The search for dark matter has been blown wide open

For decades, physicists have hunted for weakly interacting massive particles (WIMPs), a leading candidate for dark matter. But their search has run into a new problem: neutrinos. 

These tiny particles from the sun and other stars can create a “neutrino fog” that drowns out any signal of dark matter. Hitting the neutrino fog does not, however, mean an end to the search. Researchers just have to shift the focus of their hunt.

They’re now casting a much wider net. New proposals include quantum sensors, liquid-helium detectors, and even searches in Jupiter’s atmosphere.

Find out how the search for dark matter has entered entirely new territory.

—Dan Garisto

This story is from the next edition of our magazine, which is all about engineering. Subscribe now to get a copy when it lands!

Entrepreneurs in Nairobi are making the case for going solar

Shops with diesel-powered grain mills are common in Nairobi. Milcah Wanjiru’s is different: it runs on either solar energy or the grid.

About a quarter of Kenya’s population still lacks centralized electricity, and off-grid solar is being promoted as a route to universal access by 2030. In Wanjiru’s case, it cuts operating costs and can improve profits once the upfront investment is recovered.

Read the full story on the rise of solar milling systems across Kenya and beyond.

—Geoffrey Kamadi

Geoengineering still faces major practical challenges

—Casey Crownhart

Solar geoengineering is often portrayed as a sort of emergency brake. Something along the lines of “Pull in case of climate emergency to scatter light-reflecting particles to bounce sunlight out of the atmosphere and cool the planet.”

But it might be less like a simple brake the more like a complicated, entirely unsolved puzzle. My colleague James Temple dug into these engineering challenges in his latest feature story. My biggest takeaway? This all looks a lot harder than I thought.

Read the full piece to find out why.

This article is from The Spark, our weekly newsletter giving you the inside track on all things climate. Sign up to receive it in your inbox every Wednesday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The Pentagon says it used Grok in strikes on Iran
Its AI chief said it helped fire over 2,000 munitions. (Le Monde)
+ He spoke in defense of xAI in a data center pollution lawsuit. (NYT $)
+ Officials claim the company is essential to national security. (AP News)
+ Conversational AI has entered the war room. (MIT Technology Review)  
 
2 Apple will raise prices due to the memory chip shortage
Tim Cook said price increases are “unavoidable.” (WSJ $)
+ AI’s demand for data centers has led to dwindling supplies. (Reuters $)
+ iPhone prices could rise by $200 or more. (WSJ $)
 
3 Strikes beyond battlefields are pumping demand for counter-drone tech
The market for airport and infrastructure defenses is booming. (Reuters $)
+ Worried by China, Taiwan is teaching its citizens to fly drones. (Guardian)
+ Europe has a drone-filled vision for future war. (MIT Technology Review)
 
4 Anthropic and DeepMind’s CEOs have called for a US-led AI coalition
They want the alliance to shape AI rules and standards. (CNBC)
+ Anthropic’s CEO told G7 leaders to “resist the temptation to splinter.” (FT $)
 
5 American developers are turning to cheaper Chinese AI
They say DeepSeek is good enough for a fraction of the cost. (Rest of World)
+ What’s next for Chinese open-source AI? (MIT Technology Review)
 
6 Two-thirds of Americans think AI is advancing too quickly
Pew Research found increasing use but negative views. (The Verge)
+ AI is sprinting, and we’re struggling to keep up. (MIT Technology Review)
 
7 Elon Musk’s next move may be a megamerger of SpaceX and Tesla
Shareholders might object, but there’s little they could do. (NYT $)

8 White House aims for Anthropic to block jailbreaks may be impossible
Security experts say it simply isn’t technically feasible. (Wired $)
 
9 Ancient DNA is rewriting the history of plague
Genomic data suggests it emerged thousands of years earlier. (Economist $)

10 AI image generator Midjourney is shifting to full-body ultrasound scans
It also plans to build a spa in San Francisco. (The Verge)

Quote of the day

“We had a great meeting with AI.” 

—President Trump says negotiations with Anthropic over restoring access to the company’s latest AI models are going well, the Wall Street Journal reports.

One More Thing

GETTY IMAGES

Why can’t tech fix its gender problem?

Women remain grossly underrepresented in the technology industry. At the core of the problem is money: tech has generated enormous personal fortunes, and most of that wealth has gone to men.

White and Asian men manage 93% of venture dollars. In 2021, only 2% of venture capital funding went to startups founded solely by women.

The lack of investor and founder diversity doesn’t only determine who gets rich. It also shapes the kinds of problems technology companies set out to solve.

Discover why tech’s gender problem has proved so hard to fix—and why a new generation of activists believes change is finally possible.

—Margaret O’Mara

We can still have nice things

A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ Meet one of the world’s most wonderfully weird animals: the aardwolf.
+ Escape into this dreamy, minimalist photo collection about the Pacific surf.
+ Admire the casual football skills of this Venetian gondolier executing a stylish backheel while on the job.
+ Explore an interactive prehistoric globe simulation and browse an endless timeline at The Dinosaur Database.

Solar geoengineering is often portrayed as a sort of emergency brake. Something along the lines of Pull in case of climate emergency to scatter light-reflecting particles to bounce sunlight out of the atmosphere and cool the planet.

But it might be less like a simple brake and more like a complicated, entirely unsolved puzzle.

Some researchers are starting to look into how nations or companies would go about trying to cool the planet—and there’s a lot to figure out. My colleague James Temple dug into these engineering challenges in his latest feature story. My biggest takeaway? This all might be a lot harder than I thought.

I’ll admit, I’ve always thought of geoengineering as a relatively low-tech solution. That’s partly because over the years we’ve seen some companies do their own low-cost guerrilla “experiments,” tossing balloons up into the atmosphere and claiming to have made some small dent in climate change.

But to actually actively cool the planet in a significant way, and to make sure we understand exactly what effect we’re having, there’s a lot that researchers still need to learn. 

First, there’s the problem of getting up into the atmosphere. Generally, the target for solar geoengineering efforts is the stratosphere, since the air there is drier and more stable, so particles deposited there would stay aloft and move around the planet, lowering temperatures over a wider area and for a longer time.

You can release the particles in balloons, but balloons may not go where you want them to. And at a large scale, you’d be leaving a lot of litter all over the planet. That leaves aircraft, but conventional planes aren’t suited to fly around in the stratosphere. (Commercial aircraft generally fly at around 12 kilometers above the Earth’s surface, while geoengineering would require reaching roughly 20 kilometers.) The air is thinner higher up, so aircraft with massive wings would probably fare better than more conventional designs.

One design, from a startup called Iris Aero, shows just how much rethinking of our current flight technologies might be needed—the plane is almost unsettling in its proportions. Its wings are so long, on a stubby little body. It reminds me of a water strider, those bugs that have super-long legs to scurry around on a pond’s surface.

And that’s just the beginning. There’s also the question of what, exactly, would be best to scatter up in the stratosphere. The idea behind geoengineering comes from volcanoes—after an eruption, sulfuric acid ends up floating around in the atmosphere, and it can temporarily cool the planet. But that chemical is sticky and would be heavy to carry, so scattering some sort of precursor to sulfuric acid would probably be better. Researchers, including some at the University of Chicago, one of the leading institutions in this field, are working to figure out the best formula. 

I’m struck by how complicated this turns out to be, and I’m also left with a big question: As research turns from modeling and simulations to the practical aspects of this incredibly controversial technology, what does it mean to be doing this work?

There are major concerns about what effects might come from large-scale attempts to cool the planet. The effects could be positive for some parts of the globe and negative for others. Established weather patterns, like the monsoon season in South Asia, could shift. There are major questions about what the governance for the use of geoengineering should look like, and who gets to decide whether to go ahead. 

Experts who champion research in geoengineering often draw a line between a desire to support learning more about the technology and a call to deploy it. Many would argue that we should understand it better, so we can make informed decisions.

But to me, there’s a clear difference between atmospheric modeling and detailed engineering work on an aircraft. If there’s public research that essentially amounts to a set of practical instructions, I can’t help but feel like it could enable any number of individual actors or nations to take geoengineering into their own hands. It also might normalize the idea of using the technology. 

Some experts shared concerns along these lines with James, arguing that the shift to practical engineering work requires more oversight. Some called research in this area dangerous.

One alternative perspective I found interesting came from Shuchi Talati, executive director of the nonprofit Alliance for Just Deliberation on Solar Geoengineering.

Rather than further practical research making a slippery slope slipperier, it could have the opposite effect, she told James. “The actual practice of R&D will be a sticky slope, because there will be more real-world problems that come up that we haven’t even thought of yet,” she says. Engineering research could challenge the “idealized notions” of how easy the technology would actually be, she adds.

It’s hard to argue against better understanding potential tools to address climate change. But if we draw a map towards a potential future, it might become difficult to control who follows it. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. 

Isolated deep beneath these rocky shields, massive detectors filled with liquid xenon aim to make the first direct detections of dark matter, the long-sought invisible substance whose gravity has sculpted our universe.

The hope is that someday, a bit of dark matter called a weakly interacting massive particle (a WIMP, for short) will collide with a xenon atom, creating a burst of light and electric charge. After running for years, these experiments have recently begun seeing infrequent blips from a particle that glides ethereally through ordinary matter until it crashes into the detectors. Unfortunately, the new signal is not produced by dark matter. Instead, the detectors are picking up on something similarly insubstantial but much more mundane: neutrinos, the featherweight subatomic particles that the sun and other stars produce in massive quantities.

