica

• Jeff Bezos Wants to Build an ‘Artificial General Engineer’ - NYT

• Bezos Bats Down AI Job Loss Fears While Launching New Venture - WSJ

• Jeff Bezos says AI will bring ‘golden ages’ not mass job losses - FT

AI, Jobs & the Economy

• The Job That AI Was Supposed to Kill Needs More Humans Than Ever - NYT

• Where Is the AI Jobs Crisis? - Apollo

• The Great American Job-Creation Machine Comes Back to Life - WSJ

• Walmart tells workers that AI will improve their jobs, not steal them - FT

• San Francisco Is Making an AI-Powered Comeback - Bloomberg

Data Centers & the Compute Buildout

• The Teachers Getting $50,000 Bonuses Thanks to a Massive Meta Data Center - WSJ

• Meta Launches ‘Workforce Academy’ to Train Workers to Build Data Centers - WSJ

• SpaceX signs $30bn deal to lease computing capacity to Google - FT

• Why most politicians are not calling for data center bans despite voters’ anger - The Washington Post

Energy: Fusion, Nuclear & the Grid

• Commonwealth Fusion makes the physics case for its 400 MW reactor - Ars Technica

• DOE approval of Xcimer fusion power plant preconceptual design - World Nuclear News

• DOE approval milestone for Oklo reactor - World Nuclear News

• Small modular nuclear reactor reaches criticality in first test - Ars Technica

• Build It and They Will Come Around - Heatmap News

• Opinion | Geothermal permitting reform bill is a win for energy development - The Washington Post

Frontier Tech: Robots, Qubits, Superintelligence & Mobility

• House Robots Are Coming—and They Will Be Dangerously Cute - WSJ

• The quantum computing revolution is closer than you think - FT

• Superintelligent machines may well need us after all - New Scientist

• Rivian Did It - Heatmap News

• 7 advanced aircraft designs that could transform aviation - Interesting Engineering

Health, Longevity & Biotech

• At 92, she’s as fit as someone half her age - The Washington Post

• Huge Psilocybin Dose Has Incredible Effect on Elderly Dementia Patient - ScienceAlert

• The most hopeful cancer news in years - Vox

• Opinion | AI-powered genomes can help save endangered species - The Washington Post

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⤵ Down Wing Things

SpaceX & the New Space Economy

• The value of SpaceX rockets on its stock-market debut - Economist

• SpaceX is cheap on a price-to-cosmos ratio - FT

• SpaceX signs $30bn deal to lease computing capacity to Google - FT

• SpaceX Is the New East India Company - Project Syndicate

• New Glenn Explosion Just Gave NASA a Headache It Doesn’t Have Time For - Gizmodo

The Anti-AI Backlash & Influence Operations

• The Hottest Gen-Z Tech Trend? Anti-AI - Bloomberg

• The coming rise of anti-AI populism - FT

• NEW POLL: 25% of voters think AI could end humanity and don’t care - The Argument Mag

• Congress wants in on the data center backlash - Axios

• OpenAI Says China-Linked Accounts Aim to Fuel US Data Center Pushback - Bloomberg

• China-linked operatives used ChatGPT to influence data centers debate: OpenAI - Axios

AI Politics, Regulation & Legal Fights

• U.S. Bars Foreigners From Using Anthropic’s Most Advanced A.I. Models - NYT

• Anthropic shuts down Fable, Mythos models following Trump admin directive - Ars Technica

• Democrats Unveil Flood of AI Proposals in Potential Challenge to Tech Giants - WSJ

• Trump’s AI meeting looks iffy — but the fight over tech profits is very much on - Politico

• Trump’s AI fund idea is good politics, but bad economics - FT

• The Road to AI State Socialism - WSJ

• The lawsuits that could give AI its ‘Big Tobacco’ moment - POLITICO

• Anthropic CEO says government should block dangerous AI - Axios

• Anthropic’s New Fable AI Model Is Met With User Backlash Over Restrictions - WSJ

The Economics & Business of AI

• The business of AI is facing 4 harsh realities - Axios

• 4 surprising ways AI is making your life more expensive - The Washington Post

• AI Will Rip Off Consumers Unless They Fight Back - Bloomberg

• KPMG report contained AI hallucinations on benefits of . . . AI - FT

Big Ideas: Accelerationism & the Limits of AI

• What is Nick Land’s philosophy of accelerationism really? - Aeon Essays

• Cognition for Sale by Sami Mahroum - Project Syndicate

Demographics: Fertility & Dating

• Making Sense of America’s Low Fertility Rate - WSJ

• Smartphones broke dating. AI might finish the job. - Vox

Growth, Science Policy & Permitting

• Why Is Europe’s Economy Falling Short? by Philippe Aghion & Simon Johnson - Project Syndicate

• Putting American Science on a MAGA Leash by Stephen Holmes - ProSyn

• Debate over preservation law tripping up permitting talks - E&E News by POLITICO

↕️ Which Wing Things?

SpaceX & the IPO

• Skeptics Question Whether SpaceX Is Worth $1.77 Trillion - NYT

• SpaceX’s IPO is a display of Musk’s dominance - FT

• SpaceX’s $1.78tn IPO asks investors to buy Musk’s moonshots - FT

• How SpaceX’s IPO ambitions ride on Starship’s path to Mars - FT

• SpaceX Owns a Real Business That Makes Big Money: Starlink - Bloomberg

• What the SpaceX IPO Means for This Texas Border Town - WSJ

• How SpaceX Became Embedded in America’s War Machine - WSJ

Sharing the AI Windfall

• The unlikely alliance pushing an AI sovereign wealth fund - FT

• How to share AI riches - The Economist

• AI is revolutionising the stock market - FT

• For a Second Time, Trump Muses About Americans Sharing in A.I. Wealth - NYT

The Value & Economics of AI

• How much value is AI really creating? - FT

• Here’s How Long It Will Take for AI to Reach Its Potential - WSJ

• Why are we still arguing about the industrial revolution? - FT

• Is this the dawn of the Tokenpocalypse? - TechCrunch

AI Governance, Safety & Superintelligence

• Anthropic CEO says government should block dangerous AI - Axios

• Why the world must agree to regulate AI - FT

• Anthropic: You don’t need to worry about recursive-self-improving AI – yet - New Scientist

• Will artificial intelligence soon escape human control? - The Economist

AI Consciousness, Philosophy & Theology

• Will the Pope Owe an Apology to AI? - WSJ

• The Rival Theologies of Artificial Intelligence - Palladium

• Tyler Cowen: AI Isn’t Conscious. Neither Are We. - The Free Press

AI in Everyday Life — Work, Love & Companionship

• In the Hybrid A.I.-Human Work Force, Who Will Actually Thrive? - NYT

• The couples using ChatGPT as their therapist - Vox

• Want a Friend in the AI Age? Get a Dog - Bloomberg

New AI Products & IPOs

• OpenAI Files to Go Public in Test of Investor Appetite for Top AI Startups - WSJ

• Apple Reveals New A.I.-Powered Version of Its Siri Digital Assistant - NYT

• Anthropic Offers Mythos Upgrade for Cyber Partners and a ‘Safe’ Version for the Rest of You - WIRED

Other Frontiers — Gene Editing & Energy

• Are we getting to the point where it’s safe to gene-edit babies? - New Scientist

• Designer babies. Self-improving AI. Are we ready for either? - Vox

• EPA won’t set nationwide standards for data centers - POLITICO

• The Public Backs Nuclear Energy Now - WSJ

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Essays and Q&As

🛗 How to finance a space elevator

The space elevator is having a pop culture moment, anchoring storylines in streaming show For All Mankind and Foundation. The basic case: It turns space access from spectacular one-off launches into permanent off-planet infrastructure—a space bridge instead of space boats.

