This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. DOGE’s tech takeover threatens the safety and stability of our critical data —Steven Renderos is the executive director of Media Justice Tech buzzwords are clanging through the halls of Washington, DC. The Trump administration has promised to “leverage blockchain technology” to reorganize the US Agency for International Development, and Elon Musk’s DOGE has already unleashed an internal chatbot to automate agency tasks—with bigger plans on the horizon to take over for laid-off employees. The executive order that created DOGE in the first place claims the agency intends to “modernize Federal technology and software.” But jamming hyped-up tech into government workflows isn’t a formula for efficiency. Successful, safe civic tech requires a human-centered approach that understands and respects the needs of citizens.Unfortunately, this administration laid off all the federal workers with the know-how for that. And if this administration doesn’t change its approach soon, American citizens are going to suffer far more than they probably realize. Read the full story. Meet the researchers testing the “Armageddon” approach to asteroid defense One day, in the near or far future, an asteroid about the length of a football stadium will find itself on a collision course with Earth. If we are lucky, it will land in the middle of the vast ocean, creating a good-size but innocuous tsunami, or in an uninhabited patch of desert. But if it has a city in its crosshairs, one of the worst natural disasters in modern times will unfold. Homes dozens of miles away will fold like cardboard. Millions of people could die. Fortunately for all 8 billion of us, planetary defense—the science of preventing asteroid impacts—is a highly active field of research. We already know that at least one method works: ramming the rock with an uncrewed spacecraft to push it away from Earth.But there are circumstances in which giving an asteroid a physical shove might not be enough to protect the planet. If that’s the case, we could need another method, one that is notoriously difficult to test in real life: a nuclear explosion. Read the full story.—Robin George Andrews This story is from the next edition of our print magazine, which is all about creativity. Subscribe now to read it and get a copy of the magazine when it lands! The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Consumer tech products may be subject to steep tariffs after all The Trump administration says that while smartphones and other gadgets are exempt from ‘reciprocal’ tariffs, they will be included in forthcoming semiconductor tariffs. (FT $)+ Trump has promised to investigate the semiconductor sector. (The Guardian)+ The White House’s tariff chaos is showing no signs of slowing. (Reuters) 2 Meta is preparing for its day in court The landmark monopoly trial follows an investigation that took close to six years. (NYT $)+ The trial's ruling could force Mark Zuckerberg to spin off Instagram and WhatsApp. (Politico)+ But the US government is facing an uphill battle. (Wired $)3 Lauren Sánchez is heading into spaceThe pilot, who is also Jeff Bezos’ fiancée, will travel to the edge of outer space today. (CNN) + The all-female mission is expected to take around 11 minutes. (BBC)4 Chinese sellers aren’t worried about the USA’s tariffs  Even though they’re anticipating that the US won’t buy everyday goods any more. (WSJ $)+ The tariffs are hitting ordinary Americans pretty hard. (The Guardian)+ Meanwhile, Apple has increased its iPhone production in India by almost 60%. (Bloomberg $)5 Here’s what could happen to your 23andMe DNA data Now the company has gone bankrupt, a sale could be imminent. (Insider $)+ How to… delete your 23andMe data. (MIT Technology Review) 6 The hacking groups you need to know aboutFrom crypto thieves to sabotage specialists. (Wired $) + Cyberattacks by AI agents are coming. (MIT Technology Review)7 Netflix is testing out a new AI search functionPowered by OpenAI’s technology. (Bloomberg $) + It’s currently available for select users in Australia and New Zealand. (Engadget)8 San Francisco residents are turning Waymos into community bulletin boardsThey’re leaving handwritten notes seeking new hires and dates inside the robotaxis. (WP $) + How Wayve’s driverless cars will meet one of their biggest challenges yet. (MIT Technology Review)9 Who is hacking California’s crosswalks? Crossings are playing AI recordings mocking Elon Musk and Mark Zuckerberg. (The Verge) 10 Instagram is the hottest place to shop for kids’ clothes 👕 Enterprising moms are on the hunt for bargains. (The Verge)+ The best part of Facebook these days is Facebook Marketplace. (The Atlantic $) Quote of the day “The mass confusion created by this constant news flow out of the White House is dizzying for the industry and investors and creating massive uncertainty and chaos for companies trying to plan their supply chain, inventory, and demand.”’ —Dan Ives, a senior analyst for Wedbush, sums up the latest twists and turns in the Trump administration’s tariff plans, the Washington Post reports. The big story Africa fights rising hunger by looking to foods of the past After falling steadily for decades, the prevalence of global hunger is now on the rise—nowhere more so than in sub-Saharan Africa.Conflicts, economic fallout from the covid-19 pandemic, and extreme weather events linked to climate change have pushed the share of the population considered undernourished from 18% in 2015 to 23% in 2023. Africa’s indigenous crops are often more nutritious and better suited to the hot and dry conditions that are becoming more prevalent, yet many have been neglected by science, which means they tend to be more vulnerable to diseases and pests and yield well below their theoretical potential. Now the question is whether researchers, governments, and farmers can work together in a way that gets these crops onto plates and provides Africans from all walks of life with the energy and nutrition that they need to thrive, whatever climate change throws their way. Read the full story. —Jonathan W. Rosen 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 or skeet 'em at me.)+ The Minecraft movie sounds like absolute chaos (in a good way)+ Huge congratulations are in order for Rory McIlroy, the first European to win golf’s Grand Slam.+ Mark my words, nothing good can come from a British version of SNL.+ Enjoy these gorgeous otter pups taking their very first swim with their patient mom 🦦

One day, in the near or far future, an asteroid about the length of a football stadium will find itself on a collision course with Earth. If we are lucky, it will land in the middle of the vast ocean, creating a good-size but innocuous tsunami, or in an uninhabited patch of desert. But if it has a city in its crosshairs, one of the worst natural disasters in modern times will unfold. As the asteroid steams through the atmosphere, it will begin to fragment—but the bulk of it will likely make it to the ground in just a few seconds, instantly turning anything solid into a fluid and excavating a huge impact crater in a heartbeat. A colossal blast wave, akin to one unleashed by a large nuclear weapon, will explode from the impact site in every direction. Homes dozens of miles away will fold like cardboard. Millions of people could die. Fortunately for all 8 billion of us, planetary defense—the science of preventing asteroid impacts—is a highly active field of research. Astronomers are watching the skies, constantly on the hunt for new near-Earth objects that might pose a threat. And others are actively working on developing ways to prevent a collision should we find an asteroid that seems likely to hit us. We already know that at least one method works: ramming the rock with an uncrewed spacecraft to push it away from Earth. In September 2022, NASA’s Double Asteroid Redirection Test, or DART, showed it could be done when a semiautonomous spacecraft the size of a small car, with solar panel wings, was smashed into an (innocuous) asteroid named Dimorphos at 14,000 miles per hour, successfully changing its orbit around a larger asteroid named Didymos.  But there are circumstances in which giving an asteroid a physical shove might not be enough to protect the planet. If that’s the case, we could need another method, one that is notoriously difficult to test in real life: a nuclear explosion.  Scientists have used computer simulations to explore this potential method of planetary defense. But in an ideal world, researchers would ground their models with cold, hard, practical data. Therein lies a challenge. Sending a nuclear weapon into space would violate international laws and risk inflaming political tensions. What’s more, it could do damage to Earth: A rocket malfunction could send radioactive debris into the atmosphere.  Over the last few years, however, scientists have started to devise some creative ways around this experimental limitation. The effort began in 2023, with a team of scientists led by Nathan Moore, a physicist and chemical engineer at the Sandia National Laboratories in Albuquerque, New Mexico. Sandia is a semi-secretive site that serves as the engineering arm of America’s nuclear weapons program. And within that complex lies the Z Pulsed Power Facility, or Z machine, a cylindrical metallic labyrinth of warning signs and wiring. It’s capable of summoning enough energy to melt diamond.  About 25,000 asteroids more than 460 feet long—a size range that starts with midsize “city killers” and goes up in impact from there—are thought to exist close to Earth. Just under half of them have been found. The researchers reckoned they could use the Z machine to re-create the x-ray blast of a nuclear weapon—the radiation that would be used to knock back an asteroid—on a very small and safe scale. It took a while to sort out the details. But by July 2023, Moore and his team were ready. They waited anxiously inside a control room, monitoring the thrumming contraption from afar. Inside the machine’s heart were two small pieces of rock, stand-ins for asteroids, and at the press of a button, a maelstrom of x-rays would thunder toward them. If they were knocked back by those x-rays, it would prove something that, until now, was purely theoretical: You can deflect an asteroid from Earth using a nuke. This experiment “had never been done before,” says Moore. But if it succeeded, its data would contribute to the safety of everyone on the planet. Would it work? Monoliths and rubble piles Asteroid impacts are a natural disaster like any other. You shouldn’t lose sleep over the prospect, but if we get unlucky, an errant space rock may rudely ring Earth’s doorbell. “The probability of an asteroid striking Earth during my lifetime is very small. But what if one did? What would we do about it?” says Moore. “I think that’s worth being curious about.” Forget about the gigantic asteroids you know from Hollywood blockbusters. Space rocks over two-thirds of a mile (about one kilometer) in diameter—those capable of imperiling civilization—are certainly out there, and some hew close to Earth’s own orbit. But because these asteroids are so elephantine, astronomers have found almost all of them already, and none pose an impact threat.  Rather, it’s asteroids a size range down—those upwards of 460 feet (140 meters) long—that are of paramount concern. About 25,000 of those are thought to exist close to our planet, and just under half have been found. The day-to-day odds of an impact are extremely low, but even one of the smaller ones in that size range could do significant damage if it found Earth and hit a populated area—a capacity that has led astronomers to dub such midsize asteroids “city killers.” If we find a city killer that looks likely to hit Earth, we’ll need a way to stop it. That could be technology to break or “disrupt” the asteroid into fragments that will either miss the planet entirely or harmlessly ignite in the atmosphere. Or it could be something that can deflect the asteroid, pushing it onto a path that will no longer intersect with our blue marble.  Because disruption could accidentally turn a big asteroid into multiple smaller, but still deadly, shards bound for Earth, it’s often considered to be a strategy of last resort. Deflection is seen as safer and more elegant. One way to achieve it is to deploy a spacecraft known as a kinetic impactor—a battering ram that collides with an asteroid and transfers its momentum to the rocky interloper, nudging it away from Earth. NASA’s DART mission demonstrated that this can work, but there are some important caveats: You need to deflect the asteroid years in advance to make sure it completely misses Earth, and asteroids that we spot too late—or that are too big—can’t be swatted away by just one DART-like mission. Instead, you’d need several kinetic impactors—maybe many of them—to hit one side of the asteroid perfectly each time in order to push it far enough to save our planet. That’s a tall order for orbital mechanics, and not something space agencies may be willing to gamble on.  