Physicists’ failure to find dark matter where they thought it was has led to a cornucopia of proposals for new ways to search: quantum sensors, liquid-helium-based detectors, searches in Jupiter’s atmosphere, and more.

Physicists have known for decades that this neutrino background was there; they were just hoping to discover WIMP dark matter first. Now the chance is looking slim. Some of today’s WIMP detectors are simply so large and sensitive that they are entering the so-called “neutrino fog,” in which the ordinary particles are likely to drown out any signal from the main target. There is no shielding these detectors from neutrinos, which easily slip through the Earth itself. That means the next experiment to use this long-standing approach for seeking WIMP dark matter may be the last. 

Hitting the neutrino fog does not, however, mean an end to the search for dark matter. Researchers just have to shift the focus of their hunt. “We haven’t seen WIMP dark matter,” says Kathryn Zurek, a theoretical particle physicist at the California Institute of Technology. Nor, she says, have scientists found new particles in the Large Hadron Collider (LHC), the powerful proton-smashing facility that straddles the border between France and Switzerland. “And so people naturally broaden their scope,” Zurek says. As they do, there are plenty more candidates waiting in the wings

In other words, the hunt is transforming from a narrow probe into a kind of free-for-all. It’s a big shift. Today, particle physicists are less sure about dark matter’s identity than when they began looking for it. They’ll freely admit that they cannot presume the basics—for example, if the stuff that makes up dark matter is heavier than the Earth or lighter than a radio wave, or if dark matter is one kind of particle or a dozen. 

The uncertainty can be frustrating, even humbling. “The potential range where the candidates could be is so enormous that the odds of any one small experiment finding it are very, very small,” says Hugh Lippincott, a dark matter experimentalist at the University of California, Santa Barbara. 

But physicists’ failure to find dark matter where they thought it was has also led to a cornucopia of proposals for new ways to search: quantum sensors, liquid-helium-based detectors, searches in Jupiter’s atmosphere, and more. “Now there’s a great deal of excitement. And finally, there’s technology there,” says Gray Rybka, a University of Washington physicist who co-leads an experiment looking for axions, an ultra-lightweight dark matter candidate. 

Still, with so many places to look, where does it make sense for physicists to begin again? 

Astronomical ignorance

For starters: the birth of the universe. Dark matter has been with us since the beginning, and there’s much to learn from those early eons. Maps of the cosmic microwave background—the first light from the universe’s early years—are full of fluctuations caused by the clumpiness of under­lying matter. Reading these cosmic dregs, researchers can tell that only 17% of the matter in the universe is made of ordinary particles like protons and neutrons. The remaining 83% is dark matter, which has little to no interaction with light or ordinary matter other than through gravity.

We can tell quite a bit about dark matter from those gravitational effects. We know that the Milky Way contains a halo of the stuff. Our own solar system orbits the galactic center far too quickly to be bound by the tug of ordinary matter alone: without dark matter’s gravitational tether, we would be flung off into intergalactic space. We can also see how the heft of a galaxy’s dark matter bends the path of light as it makes its way to Earth’s telescopes. And on the grandest scale, we can see how superclusters of galaxies are distributed in space like dewdrops on a spiderweb. No cosmological theory without dark matter can explain all these phenomena. 

But all the astronomical and cosmological evidence has little to say about what dark matter is actually made of. “It does not tell you anything about the individual constituents. It just tells you the effect of a bunch of them together,” says Lippincott, who has led the LZ experiment, a WIMP dark matter detector currently in operation at the former Homestake Mine in South Dakota.

The idea of WIMPs emerged during the 1980s. At the time, theorists were exploring add-ons to the standard model, the overarching theory of particle physics that describes all the universe’s fundamental particles and their interactions. The standard model is powerful but doesn’t account for everything—notably, it omits gravity—so some adjustments seemed necessary. The most popular idea, a class of theories called supersymmetry (SUSY, informally), called for pairing each known particle type in the universe with an as-yet-unseen “super­partner.” To have avoided detection, superpartners would have to have a lot of mass (putting them outside the reach of existing colliders) and be weakly interacting, able to pass ghostlike through matter. That is to say, they would be WIMPs. It didn’t take too long for physicists to realize that the WIMP was also an excellent dark matter candidate: two problems, one particle. 

The appeal of SUSY was so strong that many particle physicists expected to see WIMPs as soon as the LHC turned on in 2008. Instead, as the data came in from the LHC, the most promising SUSY theories were largely ruled out. 

ALAMY, GETTY IMAGES; IMAGING BY JANA HEIDENREICH

WIMPs, though, have lived on, no longer tied to the theory that birthed them. And the latest generation of dark matter detectors have kept the hunt alive. After all, Lippincott says, “the motivation to look for dark matter has not gotten any weaker, right?” 

Now it’s looking as if those WIMPs—if they exist—may be beyond our current powers of detection. There are a range of difficulties, but the most pervasive is that when you’re looking for a needle in a haystack, even a few other needle-shaped objects can cloud the search. Interactions between neutrinos and the xenon inside the detectors, while astronomically rare, do just that.

A future, final WIMP experiment would investigate the rest of the places WIMPs could be hiding, even peering into the neutrino fog. An effort called XLZD (a somewhat ungainly acronym reflecting a mashup of existing collaborations) would use 60 to 80 metric tons of liquid xenon, which is about the yearly global production of that rare element and at least six times more xenon than the biggest current detector contains. But it may already have been scuttled, for reasons unrelated to the neutrino fog: At a particle physics meeting in December 2025, the US Department of Energy announced that the US would neither host XLZD nor pay its share of the price tag, which could be well over $300 million. “It may be that the project doesn’t happen at all,” Lippincott says. “And then the US pulling out would have effectively killed it.” 

In the meantime, the hunting ground for dark matter has been expanding dramatically. In 2022, researchers developed an enormous plot showing various candidates for what dark matter is made of and their possible masses. The options fell mainly into two ranges that span about 50 orders of magnitude (that’s 10⁵⁰, or 10 with 49 more zeroes). At the heavy end of the scale are primordial black holes, hypothetical asteroid-size objects that formed shortly after the Big Bang and might still be floating about the universe. 

But many physicists are most interested in the lightest option: the axion.

Listen closely

Like the WIMP, the axion first emerged as a solution to problems with the standard model. In the axion’s case, it was to address an outstanding question about the strong nuclear force, the fundamental force that holds atomic nuclei together. Axions were proposed by theorists in the 1970s as a mathematical tweak. By adding a particle with a trillionth to a millionth the mass of an electron, they could explain why the strong force seems to behave precisely the same way when it comes to both matter and antimatter even though it doesn’t need to—an unanswered question known as the strong CP problem. 

Axions would be abundant and interact infrequently with ordinary matter, two necessary features for dark matter. Detecting axions is no walk in the cosmic park, though. The delicate particles carry only a hint of energy—about as much as a radio wave. That makes them imperceptible to traditional particle detectors. (Proton collisions at the LHC, for example, pack about a quintillion times more energy.)

Physicists have developed strategies they hope will bear fruit. One of the most promising ideas is to use an ultracold chamber suffused with a strong magnetic field like a radio, tuning it to specific wavelengths. If an axion happens to be resonant, meaning it has the same wavelength as the chamber, it stands the chance of transforming into something far easier to detect: a particle of light. The first full-size detector, called a haloscope, was built at Lawrence Livermore National Laboratory in 1994; today there is a coterie of detectors around the world, with quirky acronymic names like MADMAX and ABRACADABRA.

Fiddling with a cosmic radio to listen for a rare invisible particle is tricky and requires quantum sensors cooled to millikelvin temperatures, a fraction of a degree above absolute zero. Even that doesn’t entirely negate background noise. “At one point, we detected a ‘message from God’ in our experiment,” Rybka tells me wryly. “We looked it up in the FCC allocation of spectrum. It was a religious programming station.” 

So far, particle physicists have combed somewhere between 10% and 20% of the parameter space—the area on a chart showing how massive and interactive dark matter might be—where an axion that solves the strong CP problem might exist. But the search for axions might not end there. Physicists are also looking for axions that don’t address the strong CP problem but could still be dark matter. “More and more people are thinking about models specifically for dark matter, even without connecting that to any other problem,” says Stefania Gori, a theorist at the University of California, Santa Cruz. “Of course,” she says, “if one can solve more than one problem at once, it’s even nicer.”

Quiet revolution

As dark matter has continued to go undetected, physicists have dropped some of their theoretical desiderata. Modern candidates don’t need the convenience of WIMPs or the clean simplicity of axions; they need only fulfill the requirements for dark matter.

The poster child for these unpretentious candidates is low-mass dark matter, so named because it is somewhere between an electron and a proton in weight. If a WIMP is a billiard ball, low-mass dark matter is a ping-pong ball, explains Rouven Essig, a theorist at Stony Brook University. Like a ping-pong ball hitting bowling pins, low-mass dark matter wouldn’t have enough heft to produce a clear signal from a collision with atomic nuclei. “One needed to really come up with new ideas for how one could detect the signals, and then, of course, also new technologies,” says Essig. 

Researchers have designed novel detectors and installed them in underground labs around the world—often right next to their WIMP-detecting forebears. Some of the new machines look for evidence that particles have collided with electrons and ionized them. Others peer into crystals whose lattices should jiggle subtly after a bump from such a particle. There are even proto­types that look for hints in liquid helium, a sensitive superfluid that should throw up a splash when hit by incident dark matter.