Going up: High-volume, continuous access to space enables space solar power, orbital data centers, asteroid mining, and lunar logistics.

Can we build it? A physicist told the Faster, Please! podcast the basic science is done—material with the required strength-to-weight ratio has existed since the mid-1990s. Carbon nanotubes and graphene just need refinement. No radical breakthrough required.

The real bottleneck is finance, not feasibility:

• Conventional math punishes it. Standard discounting penalizes anything that pays off far in the future and looks risky up front—exactly what a space elevator is.

• A new lens. Papazian and Swan’s “Space Value of Money” framework factors the project’s impact on society forward over time, so benefits spilling to non-investors carry financial weight.

• The Starship problem. Cheaper launch undercuts the cost-per-kilogram case—but that was always the wrong metric. Judge the elevator as permanent logistics infrastructure, a port or railway.

Yes, but: That dang cable still must be manufactured at enormous length and survive the orbital environment. Until proven, all economic narratives remain conditional.

Up Wing Up Shot: “Conditional” beats “impossible.”

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✨🧚 What story is Fable telling about the state of AI?

Anthropic just released Claude Fable 5, a constrained version of its Mythos system deemed too potent a hacking tool for public release. It outperforms every other publicly available AI, scoring roughly 5 percent higher than Opus 4.8, per benchmark tracker Vals AI.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

Of note, via The Wall Street Journal: “Elon Musk is Officially World’s First Trillionaire.”

Anyone who believes in the American Way of Wealth must be disgusted today by Elon Musk’s achieving trillionaire status today thanks to the Space Exploration Technologies Corporation going public. It’s one thing to reward success—up to a point, of course. (All billionaires are a policy error, obvi. Trillionaires must be a magnitude worse error! Successful bodega owners are tolerated.) But what has Musk ever done? Yes, the company he founded in 2002 is now worth nearly $2 trillion and his stake accounts for maybe two-thirds of his wealth.

Good, good for him.

But again, what did Musk do other than take advantage of Washington’s decision to effectively privatize spaceflight in the 2000s after the American public had spent billions funding NASA and the rocket technology it developed? Only for Musk—and now also Jeff Bezos—to extract and exploit this extraordinary public investment for personal gain (Big Pharma doesn’t hold a candle here), contributing little more than some incremental technical improvement and a whole lot of marketing chutzpah with all his Mars talk. It’s like something out of post-Soviet Russia, where the privatization of state industry created a legion of superrich oligarchs whose only skill was knowing the right people in Moscow.

Sure, I’m being a bit cheeky here as the table-setter before making a few basic points, with the final one the most important.

First, SpaceX’s ability to lower launch costs by roughly 90 percent—through reusable first-stage boosters, but also a vertically integrated manufacturing process and a high-cadence flight rate —is mega innovation equal to any of the past quarter century. That massive cost decline, with another 90 percent or more potentially on the way through full reusability, has fundamentally altered the economics of space and finally made possible the dreams of the original Space Age: orbital cities, deep-space habitats, space-based solar, asteroid mining. The whole retro-futurist shebang.

Second, Musk’s role in making SpaceX super valuable went far beyond introducing concept videos of a possible Mars colony at industry conferences. He made a series of company-defining bets that put SpaceX where it is today. Let’s look at a few of them, resume style:

• Kept SpaceX alive long enough for the fourth Falcon 1 launch to reach orbit, then pushed reusability after the Space Shuttle had left much of the aerospace industry deeply cynical.

• Built a vertically integrated company that could design, test, break, and improve hardware faster than the old contractor model. (Some in the media are still confused on the business model.)

• Made SpaceX its own best customer through Starlink, turning cheap launch capacity into a fast-growing broadband business rather than merely selling rides to orbit.

The 407-foot-tall Starship—stainless steel body, methane engines, full reusability—is the biggest bet of all. (More on below.)

Third, it’s definitely a good thing for Americans when someone becomes superrich starting a company that provides goods and services deemed desirable and valuable by society through its purchase decisions. It’s a sure sign American techo-capitalism is working.1 Steve Jobs, Jeff Bezos, and the Google founders all started companies that sell an economically valuable product. Apple gave us the one device. Amazon built the everything store. Google became the internet’s front door.

And as wealthy as those businesses made their founders, we assuredly made out even better. We always do when an entrepreneur builds a business around an innovative technology or a cheaper way to make something people want. Nobel laureate economist William Nordhaus actually ran the math, finding that innovators captured barely 2 percent of the value their inventions threw off across half a century, leaving the other 98 percent to the rest of us.2

The same will be the case for Musk and SpaceX if the vision outlined in its IPO prospectus—cheap and fully reusable rockets, a planet-scale Starlink business, orbital AI infrastructure, and ultimately cities on Mars—pans out. Massive benefits for humanity, not just SpaceX shareholders.3

And if that vision falters? If, for instance, SpaceX can’t quite get the ginormous Starship to do what the company needs it to do? This from the Financial Times:

At the heart of Elon Musk’s ambitions to send humans to Mars — and propel SpaceX to the largest initial public offering in history — is a gargantuan 407-foot-tall rocket known as Starship. SpaceX hopes Starship will become the world’s first fully reusable launch system. Recycling both stages of the rocket, while dramatically increasing payload capacity, would allow the company to launch more equipment into orbit, carry larger satellites and eventually undertake missions to the Moon and Mars at far lower cost. Yet Starship remains far from operational. US regulators grounded the rocket after the company lost control of its booster during a test flight in May. Turning it into a reliable transport system will require technical breakthroughs, including the ability to refuel the spacecraft while in orbit.

By the way, no Starship means no guarantee on that trillionaire status. The sustainability of the vast bulk of Musk’s wealth depends on his ability to create value through SpaceX that civilizationally benefits us more than it ever will him. Fixating on the size of any Musk’s or any individual fortune misses what is surely the bigger story: If more trillionaires emerge because AI, robots, clean energy, genetic editing, and space access become vastly cheaper and more capable (or simply because someone started a company that’s really good at selling stuff we really want) everyone gains.

That’s the real dividend of techno-market capitalism.

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The dystopian sci-fi assumption—The Blade Runner Fallacy— that advanced technology mainly entrenches elites runs against the historical record of technology raising wealth, health, and problem-solving capacity broadly. Cars, air travel, computers, and smartphones all began as expensive elite goods before becoming widely available — undercutting the fear that AI, robotics, or space tech will stay toys for the rich.

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On sale everywhere by James Pethokoukis The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

As a big fan of the potential of star power, I wasn’t exactly surprised to recently read that Helion, a highly regarded fusion startup backed by Sam Altman, was able to attract a big dollop of fresh funding, $465 million.

Pretty compelling story here. Between its (a) novel technical advances, (b) the reflected glory of Altman (who stepped down from the board in March), (c) the fundraising of other startups in the sector, and (d) the expanding need to clean power all those data centers, Helion should be able to tap investors for cash.

And it did.

I was surprised, however, that the Helion nearly tripled its valuation with this new funding round, a hefty $15.5 billion—and that before ever sending a single electron into the grid or into some Pacific Northwest data center.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

For AI optimists, Anthropic’s release of Claude Fable 5, a deliberately constrained version of the Mythos system that the company deemed too potent a hacking tool for public release (ask Fable about hacking or bioweapons and you’ll get welcomed back to Opus 4.8), might seem an important plot beat in humanity’s fairy-tale journey toward a dreamy world of superintelligence.