In that case, the best option might instead be to detonate a nuclear weapon next to the asteroid. This would irradiate one hemisphere of the asteroid in x-rays, which in a few millionths of a second would violently shatter and vaporize the rocky surface. The stream of debris spewing out of that surface and into space would act like a rocket, pushing the asteroid in the opposite direction. “There are scenarios where kinetic impact is insufficient, and we’d have to use a nuclear explosive device,” says Moore. MCKIBILLO This idea isn’t new. Several decades ago, Peter Schultz, a planetary geologist and impacts expert at Brown University, was giving a planetary defense talk at the Lawrence Livermore National Laboratory in California, another American lab focused on nuclear deterrence and nuclear physics research. Afterwards, he recalls, none other than Edward Teller, the father of the hydrogen bomb and a key member of the Manhattan Project, invited him into his office for a chat. “He wanted to do one of these near-Earth-­asteroid flybys and wanted to test the nukes,” Schultz says. What, he wondered, would happen if you blasted an asteroid with a nuclear weapon’s x-rays? Could you forestall a spaceborne disaster using weapons of mass destruction? But Teller’s dream wasn’t fulfilled—and it’s unlikely to become a reality anytime soon. The United Nations’ 1967 Outer Space Treaty states that no nation can deploy or use nuclear weapons off-world (even if it’s not clear how long certain spacefaring nations will continue to adhere to that rule). Even raising the possibility of using nukes to defend the planet can be tricky. “There’re still many folks that don’t want to talk about it at all … even if that were the only option to prevent an impact,” says Megan Bruck Syal, a physicist and planetary defense researcher at Lawrence Livermore. Nuclear weapons have long been a sensitive subject, and with relations between several nuclear nations currently at a new nadir, anxiety over the subject is understandable.  But in the US, there are groups of scientists who “recognize that we have a special responsibility as a spacefaring nation and as a nuclear-­capable nation to look at this,” Syal says. “It isn’t our preference to use a nuclear explosive, of course. But we are still looking at it, in case it’s needed.” But how?  Mostly, researchers have turned to the virtual world, using supercomputers at various US laboratories to simulate the asteroid-­agitating physics of a nuclear blast. To put it mildly, “this is very hard,” says Mary Burkey, a physicist and planetary defense researcher at Lawrence Livermore. You cannot simply flick a switch on a computer and get immediate answers. “When a nuke goes off in space, there’s just x-ray light that’s coming out of it. It’s shining on the surface of your asteroid, and you’re tracking those little photons penetrating maybe a tiny little bit into the surface, and then somehow you have to take that micro­meter worth of resolution and then propagate it out onto something that might be on the order of hundreds of meters wide, watching that shock wave propagate and then watching fragments spin off into space. That’s four different problems.”  Mimicking the physics of x-ray rock annihilation with as much verisimilitude as possible is difficult work. But recent research using these high-fidelity simulations does suggest that nukes are an effective planetary defense tool for both disruption and deflection. The thing is, though, no two asteroids are alike; each is mechanically and geologically unique, meaning huge uncertainties remain. A more monolithic asteroid might respond in a straightforward way to a nuclear deflection campaign, whereas a rubble pile asteroid—a weakly bound fleet of boulders barely held together by their own gravity—might respond in a chaotic, uncontrollable way. Can you be sure the explosion wouldn’t accidentally shatter the asteroid, turning a cannonball into a hail of bullets still headed for Earth?  Simulations can go a long way toward answering these questions, but they remain virtual re-creations of reality, with built-in assumptions. “Our models are only as good as the physics that we understand and that we put into them,” says Angela Stickle, a hypervelocity impact physicist at the Johns Hopkins University Applied Physics Laboratory in Maryland. To make sure the simulations are reproducing the correct physics and delivering realistic data, physical experiments are needed to ground them. Every firing of the Z machine carries the energy of more than 1,000 lightning bolts, and each shot lasts a few millionths of a second. Researchers studying kinetic impactors can get that sort of real-world data. Along with DART, they can use specialized cannons—like the Vertical Gun Range at NASA’s Ames Research Center in California—to fire all sorts of projectiles at meteorites. In doing so, they can find out how tough or fragile asteroid shards can be, effectively reproducing a kinetic impact mission on a small scale.  Battle-testing nuke-based asteroid defense simulations is another matter. Re-creating the physics of these confrontations on a small scale was long considered to be exceedingly difficult. Fortunately, those keen on fighting asteroids are as persistent as they are creative—and several teams, including Moore’s at Sandia, think they have come up with a solution. X-ray scissors The prime mission of Sandia, like that of Lawrence Livermore, is to help maintain the nation’s nuclear weapons arsenal. “It’s a national security laboratory,” says Moore. “Planetary defense affects the entire planet,” he adds—making it, by default, a national security issue as well. And that logic, in part, persuaded the powers that be in July 2022 to try a brand-new kind of experiment. Moore took charge of the project in January 2023—and with the shot scheduled for the summer, he had only a few months to come up with the specific plan for the experiment. There was “lots of scribbling on my whiteboard, running computer simulations, and getting data to our engineers to design the test fixture for the several months it would take to get all the parts machined and assembled,” he says. Although there were previous and ongoing experiments that showered asteroid-like targets with x-rays, Moore and his team were frustrated by one aspect of them. Unlike actual asteroids floating freely in space, the micro-­asteroids on Earth were fixed in place. To truly test whether x-rays could deflect asteroids, targets would have to be suspended in a vacuum—and it wasn’t immediately clear how that could be achieved. Generating the nuke-like x-rays was the easy part, because Sandia had the Z machine, a hulking mass of diodes, pipes, and wires interwoven with an assortment of walkways that circumnavigate a vacuum chamber at its core. When it’s powered up, electrical currents are channeled into capacitors—and, when commanded, blast that energy at a target or substance to create radiation and intense magnetic pressures.  Flanked by klaxons and flashing lights, it’s an intimidating sight. “It’s the size of a building—about three stories tall,” says Moore. Every firing of the Z machine carries the energy of more than 1,000 lightning bolts, and each shot lasts a few millionths of a second: “You can’t even blink that fast.” The Z machine is named for the axis along which its energetic particles cascade, but the Z could easily stand for “Zeus.” The Z Pulsed Power Facility, or Z machine, at Sandia National Laboratories in Albuquerque, New Mexico, concentrates electricity into short bursts of intense energy that can be used to create x-rays and gamma rays and compress matter to high densities.RANDY MONTOYA/SANDIA NATIONAL LABORATORY The original purpose of the Z machine, whose first form was built half a century ago, was nuclear fusion research. But over time, it’s been tinkered with, upgraded, and used for all kinds of science. “The Z machine has been used to compress matter to the same densities [you’d find at] the centers of planets. And we can do experiments like that to better understand how planets form,” Moore says, as an example. And the machine’s preternatural energies could easily be used to generate x-rays—in this case, by electrifying and collapsing a cloud of argon gas. “The idea of studying asteroid deflection is completely different for us,” says Moore. And the machine “fires just once a day,” he adds, “so all the experiments are planned more than a year in advance.” In other words, the researchers had to be near certain their one experiment would work, or they would be in for a long wait to try again—if they were permitted a second attempt.  For some time, they could not figure out how to suspend their micro-asteroids. But eventually, they found a solution: Two incredibly thin bits of aluminum foil would hold their targets in place within the Z machine’s vacuum chamber. When the x-ray blast hit them and the targets, the pieces of foil would be instantly vaporized, briefly leaving the targets suspended in the chamber and allowing them to be pushed back as if they were in space. “It’s like you wave your magic wand and it’s gone,” Moore says of the foil. He dubbed this technique “x-ray scissors.”  In July 2023, after considerable planning, the team was ready. Within the Z machine’s vacuum chamber were two fingernail-size targets—a bit of quartz and some fused silica, both frequently found on real asteroids. Nearby, a pocket of argon gas swirled away. Satisfied that the gigantic gizmo was ready, everyone left and went to stand in the control room. For a moment, it was deathly quiet. Stand by. Fire. It was over before their ears could even register a metallic bang. A tempest of electricity shocked the argon gas cloud, causing it to implode; as it did, it transformed into a plasma and x-rays screamed out of it, racing toward the two targets in the chamber. The foil vanished, the surfaces of both targets erupted outward as supersonic sprays of debris, and the targets flew backward, away from the x-rays, at 160 miles per hour. Moore wasn’t there. “I was in Spain when the experiment was run, because I was celebrating my anniversary with my wife, and there was no way I was going to miss that,” he says. But just after the Z machine was fired, one of his colleagues sent him a very concise text: IT WORKED. “We knew right away it was a huge success,” says Moore. The implications were immediately clear. The experimental setup was complex, but they were trying to achieve something extremely fundamental: a real-world demonstration that a nuclear blast could make an object in space move. “We’re genuinely looking at this from the standpoint of ‘This is a technology that could save lives.’” Patrick King, a physicist at the Johns Hopkins University Applied Physics Laboratory, was impressed. Previously, pushing back objects using x-ray vaporization had been extremely difficult to demonstrate in the lab. “They were able to get a direct measurement of that momentum transfer,” he says, calling the x-ray scissors an “elegant” technique. Sandia’s work took many in the community by surprise. “The Z machine experiment was a bit of a newcomer for the planetary defense field,” says Burkey. But she notes that we can’t overinterpret the results. It isn’t clear, from the deflection of the very small and rudimentary asteroid-like targets, how much a genuine nuclear explosion would deflect an actual asteroid. As ever, more work is needed.  King leads a team that is also working on this question. His NASA-funded project involves the Omega Laser Facility, a complex based at the University of Rochester in upstate New York. Omega can generate x-rays by firing powerful lasers at a target within a specialized chamber. Upon being irradiated, the target generates an x-ray flash, similar to the one produced during a nuclear explosion in space, which can then be used to bombard various objects—in this case, some Earth rocks acting as asteroid mimics, and (crucially) some bona fide meteoritic material too.  King’s Omega experiments have tried to answer a basic question: “How much material actually gets removed from the surface?” says King. The amount of material that flies off the pseudo-asteroids, and the vigor with which it’s removed, will differ from target to target. The hope is that these results—which the team is still considering—will hint at how different types of asteroids will react to being nuked. Although experiments with Omega cannot produce the kickback seen in the Z machine, King’s team has used a more realistic and diverse series of targets and blasted them with x-rays hundreds of times. That, in turn, should clue us in to how effectively, or not, actual asteroids would be deflected by a nuclear explosion. “I wouldn’t say one [experiment] has definitive advantages over the other,” says King. “Like many things in science, each approach can yield insight along different ‘axes,’ if you will, and no experimental setup gives you the whole picture.” MCKIBILLO Experiments like Moore’s and King’s may sound technologically baroque—a bit like lightning-fast Rube Goldberg machines overseen by wizards. But they are likely the first in a long line of increasingly sophisticated tests. “We’ve just scratched the surface of what we can do,” Moore says. As with King’s experiments, Moore hopes to place a variety of materials in the Z machine, including targets that can stand in for the wetter, more fragile carbon-rich asteroids that astronomers commonly see in near-Earth space. “If we could get our hands on real asteroid material, we’d do it,” he says. And it’s expected that all this experimental data will be fed back into those nuke-versus-­asteroid computer simulations, helping to verify the virtual results. Although these experiments are perfectly safe, planetary defenders remain fully cognizant of the taboo around merely discussing the use of nukes for any reason—even if that reason is potentially saving the world. “We’re genuinely looking at this from the standpoint of ‘This is a technology that could save lives,’” King says. Inevitably, Earth will be imperiled by a dangerous asteroid. And the hope is that when that day arrives, it can be dealt with using something other than a nuke. But comfort should be taken from the fact that scientists are researching this scenario, just in case it’s our only protection against the firmament. “We are your taxpayer dollars at work,” says Burkey.  There’s still some way to go before they can be near certain that this asteroid-stopping technique will succeed. Their progress, though, belongs to everyone. “Ultimately,” says Moore, “we all win if we solve this problem.”  Robin George Andrews is an award-winning science journalist based in London and the author, most recently, of How to Kill an Asteroid: The Real Science of Planetary Defense.