XENON COLLABORATION, GETTY IMAGES; IMAGING BY JANA HEIDENREICH

There is, however, a rub: noise. While all experiments in dark matter detection are hampered by noise from the outside world, low-mass searches also suffer from the intrinsic din of their detector mediums. Atomic lattices like those inside crystals are like a crowded subway car, naturally prone to shaking and jostling their electron passengers. It’s not the quiet space you want if you’re looking for dark matter. 

This noise has created challenges. In 2020, a surprising number of what physicists call “excess events” cropped up across a range of detectors looking for low-mass dark matter. Could they, some physicists wondered, be a signal of dark matter? Unfortunately, the noise causing most of these readings has been identified, and the answer is a pretty firm “no.” 

Background noise can come from anywhere: impurities in silicon-based detectors, materials that have spent too long on Earth’s surface (cosmic rays make them lightly radioactive). In one experiment, a crystalline detector was clamped too hard; the extra pressure caused vibrations that looked like evidence of dark matter. “It’s always been true that understanding those backgrounds has been difficult,” says Dan McKinsey, an experimentalist at Lawrence Berkeley National Laboratory. “But we’ve shifted our regime so quickly that suddenly we don’t understand, as a community, what the key backgrounds are.”

Getting a handle on that background noise is key, especially as experiments to detect low-mass dark matter get bigger. In a few years, for example, McKinsey and his colleagues plan to install a number of tabletop experiments in Modane, France, underneath 1,700 meters of solid rock on the Italian border. One of them is a vessel with about a tablespoon of ultracold liquid helium. If a particle of low-mass dark matter impacts the liquid, it will generate a vibration that sprays thousands of helium atoms upward, where silicon detectors will look for microscopic changes in voltage. Other setups will work with sapphire-silica crystals and gallium arsenide, a semiconductor. 

These experiments will help researchers identify the best approaches to use for bigger, more sensitive—and more expensive—detectors. “There’s still lots of ideas, and it’s still not quite clear what’s going to be the best one to really scale up,” Essig says. For now, if it fits on a table and can plausibly detect dark matter, physicists are willing to try it.

The utmost gravity 

The hunting ground for dark matter extends past the surface of any table, or even Earth itself. Some researchers have suggested we look for the stuff not in underground laboratories but on planets, stars, and moons. If dark matter particles occasionally annihilate when they encounter one another, they could ionize hydrogen in the atmosphere of a planet, creating an ultraviolet aurora visible from space. This self-annihilation could also be a strong source of heat—enough to melt a planet’s core. The fact that Earth’s core is solid provides limits for dark matter’s characteristics, and measuring the temperatures of planetary cores more precisely could set even more stringent constraints.

Searching for astrophysical signs of dark matter is not new, but in recent years physicists have become almost artistic with their proposals. One particularly evocative suggestion: looking at the icy ocean of Jupiter’s moon Ganymede. If dark matter is indeed really heavy—possibly a primordial black hole—it could punch through the surface and leave a crater that looks very different from one caused by an asteroid.

Some particle physicists think it would be better to drop all the existing assumptions and refocus. “Everything we know about dark matter has come from its interaction with gravity,” says Caltech’s Zurek. If you concentrate more specifically on that interaction, she says, at least “you’re guaranteed to learn something.” We know how dark matter behaves on the scale of the observable universe as far down as galaxies. “Below that, we really know very little about how dark matter collapses under the weight of gravity,” Zurek says. How, for example, does it clump up on the level of a solar system? 

In recent years physicists have become almost artistic with their proposals. One particularly evocative suggestion: looking at the icy ocean of Jupiter’s moon Ganymede.

This isn’t a “next year” or “next five years” project. The technologies physicists have now are simply not sensitive enough to search for these gravitational interactions. So Zurek is thinking long term. Really long term. “It’s going to take decades, like probably 100 years,” she acknowledges. “It may not be something that I see in my lifetime.” 

Someday—perhaps by monitoring the timing of distant pulsars (the spinning remnants of dead stars) or measuring slight perturbations in gravitational interaction between atoms suspended in lasers—physicists could learn more about dark matter’s true nature. 

For now, the scale of the problem seems daunting, especially compared with the ones particle physicists have tackled in the past. Before the LHC even turned on, for example, those hunting for the Higgs boson had hemmed their quarry in. They knew, from rigorous theoretical calculations and robust experimental measurements, that if the boson existed, it had to weigh between 120 times and 150 times the mass of a proton. Soon after the LHC began smashing protons, the Higgs popped out of the data, right at 133 times the mass of a proton.

Dark matter, by contrast, remains an almost total mystery. Rybka likens guessing about its mass or its interaction strength to “drawing numbers out of a hat.” “We literally don’t even know what the hat looks like,” he adds. 

With this many unknowns, success is far from certain, and the researchers have no illusions. “There’s no discovery guaranteed. You might be wasting your time completely,” Essig says. 

None of this has dissuaded him or others. “That’s just the nature of the problem. We have to search far and wide and explore lots of things,” Essig says. “If you don’t like it, do something else.” 

Dan Garisto is a freelance physics journalist based in Syracuse, New York. 

Hacking the atmosphere: geoengineering gets a reality check

Solar geoengineering, the controversial idea that we could deliberately intervene in the climate system to counteract global warming, is moving beyond computer simulations and into the practical engineering challenges required to make it real.

Researchers are now working on aircraft, materials, and other systems for solar geoengineering. But as they delve into these details, they’re finding that even early deployment would require significant new infrastructure, time, and investment.

Find out what happens when solar geoengineering encounters the realities of trying to cool the planet.

—James Temple

MIT Technology Review Narrated: inside interoception, the hidden sense of how you feel inside

Scientists have a word for how we sense ourselves from the inside: interoception. Today, thanks to a 2021 Nobel Prize and new tools that can map internal signaling across the body, research into interoception is taking off.

As researchers decode how signals move between body and brain, a clearer picture is starting to take shape—with implications for how we treat conditions from obesity to anxiety.

—Katherine W. Isaacs

This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we publish each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 SpaceX is now valued higher than Amazon 
Its market value hit $2.659 trillion yesterday. (Axios)
+ A post-IPO stock surge also briefly pushed it above Microsoft’s. (Quartz)
+ It’s now the world’s fifth most valuable company. (Guardian)
+ SpaceX is acquiring AI coding startup Cursor for $60 billion. (CNBC)

2 G7 leaders want access to top US AI models
They’re pushing to escape restrictions on the likes of Fable 5. (Reuters $)
+ The Mythos shutdown has sparked a global scramble for sovereign AI. (Fortune)
+ The world is looking to ditch US AI models. (MIT Technology Review)

3 Trump’s AI export strategy has run into Trump’s export controls
His administration risks undermining its own AI plans. (Axios)
+ It now effectively has a licensing regime for frontier AI. (Fortune)
+ Here’s how a top Chinese AI model overcame US sanctions. (MIT Technology Review) 

4 Huawei’s big comeback has exposed the limits of US chip controls
It’s overcome restrictions on advanced chipmaking gear. (Financial Times $)
+ The AI boom has ignited Asia’s chip companies. (NYT $)

5 AI fears are pushing Silicon Valley toward gene-editing startups
They want smarter babies to counter superintelligent AI. (Mother Jones)
+ The pursuit of perfect babies is an ethical mess. (MIT Technology Review)

6 A brain implant has enabled a speechless ALS patient to work full-time
The system translates his brain activity into speech. (The Register)
+ He’s become the first “power user” of a BCI. (MIT Technology Review)

7 A leak has revealed details of Peter Thiel’s secret society
Its program ranges from cult-building to prepping for World War III. (Wired $)

8 ChatGPT’s market share has slipped below 50% for the first time
Thanks to the rise of Gemini and Claude. (TechCrunch)

9 A quantum state that lasts forever may finally be within our grasp
Experiments suggest that quantum “eternity” is possible. (New Scientist $)

10 Commodore has made a digital detox phone that isn’t dumb
The Callback combines gadget nostalgia with modern needs. (The Verge)

Quote of the day

“The Entity List is like whack-a-mole and you’ve got to ‌keep whacking ⁠the moles.” 

—Philip Luck, who studies global supply chains at the Center for Strategic and International Studies, tells Reuters that a lack of new blacklistings is likely leading American innovations to adversaries who could use them against the US.

One More Thing

COURTESY OF DEEPMIND

This is the reason Demis Hassabis started DeepMind

Watching DeepMind’s AI master the ancient board game Go, Demis Hassabis realized that his company was ready to take on one of the most important and complicated puzzles in biology: predicting the structure of proteins. 

The result was AlphaFold2, an AI that could predict the shape of proteins down to the nearest atom. “It’s the most complex thing we’ve ever done,” Hassabis told MIT Technology Review.

Taking on scientific problems is the culmination of what Hassabis set out to achieve, and it’s what he wants to be known for.  “This is the reason I started DeepMind,” he says. “In fact, it’s why I’ve worked my whole career in AI.”

Discover how he plans to transform science with AI. 

—Will Douglas Heaven

We can still have nice things

A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ This mesmerising footage of wind rolling through grass looks like CGI.
+ The glorious early days of internet discovery have been revived by the return of StumbleUpon.
+ A German subway entrance has been delightfully designed as an old tram car crashing into the pavement.
+ The Last Museum lets you search across 5.8 million museum artworks spanning from 3000 BC to the present day.