According to benchmark testing by Vals AI, which tracks frontier model performance, Fable outperforms every other publicly available AI system. It scores roughly 5 percent higher overall than Claude Opus 4.8, The New York Times reports. Wharton business professor Ethan Mollick writes that Fable “represents a very real leap over every model I have used before, and, maybe more important, suggests our relationship with AI is changing in drastic ways.”

For its part, Anthropic describes Fable’s capabilities as such (and offered the following chart): “Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.”

That chart illustrates Fable's particular strength at coding, something worth noting in light of Anthropic's recent research note, "When AI Builds Itself." The company's own data, combining public benchmarks with internal figures, suggests AI is already accelerating its own development. One eyepopping illustration: Anthropic engineers are now shipping roughly eight times as much code per quarter as they did during the 2021–2025 period. That trajectory, Anthropic argues, points toward recursive self-improvement—"an AI system capable of fully autonomously designing and developing its own successor."

The company continues:

AI that can build itself would be a major development in the history of technology—one that could bring enormous good for the world in science, healthcare, and beyond. But full recursive self-improvement also might increase the risks of humans losing control over AI systems. If systems are capable of fully building their own successors, the ways we secure them, monitor them, and shape their behavior all grow much more important.

More on the progress toward RSI in recent Economist piece that cites a number of reasons to think the ball is moving forward, including a METR benchmark on which the latest models can finish jobs that would occupy a human engineer for more than a working day versus under an hour at the start of 2025. The piece also cites Andrej Karpathy, a former OpenAI researcher and Tesla AI chief who now works for Anthropic, who handed his basic Nanochat model to an AI agent that trimmed its training time by 18 percent without him, as he puts it, touching anything. Also of note in the piece: Jack Clark, an Anthropic co-founder, thinks there is a 60 percent chance that, by the end of 2028, an AI system will be capable of creating its own successor with no human involvement.

Which leads to this:

That moment would mark the beginning of a process called “recursive self-improvement” (RSI), a closed loop. … Build an AI system capable of this, and your human engineers never need to build another one again. ..Nobody knows for sure what the consequences of RSI would be. Because AI can, unlike humans, work tirelessly and constantly, some think it would in short order lead to a superintelligent AI—a “fast take-off”. (It has also been onomatopoeically dubbed “going foom”, for the sound one might imagine an intelligence explosion making). AI doomers fear the superintelligence would be beyond human control, and that the start of RSI is the moment at which humanity’s fate is handed over to the machines.

⚠️ Warning: Super AI Optimists should stop reading here ⚠️

While reading the Fable coverage and tinkering with the model, it occurred to me to do my regular check on prediction markets and what they're signaling about the march toward AGI and superintelligence. This wasn't exhaustive, but I think it's directionally correct. A few contracts and forecasts give a flavor of what I'm seeing:

• “By 2028, will there be a visible break in trend line on US GDP, GDP per capita, unemployment, or productivity, which most economists attribute directly to the effects of AI?” (Manifold Markets) | Currently at 38 percent, down from 52 percent in February

• “When will OpenAI achieve AGI?” (Kalshi) | The “before 2030” contract is currently at 49 percent, down from 62 percent in April.

• “Conditional on no existential catastrophe, will there be a superintelligence by 2030?” (Manifold) | Currently at 28 percent, down from 61 percent in February 2025.

• “When will the first weakly general AI system be devised, tested, and publicly announced?” (Metaculus) | Currently at May 28, 2028 versus May 29 a week ago and April 17 two months ago.

A different vibe, in other words, than what I see on social media. The elephant in the room is the stock market, a pretty important prediction market sending what could be read as a strong signal about the impending arrival of self-improving AI and beyond. But the signal is hardly pure. As the Financial Times notes, some big winners of the AI era—turbine makers like Siemens Energy, steel suppliers like Nucor, air conditioning installers like Comfort Systems USA—are not AGI plays at all. They're just construction companies with a high-demand, deep-pocketed customer.

And even among the purer AI bets, the investment math may work OK without something clearly indicative of superintelligence being achieved. Example: A new general-purpose technology that lifted economywide labor productivity growth by a full point, or even half of one, on a sustained basis would rank among the most valuable inventions in history. I’m not a hedgie, but do investors need to believe in superintelligence soonish to justify hefty bets on Nvidia or Anthropic? Maybe they only need believe AI can do for knowledge work what electrification did for the factory floor.

Mind the gap

My explanation for the apparent paradox: a sizable gap remains between what AI models can do in the lab and how broadly businesses are adopting them in economically valuable ways. That's the core insight of a new NBER paper, "Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools," by MIT researchers Mert Demirer, Leon Musolff, and Liyuan Yang. Studying more than 100,000 GitHub developers, they find that AI coding tools produce large gains in the act of writing code. Alas, much of that gain evaporates before it reaches actual products. A 180 percent jump in commits (the individual code changes developers save to a codebase) becomes only a 50 percent increase in projects and a 30 percent increase in releases. Across major app stores, AI appears to be generating more apps, but not more usage.

From the paper:

When stages of production are complementary, automating one stage has bounded effects on final output: a vertical analog of the “weak links” logic in the macroeconomic growth literature. In software, the binding constraint appears to be shifting from writing code to reviewing, integrating, and ultimately distributing it. Whether future generations of AI tools can ease these downstream constraints—by producing higher-quality code that requires less human review, automating review and integration, or improving discovery and adoption—will determine whether the large task-level productivity gains we document ultimately translate into commensurate increases in shipped and used software.

We’ll see if Fable qualifies as the “higher quality” code that creates more material real-world impact.

Further empirical evidence of that “gap” comes from the updated AI Economic Indicators dashboard from the Stanford Digital Economy Lab. Even as business adoption spreads quickly, the economic payoff remains well short of transformational. Most indicators still look broadly normal, overall efficiency growth as measured by Total Factor Productivity hasn't clearly accelerated, and only a handful of investment-related measures are flashing strong signals. More patience required, I guess.

This much is clear: The productivity revolution is still waiting to arrive. Also clear: The delay may not be entirely because Silicon Valley has failed to build clever enough models. The harder work is turning software into products people actually use, embedding them in firms, and wringing measurable economic value from them. These are problems of organization and execution, not merely of intelligence. Fable’s real test, then, might be whether it can help conjure away those bottlenecks. If it can’t, its technical wizardry will count for far less.

No fairytale ending there.

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On sale everywhere by James Pethokoukis The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

Until recently, the only film or television depiction I had seen of a space elevator was in “Rise,” a 1997 episode of Star Trek: Voyager. Yes, it was pretty cool (as the below image suggests.) As these things go, however, it was a modest example of such a superstructure: a roughly 300-kilometer orbital tether, or cable, linking the surface of an alien planet to a orbital station. Imagine taking a 12-hour journey by maglev cable car to the International Space Station.

Something like that.

Arthur C. Clarke’s classic vision in The Fountains of Paradise was considerably more ambitious. The book’s “orbital tower” anchored on Sri Kanda, a sacred mountain in Clarke’s fictional equatorial island of Taprobane (modeled on Sri Lanka where Clarke lived). Built from fantastically strong “diamond hyperfilament,” the tower would carry passenger cars from the surface to a geostationary satellite roughly 36,000 kilometers above Earth.

In Apple TV’s Foundation, Star Bridge is a space-elevator megaproject clearly in the tradition of Clarke’s concept. Created for the television adaptation rather than taken from Isaac Asimov’s original novels, the structure links the surface of Trantor to a vast orbital platform in geosynchronous orbit by means of a colossal tether, or “stalk,” that’s some 40,000 kilometers long. To give a sense of scale, if the Star Bridge were—for whatever reason!—to completely collapse the damage would be planetary in nature.