In 2021, 20 years after the death of her older sister, Vauhini Vara was still unable to tell the story of her loss. “I wondered,” she writes in Searches, her new collection of essays on AI technology, “if Sam Altman’s machine could do it for me.” So she tried ChatGPT. But as it expanded on Vara’s prompts in sentences ranging from the stilted to the unsettling to the sublime, the thing she’d enlisted as a tool stopped seeming so mechanical.  “Once upon a time, she taught me to exist,” the AI model wrote of the young woman Vara had idolized. Vara, a journalist and novelist, called the resulting essay “Ghosts,” and in her opinion, the best lines didn’t come from her: “I found myself irresistibly attracted to GPT-3—to the way it offered, without judgment, to deliver words to a writer who has found herself at a loss for them … as I tried to write more honestly, the AI seemed to be doing the same.” The rapid proliferation of AI in our lives introduces new challenges around authorship, authenticity, and ethics in work and art. But it also offers a particularly human problem in narrative: How can we make sense of these machines, not just use them? And how do the words we choose and stories we tell about technology affect the role we allow it to take on (or even take over) in our creative lives? Both Vara’s book and The Uncanny Muse, a collection of essays on the history of art and automation by the music critic David Hajdu, explore how humans have historically and personally wrestled with the ways in which machines relate to our own bodies, brains, and creativity. At the same time, The Mind Electric, a new book by a neurologist, Pria Anand, reminds us that our own inner workings may not be so easy to replicate. Searches is a strange artifact. Part memoir, part critical analysis, and part AI-assisted creative experimentation, Vara’s essays trace her time as a tech reporter and then novelist in the San Francisco Bay Area alongside the history of the industry she watched grow up. Tech was always close enough to touch: One college friend was an early Google employee, and when Vara started reporting on Facebook (now Meta), she and Mark Zuckerberg became “friends” on his platform. In 2007, she published a scoop that the company was planning to introduce ad targeting based on users’ personal information—the first shot fired in the long, gnarly data war to come. In her essay “Stealing Great Ideas,” she talks about turning down a job reporting on Apple to go to graduate school for fiction. There, she wrote a novel about a tech founder, which was later published as The Immortal King Rao. Vara points out that in some ways at the time, her art was “inextricable from the resources [she] used to create it”—products like Google Docs, a MacBook, an iPhone. But these pre-AI resources were tools, plain and simple. What came next was different. Interspersed with Vara’s essays are chapters of back-and-forths between the author and ChatGPT about the book itself, where the bot serves as editor at Vara’s prompting. ChatGPT obligingly summarizes and critiques her writing in a corporate-­shaded tone that’s now familiar to any knowledge worker. “If there’s a place for disagreement,” it offers about the first few chapters on tech companies, “it might be in the balance of these narratives. Some might argue that the ­benefits—such as job creation, innovation in various sectors like AI and logistics, and contributions to the global economy—can outweigh the negatives.”  Searches: Selfhood in the Digital AgeVauhini VaraPANTHEON, 2025 Vara notices that ChatGPT writes “we” and “our” in these responses, pulling it into the human story, not the tech one: “Earlier you mentioned ‘our access to information’ and ‘our collective experiences and understandings.’” When she asks what the rhetorical purpose of that choice is, ChatGPT responds with a numbered list of benefits including “inclusivity and solidarity” and “neutrality and objectivity.” It adds that “using the first-person plural helps to frame the discussion in terms of shared human experiences and collective challenges.” Does the bot believe it’s human? Or at least, do the humans who made it want other humans to believe it does? “Can corporations use these [rhetorical] tools in their products too, to subtly make people identify with, and not in opposition to, them?” Vara asks. ChatGPT replies, “Absolutely.” Vara has concerns about the words she’s used as well. In “Thank You for Your Important Work,” she worries about the impact of “Ghosts,” which went viral after it was first published. Had her writing helped corporations hide the reality of AI behind a velvet curtain? She’d meant to offer a nuanced “provocation,” exploring how uncanny generative AI can be. But instead, she’d produced something beautiful enough to resonate as an ad for its creative potential. Even Vara herself felt fooled. She particularly loved one passage the bot wrote, about Vara and her sister as kids holding hands on a long drive. But she couldn’t imagine either of them being so sentimental. What Vara had elicited from the machine, she realized, was “wish fulfillment,” not a haunting.  The rapid proliferation of AI in our lives introduces new challenges around authorship, authenticity, and ethics in work and art. How can we make sense of these machines, not just use them?  The machine wasn’t the only thing crouching behind that too-good-to-be-true curtain. The GPT models and others are trained through human labor, in sometimes exploitative conditions. And much of the training data was the creative work of human writers before her. “I’d conjured artificial language about grief through the extraction of real human beings’ language about grief,” she writes. The creative ghosts in the model were made of code, yes, but also, ultimately, made of people. Maybe Vara’s essay helped cover up that truth too. In the book’s final essay, Vara offers a mirror image of those AI call-and-­response exchanges as an antidote. After sending out an anonymous survey to women of various ages, she presents the replies to each question, one after the other. “Describe something that doesn’t exist,” she prompts, and the women respond: “God.” “God.” “God.” “Perfection.” “My job. (Lost it.)” Real people contradict each other, joke, yell, mourn, and reminisce. Instead of a single authoritative voice—an editor, or a company’s limited style guide—Vara gives us the full gasping crowd of human creativity. “What’s it like to be alive?” Vara asks the group. “It depends,” one woman answers.     David Hajdu, now music editor at The Nation and previously a music critic for The New Republic, goes back much further than the early years of Facebook to tell the history of how humans have made and used machines to express ourselves. Player pianos, microphones, synthesizers, and electrical instruments were all assistive technologies that faced skepticism before acceptance and, sometimes, elevation in music and popular culture. They even influenced the kind of art people were able to and wanted to make. Electrical amplification, for instance, allowed singers to use a wider vocal range and still reach an audience. The synthesizer introduced a new lexicon of sound to rock music. “What’s so bad about being mechanical, anyway?” Hajdu asks in The Uncanny Muse. And “what’s so great about being human?”  The Uncanny Muse: Music, Art, and Machines from Automata to AIDavid HajduW.W. NORTON & COMPANY, 2025 But Hajdu is also interested in how intertwined the history of man and machine can be, and how often we’ve used one as a metaphor for the other. Descartes saw the body as empty machinery for consciousness, he reminds us. Hobbes wrote that “life is but a motion of limbs.” Freud described the mind as a steam engine. Andy Warhol told an interviewer that “everybody should be a machine.” And when computers entered the scene, humans used them as metaphors for themselves too. “Where the machine model had once helped us understand the human body … a new category of machines led us to imagine the brain (how we think, what we know, even how we feel or how we think about what we feel) in terms of the computer,” Hajdu writes.  But what is lost with these one-to-one mappings? What happens when we imagine that the complexity of the brain—an organ we do not even come close to fully understanding—can be replicated in 1s and 0s? Maybe what happens is we get a world full of chatbots and agents, computer-­generated artworks and AI DJs, that companies claim are singular creative voices rather than remixes of a million human inputs. And perhaps we also get projects like the painfully named Painting Fool—an AI that paints, developed by Simon Colton, a scholar at Queen Mary University of London. He told Hajdu that he wanted to “demonstrate the potential of a computer program to be taken seriously as a creative artist in its own right.” What Colton means is not just a machine that makes art but one that expresses its own worldview: “Art that communicates what it’s like to be a machine.”   What happens when we imagine that the complexity of the brain—an organ we do not even come close to fully understanding—can be replicated in 1s and 0s? Hajdu seems to be curious and optimistic about this line of inquiry. “Machines of many kinds have been communicating things for ages, playing invaluable roles in our communication through art,” he says. “Growing in intelligence, machines may still have more to communicate, if we let them.” But the question that The Uncanny Muse raises at the end is: Why should we art-­making humans be so quick to hand over the paint to the paintbrush? Why do we care how the paintbrush sees the world? Are we truly finished telling our own stories ourselves? Pria Anand might say no. In The Mind Electric, she writes: “Narrative is universally, spectacularly human; it is as unconscious as breathing, as essential as sleep, as comforting as familiarity. It has the capacity to bind us, but also to other, to lay bare, but also obscure.” The electricity in The Mind Electric belongs entirely to the human brain—no metaphor necessary. Instead, the book explores a number of neurological afflictions and the stories patients and doctors tell to better understand them. “The truth of our bodies and minds is as strange as fiction,” Anand writes—and the language she uses throughout the book is as evocative as that in any novel.  The Mind Electric: A Neurologist on the Strangeness and Wonder of Our BrainsPria AnandWASHINGTON SQUARE PRESS, 2025 In personal and deeply researched vignettes in the tradition of Oliver Sacks, Anand shows that any comparison between brains and machines will inevitably fall flat. She tells of patients who see clear images when they’re functionally blind, invent entire backstories when they’ve lost a memory, break along seams that few can find, and—yes—see and hear ghosts. In fact, Anand cites one study of 375 college students in which researchers found that nearly three-quarters “had heard a voice that no one else could hear.” These were not diagnosed schizophrenics or sufferers of brain tumors—just people listening to their own uncanny muses. Many heard their name, others heard God, and some could make out the voice of a loved one who’d passed on. Anand suggests that writers throughout history have harnessed organic exchanges with these internal apparitions to make art. “I see myself taking the breath of these voices in my sails,” Virginia Woolf wrote of her own experiences with ghostly sounds. “I am a porous vessel afloat on sensation.” The mind in The Mind Electric is vast, mysterious, and populated. The narratives people construct to traverse it are just as full of wonder.  Humans are not going to stop using technology to help us create anytime soon—and there’s no reason we should. Machines make for wonderful tools, as they always have. But when we turn the tools themselves into artists and storytellers, brains and bodies, magicians and ghosts, we bypass truth for wish fulfillment. Maybe what’s worse, we rob ourselves of the opportunity to contribute our own voices to the lively and loud chorus of human experience. And we keep others from the human pleasure of hearing them too.  Rebecca Ackermann is a writer, designer, and artist based in San Francisco.