Most of Kenya’s power grid runs on renewables. But with 25% of communities lacking centralized electricity, the nation is looking to off-grid solar to hit its goal of delivering universal electricity access by 2030 without driving up emissions. The ever-­improving economics of solar technology have helped. A couple of years ago, a panel cost about $3 a watt; now it’s down to cents. 

On the margins of a bustling Nairobi, we wind past a mix of high-rises and hardware shops interspersed with small plots growing corn or potatoes. After a few minutes, we arrive at a street-side stall run by the bespectacled Milcah Wanjiru. She sells plenty of half-liter packets of milk, loaves of bread, and matches, but Wanjiru’s core business is a service: She mills corn flour for local residents, which they most often use in ugali—a common Kenyan dish that is similar to polenta, albeit less creamy. 

In the middle of her small shop, a milling machine stands on three adjustable legs. “Whenever customers came to mill their grain, they asked for other goods,” says Wanjiru, “and this is how I got to stock these other items.” 

Shops with a grain mill are common here in rural areas and most neighborhoods, especially low-income ones—even in the city. But most of these mills burn diesel fuel. Hers? It runs on either solar energy or electricity from the grid. 

Matt Carr, the CEO and cofounder of Agsol, the company that designed Wanjiru’s mill, is here with me, visiting to get her feedback on his product. One issue bothers her. “It can be slow,” Wanjiru tells Carr, explaining that grains can get stuck in the front chamber where they feed into the machine. Sometimes, the whole thing jams. 

Carr says the mill automatically reduces its speed if the grain is at all damp, so that the pulverizing hammers within can squeeze out as much flour as possible. That process can unfortunately lead to the problem she’s describing. 

Overall, Wanjiru seems happy with the machine, which she’s been using since December 2025. It makes running her business cheaper. About 40% of what shop owners who use diesel-powered mills charge customers goes toward paying for fuel, according to Carr, whereas operating Agsol’s solar-powered machine can be up to 80% more profitable once the initial cost (about $1,300) is paid off, which takes between six and 12 months. Wanjiru also likes the fact that—unlike diesel-burning models—her mill can handle very small amounts of grain, which has brought a few new customers her way.  

Carr launched the first Agsol product in 2018 in Kenya and has raised over $4 million of investment—much of that via a UK government program that supports clean energy projects in the region. Last year, Agsol sold 530 units. The company, which is based just outside Nairobi, has received orders from as far as Mozambique and Angola.

As we say goodbye to Wanjiru, she turns and bends over burlap sacks half full of peanuts, mung beans, rice, and millet, arranged neatly on wooden pallets on the cement floor. She lifts a scoopful from one of the sacks and dumps its contents on a scale. A customer waits to be served. 

Geoffrey Kamadi is an award-winning freelance journalist based in Nairobi, focusing on science, climate change, environment, technology, and development. 

The uncrewed plane is soaring thousands of meters higher than commercial jets fly—so high you can see the curvature of the Earth. It’s precisely the type of aircraft one would need to begin artificially cooling the planet. Those outsize wings would keep the plane and its payload aloft in the stratosphere, about a dozen miles (or 20 kilometers) above the surface, where the air is much thinner—as little as 5% the density near the ground. Once at altitude, the plane would release materials that could, after a few steps of chemistry, reflect sunlight back into space.

The concept came from volcanoes. Massive eruptions in the past have reduced temperatures worldwide by blasting sulfur dioxide and other compounds into the stratosphere, where they convert into sunlight-scattering particles. Hundreds of studies in recent decades have suggested that a human attempt to mimic this mechanism would work quickly and efficiently—at least within the confines of climate models.

But these computer simulations are approximations of how the real world works. They gloss over numerous challenges. Like the fact that aircraft capable of carrying the necessary loads to the necessary altitudes don’t exist. Or that we don’t know for sure how to release material so that most of it turns into tiny reflective aerosols instead of, say, clumping together and falling out of the sky. Or even what specific substance we would want to load onto an aircraft, given open questions about safety, cost, and effectiveness. 

Amid these compounding unknowns, more and more research on solar geoengineering is moving beyond computer simulations, delving into the detailed design and practical engineering work that would be needed before we could carry out a campaign to dial down temperatures. The tasks required range from inventing high-altitude aircraft to mastering the precise chemistry and delivery mechanisms for dispersing materials to building out the monitoring infrastructure that we’ll need in order to know if any of it actually works.

The question of whether we should geoengineer the planet has no clear-cut answer. It might save millions of lives by reducing the dangers of catastrophic heat waves, floods, droughts, and famines. But many fear it’s too dangerous to even consider, much less seriously study, arguing that we can’t possibly predict the spiraling consequences of manipulating such large, complex, interconnected planetary systems. 

Critics argue that the building momentum in this phase of research will make it ever more likely that someone, somewhere in the world, will eventually pull the trigger on geoengineering, no matter the remaining unknowns or the dangers for certain parts of the world.  

“I do think it’s very dangerous because of what we know about science and technology,” says Jennie Stephens, a professor of climate justice at Maynooth University in Ireland. “The more investment that’s made, the further the advances, the more likely it is that it will be deployed.”

But proponents of this practical research argue that playing out how we’d mount a solar geoengineering program will improve our understanding of the potential benefits and risks, helping to ensure that if anyone does try to tweak the climate, they might at least do so in an informed and potentially safer way.

MIT TECHNOLOGY REVIEW | JUSTIN SAGLIO

It’s still very much a niche field. Much of the work now underway is happening at the Climate Systems Engineering Initiative (CSEi) at the University of Chicago, which formally launched in 2024 under the leadership of the prominent geoengineering researcher David Keith. 

Franke, a professional engineer before earning his doctorate in geosciences, is overseeing a series of overlapping research projects and collaborations aimed at resolving many of the engineering uncertainties. That includes working out the designs now on his desk—renderings of the type of aircraft that could be used in the initial phase of a geoengineering program. 

Franke argues that more computer simulations are simply not going to answer the big remaining questions in the field, including the most compelling one: the “boogeyman” of what could go wrong. 

“I’m kind of personally skeptical that additional model development or more simulations are going to satisfactorily resolve those things,” he says. “And so I’m not really that interested in turning the crank on more models.”

For Franke, it’s time for the next step: “We’re interested in seeing how you’d actually do this thing if you wanted to do it.”

What we don’t know

Solar geoengineering is often portrayed as a relatively cheap and easy fix for climate change. But as researchers take a harder look at the nuts and bolts, they’re finding considerable uncertainties, missing tools, and unbuilt infrastructure.

None of that may be a showstopper, but we’ll need time and money to develop the components necessary to implement even the early stages of a solar geoengineering program. What this research is about, at its core, is not actually launching something, but figuring out what it would take to do so. 

A young San Francisco nonprofit, Reflective, recently worked with scientists in the field to figure out just how much we still don’t know.

The process began by outlining what the organization, which pools money from donors to fund geoengineering studies, describes as a “well-managed, moderate” scenario: In 2035, some nation or group of nations begins a small-scale geoengineering deployment, spraying an equal amount of sulfur dioxide or hydrogen sulfide—gases that should convert into reflective aerosols in the stratosphere—near both the North and South Poles. The initial program would release enough material to reduce temperatures by about 0.1 °C, shaving off a fraction of the roughly 1.4 °C of worldwide warming that’s occurred since the start of the industrial era.

The poles figure prominently in this and other early-stage geoengineering scenarios, for a simple reason: The stratosphere starts as low as seven kilometers there—as opposed to around 18 to 20 kilometers at the equator. That makes it easier to reach, enabling existing aircraft, with some modifications, to carry sizable payloads up there. 

The wrinkle is that the cooling effect would be more pronounced in the northernmost and southernmost latitudes. That’s because, among other complicated mechanisms, higher temperatures in the tropical stratosphere would mostly prevent aerosols released around the poles from drifting toward the equator. So deploying geoengineering in those areas would likely have milder effects on the hotter and poorer nations around the tropics, which are also some of the areas most vulnerable to climate change.

To cool the world evenly—and fairly—you’d eventually want to add flights closer to the equator. Over the following decade or so, under Reflective’s scenario, the program would scale up, shift to novel aircraft flying above the subtropics, and release enough material to achieve global cooling of 0.5 °C. 

Among them: sorting out how hard or expensive it would be to retrofit existing aircraft to carry out the early stages of the project. Deploying at the poles could also require constructing new airports, establishing new shipping lanes or railways to transport supplies, and building facilities that could process raw materials—by, for example, combusting elemental sulfur to produce sulfur dioxide.

We would also need to build more instruments and send them up to the stratosphere aboard balloons, drones, or other aircraft to observe the baseline chemistry, reflectivity, and distribution of compounds there—and to track what changed once new materials were released.

Finally, the main satellites that observe the stratosphere from space are set to go out of commission in the coming years, creating the risk of an “imminent data desert,” as a 2025 paper in the Bulletin of the American Meteorological Society warned. Several new instruments are in development or available for launch, but there could be a gap in observations at a point where we’d want to have a clear picture of the baseline conditions, Reflective notes.