Finally, the just-completed fifth season of (the extraordinarily Up Wing) For All Mankind revolves around construction of a space elevator that would connect Mars with Goldilocks, a captured, iridium-rich asteroid that has become the economic prize at the center of the Red Planet’s future. The show offers lots of nice in-universe, worldbuilding detail, as seen in the following short video:

A space bridge, not a space boat

Let’s start here: Why would a space elevator be worth building, exactly? The basic case is that it turns space access from a series of spectacular one-off launches into permanent off-planet infrastructure—a bridge instead of boats, as enthusiasts like to say. Rather than carrying and burning its own combustible propellant and waiting on weather to be just right, an electric climber ascends a tether to deliver payloads routinely, safely, and far more cheaply. Up and down, no drama.

A second, utterly reasonable question: Can we do this? Even before considering an AI technological kicker, there is definitely a there there.

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In Case You Missed It ...

😵‍💫 AI anxiety and the 3+ confusions of Bernie Sanders (Tuesday)

⤵️ The axis of US decline: anti-data center, anti-AI, anti-nuclear (Wednesday)

🚀 SpaceX and the economics of space (Thursday)

⤴️⤵️ Up Wing/Down Wing

A selection of pro-progress and anti-progress news items from the past week.

⤴ Up Wing Things

Space, energy & infrastructure

• There’s More to Space Stocks Than SpaceX - WSJ

• Elon Musk’s SpaceX pitches investors $1.78tn valuation in historic IPO - The Washington Post

• Goldman Sachs expects SpaceX’s AI revenue to increase 100-fold by 2030 - FT

• Who’s Excited for SpaceX’s I.P.O.? Space Nerds. - NYT

• It Was a Messy Week for Jeff Bezos’ and Elon Musk’s Space Race - WSJ

• Solar sails edge closer to reality, but interstellar travel is another story - Phys.org

• How to Stop a Killer Asteroid - The MIT Press Reader

• X-energy submits Xe-100 for UK regulatory assessment - World Nuclear News

• Nineteen years on, companies team up for US new-build project - World Nuclear News

• Google pushes water standards amid data center backlash - Axios

AI economy, investing & policy

• Anthropic files for blockbuster initial public offering - FT

• OpenAI and Anthropic May Be Rivals, but Investors Aren’t Picking Sides - WIRED

• Alphabet to sell up to $80bn in shares to fund its AI build-out - FT

• Venture Capital Turns to Hardware Bets as AI Threatens Software Companies - WSJ

• Artificial Intelligence and the Global Economy: A Decade of Transformation Toward the 100-Year Economic Quarter (2025–2030) - SSRN

• How AI Could Improve Economic Policymaking - WSJ

• AI Boosting Business Formation - Apollo

• The US Exports Intelligence - Marginal REVOLUTION

• Javier Milei: Argentina invites AI to free itself - FT

• China’s comparative advantage is industrial policy - FT

• Texas is becoming America Inc’s centre of gravity - The Economist

AI jobs & labor

• How One Tech Company Created 13 New Types of Jobs Because of A.I. - NYT

• AI Made My Expertise More Effective - WSJ

• AI Is Taking Over the Most Cursed Job in the World - WIRED

AI in business, industry & products

• How small businesses can leverage AI - MIT Technology Review

• Uber’s AI Doubts Are Just Normal Growing Pains - Bloomberg

• From 15 hours to one minute: How AI/ML is speeding up GM’s development - Ars Technica

• From Cow-Milking Robots to Weed-Zapping Lasers, Farmers Are Embracing A.I. - NYT

• What Are A.I. Agents Actually Doing? - NYT

• Nvidia Introduces First PCs Designed for AI Agents - WSJ

• Nvidia expands AI push with Cosmos 3 world model - Axios

Science, health & medicine

• Inside the Trump-backed push to bring AI doctors into American medicine - The Washington Post

• The blood cancer that became solvable - Works in Progress Magazine

• Cancer jab can eradicate entire tumours in patients, trial shows - The Guardian

• Pancreatic cancer halted by virus injection in three patients - New Scientist

• The science around GLP-1 drugs and cancer is suddenly getting a lot more interesting - The Washington Post

• We May Already Have an Anti-Aging Vaccine - RealClearScience

• Jeff Bezos Is Funding a Wild Hunt for the Brain’s ‘Core Algorithm’ - WIRED

• A golden age of maths is dawning and mathematicians are freaking out - New Scientist

Transport & housing

• Joby Demonstrated its Air Taxi in Manhattan, but You Can’t Fly in It Yet - NYT

• Berkshire Is Convinced the American Dream of Homeownership Will Stay Alive - WSJ

⤵ Down Wing Things

Data centers, power & the build-out

• America’s Data Center Build-Out Is Falling Way Behind Schedule - WSJ

• 60% of planned US data center capacity not under - WSJ

• Americans Now Blame Data Centers for Their Rising Power Bills - Heatmap News

• China fueling U.S. data center resistance, AI groups claim - Axios

AI policy, regulation & risk

• U.S. Officials Discuss Taking Financial Stakes in AI Industry - WSJ

• Trump plan to test AI models has a problem—US security teams were gutted by DOGE - Ars Technica

• The White House’s Missing AI Rule Book Is a Growing Liability - Bloomberg

• Florida sues OpenAI and CEO Sam Altman over ChatGPT - Axios Tampa Bay

• Scientists Find Way to Supercharge Dangerous Computer ‘Worms’ With A.I. - NYT

• How AI could make wars go nuclear - Vox

• China Aims A.I. at Predicting Who Could Pose a Political Risk - NYT

AI companies & models

• Anthropic faces AI spending backlash before IPO - Axios

• Meta Keeps Delaying the Release of Its New AI Model to Developers - WSJ

• The skeptic’s guide to humanoid robots going viral on the Internet - Ars Technica

AI skepticism, sentiment & culture

• Nearly Half of Americans Are Pessimistic About AI’s Effect on Their Lives - Heatmap News

• ‘More harmful than helpful’: young people sour on AI - FT

• The Hallucinatory AI Math - WSJ

• Meet the Sad Wives of AI - Wired

• His Chatbot Nearly Ruined Him. To Recover, He Had to Destroy It. - WSJ

AI, jobs & the professions

• Is A.I. Replacing Tech Workers or Providing an Excuse for Job Cuts? - NYT

• Mathematicians warn of AI threats to profession as industry encroaches - Ars Technica

• AI is ushering in a new era of colonialism - Axios

Science, business & space

• Donald Trump’s proposed grant rules could destroy US science, researcher warns - FT

• Another red alert for American science - Science

• How Rachel Carson’s Silent Spring changed the world in 1962 - New Scientist

• American capitalism has taken an apocalyptic turn - The Economist

• How long will it take to rebuild Blue Origin’s launch pad? We asked some SpaceX vets. - Ars Technica

↕️ Which Wing Things?