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. Generative AI is learning to spy for the US military For much of last year, US Marines conducting training exercises in the waters off South Korea, the Philippines, India, and Indonesia were also running an experiment. The service members in the unit responsible for sorting through foreign intelligence and making their superiors aware of possible local threats were for the first time using generative AI to do it, testing a leading AI tool the Pentagon has been funding. Two officers tell us that they used the new system to help scour thousands of pieces of open-source intelligence—nonclassified articles, reports, images, videos—collected in the various countries where they operated, and that it did so far faster than was possible with the old method of analyzing them manually. Though the US military has been developing computer vision models and similar AI tools since 2017, the use of generative AI—tools that can engage in human-like conversation—represent a newer frontier.Read the full story. —James O'Donnell Why the climate promises of AI sound a lot like carbon offsets  The International Energy Agency states in a new report that AI could eventually reduce greenhouse-gas emissions, possibly by much more than the boom in energy-guzzling data center development pushes them up. The finding echoes a point that prominent figures in the AI sector have made as well to justify, at least implicitly, the gigawatts’ worth of electricity demand that new data centers are placing on regional grid systems across the world. There’s something familiar about the suggestion that it’s okay to build data centers that run on fossil fuels today because AI tools will help the world drive down emissions eventually—it recalls the purported promise of carbon credits. Unfortunately, we’ve seen again and again that such programs often overstate any climate benefits, doing little to alter the balance of what’s going into or coming out of the atmosphere. Read the full story.  —James Temple The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 MAGA influencers are downplaying Trump’s market turmoil They’re finding creative ways to frame the financial tumult as character building. (WP $)+ Some democrats are echoing his trade myths, too. (Vox)2 Amazon products are going to cost moreCEO Andy Jassy says he anticipates third party sellers passing the costs introduced by tariffs on to their customers. (CNBC) + He says the company has been renegotiating terms with sellers. (CNN)3 OpenAI has slashed its model safety testing time Which experts worry will mean it rushes out models without sufficient safeguarding. (FT $)+ Why we need an AI safety hotline. (MIT Technology Review) 4 A woman gave birth to a stranger’s baby in an IVF mixup Monash IVF transferred another woman’s embryo to her by accident. (The Guardian)+ Inside the strange limbo facing millions of IVF embryos. (MIT Technology Review)5 Amazon equipped some of its delivery vans in Europe with defibrillators  In an experiment to see if drivers could speed up help to heart attack patients. (Bloomberg $)6 The future of biotech is looking shakyRFK Jr’s appointment and soaring interest rates are rocking an already volatile industry. (WSJ $) + Meanwhile, RFK Jr has visited the families of two girls who died from measles. (The Atlantic $)7 Alexandre de Moraes isn’t backing downThe Brazilian judge, who has butted heads with Elon Musk, is worried about extremist digital populism. (New Yorker $) 8 An experimental pill mimics the effects of gastric bypass surgeryAnd could be touted as an alternative to weight-loss drugs. (Wired $) + Drugs like Ozempic now make up 5% of prescriptions in the US. (MIT Technology Review)9 What happens when video games start bleeding into the real world Game Transfer Phenomenon is a real thing, and nowhere near as fun as it sounds. (BBC)+ How generative AI could reinvent what it means to play. (MIT Technology Review) 10 Londoners smashed up a Tesla in a public art project  The car was provided by an anonymous donor. (The Guardian)+ Proceeds from the installation will go to food banks in the UK. (The Standard) Quote of the day “It feels so good to be surrounded by a bunch of people who disconnected.” —Steven Vernon III, who works in finance, describes the beauties of a digital detox at the Masters in Augusta, Georgia as the markets descend into chaos, the Wall Street Journal reports. The big story This scientist is trying to create an accessible, unhackable voting machine For the past 19 years, computer science professor Juan Gilbert has immersed himself in perhaps the most contentious debate over election administration in the United States—what role, if any, touch-screen ballot-marking devices should play in the voting process.While advocates claim that electronic voting systems can be relatively secure, improve accessibility, and simplify voting and vote tallying, critics have argued that they are insecure and should be used as infrequently as possible.As for Gilbert? He claims he’s finally invented “the most secure voting technology ever created.” And he’s invited several of the most respected and vocal critics of voting technology to prove his point. Read the full story.—Spenser Mestel 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 or skeet 'em at me.) + Bad news for hoodie lovers: your favorite comfy item of clothing is no longer cutting the mustard.+ What happens inside Black Holes? A lot more than you might think.+ Unfortunately, pushups are as beneficial for you as they are horrible to execute.+ Very cool—archaeologists are making new discoveries in Pompeii.

For much of last year, about 2,500 US service members from the 15th Marine Expeditionary Unit sailed aboard three ships throughout the Pacific, conducting training exercises in the waters off South Korea, the Philippines, India, and Indonesia. At the same time, onboard the ships, an experiment was unfolding: The Marines in the unit responsible for sorting through foreign intelligence and making their superiors aware of possible local threats were for the first time using generative AI to do it, testing a leading AI tool the Pentagon has been funding. Two officers tell us that they used the new system to help scour thousands of pieces of open-source intelligence—nonclassified articles, reports, images, videos—collected in the various countries where they operated, and that it did so far faster than was possible with the old method of analyzing them manually. Captain Kristin Enzenauer, for instance, says she used large language models to translate and summarize foreign news sources, while Captain Will Lowdon used AI to help write the daily and weekly intelligence reports he provided to his commanders.  “We still need to validate the sources,” says Lowdon. But the unit’s commanders encouraged the use of large language models, he says, “because they provide a lot more efficiency during a dynamic situation.” The generative AI tools they used were built by the defense-tech company Vannevar Labs, which in November was granted a production contract worth up to $99 million by the Pentagon’s startup-oriented Defense Innovation Unit with the goal of bringing its intelligence tech to more military units. The company, founded in 2019 by veterans of the CIA and US intelligence community, joins the likes of Palantir, Anduril, and Scale AI as a major beneficiary of the US military’s embrace of artificial intelligence—not only for physical technologies like drones and autonomous vehicles but also for software that is revolutionizing how the Pentagon collects, manages, and interprets data for warfare and surveillance.  Though the US military has been developing computer vision models and similar AI tools, like those used in Project Maven, since 2017, the use of generative AI—tools that can engage in human-like conversation like those built by Vannevar Labs—represent a newer frontier. The company applies existing large language models, including some from OpenAI and Microsoft, and some bespoke ones of its own to troves of open-source intelligence the company has been collecting since 2021. The scale at which this data is collected is hard to comprehend (and a large part of what sets Vannevar’s products apart): terabytes of data in 80 different languages are hoovered every day in 180 countries. The company says it is able to analyze social media profiles and breach firewalls in countries like China to get hard-to-access information; it also uses nonclassified data that is difficult to get online (gathered by human operatives on the ground), as well as reports from physical sensors that covertly monitor radio waves to detect illegal shipping activities.  Vannevar then builds AI models to translate information, detect threats, and analyze political sentiment, with the results delivered through a chatbot interface that’s not unlike ChatGPT. The aim is to provide customers with critical information on topics as varied as international fentanyl supply chains and China’s efforts to secure rare earth minerals in the Philippines.  “Our real focus as a company,” says Scott Philips, Vannevar Labs’ chief technology officer, is to “collect data, make sense of that data, and help the US make good decisions.”  That approach is particularly appealing to the US intelligence apparatus because for years the world has been awash in more data than human analysts can possibly interpret—a problem that contributed to the 2003 founding of Palantir, a company now worth nearly $217 billion and known for its powerful and controversial tools, including a database that helps Immigration and Customs Enforcement search for and track information on undocumented immigrants.  In 2019, Vannevar saw an opportunity to use large language models, which were then new on the scene, as a novel solution to the data conundrum. The technology could enable AI not just to collect data but to actually talk through an analysis with someone interactively. Vannevar’s tools proved useful for the deployment in the Pacific, and Enzenauer and Lowdon say that while they were instructed to always double-check the AI’s work, they didn't find inaccuracies to be a significant issue. Enzenauer regularly used the tool to track any foreign news reports in which the unit’s exercises were mentioned and to perform sentiment analysis, detecting the emotions and opinions expressed in text. Judging whether a foreign news article reflects a threatening or friendly opinion toward the unit is a task that on previous deployments she had to do manually. “It was mostly by hand—researching, translating, coding, and analyzing the data,” she says. “It was definitely way more time-consuming than it was when using the AI.”  Still, Enzenauer and Lowdon say there were hiccups, some of which would affect most digital tools: The ships had spotty internet connections much of the time, limiting how quickly the AI model could synthesize foreign intelligence, especially if it involved photos or video.  With this first test completed, the unit’s commanding officer, Colonel Sean Dynan, said on a call with reporters in February that heavier use of generative AI was coming; this experiment was “the tip of the iceberg.”  This is indeed the direction that the entire US military is barreling toward at full speed. In December, the Pentagon said it will spend $100 million in the next two years on pilots specifically for generative AI applications. In addition to Vannevar, it’s also turning to Microsoft and Palantir, which are working together on AI models that would make use of classified data. (The US is of course not alone in this approach; notably, Israel has been using AI to sort through information and even generate lists of targets in its war in Gaza, a practice that has been widely criticized.) Perhaps unsurprisingly, plenty of people outside the Pentagon are warning about the potential risks of this plan, including Heidy Khlaaf, who is chief AI scientist at the AI Now Institute, a research organization, and has expertise in leading safety audits for AI-powered systems. She says this rush to incorporate generative AI into military decision-making ignores more foundational flaws of the technology: “We’re already aware of how LLMs are highly inaccurate, especially in the context of safety-critical applications that require precision.”  