Dakota Gruener, the chief executive officer of the nonprofit, stresses that the organization isn’t advocating the use of solar geoengineering. But she says it’s important for the field to begin addressing engineering uncertainties now because it stress-tests the assumptions in climate models. It helps us determine whether the scenarios explored in silico are feasible in the real world.

It’s also important to do this, she says, because it may take a long time to resolve all these unknowns while the climate grows steadily warmer. “If we aren’t putting adequate attention to them now, we might be caught flat-footed,” Gruener told MIT Technology Review.

A 2024 analysis in the journal Earth’s Future highlighted just how expensive and time-consuming it might be to develop the aircraft and infrastructure required for an initial deployment. The study explored what it would take for a geoengineering program around the poles, capable of reducing temperatures by 2 °C in the northernmost and southernmost parts of the planet, to be up and running by 2040. The conclusion: It could require at least a decade of work and a $35 billion investment. 

Wake Smith, a research fellow at Harvard and lead author of the study, also says that researchers need to move forward with engineering studies now, because the urge to use the technology will likely grow stronger as climate change becomes increasingly catastrophic.

“The risk I worry about is needing it before we understand it and therefore doing it badly,” he says, later adding: “The sooner we get going with it, the better decisions we’ll be able to make a few decades hence in terms of whether to do it, how to do it, when to do it.”

A novel aircraft

The aircraft pictured on Franke’s desk, which is still just a concept, could reach just beyond the threshold of the stratosphere above the tropics when fully loaded. A fleet of 270 of them could disperse about a million metric tons of material per year, enough to ease global surface temperatures by about 0.26 °C. 

The CSEi outsourced the work of designing it to John Langford, a well-known aeronautical engineer and entrepreneur. Langford’s company, Electra.aero, had previously collaborated with the MIT Department of Aeronautics and Astronautics to develop autonomous, solar-powered aircraft that could carry out extended scientific missions in the stratosphere. He is now spinning out a new business, Iris Aero, to produce those planes, which are assembled from a single, continuous wing covered in solar panels and suspended above a tiny fuselage.

Langford expects the solar plane to find its main initial commercial applications in wildfire monitoring and forecasting. But by swapping in a different set of instruments, it could be used to monitor how materials dispersed in the stratosphere might alter conditions there, he says.

The novel aircraft is a variation on the observational plane, with the added space and thrust necessary to carry these materials to the stratosphere and release them. It has a wider wingspan and swaps out those solar panels for a pair of Rolls-Royce AE 3007 engines.

The aircraft would also include a detachable tank that would function something like a trailer on a semi. This would make it possible to load materials between flights and prevent any damage to the plane itself from those materials, some of which are corrosive, Langford says. 

He says he and his team have completed the initial designs and are now doing more detailed engineering and cost analyses. They intend to publish the findings when the effort is complete. 

“We’d love to build a prototype of such an airplane and feel we could do so relatively quickly,” Langford says. “But that all depends on what David’s group wants to do.”

The program

The university saw an opportunity to step up as a leader in a field that wasn’t getting adequate academic attention despite its potential to address the dangers of climate change, says Michael Greenstone, a climate economist and the founding director of the university’s Institute for Climate and Sustainable Growth.

Keith, 62, previously spent nearly 13 years as a professor of applied physics and public policy at Harvard, where he led the establishment of the university’s Solar Geoengineering Research Program. More famously, he strove to carry out what could have been the first solar geoengineering experiment to release material in the stratosphere, known as SCoPEx. But after years of work and multiple delays, the research team finally scrapped the project in early 2024, following mounting criticism from environmental and Indigenous groups and the eventual intervention of the Swedish government.

Keith has long argued that researchers should seriously study geoengineering because it might substantially reduce the dangers of climate change, alleviating death, destruction, and suffering on massive scales.

He says that the overarching goal of the Chicago initiative is to expand the field by bringing together “enough independent professors and other research professionals” to “build a community around climate engineering as a broad field of inquiry.”

“Solar geoengineering certainly has complex and potentially dangerous political consequences, but so do a host of other emerging ideas and technologies.”

David Keith, geoengineering researcher

The CSEi researchers are now exploring nearly every engineering challenge that Reflective highlighted in its analysis. In addition to the work on novel aircraft and in situ observations, the group is designing small “cube” satellites with optical sensors optimized for observing the stratosphere. It is also studying which materials might prove most practical to ship to the stratosphere and how best to release them.

The goal is “producing public information which can be independently assessed, critically assessed, so policymakers can understand more about what’s possible and not,” Keith says.

Normalizing a dangerous idea

The debate around solar geoengineering is quickly moving beyond the academic and theoretical realm. A handful of startups, some more serious than others, have begun testing technologies that could one day be used to cool the planet. 

Yet to critics, solar geoengineering is the peak of techno-solutionism, affixing a high-tech Band-Aid to a global crisis caused by earlier technologies instead of addressing the root cause. Further, they argue that there’s no way to deploy or govern it in a globally equitable way, because any use of it will prove more advantageous to some regions than others. 

Even if solar geoengineering succeeded in reducing the average global temperature by 1 °C or so, that would mean very different things in different regions.

It could keep farmers prosperous and cities safe across, say, much of the US and the world’s temperate zones. But the lower temperature might be too cool for Russia to boost its agricultural productivity, while it might still be too hot for subsistence farming in northern Africa. 

Some studies also suggest that high levels of solar geoengineering could create new dangers in some regions, potentially altering monsoon rains, decreasing agricultural output, shifting the range of infectious diseases, and more. 

These complications raise a long list of thorny and divisive ethical questions. Even if solar geoengineering produced better conditions across most of the planet relative to a world with unchecked climate change, would it still be acceptable if it unleashed deadly famines or floods in a few regions? What kind of global consensus should be required to decide it’s okay to deploy it? And how should we determine where to set the planet’s temperature—and when, if ever, to shut the technology off?

Stephens argues that the answers, like so much else in the world, will come down to wealth and power. Countries, corporations, or even wealthy individuals with the resources to deploy such a system would have every incentive to tune it for their optimal benefit, no matter what it might mean for others. 

“It will be certain people who have a lot of wealth and power deciding when and how, and who should benefit and who will get screwed,” she says. “That’s the fundamental reason I think any advance in this technology is so dangerous.”

Duncan McLaren, an environmental researcher and political scientist, argues that the shift into practical engineering studies demands more oversight of the research field.  

For many critics of outdoor experiments like SCoPEx, he explains, the major concern wasn’t the environmental or safety risks, which were minimal; the issue was the normalization of a concept that could reduce pressures to cut greenhouse-­gas emissions. 

He says that any advance in research—whether it’s on paper, in the lab, or in the stratosphere—raises a similar risk: undermining progress on climate action by allowing the fossil-fuel sector and other business interests to say there’s an easier solution in development that doesn’t require overhauling our energy systems. A policy paper that the Texas Conservative Coalition Research Institute released in March advanced this very argument, citing the far lower costs of solar geoengineering relative to the “staggering costs” of a “forced transition.” 

Given this so-called moral hazard risk, design and engineering work should demand the same level of scientific supervision that outdoor experiments do, including ethical review, risk assessments, and public engagement, McLaren says.

“It ought to be more onerous,” he says. “There ought to be more barriers to researchers saying they want to do this.”

“The next ethical step”

Keith pushes back forcefully on that assertion, condemning as “profoundly illiberal” the idea that we should regulate open academic research posing no physical risks. 

“Solar geoengineering certainly has complex and potentially dangerous political consequences, but so do a host of other emerging ideas and technologies,” he said in an email. “The best chance to manage these challenges is to debate them openly and freely.”

Keith is all for keeping solar geoengineering technology in the public domain, and he agrees that the first line of climate defense must be rapid and deep reduction of greenhouse-gas emissions. But the world has made little progress in cutting climate pollution, carbon dioxide can persist for thousands of years in the atmosphere, and the planet is heating up fast. So, he argues, we may need to pursue other measures to temper the growing threats.

The bar for restricting research in this field should be “very high,” he says, given the potential promise of the technology. 

After visiting flood-devastated villages in Bangladesh, Keith underscored this point in an interview with the director of Plan C for Civilization, a recent documentary that profiles his work. “I think people have to take the next ethical step,” he said. “Because if you are really going to withhold access to and knowledge of a technology that could potentially save enormous numbers of lives—real lives, people we’ve met in the last few days—you’ve got to be very confident that that technology is going to be misused.”

The particles

Mingyi Wang, an assistant professor at the University of Chicago, leads me down the hall to a square, white lab room in the Henry Hinds Laboratory for Geophysical Sciences.

He pulls open the doors to a gray Haier biomedical freezer just inside the entrance, revealing a transparent flow tube hanging vertically and tapering at the bottom.

It’s a miniature stratosphere, chilled below −50 °C and filled with the same mix  of oxygen, nitrogen, and other air molecules you’d find 20 or so kilometers above us. A series of Teflon and stainless-­steel tubes run into the vessel, allowing Wang and his team to add various gases or particles and observe how they react.

Wang is an atmospheric scientist who studies how aerosols form, and he is now exploring what materials might be the most effective for reducing temperatures. 

COURTESY OF IRIS AERO CORP.

Most modeling experiments focusing on solar geoengineering explore the impact of adding sulfuric acid to the stratosphere, because that’s what ultimately ends up there after a volcanic blast. 