SpaceX, Blue Origin & the space race

• Massive Blue Origin rocket explosion gives edge to Elon Musk in space race - The Washington Post

• SpaceX IPO: Elon Musk Capital Needs Are Out of This World - Bloomberg

• SpaceX Needs to Get to $5 Quadrillion to Rival Mag Seven Magic - Bloomberg

• Can the stockmarket swallow Anthropic, SpaceX and OpenAI? - The Economist

AI energy & data centers

• The Electricity Economy Is Having Its Moment - Heatmap News

• How to Fix the Fastest-Rising Electricity Prices in the U.S. - Heatmap News

• AI is turning energy into the hottest business in America - Axios

• Phoenix Is a Data-Center Mecca—and Test Case for How to Pay for AI’s Power Needs - WSJ

AI policy, regulation & national security

• Trump Signs Executive Order Seeking Oversight of A.I. Models - NYT

• The Government Is Finally Taking A.I. Risk Seriously - NYT

• OpenAI diverges from White House on AI safety rules - Politico

• Top AI CEOs Call for Law Protecting Against Biological Weapons - WSJ

• US National Security Agency using Anthropic’s Mythos for cyber attacks - FT

• The China-US tech truce is fragile - FT

• Opt-In Surveillance Is Approaching - AI Frontiers Substack

AI labs, self-improvement & existential risk

• Inside Alexandr Wang’s bid to revive Meta’s AI edge - FT

• The race to build AI that can improve itself - FT

• Anthropic warns AI could soon help build its own successors - Axios

• Anthropic Urges Global Pause in AI Development, Flags ‘Self-Improvement’ Risk - WSJ

• Anthropic’s relentless race to the top - FT

• AI Agents Plunged the Tech World Into Chaos. Here’s Exactly How That Happened - WIRED

AI capabilities, consciousness & philosophy

• A guide for the perplexed on AI - FT

• Why AI can solve hard math problems but can’t count - The Argument

• Top AI labs expand research into machine ‘consciousness’ - FT

• No, Artificial Intelligence Is Not Conscious - The Atlantic

• Robotics: Humanoid Hands Are Physical AI’s Anti-Hype Test - Bloomberg

• The Pope’s AI Vision and Its Limits - Project Syndicate

AI economy, jobs, education & society

• How much value is AI really creating? - FT

• U.S. Capitalism at a Crossroads: Three Questions the Country Now Faces - WSJ

• 5 ideas for how we survive the possible AI jobs apocalypse - The Washington Post

• Classrooms lean into analog learning in the AI era - Axios

• How to Raise ‘AI-Native’ Kids - The Free Press

• China’s Rise in Drug Development Looms Over U.S. - NYT

Essays and Q&As

😵‍💫 AI anxiety and the 3+ confusions of Bernie Sanders

Bernie Sanders wants Washington to seize half of America’s biggest AI companies. In a New York Times op-ed, the Vermont socialist proposed a one-time tax, paid in stock, handing the government 50 percent of OpenAI, Anthropic, xAI, and others—plus board seats and voting power.

Why it matters: This would be an unprecedented act of government intervention in private enterprise, justified by the claim that since AI is built on humanity’s collective knowledge, its wealth must benefit humanity.

A big puzzlement: Sanders is confused on three fronts:

• How innovation benefits society. He downplays cancers diagnosed earlier, productivity gains, cheaper goods, and scientific breakthroughs. There’s more to ROI than government checks.

• AI’s trade-offs. A government owning half of OpenAI has every incentive to keep it growing, not slow it down. Sanders seems confused.

• AI being like oil. Data is an input, not a scarce product. No working GPT existed before OpenAI. What a tired analogy.

Up Wing Up Shot: Social-media-ready politics, not serious policy.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

A public SpaceX will be a great boon for those intrigued by the economics of space. Elon Musk's rocket company was responsible for more than 80 percent of all mass launched to orbit in 2025 and is a key element of America's long-term space efforts. You can’t study the subject without studying SpaceX, and it will soon be a lot easier.

SpaceX’s new status is also going to give plenty of insight into Musk's artificial-intelligence plans. The Financial Times reports that while SpaceX wants investors to believe in its rockets—especially Starship—they should also focus on chatbots. The $1.8 trillion valuation that Musk is chasing rests on a wager that xAI, its AI arm, can multiply revenues roughly 100-fold by 2030. Goldman Sachs, the lead investment bank, reckons the unit will generate a whopping $322 billion in revenue that year, up from $3.2 billion in 2025. Such arithmetic assumes, according to the FT that xAI addresses a $27 trillion potential market, and that Grok, the unit's family of models, vaults past rivals Anthropic, Google, and OpenAI across coding, security, and agentic tools. (The latter may be more a stunner than the former.)

Good luck, and let’s light that IPO candle!

But let’s also return to the economics of space, which will no doubt play a role in the future prospects of SpaceX, Blue Origin, and other players in the expanding sector. To me, it’s a fascinating topic made less theoretical by SpaceX, as will become clear in the following paragraphs. Some of this quasi-literature review may be familiar to long-time readers, most of it won’t be.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

The following pair of public-opinion polls (both from the always informative Heatmap) will no doubt hearten Down Wing activists who (a) hate artificial intelligence for myriad reasons, (b) hate the idea of nuclear energy powering AI, and (c) hate the idea of nuclear-powered AI increasing humanity’s productive capacity and material progress.

Up Wingers, on the other hand, should find these survey results concerning, even demoralizing. I mean, it isn’t complicated. If you think the application of machine intelligence could mean a massive upgrade in our civilizational ability to solve our biggest problems today and new ones tomorrow, then you want to see the continued buildout of the physical backbone of the AI Revolution—including data centers.

A lot of that infrastructure is already being built, and a lot more is on tap. Goldman Sachs says private data-center construction has accelerated sharply, with a significant backlog still not under construction, and its equity research team now expects the four largest hyperscalers—Meta, Microsoft, Amazon, and Alphabet—to spend a combined $5.3 trillion in capex from 2025 through 2030.

Regular folks have lots of (mostly unfounded) worries about electricity and water usage, as well as about AI itself—threats both job-related and existential—that data centers enable. But I have little doubt some activists are not only concerned about those issues but see data centers as a welcome new attack vector against the ongoing nuclear revival.

It must have been incredibly galling for old-school environmentalists to see Constellation Energy is restarting the undamaged Three Mile Island Unit 1 reactor, now renamed the Crane Clean Energy Center, to provide a reliable, carbon-free energy supply for Microsoft’s AI data centers. The 1979 TMI accident was, after all, pretty much the final nail in the coffin for the further expansion of American nuclear energy in the 20th century.

Five decades later, not much has changed: This from the Sierra Club, the country’s largest environmental organization:

The Sierra Club remains unequivocally opposed to nuclear energy. Although nuclear plants have been in operation for less than 60 years, we now have seen three serious disasters. Tragically, it took a horrific disaster in Japan to remind the world that none of the fundamental problems with nuclear power have ever been addressed.

While the Sierra Club was not one of some two hundred environmental groups (including Greenpeace USA) signing a letter demanding a halt to new US data centers, the organization’s data-center page is essentially nothing but worries—certainly nothing that frames any aspect of them as a positive, or as possibly contributing to solving environmental problems through AI.

To continue the logic chain: if AI is at best a problematic innovation, as the activists see things, then certainly we shouldn’t be expanding another troubling innovation—nuclear energy—to power it.

No wonder many of these groups are already against small modular reactors even before they’ve sent a single electron into the grid. As a new JPMorgan report explains, these warehouse-sized supercomputers have become the most conspicuous source of new electricity demand, and that demand is improving the economic case for SMRs, which is making them interesting to Wall Street.

According to the megabank, data centers consumed roughly 4.4 percent of American electricity in 2023. No doubt it’s more now, and by 2028 the share could reach 12 percent. The hyperscalers have noticed this, which has been great news for the fledgling SMR companies. As seen in the slide below, Oklo has secured a 1.2-gigawatt deal with Meta. Amazon has put more than $300m into X-Energy alongside a 5-gigawatt order. Google has signed with Kairos Power. Companies racing to build AI capacity need firm, round-the-clock power that wind and solar cannot reliably provide.

Those hyperscaler investments aside, plenty else has been cooking in the space over the past year:

• In May 2025, federal regulators approved NuScale’s upgraded 77-megawatt reactor design, a step that doesn’t authorize construction but does give the company a stronger foundation for eventually getting license approval.