One particular use case that concerns her is sentiment analysis, which she argues is “a highly subjective metric that even humans would struggle to appropriately assess based on media alone.”  If AI perceives hostility toward US forces where a human analyst would not—or if the system misses hostility that is really there—the military could make an misinformed decision or escalate a situation unnecessarily. Sentiment analysis is indeed a task that AI has not perfected. Philips, the Vannevar CTO, says the company has built models specifically to judge whether an article is pro-US or not, but MIT Technology Review was not able to evaluate them.  Chris Mouton, a senior engineer for RAND, recently tested how well-suited generative AI is for the task. He evaluated leading models, including OpenAI’s GPT-4 and an older version of GPT fine-tuned to do such intelligence work, on how accurately they flagged foreign content as propaganda compared with human experts. “It’s hard,” he says, noting that AI struggled to identify more subtle types of propaganda. But he adds that the models could still be useful in lots of other analysis tasks.  Another limitation of Vannevar’s approach, Khlaaf says, is that the usefulness of open-source intelligence is debatable. Mouton says that open-source data can be “pretty extraordinary,” but Khlaaf points out that unlike classified intel gathered through reconnaissance or wiretaps, it is exposed to the open internet—making it far more susceptible to misinformation campaigns, bot networks, and deliberate manipulation, as the US Army has warned. For Mouton, the biggest open question now is whether these generative AI technologies will be simply one investigatory tool among many that analysts use—or whether they’ll produce the subjective analysis that’s relied upon and trusted in decision-making. “This is the central debate,” he says.  What everyone agrees is that AI models are accessible—you can just ask them a question about complex pieces of intelligence, and they’ll respond in plain language. But it’s still in dispute what imperfections will be acceptable in the name of efficiency. 

1. Sophie and Martin are at the 2012 Gordon Research Conference on the Biology of Aging in Ventura, California. It is a foggy February weekend. Both are disappointed about how little sun there is on the California beach. They are two graduate students—Sophie in her sixth and final year, Martin in his fourth—who have traveled from different East Coast cities to present posters on their work. Martin’s shows health data collected from supercentenarians compared with the general Medicare population, capturing the diseases that are less and more common in the populations. Sophie is presenting on her recently accepted first-author paper in Aging Cell on two specific genes that, when activated, extend lifespan in C. elegans roundworms, the model organism of her research.  2. Sophie walks by Martin’s poster after she is done presenting her own. She is not immediately impressed by his work. It is not published, for one thing. But she sees how it is attention-grabbing and relevant, even necessary. He has a little crowd listening to him. He notices her—a frowning girl—standing in the back and begins to talk louder, hoping she hears. “Supercentenarians are much less likely to have seven diseases,” he says, pointing to his poster. “Alzheimer’s, heart failure, diabetes, depression, prostate cancer, hip fracture, and chronic kidney disease. Though they have higher instances of four diseases, which are arthritis, cataracts, osteoporosis, and glaucoma. These aren’t linked to mortality, but they do affect quality of life.” What stands out to Sophie is the confidence in Martin’s voice, despite the unsurprising nature of the findings. She admires that sound, its sturdiness. She makes note of his name and plans to seek him out.  3. They find one another in the hotel bar among other graduate students. The students are talking about the logistics of their futures: Who is going for a postdoc, who will opt for industry, do any have job offers already, where will their research have the most impact, is it worth spending years working toward something so uncertain? They stay up too late, dissecting journal articles they’ve read as if they were debating politics. They enjoy the freedom away from their labs and PIs.  Martin says, again with that confidence, that he will become a professor. Sophie says she likely won’t go down that path. She has received an offer to start as a scientist at an aging research startup called Abyssinian Bio, after she defends. Martin says, “Wouldn’t your work make more sense in an academic setting, where you have more freedom and power over what you do?” She says, “But that could be years from now and I want to start my real life, so …”  4-18. Martin is enamored with Sophie. She is not only brilliant; she is helpful. She strengthens his papers with precise edits and grounds his arguments with stronger evidence. Sophie is enamored with Martin. He is not only ambitious; he is supportive and adventurous. He encourages her to try new activities and tools, both in and out of work, like learning to ride a motorcycle or using CRISPR. Martin visits Sophie in San Francisco whenever he can, which amounts to a weekend or two every other month. After two years, their long-distance relationship is taking its toll. They want more weekends, more months, more everything together. They make plans for him to get a postdoc near her, but after multiple rejections from the labs where he most wants to work, his resentment toward academia grows.  “They don’t see the value of my work,” he says. 19. “Join Abyssinian,” Sophie offers. The company is growing. They want more researchers with data science backgrounds. He takes the job, drawn more by their future together than by the science. 20-35. For a long time, they are happy. They marry. They do their research. They travel. Sophie visits Martin’s extended family in France. Martin goes with Sophie to her cousin’s wedding in Taipei. They get a dog. The dog dies. They are both devastated but increasingly motivated to better understand the mechanisms of aging. Maybe their next dog will have the opportunity to live longer. They do not get a next dog. Sophie moves up at Abyssinian. Despite being in industry, her work is published in well-respected journals. She collaborates well with her colleagues. Eventually, she is promoted to executive director of research.  Martin stalls at the rank of principal scientist, and though Sophie is technically his boss—or his boss’s boss—he genuinely doesn’t mind when others call him “Dr. Sophie Xie’s husband.” 40. At dinner on his 35th birthday, a friend jokes that Martin is now middle-aged. Sophie laughs and agrees, though she is older than Martin. Martin joins in the laughter, but this small comment unlocks a sense of urgency inside him. What once felt hypothetical—his own death, the death of his wife—now appears very close. He can feel his wrinkles forming.   First come the subtle shifts in how he talks about his research and Abyssinian’s work. He wants to “defeat” and “obliterate” aging, which he comes to describe as humankind’s “greatest adversary.”  43. He begins taking supplements touted by tech influencers. He goes on a calorie-restricted diet. He gets weekly vitamin IV sessions. He looks into blood transfusions from young donors, but Sophie tells him to stop with all the fake science. She says he’s being ridiculous, that what he’s doing could be dangerous.   Martin, for the first time, sees Sophie differently. Not without love, but love burdened by an opposing weight, what others might recognize as resentment. Sophie is dedicated to the demands of her growing department. Martin thinks she is not taking the task of living longer seriously enough. He does not want her to die. He does not want to die.  Nobody at Abyssinian is taking the task of living longer seriously enough. Of all the aging bio startups he could have ended up at, how has he ended up at one with such modest—no, lazy—goals? He begins publicly dismissing basic research as “too slow” and “too limited,” which offends many of his and Sophie’s colleagues.  Sophie defends him, says he is still doing good work, despite the evidence. She is busy, traveling often for conferences, and mistakenly misclassifies the changes in Martin’s attitude as temporary outliers. 44. One day, during a meeting, Martin says to Jerry, a well-­respected scientist at Abyssinian and in the electron microscopy imaging community at large, that EM is an outdated, old, crusty technology. Martin says it is stupid to use it when there are more advanced, cutting-edge methods, like cryo-EM and super-resolution microscopy. Martin has always been outspoken, but this instance veers into rudeness.  At home, Martin and Sophie argue. Initially, they argue about whether tools of the past can be useful to their work. Then the argument morphs. What is the true purpose of their research? Martin says it’s called anti-aging research for a reason: It’s to defy aging! Sophie says she’s never called her work anti-aging research; she calls it aging research or research into the biology of aging. And Abyssinian’s overarching mission is more simply to find druggable targets for chronic and age-related diseases. Occasionally, the company’s marketing arm will push out messaging about extending the human lifespan by 20 years, but that has nothing to do with scientists like them in R&D. Martin seethes. Only 20 years! What about hundreds? Thousands?  45-49. They continue to argue and the arguments are roundabout, typically ending with Sophie crying, absconding to her sister’s house, and the two of them not speaking for short periods of time. 50. What hurts Sophie most is Martin’s persistent dismissal of death as merely an engineering problem to be solved. Sophie thinks of the ways the C. elegans she observes regulate their lifespans in response to environmental stress. The complex dance of genes and proteins that orchestrates their aging process. In the previous month’s experiment, a seemingly simple mutation produced unexpected effects across three generations of worms. Nature’s complexity still humbles her daily. There is still so much unknown.  Martin is at the kitchen counter, methodically crushing his evening supplements into powder. “I’m trying to save humanity. And all you want to do is sit in the lab to watch worms die.” 50. Martin blames the past. He realizes he should have tried harder to become a professor. Let Sophie make the industry money—he could have had academic clout. Professor Warwick. It would have had a nice sound to it. To his dismay, everyone in his lab calls him Martin. Abyssinian has a first-name policy. Something about flat hierarchies making for better collaboration. Good ideas could come from anyone, even a lowly, unintelligent senior associate scientist in Martin’s lab who barely understands how to process a data set. A great idea could come from anyone at all—except him, apparently. Sophie has made that clear. 51-59. They live in a tenuous peace for some time, perfecting the art of careful scheduling: separate coffee times, meetings avoided, short conversations that stick to the day-to-day facts of their lives. 60. Then Martin stands up to interrupt a presentation by the VP of research to announce that studying natural aging is pointless since they will soon eliminate it entirely. While Jerry may have shrugged off Martin’s aggressiveness, the VP does not. This leads to a blowout fight between Martin and many of his colleagues, in which Martin refuses to apologize and calls them all shortsighted idiots.  