But it would be costly and complicated to simply haul sulfuric acid up there and release it, because it’s heavy and sticky. So Wang and his team are conducting experiments in that chilly flow tube to determine what substances, including precursors to the acid, might do the best job of producing aerosols of the ideal size for reflecting away sunlight—and how best to prevent the materials from simply clumping together with existing particles and falling out of the stratosphere.

Wang, whom Keith refers to as a “young star,” has arrived at a novel solution to this problem, though he’s not ready to share the full details yet. He and his team are feeding the findings from their experiments into computer simulations of stratospheric plumes that they’ve developed. These, in turn, can be plugged into large-scale climate models to improve their simulation of smaller-scale effects—and thus enhance our understanding of stratospheric chemistry.

Wang says that it’s important to do this detailed research because until now, climate models simply assumed you’d wind up with the right aerosols of the right size. 

“Scientifically, we may understand it reasonably well, but on the engineering perspective—do we really know how to do it right?” he asks. “That’s a big question.” 

What’s next

As I began reporting on CSEi, I assumed that some of the engineering and design work would lead to new proposals for stratospheric experiments, picking up from where SCoPEx left off. 

Keith, though, insists he has no interest in reliving that experience, given the weight the experiment took on as the focal point for a broader societal debate over solar geoengineering. He doesn’t see any of the other “practical engineering” work at the initiative leading toward field experiments either, at least at this stage.

Much of the work, in fact, is focused on a step beyond that: exploring what it would take to start a geoengineering campaign, if a nation or group of them eventually decides to. Franke notes that we already have balloons and other aircraft that could get to the lower bounds of the stratosphere to release an experimental amount of, say, sulfur dioxide. 

“I think that this field needs to stop being so ashamed of using the ‘deployment’ word,” he says. 

This subscriber-only eBook is a package of six stories that were originally published in MIT Technology Review between April 11, 2025, and April 21, 2026, and have been updated to reflect recent developments.

Stories written by James O’Donnel by James O’Donnell

Choose which file format to download this eBook:

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This man with ALS is the first “power user” of a brain implant that lets him speak

Casey Harrell has had a set of electrodes embedded in his brain for almost three years. Harrell, who has ALS and is paralyzed, first used his brain-computer interface (BCI) to “speak” in 2023. Since then, he’s clocked thousands of hours of use. 

Harrell can now use the device largely independently. His team has added new features to it, and he also uses it to surf the web and perform his job. “Living with a disease like ALS, you are supposed to have diminished dreams. I do not,” Harrell told MIT Technology Review. 

The team behind the device call Harrell “the first power user of a speech BCI.” They now plan to add further enhancements to the device.

Dive into the groundbreaking impact of Casey Harrell’s BCI.

—Jessica Hamzelou

Why do South Koreans love AI so much?

While a public backlash against AI brews across the US, South Koreans are optimistic. Only 16% say they are more concerned than excited about AI—the lowest of the 25 countries surveyed by the Pew Research Center—while 50% of Americans were more worried than excited. 

South Koreans share a deep conviction that embracing technology is integral to modernizing the country and cementing its place in the global order. Their fascination with AI is just the latest incarnation of that ethos—and it’s making them anxious to stay ahead.

Read the full story on South Korea’s AI fervour.

—Michelle Kim

This story is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The US says it restricted Anthropic AI over foreign intelligence risks
Commerce chief Lutnick said he acted over national security fears. (Reuters $)
+ Following the ban, Anthropic disabled access to its new models. (BBC)
+ Both sides are increasingly desperate for a resolution. (WSJ $)

2 DeepSeek just became China’s most valuable startup
It raised $7 billion, the largest-ever first-round funding for an AI startup. (The Information $)
+ The deal values DeepSeek at over $50 billion. (WSJ $)
+ Its unusual structure preserves founder control. (Reuters $)
+ DeepSeek’s new flagship model has caused a stir. (MIT Technology Review)
 
3 Alibaba has unveiled AI models for robots amid a shift from chatbots
It’s joined a global race to move AI into the physical world. (SCMP)
+ AI is learning to understand its surroundings. (MIT Technology Review)
 
4 Fox is buying streaming giant Roku for $22 billion
The deal creates the third-largest player in US TV by viewing share. (BBC)
+ Fox is making a big bet on free streaming. (Washington Post $)

5 EA has launched a new way to advertise “directly into gameplay”
EA Advertising allows brands to become part of the game itself. (CNBC)
+ Xbox’s new chief strategy officer is also eyeing in-game ads. (PC Gamer)
+ GenAI could reinvent what it means to play. (MIT Technology Review)

6 It’s trivially easy to use Reddit to manipulate AI search
A tiny snippet of text can trick ChatGPT and Google’s AI search. (404 Media)
+ AI search is being manipulated to generate dangerous biases. (BBC)
 
7 Sperm have been made magnetic to allow IVF inside the body
The technique enables remote guidance towards an egg. (New Scientist $)
+ Automation and AI are transforming IVF. (MIT Technology Review)
 
8 The world’s leading deepfake expert no longer trusts his own eyes
He’s struggling to prove what’s real before the internet decides. (NYT $)
 
9 Meta’s CTO admits its AI reorganisation was “atrocious”
He’s promised staff better communication—and snacks. (Wired $)
 
10 Silicon Valley billionaires are pretending to kill each other for fun
In a new game show from Peter Thiel’s Founders Fund. (WSJ $)

Quote of the day

“There was a speeding ticket, and they gave Fable the death penalty.” 

—Alex Stamos, the former chief security officer of Facebook, tells the Washington Post that banning foreign access to Anthropic’s leading model is a disproportionate punishment.

One More Thing

VICTOR KERLOW

Inside effective altruism, where the far future counts a lot more than the present

Since its birth in the late 2000s, effective altruism has aimed to answer a deceptively simple question: “How can those with means have the greatest impact?”

Directing money to evidence-based approaches is EA’s best-known technique. But as it’s expanded from an academic philosophy into a community and a movement, its ideas of the “best” way to change the world have evolved as well. 

Find out how effective altruism became one of the most influential—and contested—forces in philanthropy.

—Rebecca Ackermann

We can still have nice things

A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ The humble table has been reimagined as an unconventional public artifact.
+ Take a visual tour of the weird, centuries-old history of architecture’s most gruesome gargoyles.
+ A colorful parakeet unseen for an entire century was triumphantly rediscovered in an unexplored Indonesian forest.
+ This shimmering Southern Lights timelapse filmed by an astronaut on the SpaceX Dragon is stunning.

Just as those kettles started heating up, an AI program sent instructions to a data center in London to slow down some of the facility’s power-hungry chips. This reduction helped make sure there was enough supply to match demand, staving off potential blackouts or damage to electrical hardware. For data centers, which normally guzzle power without consideration for anyone or anything else’s needs, it was a radical departure.

It was also a simulation. In December 2025, engineers sought to test a new breed of data center built to be flexible about its electricity needs, so they re-created the energy demand facing the UK’s grid during a match from the 2020 Euro tournament. They wanted to see how their software, called Conductor, would have responded had it been online at the time.

Conductor is the signature product of Emerald AI, a firm based in Washington, DC, that’s part of a wave of companies trying to figure out whether data centers can work within the confines of the existing electric grid.

This year, Emerald is set to deploy Conductor in a new facility in the part of Virginia known as Data Center Alley, this time connected to the live grid. When overall demand spikes, Conductor will turn down the power used by the data center, while making sure its servers still carry out their timeliest and most important jobs. Emerald’s partners on the project—which include Nvidia and the giant data-center operator Digital Realty—bill it as one of the world’s first “power-flexible AI factories.”

Demonstrating that data centers can participate in this kind of give-and-take could ease what many tech leaders identify as the bottleneck in getting facilities online: It takes far longer to get approval for, construct, and connect new power plants than to build data centers. PJM, the grid operator in Virginia and the largest one in the US, for instance, needs eight years to bring new generation online, according to RMI, an energy research and advocacy group. “We need to solve the energy equation,” says Josh Parker, head of sustainability at Nvidia. “AI factory flexibility is the bridge between the incredible demand for AI and the immediate limitations of our energy grid.”

Speed, though, is only one of the issues. Once facilities do plug in, neighbors often criticize them for drawing too much electricity and contributing to rising prices. They say the data centers generate more noise than they do long-term jobs, contribute to pollution, and threaten to put people out of work. Organizers stalled over $150 billion worth of projects in 2025, according to Data Center Watch, and policymakers alert to the public mood are starting to impose limitations on development.

More than a dozen states are considering bans, and local moratoriums are in effect in places like Minneapolis and DeKalb County in Georgia. At the federal level, the GRID Act, a bipartisan bill in the US Senate, proposes to sever new data centers from public grids entirely. Some operators are already moving that way by trying to develop their own power generation.

Rather than rushing to build new power plants, companies could find part of the solution to the crunch right under our noses—or, more precisely, in the transmission lines under our feet and above our heads. The existing system operates near its full capacity during only a small number of high-demand hours throughout the year. This means, some grid experts argue, that if data centers can limit the power they draw during those stretches, they won’t need to wait for big infrastructure upgrades or build their own off-grid generation. 

Indeed, a growing number of studies have shown there could be plenty of power available for data centers that can flex. A widely discussed 2025 report from researchers at Duke University found that the US grid could offer an additional 76 gigawatts—about 5% of its entire capacity, and about enough to accommodate projected data-center growth in the US through 2030—to facilities that are willing to reduce their usage just 0.25% of the time. That’s about 22 hours a year. And when researchers from Princeton University and two grid-modernization companies looked at locations for new data centers in the PJM region, their report, which was funded by Google, found that a 500-megawatt facility capable of flexing for less than 1% of the year could reach full operation three to five years faster than one that’s inflexible. 