• Then in December, the Department of Energy selected the TVA and Holtec for up to $800 million in cost-shared funding to advance early SMR projects in Tennessee and Michigan.

• The biggest milestone came in March 2026, when TerraPower received a construction permit for its Natrium reactor in Wyoming. It was the clearest sign yet that an advanced reactor project has moved beyond slide deck presentations.

• In May, Dow and X-energy cleared an environmental review for four advanced reactors at an industrial site in Texas, while Utah’s revived Green River project could give Holtec another place to build and prove its small reactor design.

When thinking about these groups and their opinions about AI, data centers, and nuclear energy, consider an intriguing alternate-history scenario from an Up Wing perspective. What if the United States had followed through on a 1960s Atomic Energy Commission plan to construct a thousand nuclear power plants by the year 2000?

One version of that thought experiment has been explored by For All Mankind on Apple TV, which is built on the premise that the US-Soviet space race never ends. An earthly dividend of that continuing contest is that the federal government keeps pouring money into scientific research, ultimately cracking nuclear fusion. In the show, a fictional James Hansen—the real NASA climate scientist who famously warned Congress about global warming in 1988—testifies that warming has slowed thanks to widespread fusion power.

But I don’t think you even need that sort of technological leap to imagine huge benefits from a nuclear-powered American economy. Maybe things would have played out something like this:1

Again, decline is a choice. What sort of future will America choose this time?

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1

This timeline was generated by Claude through an obvious prompt: Give me an Up Wing, alt-history if the US had kept expanding nuclear energy as was envisioned in the 1960s.

---

On sale everywhere by James Pethokoukis The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

A scenario to consider: If the US federal government were ever to quasi-nationalize the big artificial-intelligence labs, it might look something like what investor and AI researcher Leopold Aschenbrenner proposed in a viral 2024 analysis. He envisioned a catalyzing moment when, as AI rapidly approaches the inflection point of general or even superintelligence, Washington would fold the labs and leading cloud providers into a government-orchestrated—but voluntary—consortium for national-security reasons.

Exciting stuff! Think of it as a 21st-century version of the Manhattan Project (though the AI-nuclear comparisons typically obfuscate more than they illuminate).

Now, I’m not even sure that scenario is all that likely, even assuming the conditional technological advance.

But far less likely, I think, is what Bernie Sanders just proposed in The New York Times. Even though AI is currently neither (a) disrupting the labor market nor (b) supercharging productivity growth, the socialist US senator from Vermont would have the federal government ASAP seize 50 percent of the stock in the largest AI companies—OpenAI, Anthropic, and xAI among them—through a one-time tax paid in stock.

Hey, no time like the present. I guess.

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In Case You Missed It ...

✝️✨ On Pope Leo’s AI encyclical letter (Wednesday)

⤵️ Decline is still a choice (Thursday)

💥 A bad day for the American space program. There will be more. And that’s OK (Friday)

⤴️⤵️ Up Wing/Down Wing

A selection of pro-progress and anti-progress news items from the past week.

⤴ Up Wing Things

• Why data centers don’t deserve so much hate - WashPost

• Google DeepMind CEO Demis Hassabis says we’re close to AGI - Axios

• Mathematicians stunned by AI’s biggest breakthrough in mathematics yet - NewSci

• Sundar Pichai Understands Why People Are Anxious About A.I. - NYT

• France’s Answer to OpenAI Warns of Dangers of U.S. Tech Dominance - WSJ

• Agentic AI System Is a Foreseeable Pathway to AGI - Arxiv

• AI Has Made Memory Chips More Valuable Than Oil - WSJ - WSJ

• Seven Ways to Avoid Losing Your Job to AI - Free Press

• How Amazon Went From an AI Also-Ran to a Real Contender - WSJ

• I Have Seen the Future of Physical AI in Dusty West Texas - Bloomberg

• NASA takes steps toward building Moon Base, including discussing a “perimeter” - Ars Technica

• Tesla’s Newest Electric Vehicle Could Jolt the Trucking Industry - NYT

• Musk’s SpaceX Writes Tesla’s Future in the Stars - Bloomberg

• SpaceX IPO filing lays out Musk’s interplanetary manifesto - Semafor

• Ozempic may be reshaping the brain, scientists say - WashPost

• A plan to make drugs in orbit is going commercial - MIT Tech Review

• SandboxAQ brings its drug discovery models to Claude — no PhD in computing required - TechCrunch

• A revolutionary cancer treatment could transform autoimmune disease - Ars Technica

• The smartphone theory of birth rate decline doesn’t hold up - Reason

• Can geoengineering avert a climate catastrophe? - FT

⤵ Down Wing Things

• China overhauls world’s biggest surveillance network with advanced AI - FT

• The most spectacular rocket explosion since N1 just happened in Florida - Ars technica

• AI billionaires brace for pitchforks - Axios

• Inside the Democratic resistance on AI - Axios

• Corporate America Is Starting to Ration AI as Cost Skyrockets - WSJ

• Ebola Science Is Moving Fast. It Might Not Be Enough - Bloomberg

• Q-Day could destroy bitcoin – and our retirement saving - NewSci

• MAGA’s civil war over immigration is over. Silicon Valley lost. - Vox

• The Great Depopulation - The Atlantic

• The looming energy crunch - FT

↕️ Which Wing Things?

• Elon Musk is going all-in on an unproven technology - Economist

• AI’s Macroeconomic Challenges and Promises - NY Fed

• Phoenix Built an Empire of Cubicle Jobs. AI Is Coming to Tear It Down. - WSJ

• The internet is being rebuilt for machines - TechCrunch

• What if remote working, not AI, is to blame for weak junior hiring? - FT

Essays and Q&As

✝️✨ On Pope Leo’s AI encyclical letter

The good: Leo’s vision of keeping humanity central to the Age of AI aligns with the Up Wing project: using technology and policy to alleviate suffering and unlock new possibilities. Not utopia. Just a wealthier, healthier world.

The concern: The encyclical frames AI-driven automation almost entirely through “social disruption and moral risk”—warning that pursuing greater profits cannot justify “systematically sacrificing jobs.”

Why it matters: That view ignores the historical pattern whereby disruptive general-purpose technologies—steam, electrification, the internet—eventually created new industries and dramatically higher living standards.

The bottom line: Pope Leo’s “technocratic paradigm” framing carries a Down Wing intellectual pedigree that has proven harmful to human flourishing for more than half a century. The Vatican should hire better economists.

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⤵️ Decline is still a choice

The pattern: At precisely the moment innovation became harder after the postwar boom, America became less willing to tolerate the risks and disruptions inseparable from innovative discovery. We underfunded science, overregulated the physical economy, and abandoned Apollo-scale aspirations.

The new wrinkle: A Peterson Institute brief finds the AI economy is growing at over 2,000 percent per year in quality-adjusted terms—yet barely registering in GDP because per-unit prices are crashing as fast as output rises. We may be dramatically underestimating AI’s impact.

The real question: Imagine Washington pushing an EU-style AI Act, compute restrictions, algorithmic mandates. What would that cost us—economically and in national security terms?

The bottom line: So many decisions to be made. Are our current leaders ready to make them?

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🚀💥 A bad day for the American space program. There will be more. And that’s OK

The week: NASA awarded contracts for the first elements of a lunar base — then Blue Origin’s New Glenn rocket exploded during a static-fire test, badly damaging its only launch pad and possibly grounding the rocket for a year or longer.