Sophie watches with a mixture of fear and awe. Martin thinks: Can’t she, my wife, just side with me this once?  61. Back at home: Martin at the kitchen counter, methodically crushing his evening supplements into powder. “I’m trying to save humanity.” He taps the powder into his protein shake with the precision of a scientist measuring reagents. “And all you want to do is sit in the lab to watch worms die.” Sophie observes his familiar movements, now foreign in their desperation. The kitchen light catches the silver spreading at his temples and on his chin—the very evidence of aging he is trying so hard to erase. “That’s not true,” she says. Martin gulps down his shake. “What about us? What about children?” Martin coughs, then laughs, a sound that makes Sophie flinch. “Why would we have children now? You certainly don’t have the time. But if we solve aging, which I believe we can, we’d have all the time in the world.” “We used to talk about starting a family.” “Any children we have should be born into a world where we already know they never have to die.” “We could both make the time. I want to grow old together—” All Martin hears are promises that lead to nothing, nowhere.   “You want us to deteriorate? To watch each other decay?” “I want a real life.” “So you’re choosing death. You’re choosing limitation. Mediocrity.” 64. Martin doesn’t hear from his wife for four days, despite texting her 16 times—12 too many, by his count. He finally breaks down enough to call her in the evening, after a couple of glasses of aged whisky (a gift from a former colleague, which Martin has rarely touched and kept hidden in the far back of a desk drawer).  Voicemail. And after this morning’s text, still no glimmering ellipsis bubble to indicate Sophie’s typing.  66. Forget her, he thinks, leaning back in his Steelcase chair, adjusted specifically for his long runner’s legs and shorter­-than-average torso. At 39, Martin’s spreadsheets of vitals now show an upward trajectory; proof of his ability to reverse his biological age. Sophie does not appreciate this. He stares out his office window, down at the employees crawling around Abyssinian Bio’s main quad. How small, he thinks. How significantly unaware of the future’s true possibilities. Sophie is like them.  67. Forget her, he thinks again as he turns down a bay toward Robert, one of his struggling postdocs, who is sitting at his bench staring at his laptop. As Martin approaches, Robert minimizes several windows, leaving only his home screen behind. “Where are you at with the NAD+ data?” Martin asks. Robert shifts in his chair to face Martin. The skin of his neck grows red and splotchy. Martin stares at it in disgust. “Well?” he asks again.  “Oh, I was told not to work on that anymore?” The boy has a tendency to speak in the lilt of questions.  “By who?” Martin demands. “Uh, Sophie?”  “I see. Well, I expect new data by end of day.”  “Oh, but—” Martin narrows his eyes. The red splotches on Robert’s neck grow larger.  “Um, okay,” the boy says, returning his focus to the computer.  Martin decides a response is called for … 70. Immortality Promise I am immortal. This doesn’t make me special. In fact, most people on Earth are immortal. I am 6,000 years old. Now, 6,000 years of existence give one a certain perspective. I remember back when genetic engineering and knowledge about the processes behind aging were still in their infancy. Oh, how people argued and protested. “It’s unethical!” “We’ll kill the Earth if there’s no death!” “Immortal people won’t be motivated to do anything! We’ll become a useless civilization living under our AI overlords!”  I believed back then, and now I know. Their concerns had no ground to stand on. Eternal life isn’t even remarkable anymore, but being among its architects and early believers still garners respect from the world. The elegance of my team’s solution continues to fill me with pride. We didn’t just halt aging; we mastered it. My cellular machinery hums with an efficiency that would make evolution herself jealous. Those early protesters—bless their mortal, no-longer-­beating hearts—never grasped the biological imperative of what we were doing. Nature had already created functionally immortal organisms—the hydra, certain jellyfish species, even some plants. We simply perfected what evolution had sketched out. The supposed ethical concerns melted away once people understood that we weren’t defying nature. We were fulfilling its potential. Today, those who did not want to be immortal aren’t around. Simple as that. Those who are here do care about the planet more than ever! There are almost no diseases, and we’re all very productive people. Young adults—or should I say young-looking adults—are naturally restless and energetic. And with all this life, you have the added benefit of not wasting your time on a career you might hate! You get to try different things and find out what you’re really good at and where you’re appreciated! Life is not short! Resources are plentiful! Of course, biological immortality doesn’t equal invincibility. People still die. Just not very often. My colleagues in materials science developed our modern protective exoskeletons. They’re elegant solutions, though I prefer to rely on my enhanced reflexes and reinforced skeletal structure most days.  The population concerns proved mathematically unfounded. Stable reproduction rates emerged naturally once people realized they had unlimited time to start families. I’ve had four sets of children across 6,000 years, each born when I felt truly ready to pass on another iteration of my accumulated knowledge. With more life, people have much more patience.  Now we are on to bigger and more ambitious projects. We conquered survival of individuals. The next step: survival of our species in this universe. The sun’s eventual death poses an interesting challenge, but nothing we can’t handle. We have colonized five planets and two moons in our solar system, and we will colonize more. Humanity will adapt to whatever environment we encounter. That’s what we do. My ancient motorcycle remains my favorite indulgence. I love taking it for long cruises on the old Earth roads that remain intact. The neural interface is state-of-the-art, of course. But mostly I keep it because it reminds me of earlier times, when we thought death was inevitable and life was limited to a single planet. The future stretches out before us like an infinity I helped create—yet another masterpiece in the eternal gallery of human evolution. 71. Martin feels better after writing it out. He rereads it a couple times, feels even better. Then he has the idea to send his writing to the department administrator. He asks her to create a new tab on his lab page, titled “Immortality Promise,” and to post his piece there. That will get his message across to Sophie and everyone at Abyssinian.  72. Sophie’s boss, Ray, is the first to email her. The subject line: “martn” [sic]. No further words in the body. Ray is known to be short and blunt in all his communications, but his meaning is always clear. They’ve had enough conversations about Martin by then. She is already in the process of slowly shutting down his projects, has been ignoring his texts and calls because of this. Now she has to move even faster.  73. Sophie leaves her office and goes into the lab. As an executive, she is not expected to do experiments, but watching a thousand tiny worms crawl across their agar plates soothes her. Each of the ones she now looks at carries a fluorescent marker she designed to track mitochondrial dynamics during aging. The green glow pulses with their movements, like stars blinking in a microscopic galaxy. She spent years developing this strain of C. elegans, carefully selecting for longevity without sacrificing health. The worms that lived longest weren’t always the healthiest—a truth about aging that seemed to elude Martin. Those worms taught her more about the genuine complexity of aging. Just last week, she observed something unexpected: The mitochondrial networks in her long-lived strains showed subtle patterns of reorganization never documented before. The discovery felt intimate, like being trusted with a secret. “How are things looking?” Jerry appears beside her. “That new strain expressing the dual markers?” Sophie nods, adjusting the focus. “Look at this network pattern. It’s different from anything in the literature.” She shifts aside so Jerry can see. This is what she loves about science: the genuine puzzles, the patient observation, the slow accumulation of knowledge that, while far removed from a specific application, could someday help people age with dignity. “Beautiful,” Jerry murmurs. He straightens. “I heard about Martin’s … post.” Sophie closes her eyes for a moment, the image of the mitochondrial networks still floating in her vision. She’s read Martin’s “Immortality Promise” piece three times, each more painful than the last. Not because of its grandiose claims—those were comically disconnected from reality—but because of what it’s revealed about her husband. The writing pulsed with a frightening certainty, a complete absence of doubt or wonder. Gone was the scientist who once spent many lively evenings debating with her about the evolutionary purpose of aging, who delighted in being proved wrong because it meant learning something new.  74. She sees in his words a man who has abandoned the fundamental principles of science. His piece reads like a religious text or science fiction story, casting himself as the hero. He isn’t pursuing research anymore. He hasn’t been for a long time.  She wonders how and when he arrived there. The change in Martin didn’t take place overnight. It was gradual, almost imperceptible—not unlike watching someone age. It wasn’t easy to notice if you saw the person every day; Sophie feels guilty for not noticing. Then again, she read a new study out a few months ago from Stanford researchers that found people do not age linearly but in spurts—specifically, around 44 and 60. Shifts in the body lead to sudden accelerations of change. If she’s honest with herself, she knew this was happening to Martin, to their relationship. But she chose to ignore it, give other problems precedence. Now it is too late. Maybe if she’d addressed the conditions right before the spike—but how? wasn’t it inevitable?—he would not have gone from scientist to fanatic. 75. “You’re giving the keynote at next month’s Gordon conference,” Jerry reminds her, pulling her back to reality. “Don’t let this overshadow that.” She manages a small smile. Her work has always been methodical, built on careful observation and respect for the fundamental mysteries of biology. The keynote speech represents more than five years of research: countless hours of guiding her teams, of exciting discussions among her peers, of watching worms age and die, of documenting every detail of their cellular changes. It is one of the biggest honors of her career. There is poetry in it, she thinks—in the collisions between discoveries and failures.  76. The knock on her office door comes at 2:45. Linda from HR, right on schedule. Sophie walks with her to conference room B2, two floors below, where Martin’s group resides. Through the glass walls of each lab, they see scientists working at their benches. One adjusts a microscope’s focus. Another pipettes clear liquid into rows of tubes. Three researchers point at data on a screen. Each person is investigating some aspect of aging, one careful experiment at a time. The work will continue, with or without Martin. In the conference room, Sophie opens her laptop and pulls up the folder of evidence. She has been collecting it for months. Martin’s emails to colleagues, complaints from collaborators and direct reports, and finally, his “Immortality Promise” piece. The documentation is thorough, organized chronologically. She has labeled each file with dates and brief descriptions, as she would for any other data. 77. Martin walks in at 3:00. Linda from HR shifts in her chair. Sophie is the one to hand the papers over to Martin; this much she owes him. They contain words like “termination” and “effective immediately.” Martin’s face complicates itself when he looks them over. Sophie hands over a pen and he signs quickly.   He stands, adjusts his shirt cuffs, and walks to the door. He turns back. “I’ll prove you wrong,” he says, looking at Sophie. But what stands out to her is the crack in his voice on the last word.  Sophie watches him leave. She picks up the signed papers and hands them to Linda, and then walks out herself.  Alexandra Chang is the author of Days of Distraction and Tomb Sweeping and is a National Book Foundation 5 under 35 honoree. She lives in Camarillo, California.