Flexible power connections could also help data centers address some of their PR problems. By decreasing their draw at times of grid stress, for instance, they could avoid diverting power from where it’s most needed, thus boosting stability. By using existing capacity, they might be able to reduce the need for new fossil-fuel power plants and spread fixed costs over more electricity users, pushing prices down. 

The AI power pinch is attracting resources and research into strategies for grid flexibility overall, which could help negotiate a tricky period: Taken together with electric vehicles, air-conditioning, and other sectors, data centers are helping drive what analysts predict will be a 25% increase in US electricity demand by 2030 compared with 2023 levels.

Ideally, flexibility gives grid operators more control over the flow of electrons, making them leaders of a harmonious ensemble rather than hostages to inflexible electricity requirements. That will help them manage demand spikes across the entire system and deal more effectively with the intermittent nature of renewables like wind and solar. “Demand flexibility is incredibly useful for power grids,” says Johanna Mathieu, a grid expert at the University of Michigan. “It helps reduce electricity costs and improve grid reliability.”

But while advocates see plenty of benefits, the concept brings complexity. For data centers, compromising on energy needs can be a hard sell. Flexibility requires utilities and grid operators, which tend to be operationally conservative, to change long-held practices. And some skeptics also say that flexibility distracts from the very real need to build more grid infrastructure faster, and could even pose risks to our electricity supply. 

Still, some technologists, grid operators, and utilities are hoping to show that flexibility works—not only in white papers or simulations but in real life. 

The poster children for data-center growth default toward inflexibility. Hyperscalers like Microsoft and Oracle have proposed enormous new centers, many of which would rely on off-grid, natural-­gas-burning power plants. When xAI wanted to speed up the buildout of the Colossus site outside Memphis, Tennessee, it rolled up with gas turbines on flatbed trucks. The facility, now in operation, is facing blowback from regulators and residents about the spike it’s causing in emissions and other pollution. In any case, there aren’t enough gas turbines worldwide to meet the demand from data-center operators. 

One big obstacle for anyone demanding a lot of power is that our grids are mostly rigid. They’re designed to supply enough power to meet total demand when it’s highest, even if that’s for only a relatively small number of hours a year. That conservative approach is a simple route to reliability, but it means that the grid has quite a bit of headroom. “The grid is already overbuilt by a lot. If you were an airline running at 30% utilization, you would not buy more planes,” says Amit Narayan, the cofounder and CEO of GridCare, a company developing flexibility technologies, referring to a 2025 Stanford study of transmission lines in western North America. “If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.” 

“If you were an airline running at 30% utilization, you would not buy more planes. If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.”

To be fair, the idea of flexibility isn’t entirely foreign to grid operators. For decades, they’ve practiced a technique called demand response: When it looks as if demand will get too close to supply, as it might during a heat wave when many people turn on the AC at the same time, they call large commercial or industrial facilities and ask them to shut down parts of their operations. This method can help avoid the need to fire up so-called peaker plants, which run on fossil fuels, but it’s slow, imprecise, and hard to scale.

In the 2000s, as the adoption of technologies like electric cars and solar panels presented new challenges, more internet-­connected grids also provided new means of flexibility. Virtual power plants, or VPPs, offered a smarter, faster, more granular alternative. Electricity customers ranging from factories to homeowners with smart thermostats, solar panels, or big batteries would allow the utility to adjust their draw to help meet demand—often getting paid for their (frequently unnoticed) trouble. 

After the generative AI boom began with the release of ChatGPT in 2022, some companies began to see flexibility as a way to get data centers set up more easily, efficiently, and affordably. If they bring AI money into existing grids and reduce or defer the need for expensive upgrades, data centers could actually help spread out fixed costs so as to lower rates for other users. A study from Duke University published this past February, for instance, found that flexibility could reduce rates by 0.5% to 2.8%. 

PETRA PÉTERFFY

The trick is figuring out how data centers, notorious power hogs, can keep operating when their flexible connections are throttled. Flexibility specialists envision three possible ways. The simplest is for the new data center to install on-site backup power storage or generation to tap when the grid is maxed out—at their own expense, of course.

A facility could also fill the gap by drawing on a VPP. The utility would turn down the electricity going to users who signed up for the VPP, and the data center would pay them for their flexibility. This method wouldn’t require any major infrastructure, but it would require the utility to have a big VPP program and to coordinate the exchange at a time when the grid was under stress. While VPPs exist to some extent in nearly 40 states, the rules governing them vary widely, and they are empowered to do more in some areas than in others. 

Finally, a data center could simply use less power at peak times. The conventional wisdom is that they won’t go for such limits, particularly when every number-­crunching server can feel like a goose potentially laying little golden eggs. But some experts are betting that the value of getting up and running quickly is enough to change their minds. “There is a clear and growing trend,” says Ayse Coskun, chief scientist at Emerald AI. “Operators are increasingly willing to trade some level of flexibility for faster grid interconnection.” 

GridCare, a startup based in Silicon Valley, was one of the first companies to use flexibility to get data centers online quickly. Instead of looking at grids only in worst-case scenarios when electricity demand is highest, the company analyzes the system under all conditions, explains CEO Narayan, who studied smart grids at Stanford. It feeds every part of the grid—including power plants, lines, substations, and homes—into a generative AI model that creates a “digital twin” for different grid configurations. It then picks out results that could unlock capacity while maintaining reliability, and it feeds those into another model trained on the physics of electrical components like resistors and capacitors to make sure they’re realistic.

GridCare found its first customer in the Silicon Forest, an area in the Pacific Northwest named for the trees that dominate the landscape and the IT industry that has more recently sprouted up there. The local grid needed more capacity to support more data centers. “Data centers wanted ‘speed to power,’” says Isaac Barrow, a manager of data-center relations at Portland General Electric, or PGE, the local power generator and distributor, “but transmission buildout is a long process that’s very costly.”

In 2024, Aligned Data Centers came to PGE wanting to expand its operation in Hillsboro, Oregon, and PGE followed a recommendation from GridCare. Aligned will install a 31-megawatt battery, set to be in service in May 2027, and decrease its draw by up to that amount when the grid becomes congested. Bundled with other flexibility measures, that battery has allowed PGE to increase the capacity it can offer Aligned and other nearby operators by 80 megawatts without any new power plants. Though the buildout of data centers in Hillsboro has faced plenty of pushback from locals, Barrow points out that it could have the knock-on effect of lowering costs for ratepayers, because it spreads out the tab.

Other companies are promoting different flavors of flexibility. Google has been moving processing loads from facilities in areas experiencing demand spikes to those in less stressed spots since 2023. It’s signed agreements with five utilities, including the Tennessee Valley Authority and Indiana Michigan Power, that add as much as a gigawatt of flexibility. 

Voltus, a major VPP provider across the US and Canada, markets a “bring your own capacity” program in which a data-­center company can fund a VPP nearby. The grid operator can use the VPP to decrease demand at busy times, and participants get a financial thank-you. “We can spin up new VPPs on the order of months,” says Emily Orvis, Voltus’s vice president of energy markets. In June, the company signed their first such data-center deal: a three-year plan in which Google will bankroll a VPP in the PJM interconnection.

Of all the approaches to flexibility, Emerald AI’s may be the most ambitious: asking data centers to dial into the grid’s needs. The company’s Conductor software, which can run on premises or in the cloud, builds on the research of chief scientist Coskun. Her group at Boston University showed in a pair of 2013 papers that a data center could watch the grid and help balance big power fluctuations, such as the intermittent effects of solar and wind power. By 2022, she and her colleagues had tested their methods on a cluster of 36 research servers and shown that the system could respect power limits without breaking the processes it was running. 

One of the most important questions for Conductor is deciding which AI processes can be slowed down to save energy without kneecapping performance. A lot of companies label their jobs by priority—a real-time chatbot query, for instance, might outrank something like a web search that’s part of a deep research project. When they don’t, Emerald AI tries to infer priority from the nature of the job. Conductor then analyzes the AI workload to determine how tweaking the power to a given processor will affect the performance and help meet the usage limits set by the grid operator.

“The performance curve changes for different kinds of workloads,” says Coskun. “Each AI job is going to have a different location on that curve. Our intelligence is figuring out where you are on that curve.” 

PETRA PÉTERFFY

Last year, Emerald AI began assessing the technology’s readiness for real-world use in a series of tests, raising the difficulty each time. The trials were carried out in partnership with the Data Center Flexible Load Initiative—a collaboration among tech companies like Google and Nvidia, utilities like Duke Energy, and grid operators like PJM that aims to help establish a repeatable framework for power-­flexible data centers.

The first challenge was in Phoenix, a fast-growing computing hub. For the test, Conductor took control of a group of server racks laden with 256 Nvidia A100 GPUs—hardware that can use about as much power as around 170 US homes. When presented with a simulation of a busy grid, Conductor reduced the power to the chips by 25% for three hours, while maintaining acceptable computing performance. Emerald AI and its partners reported the results in a paper in Nature Energy in December 2025.

The next trial forced the system to juggle surprise grid fluctuations without advance warning and redirect AI jobs from a data center in Virginia to a less busy one in Chicago. Then, in London, Conductor took the reins of equipment beyond the main GPU processors and faced a more complicated mix of fluctuations, including very short and long bouts of congestion—plus the notorious teakettle effect.