The stakes: China is steadily ticking off boxes for a crewed lunar landing before 2030—maybe before America. A successful Chinese landing would hand Beijing a soft-power coup beamed across social media.

The history lesson: The New Glenn explosion echoes the Soviet N1 disaster of July 1969—one of the largest non-nuclear explosions in history. The N1 catastrophe ultimately helped kill the Soviet lunar program entirely.

Why this is different: America today enjoys what the Soviets lacked—multiple rockets, multiple firms, multiple reasons to keep going. Commercial incentives plus strategic competition with China make space imperative regardless of setbacks.

The bottom line: We will continue to keep lighting the candle!

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On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

It’s never easy being a spacefaring nation, especially at the dawn of a new space age.

On Tuesday, a key moment for the prospects of humanity’s off-planet existence. NASA awarded contracts for some of the first elements of a future American lunar base. The agency tasked Astrolab and Lunar Outpost with building large, autonomous lunar rovers for astronauts, while Jeff Bezos’s Blue Origin won a contract worth up to $468 million to deliver those rovers to the Moon. The news further cemented Blue Origin as a central player in NASA’s Artemis program.

Then Thursday happened. Boom.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

Let’s set the mood with some recent headlines:

“More Than Half of US Says AI Likely to Harm Them, Poll Finds” - Bloomberg

“‘The Most Bipartisan Issue Since Beer’: Opposition to Data Centers”- NYT

“The American Rebellion Against AI Is Gaining Steam” - WSJ

“The great American data centre divide” - FT

Folks, this is why “decline is a choice” is an underrated thesis. Implicit is the notion that our choices matter. We have societal—even civilizational—agency. If I didn’t believe that, I wouldn’t be an economic policy analyst and writer.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

The aspects of Pope Leo’s Magnifica Humanitas that resonated most with me did so as a Christian Up Winger. The parts that made me sigh were those that irked me as a market- and growth-oriented analyst.

Let’s start with the former. The more-than-42,000-word encyclical laid out a vision for keeping humanity at the center of the Age of AI. As I explain in my book, the term “Up Wing” is a philosophical framing from futurist writer F. M. Esfandiary, He’s widely considered the godfather of modern transhumanism, a movement seeking to use technology to enhance our current biological capabilities and then transcend them. This would be a redesigned species of limitless potential. Technology would allow humanity to outgrow old political systems, old social institutions, and eventually even old biological limits.

The pope’s rejection of that view, even as updated in today’s Silicon Valley, shouldn’t be surprising. For most Christians, authentic transcendence doesn’t come from AI-enabled human optimization project but through a relationship with God. From the encyclical:

We can embrace the technological progress that alleviates suffering and unlocks new possibilities, provided that we do not abandon the very essence of our humanity, namely the capacity for relationship and love. This leads to a crucial question: if an authentic ‘more than human’ exists, where is it to be found? The Christian faith answers that question by pointing to a fulfillment that does not arise from a technological divinization, but through God’s grace received in Christ.

That works for me, both as a Christian (though not a Roman Catholic) and as a techno-optimist. My Up Wing project isn't a utopian effort to create some perfected, evolved humanity. It's far less grandiose: the use of public policy—responding to the preferences of society operating through a liberal democratic government and market economy—for the exact goals the pope stated: the alleviation of suffering and the unlocking of new possibilities. In that project, technological advances will often play a big role in achieving a wealthier, healthier world, though not a perfect one.

Recall my idea for a Genesis Clock, the Up Wing counterpart to the Doomsday Clock. Instead of suggesting how close humanity is to the Midnight of our existence, this symbolic timepiece would suggest how close we are to the Dawn of a new age of abundance and opportunity. And instead of vibes, the Genesis Clock would have more substantive metrics: How close are we to extending the average human lifespan to 120? Do we have a cancer vaccine and a cure for Alzheimer’s? Can we deflect a larger asteroid or comet headed toward Earth? Is even the poorest nation no poorer than the average economy of 2000? Is even the least free nation as free as the average nation of 2000?

I don’t think the pope would have problems with any of those goals of less suffering and more opportunity.

I am, however, less enamored with how Magnifica Humanitas ultimately reflects a far more cautious—and at times skeptical—view of economic growth and the dynamism that drives it. The pope consistently presents AI-driven automation through the lens of social disruption and moral risk. He warns that a society with high technological sophistication but insufficient employment risks “human and cultural impoverishment” and insists that “the pursuit of greater profits cannot justify choices that systematically sacrifice jobs.”

Is that the most likely scenario? The document gives too little weight to the historical pattern whereby disruptive general-purpose technologies—steam power, electrification, the PC, the internet—eventually created new industries, new forms of work, and dramatically higher living standards despite sometimes painful transitions. My baseline expectation is that we will see a repeat of that pattern.

And it’s not just me. A recent survey of economists and AI experts found that both groups, assuming a rapid-AI scenario, anticipated a richer, faster-growing economy but neither one of science-fictional abundance nor mass unemployment. This was still a recognizable world that required a recognizable policy toolkit to address societal problems.

Pope Leo also raises concerns with a Down Wing intellectual pedigree that has proven quite harmful to the aforementioned alleviation of suffering and the unlocking of new possibilities for more than half a century.

Having considered the issues of responsibility and governance of AI, we must now return to our central question: what does it mean to safeguard our humanity? The risk extends beyond the misuse of certain technologies. More gravely, the pervasive technocratic paradigm in which we are immersed, and that is amplified by the digital revolution and AI, threatens to normalize an anti-human vision. In that vision, the fullness of life is equated with having more, reducing weakness, eliminating uncertainty and exerting total control. When efficiency becomes the ultimate measure of value, human beings are tempted to see themselves as a project to be optimized rather than as persons called to relationship and communion.

Both that passage and a few other sections reminded me of the “Mega-Machine,” technology philosopher Lewis Mumford‘s term for modern technological civilization—a vast, hierarchical, centralized system in which humans become mere components, much like the laborers who built the pyramids. (Pope Leo frets about a technocratic paradigm in which workers become “mere cogs in a system driven toward ever greater efficiency.”) Mumford saw postwar America—with its military-industrial complex, corporate bureaucracies, and technocratic management—as the latest and most powerful incarnation of this ancient pattern.

But the Mega-Machine thesis underestimated how disruptive and decentralizing capitalism could be. Mid-century critics like Mumford imagined giant bureaucratic systems steadily absorbing freedom and dynamism. Instead came personal computing, the internet, startup culture, and repeated waves of creative destruction that toppled incumbents from IBM to AT&T.

As others have said—and I agree—the Vatican should hire better economists.

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On sale everywhere by James Pethokoukis: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

President Trump is expected to issue a long-awaited executive order on AI safety as soon as Thursday. Whether the focus is rules governing frontier models or regulating potential AI downsides, this counterfactual often comes to mind.

Imagine it’s late 2022, and you see the following breaking news notification on your phone: Some Chinese technology company—maybe a giant like Alibaba or Tencent, or maybe a mysterious startup called DeepSeek—has unveiled a powerful artificial intelligence, or “large language,” model.

Yikes: American LLM efforts are considered a year or two behind! We get social media, and Communist China gets “humanity’s last invention.”

Thanks a lot, Silicon Valley.

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My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

Having attended college graduation ceremonies for five of my seven kids, I guarantee I would’ve preferred ex-Google CEO Eric Schmidt over any of the speakers at those events. Schmidt is deeply involved in artificial intelligence in both the business and government sectors, and the students who booed his mentions of AI at the University of Arizona’s commencement last week instead should have been hyperfocused.

But I don’t entirely blame those boisterous boo birds. While young capitalism haters would have jeered at any Silicon Valley billionaire at any time, a not insignificant number in the crowd were surely concerned that AI will make the job market—and maybe the world—a worse place.