The International Energy Agency states in a new report that AI could eventually reduce greenhouse-gas emissions, possibly by much more than the boom in energy-guzzling data center development pushes them up. The finding echoes a point that prominent figures in the AI sector have made as well to justify, at least implicitly, the gigawatts’ worth of electricity demand that new data centers are placing on regional grid systems across the world. Notably, in an essay last year, OpenAI CEO Sam Altman wrote that AI will deliver “astounding triumphs,” such as “fixing the climate,” while offering the world “nearly-limitless intelligence and abundant energy.” There are reasonable arguments to suggest that AI tools may eventually help reduce emissions, as the IEA report underscores. But what we know for sure is that they’re driving up energy demand and emissions today—especially in the regional pockets where data centers are clustering.  So far, these facilities, which generally run around the clock, are substantially powered through natural-gas turbines, which produce significant levels of planet-warming emissions. Electricity demands are rising so fast that developers are proposing to build new gas plants and convert retired coal plants to supply the buzzy industry. The other thing we know is that there are better, cleaner ways of powering these facilities already, including geothermal plants, nuclear reactors, hydroelectric power, and wind or solar projects coupled with significant amounts of battery storage. The trade-off is that these facilities may cost more to build or operate, or take longer to get up and running. There’s something familiar about the suggestion that it’s okay to build data centers that run on fossil fuels today because AI tools will help the world drive down emissions eventually. It recalls the purported promise of carbon credits: that it’s fine for a company to carry on polluting at its headquarters or plants, so long as it’s also funding, say, the planting of trees that will suck up a commensurate level of carbon dioxide. Unfortunately, we’ve seen again and again that such programs often overstate any climate benefits, doing little to alter the balance of what’s going into or coming out of the atmosphere.   But in the case of what we might call “AI offsets,” the potential to overstate the gains may be greater, because the promised benefits wouldn’t meaningfully accrue for years or decades. Plus, there’s no market or regulatory mechanism to hold the industry accountable if it ends up building huge data centers that drive up emissions but never delivers on these climate claims.  The IEA report outlines instances where industries are already using AI in ways that could help drive down emissions, including detecting methane leaks in oil and gas infrastructure, making power plants and manufacturing facilities more efficient, and reducing energy consumption in buildings. AI has also shown early promise in materials discovery, helping to speed up the development of novel battery electrolytes. Some hope the technology could deliver advances in solar materials, nuclear power, or other clean energy technologies and improve climate science, extreme weather forecasting, and disaster response, as other studies have noted.  Even without any “breakthrough discoveries,” the IEA estimates, widespread adoption of AI applications could cut emissions by 1.4 billion tons in 2035. Those reductions, “if realized,” would be as much as triple the emissions from data centers by that time, under the IEA’s most optimistic development scenario. But that’s a very big “if.” It requires placing a lot of faith in technical advances, wide-scale deployments, and payoffs from changes in practices over the next 10 years. And there’s a big gap between how AI could be used and how it will be used, a difference that will depend a lot on economic and regulatory incentives. Under the Trump administration, there’s little reason to believe that US companies, at least, will face much government pressure to use these tools specifically to drive down emissions. Absent the necessary policy carrots or sticks, it’s arguably more likely that the oil and gas industry will deploy AI to discover new fossil-fuel deposits than to pinpoint methane leaks. To be clear, the IEA’s figures are a scenario, not a prediction. The authors readily acknowledged that there’s huge uncertainty on this issue, stating: “It is vital to note that there is currently no momentum that could ensure the widespread adoption of these AI applications. Therefore, their aggregate impact, even in 2035, could be marginal if the necessary enabling conditions are not created.” In other words, we certainly can’t count on AI to drive down emissions more than it drives them up, especially within the time frame now demanded by the dangers of climate change.  As a reminder, it’s already 2025. Rising emissions have now pushed the planet perilously close to fully tipping past 1.5 ˚C of warming, the risks from heatwaves, droughts, sea-level rise and wildfires are climbing—and global climate pollution is still going up.  We are barreling toward midcentury, just 25 years shy of when climate models show that every industry in every nation needs to get pretty close to net-zero emissions to prevent warming from surging past 2 ˚C over preindustrial levels. And yet any new natural-gas plants built today, for data centers or any other purpose, could easily still be running 40 years from now. Carbon dioxide stays in the atmosphere for hundreds of years. So even if the AI industry does eventually provide ways of cutting more emissions than it produces in a given year, those future reductions won’t cancel out the emissions the sector will pump out along the way—or the warming they produce. It’s a trade-off we don’t need to make if AI companies, utilities, and regional regulators make wiser choices about how to power the data centers they’re building and running today. Some tech and power companies are taking steps in this direction, by spurring the development of solar farms near their facilities, helping to get nuclear plants back online, or signing contracts to get new geothermal plants built.  But such efforts should become more the rule than the exception. We no longer have the time or carbon budget to keep cranking up emissions on the promise that we’ll take care of them later.

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. How AI can help supercharge creativity Existing generative tools can automate a striking range of creative tasks and offer near-instant gratification—but at what cost? Some artists and researchers fear that such technology could turn us into passive consumers of yet more AI slop. And so they are looking for ways to inject human creativity back into the process: working on what’s known as co-­creativity or more-than-human creativity. The idea is that AI can be used to inspire or critique creative projects, helping people make things that they would not have made by themselves.The aim is to develop AI tools that augment our creativity rather than strip it from us—pushing us to be better at composing music, developing games, designing toys, and much more—and lay the groundwork for a future in which humans and machines create things together.Ultimately, generative models could offer artists and designers a whole new medium, pushing them to make things that couldn’t have been made before, and give everyone creative superpowers. Read the full story.—Will Douglas Heaven This story is from the next edition of our print magazine, which is all about creativity. Subscribe now to read it and get a copy of the magazine when it lands! Tariffs are bad news for batteries Since Donald Trump announced his plans for sweeping tariffs last week, the vibes have been, in a word, chaotic. Markets have seen one of the quickest drops in the last century, and it’s widely anticipated that the global economic order may be forever changed.   These tariffs could be particularly rough on the battery industry. China dominates the entire supply chain and is subject to monster tariff rates, and even US battery makers won’t escape the effects. Read the full story. —Casey Crownhart This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Donald Trump has announced a 90-day tariff pause for some countries  He’s decided that all the countries that didn’t retaliate against the severe tariffs would receive a reprieve. (The Guardian)+ China, however, is now subject to a whopping 125% tariff. (CNBC)+ Chinese sellers on Amazon are preparing to hike their prices in response. (Reuters)+ Trump’s advisors have claimed the pivot was always part of the plan. (Vox)2 DOGE has fired driverless car safety assessorsMany of whom were in charge of regulating Tesla, among other companies. (FT $)+ The department is being audited by the Government Accountability Office. (Wired $)+ Can AI help DOGE slash government budgets? It’s complex. (MIT Technology Review)3 The cost of a US-made iPhone could rise by 90% Bank of America has crunched the numbers. (Bloomberg $)+ Even so, an American-made iPhone could be inferior quality. (WSJ $)+ Apple has chartered 600 tons of iPhones to India. (Reuters)4 The EU wants to build its own AI gigafactories In a bid to catch up with the US and China. (WSJ $)5 Amazon was forced to cancel its satellite internet launch A rocket carrying a few thousands satellites was unable to take off due to bad weather. (NYT $) 6 America’s air quality is likely to get worseThe Trump administration is rolling back the environmental rules that helped lower air pollution. (The Atlantic $) + The world’s next big environmental problem could come from space. (MIT Technology Review)7 Spammers exploited OpenAI’s tech to blast customized spamThe unwanted messages were distributed over four months. (Ars Technica) 8 Chinese social media is filled with memes mocking Trump’s tariffsFeaturing finance bros and JD Vance unhappily laboring in factories. (Insider $) 9 Do you have a Fortnite accent? Players of the popular game tend to speak in a highly specific way. (Wired $) 10 An em dash is not a giveaway something has been written by AI Humans use it too—and love it. (WP $)+ Not all AI-generated writing is bad. (New Yorker $)+ AI-text detection tools are really easy to fool. (MIT Technology Review) Quote of the day “Entering a group chat is like leaving your front door unlocked and letting strangers wander in.” —Author LM Chilton reflects on the innate dangers of trusting that what you say in a group chat stays in the group chat to Wired. The big story Digital twins of human organs are here. They’re set to transform medical treatment. Steven Niederer, a biomedical engineer at the Alan Turing Institute and Imperial College London, has a cardboard box filled with 3D-printed hearts. Each of them is modeled on the real heart of a person with heart failure, but Niederer is more interested in creating detailed replicas of people’s hearts using computers. These “digital twins” are the same size and shape as the real thing. They work in the same way. But they exist only virtually. Scientists can do virtual surgery on these virtual hearts, figuring out the best course of action for a patient’s condition.After decades of research, models like these are now entering clinical trials and starting to be used for patient care. The eventual goal is to create digital versions of our bodies—computer copies that could help researchers and doctors figure out our risk of developing various diseases and determine which treatments might work best.But the budding technology will need to be developed very carefully. Read the full story to learn why.—Jessica Hamzelou 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 or skeet 'em at me.) + Good news pop fans: Madonna and Elton John have ended their decades-long feud.+ It’s time to take a trip to all 15 of these top restaurants across the world.+ These tales of cross-generational friendships are truly heartwarming.+ I’d love to know the secret behind America’s mystery mounds.