The progress so far shows that flexibility can work, at least in some situations, but only a small fraction of operators have pursued it as yet. “We’re just in the beginning innings of the game,” says Jesse Jenkins, one of the authors of the 2025 Princeton study and cofounder of Firma, a startup that works on data-center flexibility. “People are recognizing that this is a potential solution. The motivation is there; there are some bespoke examples. But there’s no uniform solution set that’s the default option, which is where we need to get.”

While data centers are going up across the US, no place on Earth comes close to the accumulated computing muscle in Northern Virginia’s Data Center Alley. The region is home to around 500 compute-crunching facilities, which represent 13% of the entire world’s capacity; the next two hot spots, Beijing and Oregon, contain 6% each.

There are proposals to build hundreds more facilities in Virginia, but a government study found that the state’s electricity demand will increase 183% (around 26 gigawatts) by 2040 if they all go forward, and supporting even half would be difficult. The power-flexible data center that Emerald AI, Nvidia, Digital Realty, and their partners are building in the suburb of Manassas could demonstrate how data centers can squeeze the power they need out of existing capacity. The facility, slated to come online later this year, is intended to give Conductor the chance to manage power at the largest scale yet and to respond to conditions on a live grid for the first time. In the UK demonstration, Conductor managed a 130-kilowatt AI cluster; in Manassas, it will pull the strings of a 96-megawatt hyperscale AI factory. 

Some degree of flex will play a key role as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars.

For PJM, the Manassas facility points to a potential path through the current power crunch. “We think data-center flexibility, in different forms, will be essential for the reliable integration of data-center load over the short to mid term,” says Scott Baker, who manages demand-side markets at PJM. 

But not all grid experts are so sanguine. PJM’s market monitor, which oversees the grid operator, says there are no workarounds when it comes to adding capacity. “The notion that large amounts of data-center load can be added without adding new generation is magical thinking,” says Joseph Bowring, an economist and the head of PJM’s market monitor since 1999.

One problem, he says, is that there’s no way to guarantee that a data center will actually take less power when demand is high. That is, absent any legal or regulatory push for flexibility or compliance, the utility won’t be able to step in to help prevent, say, a blackout. Utilities can rely on resources like power plants, but they can’t control or rely on data centers. “They do not want to be fully interruptible,” Bowring says of the facilities.

Stephen Empedocles, an advisor for technology companies, views flexibility as more of a tool than a silver bullet. “These approaches are excellent for improving grid reliability and getting more out of the infrastructure we already have,” he says, “but they are optimization tools.” They’re not substitutes for the “generation, transmission, and distribution expansion that will still be required,” he continues.

Flexibility advocates agree that over the long term, whether or not AI continues to boom, electrification will drive a need for more generation and transmission. Some degree of flex will play a key role in using grid infrastructure better as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars. A report published by the International Renewable Energy Agency in January 2026 found that grids around the world will need three times as much flexibility in 2030 as they had in 2019—and 10 times as much by 2050—to balance increasing demand with fluctuating supplies of renewable energy. 

The challenge of powering AI could provide just the spark we need to do the work of designing and building smarter, more flexible grids, says Coskun. “I think with a crisis like this, there’s no quick solution,” she says. “Sometimes a crisis like this creates an opportunity to do something differently.” 

Amos Zeeberg is a freelance science and technology journalist based in Bucharest. He’s developing a book about technology networks, including electric grids.

When I landed in Seoul after a grueling 12-hour flight from San Francisco, I walked through an unmanned immigration checkpoint, where a machine scanned my face and passport. On the subway home, people were glued to their phones (powered by flawless 5G even underground), as we raced past platforms lined with LED screens of ads celebrating K-pop idols’ birthdays. When I got off the station in Gangnam, a cartoon-eyed robot on wheels was waiting patiently at a crosswalk to deliver someone’s dinner. Internet cafés dotted the sidewalks, crammed with teenagers playing computer games, maybe hoping to become the next legendary pro gamer.

I stood at a bus stop with interactive touch screens showing real-time bus schedule updates. It will soon become an “AI bus stop,” the Gangnam district announced in June, with a kiosk that answers riders’ questions in multiple languages. The news didn’t surprise me. Having grown up in the city, I’ve watched Seoul transform from a scrappy boomtown into the gleaming tech capital it is today.

South Korea loves AI.

While a public backlash against AI is brewing across the US, South Koreans are optimistic. Only 16% say they are more concerned than excited about AI—the lowest of any of the 25 countries surveyed by the Pew Research Center—while 50% of Americans were more worried than excited. A majority of Koreans use AI every day, either as a sort of personal assistant or to do tasks at work, according to surveys by the Ministry of Culture, Sports, and Tourism and Korea Chamber of Commerce and Industry.

One of the most wired countries in the world, South Korea loves to street-test every new technology on the block—AI webcomics, virtual K-pop idols, and humanoid monks. And the appetite for experimentation doesn’t stop with ordinary citizens. Government agencies are early adopters too, deploying AI textbooks in schools and AI eldercare robots in welfare centers. South Koreans share a deep conviction that embracing technology is integral to modernizing the country and cementing its place in the global order. Their fascination with AI is just the latest incarnation of that ethos—and it’s making them anxious to stay ahead.

Engineered enthusiasm

All this techno-optimism has largely been engineered by South Korea’s national agenda to make AI a motor of economic growth. “The South Korean government has designated an AI-powered Fourth Industrial Revolution as the country’s path forward and aggressively promoted and invested in it,” says Chihyung Jeon, a professor of science and technology policy at the Korea Advanced Institute of Science and Technology. “South Koreans have consistently and relentlessly been told by the government about AI’s potential to create a better future.”

As South Korea rose from the ashes of the Korean War, technology lifted the nation from poverty into an economic powerhouse. In the 1970s, South Korea manufactured steel and ships, then semiconductors in the 1980s, broadband in the 1990s, and smartphones in the 2000s. Today, Samsung and SK Hynix supply most of the world’s high-bandwidth memory chips, which power the cutting-edge Nvidia hardware used to train AI models. South Korea’s economy now orbits these two semiconductor giants: The country’s main equity index, Kospi, surged to record highs in 2026, powered by the soaring share prices of both companies, each valued above $1 trillion.

Lee Jae-myung, president of South Korea, has pledged to vault the country into the ranks of the “top three AI powers” alongside the US and China. After taking office in 2025, he launched the Presidential Council on National AI Strategy to help buy massive amounts of computing power and a sovereign AI foundation model project that funds Korean companies to develop homegrown AI models. The government has also supported semiconductor titans, including Samsung and SK Hynix, through generous tax credits and low-interest financing. 

South Korea’s policy posture also prioritizes accelerating AI development over safety considerations. In 2024, South Korea’s legislature passed the AI Basic Act, one of the world’s first comprehensive AI laws, to promote AI development and establish light-touch regulatory guardrails. Seventy percent of South Koreans say advancing science and medicine through AI innovation is a bigger priority than protecting industries through regulation, according to the 2026 Stanford AI Index.

All of that effort might be paying off. The same index ranked South Korea as having the third largest number of notable AI models in the world, based on criteria such as state-of-the-art advancements or high citation rates. For many small countries like South Korea, AI is a chance to punch above their weight.

The blind spots

But that single-mindedness can crowd out critical reflection on AI’s broader societal impacts. “Because the national agenda on AI prioritizes economic development,” says Jeon, the professor of science and technology policy, “there isn’t much reflection on the social, political, ethical dimensions of the technology.” In 2025, the South Korean government faced a fierce backlash for rolling out AI textbooks riddled with factual inaccuracies and data privacy risks without testing them first in a pilot program to evaluate how they affect student learning.

And despite their optimism, South Koreans are still worried that AI could displace them from their jobs. After Hyundai announced in January that it will deploy Atlas humanoid robots across its car factories, the Hyundai Motor Group union protested vehemently. “Without labor-management agreement, not a single robot using new technology will be allowed to enter the workplace,” the union said. Sixty-four percent of South Koreans fear AI could displace human labor and exacerbate inequality, although 52% believe it could also increase productivity. 

On a recent Friday night in the Seoul Central Market, I went out with my cousins to a pocha, a late-night restaurant that serves fish cakes stacked in neat pyramids. As we clinked our cups of soju cut with beer—the scrappy staple cocktail of every Korean night out—one cousin asked me if I’d asked ChatGPT about my saju, a traditional Korean fortune-telling practice.

A 29-year-old insurance agent in Seoul praying for a new job and a boyfriend, she said asking ChatGPT about work and dating was her favorite pastime. She pulled up her phone and punched my birth date into the chatbot. 

Addicted to their screens, trapped between unemployment and dead-end jobs, and priced out of marriage and homeownership, 46% of South Koreans in their 20s have used a chatbot to read their fortunes, according to a survey by Korea Gallup. 

My cousin said she also asks ChatGPT for tips on trading stocks, dreaming big about making bank on her investment accounts into which she’s been pouring her salary. ChatGPT, she believes, is her portal out of reality into a better future.

Despite how fond she is of the chatbot as her shaman and financial advisor, she fears losing her job to AI. She still uses ChatGPT feverishly at work, as all her coworkers do, afraid of falling behind. 

“I sometimes fear AI, but for now, it’s just so useful,” she said.