It’s completely understandable. They’ve consumed years of popular culture telling them AI and robots will destroy humanity, and all they have to do is scan the headlines to find executives predicting an AI jobpocalypse starting sooner rather than later. Then there are all those TikTok videos.

So here are four pieces of advice for any commencement speaker who wants to talk about AI:

✨ Give a brief history lesson. AI looks like it will be a powerful, economywide general-purpose technology—”everything’s computer,” basically—but it’s hardly the first. Steam power, electrification, the internal combustion engine, the PC, the internet: what economists call the “Great Inventions.” History’s pattern is consistent: People worry about job disruption, disruption happens, new jobs emerge that nobody predicted. After 250 years of such tumult, we are wealthier and well-employed. That record should inform your baseline forecast about AI’s socioeconomic impacts.

Take the internet. Jeremy Rifkin’s 1994 The End of Work set an anxious tone for the emerging Digital Revolution. Some jobs did collapse—travel agents, where the internet directly substituted for their core tasks.1 But mostly the internet transformed work rather than eliminated it, as outlined in an excellent Wall Street Journal piece from late last year. Dental-lab technicians moved from manual molds to digital scanning. Administrative assistants stopped answering phones and started managing vendors. Today only 10 percent of workers use the internet little or not at all on the job.

Then came the jobs nobody predicted: 65,000 social media managers, 200,000 information-security analysts, and the biggest surprise—warehouse workers and delivery drivers thanks to e-commerce. From 1990 through 2019, real wages of typical workers rose 45 percent, notes my AEI colleague Michael Strain.2 The post-2001 dip in labor force participation is mostly demographic. A repeat of this good outcome with AI is hardly unlikely.

✨ Give a reality check. Forget history, maybe this time is different. After all, CEOs and other executives of the most important American technology companies predicting a white-collar wipeout even as they also predict that AI will produce techno-marvels that drive science fictional increases in productivity and economic growth. But should such fantastical forecasts—sure to grab the attention of potential investors— be your baseline expectation?

Not really. The Forecasting Research Institute recently surveyed more than 500 economists, AI professionals, policy experts, superforecasters, and members of the general public on AI’s likely economic effects. The results tell a more modest story. Both economists and AI professionals put roughly 47 percent odds on a “moderate progress” scenario—one where AI automates substantial work but falls well short of cognitive dominance. Under that most-likely path, neither group is forecasting anything close to a supernova explosion of growth. Economists see real GDP growth near 2.5 percent in the near term, rising to around 2.8 percent by midcentury. AI experts are somewhat more bullish—around three percent by 2030 and closer to four percent by 2050.

The real disagreement surfaces only under the rapid-progress scenario: Economists see long-run growth around 3.5 percent. AI experts see just over five percent. The gap sounds small but compounds dramatically. Yet even five percent growth isn’t unprecedented. The U.S. averaged four percent in the second half of the 1990s. Transformative, perhaps. Science-fictional, no.

✨ Concede this time might be different. Maybe those AI CEOs will eventually be correct. A few experts in the FRI survey forecast double-digit GDP growth. Technologists appear more willing than economists to entertain such tail outcomes. But even a superintelligence must deal with the real world. However dazzling its capabilities, an AI of godlike reasoning power would still have to navigate the stubborn constraints that have always governed how economies actually change.

Benjamin Jones of Northwestern points out that 30 percent annual growth would double living standards every 2.5 years, leaving society a thousand times richer after just twenty-five years. The creative destruction involved would be staggering: rapid turnover in technology, mass obsolescence of skills, entire industries remade before displaced workers finish retraining. Probably a considerable backlash.

Bottlenecks are a related worry. Stanford’s Charles Jones argues that in any system built from complementary parts, the slowest component sets the pace. A superintelligent model could transform coding and scientific research—but if energy infrastructure, physical capital, regulatory approval, and human decision-making keep moving at their usual speeds, those become the ceiling. There’s a gap between raw capability and deployed productivity.

Nor does faster productivity growth automatically produce faster output growth. Dietrich Vollrath of Houston observes that richer societies tend to take gains as time rather than income—shorter weeks, earlier retirements—muting the aggregate effect on GDP even as living standards improve. And as wages rise, spending drifts toward health care, education, and in-person services, where output stays tied to human hours—the Baumol effect—quietly offsetting gains made elsewhere. Superintelligence would be formidable. It wouldn’t necessarily repeal economics.

✨ Outline a better world, and what it costs. Growth isn’t just about accumulating more stuff. Benjamin Friedman, a Harvard economist, spent a career showing that rising living standards correlate with tolerance, civil liberties, and openness to outsiders—and that stagnation reverses all three. The years after 2008 offered proof. The slow crawl out of the Global Financial Crisis fed a zero-sum, populist politics of grievance. AI-driven growth matters because of the society it makes possible when citizens aren’t fighting over a shrinking pie.

It’s also worth recalling what fear has already cost. Nuclear power could have supplied the world with clean, abundant energy decades ago. Instead, public anxiety and regulatory overreach mothballed a generation of nuclear progress. The Apple TV+ drama For All Mankind imagines the road not taken: a sustained space race accelerates fusion power, electric vehicles arrive early, and a fictional James Hansen—the real NASA climate scientist warned Congress about climate change in 1988—testifies that warming has slowed.

Yet the tension is genuine. As Sebastian Mallaby writes in his new book on DeepMind, scientists have always faced a paradox: discovery can destroy jobs, shatter certainties, and in extreme cases imperil existence itself. AI might embody this more fully than any predecessor. Its dangers are real, but so is the promise: medical breakthroughs, climate solutions, tutors of infinite patience. From gunpowder to nuclear fission, technology has repeatedly made the world more dangerous while also extending lifespans and deepening human capability.

A great lesson for new grads: Life is about trade-offs.

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2

Again, Tedeschi: “Average weekly earnings at travel agencies were 87% of overall average weekly earnings back in the heyday of 2000. By 2025, the ratio had reached 99%, meaning travel agency wages had outpaced the rest of the private sector over that span.”

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On sale everywhere by James Pethokoukis:

The Conservative Futurist: How To Create the Sci-Fi World We Were Promised

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:

Perhaps the main upside to SpaceX from going public next month is access to gobs more capital—as much as $75 billion—to accelerate all of Elon Musk’s off-planet dreams. For me, personally, the main upside of this largest-ever IPO (perhaps as high as $2 trillion) will be greater focus on SpaceX from Wall Street. That should mean lots more transparency for what’s potentially the most important company in human history. I’m especially eager for more insight into Starship, with the bigger, more capable V3 due for its debut launch as soon as this Tuesday.

A recent Barron’s article referred to Starship as SpaceX’s “ace in the hole.” But that might understate the importance of this ginormous rocket.1 Every business SpaceX wants to build—expanded Starlink coverage, Moon and Mars colonization, space-based computing (more on that later)—depends on dramatically cheaper and more frequent access to orbit and beyond.

The key here, of course, is full reusability of both stages, something no operational rocket yet delivers. The workhorse (more than 600 launches) Falcon 9’s partial reusability was transformative. Starship’s complete reusability, if achieved, would be more so. The former cut the cost of reaching orbit by roughly ninety-five percent compared with the Space Shuttle. The latter is designed to cut it by a further ninety percent, if not even more eventually.

Everything’s computer, even in orbit

But space enthusiasts and potential investors aren’t the only folks thinking hard about Starship these days. While the rocket may be central to dreams of humanity someday becoming a multiplanetary civilization, it might also be central to humanity becoming an AI-empowered civilization.

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