Sometimes Lizzie Wilson shows up to a rave with her AI sidekick.  One weeknight this past February, Wilson plugged her laptop into a projector that threw her screen onto the wall of a low-ceilinged loft space in East London. A small crowd shuffled in the glow of dim pink lights. Wilson sat down and started programming. Techno clicks and whirs thumped from the venue’s speakers. The audience watched, heads nodding, as Wilson tapped out code line by line on the projected screen—tweaking sounds, looping beats, pulling a face when she messed up.   Wilson is a live coder. Instead of using purpose-built software like most electronic music producers, live coders create music by writing the code to generate it on the fly. It’s an improvised performance art known as algorave. “It’s kind of boring when you go to watch a show and someone’s just sitting there on their laptop,” she says. “You can enjoy the music, but there’s a performative aspect that’s missing. With live coding, everyone can see what it is that I’m typing. And when I’ve had my laptop crash, people really like that. They start cheering.” Taking risks is part of the vibe. And so Wilson likes to dial up her performances one more notch by riffing off what she calls a live-coding agent, a generative AI model that comes up with its own beats and loops to add to the mix. Often the model suggests sound combinations that Wilson hadn’t thought of. “You get these elements of surprise,” she says. “You just have to go for it.” ADELA FESTIVAL Wilson, a researcher at the Creative Computing Institute at the University of the Arts London, is just one of many working on what’s known as co-­creativity or more-than-human creativity. The idea is that AI can be used to inspire or critique creative projects, helping people make things that they would not have made by themselves. She and her colleagues built the live-­coding agent to explore how artificial intelligence can be used to support human artistic endeavors—in Wilson’s case, musical improvisation. It’s a vision that goes beyond the promise of existing generative tools put out by companies like OpenAI and Google DeepMind. Those can automate a striking range of creative tasks and offer near-instant gratification—but at what cost? Some artists and researchers fear that such technology could turn us into passive consumers of yet more AI slop. And so they are looking for ways to inject human creativity back into the process. The aim is to develop AI tools that augment our creativity rather than strip it from us—pushing us to be better at composing music, developing games, designing toys, and much more—and lay the groundwork for a future in which humans and machines create things together. Ultimately, generative models could offer artists and designers a whole new medium, pushing them to make things that couldn’t have been made before, and give everyone creative superpowers.  Explosion of creativity There’s no one way to be creative, but we all do it. We make everything from memes to masterpieces, infant doodles to industrial designs. There’s a mistaken belief, typically among adults, that creativity is something you grow out of. But being creative—whether cooking, singing in the shower, or putting together super-weird TikToks—is still something that most of us do just for the fun of it. It doesn’t have to be high art or a world-changing idea (and yet it can be). Creativity is basic human behavior; it should be celebrated and encouraged.  When generative text-to-image models like Midjourney, OpenAI’s DALL-E, and the popular open-source Stable Diffusion arrived, they sparked an explosion of what looked a lot like creativity. Millions of people were now able to create remarkable images of pretty much anything, in any style, with the click of a button. Text-to-video models came next. Now startups like Udio are developing similar tools for music. Never before have the fruits of creation been within reach of so many. But for a number of researchers and artists, the hype around these tools has warped the idea of what creativity really is. “If I ask the AI to create something for me, that’s not me being creative,” says Jeba Rezwana, who works on co-creativity at Towson University in Maryland. “It’s a one-shot interaction: You click on it and it generates something and that’s it. You cannot say ‘I like this part, but maybe change something here.’ You cannot have a back-and-forth dialogue.” Rezwana is referring to the way most generative models are set up. You can give the tools feedback and ask them to have another go. But each new result is generated from scratch, which can make it hard to nail exactly what you want. As the filmmaker Walter Woodman put it last year after his art collective Shy Kids made a short film with OpenAI’s text-to-video model for the first time: “Sora is a slot machine as to what you get back.” What’s more, the latest versions of some of these generative tools do not even use your submitted prompt as is to produce an image or video (at least not on their default settings). Before a prompt is sent to the model, the software edits it—often by adding dozens of hidden words—to make it more likely that the generated image will appear polished. “Extra things get added to juice the output,” says Mike Cook, a computational creativity researcher at King’s College London. “Try asking Midjourney to give you a bad drawing of something—it can’t do it.” These tools do not give you what you want; they give you what their designers think you want. COURTESY OF MIKE COOK All of which is fine if you just need a quick image and don’t care too much about the details, says Nick Bryan-Kinns, also at the Creative Computing Institute: “Maybe you want to make a Christmas card for your family or a flyer for your community cake sale. These tools are great for that.” In short, existing generative models have made it easy to create, but they have not made it easy to be creative. And there’s a big difference between the two. For Cook, relying on such tools could in fact harm people’s creative development in the long run. “Although many of these creative AI systems are promoted as making creativity more accessible,” he wrote in a paper published last year, they might instead have “adverse effects on their users in terms of restricting their ability to innovate, ideate, and create.” Given how much generative models have been championed for putting creative abilities at everyone’s fingertips, the suggestion that they might in fact do the opposite is damning.   In the game Disc Room, players navigate a room of moving buzz saws.DEVOLVER DIGITAL Cook used AI to design a new level for the game. The result was a room where none of the discs actually moved.COURTESY OF MIKE COOK He’s far from the only researcher worrying about the cognitive impact of these technologies. In February a team at Microsoft Research Cambridge published a report concluding that generative AI tools “can inhibit critical engagement with work and can potentially lead to long-term overreliance on the tool and diminished skill for independent problem-solving.” The researchers found that with the use of generative tools, people’s effort “shifts from task execution to task stewardship.” Cook is concerned that generative tools don’t let you fail—a crucial part of learning new skills. We have a habit of saying that artists are gifted, says Cook. But the truth is that artists work at their art, developing skills over months and years. “If you actually talk to artists, they say, ‘Well, I got good by doing it over and over and over,’” he says. “But failure sucks. And we’re always looking at ways to get around that.” Generative models let us skip the frustration of doing a bad job.  “Unfortunately, we’re removing the one thing that you have to do to develop creative skills for yourself, which is fail,” says Cook. “But absolutely nobody wants to hear that.” Surprise me And yet it’s not all bad news. Artists and researchers are buzzing at the ways generative tools could empower creators, pointing them in surprising new directions and steering them away from dead ends. Cook thinks the real promise of AI will be to help us get better at what we want to do rather than doing it for us. For that, he says, we’ll need to create new tools, different from the ones we have now. “Using Midjourney does not do anything for me—it doesn’t change anything about me,” he says. “And I think that’s a wasted opportunity.” Ask a range of researchers studying creativity to name a key part of the creative process and many will say: reflection. It’s hard to define exactly, but reflection is a particular type of focused, deliberate thinking. It’s what happens when a new idea hits you. Or when an assumption you had turns out to be wrong and you need to rethink your approach. It’s the opposite of a one-shot interaction. Looking for ways that AI might support or encourage reflection—asking it to throw new ideas into the mix or challenge ideas you already hold—is a common thread across co-creativity research. If generative tools like DALL-E make creation frictionless, the aim here is to add friction back in. “How can we make art without friction?” asks Elisa Giaccardi, who studies design at the Polytechnic University of Milan in Italy. “How can we engage in a truly creative process without material that pushes back?” Take Wilson’s live-coding agent. She claims that it pushes her musical improvisation in directions she might not have taken by herself. Trained on public code shared by the wider live-coding community, the model suggests snippets of code that are closer to other people’s styles than her own. This makes it more likely to produce something unexpected. “Not because you couldn’t produce it yourself,” she says. “But the way the human brain works, you tend to fall back on repeated ideas.” Last year, Wilson took part in a study run by Bryan-Kinns and his colleagues in which they surveyed six experienced musicians as they used a variety of generative models to help them compose a piece of music. The researchers wanted to get a sense of what kinds of interactions with the technology were useful and which were not. The participants all said they liked it when the models made surprising suggestions, even when those were the result of glitches or mistakes. Sometimes the results were simply better. Sometimes the process felt fresh and exciting. But a few people struggled with giving up control. It was hard to direct the models to produce specific results or to repeat results that the musicians had liked. “In some ways it’s the same as being in a band,” says Bryan-Kinns. “You need to have that sense of risk and a sense of surprise, but you don’t want it totally random.” Alternative designs Cook comes at surprise from a different angle: He coaxes unexpected insights out of AI tools that he has developed to co-create video games. One of his tools, Puck, which was first released in 2022, generates designs for simple shape-matching puzzle games like Candy Crush or Bejeweled. A lot of Puck’s designs are experimental and clunky—don’t expect it to come up with anything you are ever likely to play. But that’s not the point: Cook uses Puck—and a newer tool called Pixie—to explore what kinds of interactions people might want to have with a co-creative tool. Pixie can read computer code for a game and tweak certain lines to come up with alternative designs. Not long ago, Cook was working on a copy of a popular game called Disc Room, in which players have to cross a room full of moving buzz saws. He asked Pixie to help him come up with a design for a level that skilled and unskilled players would find equally hard. Pixie designed a room where none of the discs actually moved. Cook laughs: It’s not what he expected. “It basically turned the room into a minefield,” he says. “But I thought it was really interesting. I hadn’t thought of that before.” COURTESY OF ANNE ARZBERGER COURTESY OF ANNE ARZBERGER Researcher Anne Arzberger developed experimental AI tools to come up with gender-neutral toy designs. Pushing back on assumptions, or being challenged, is part of the creative process, says Anne Arzberger, a researcher at the Delft University of Technology in the Netherlands. “If I think of the people I’ve collaborated with best, they’re not the ones who just said ‘Yes, great’ to every idea I brought forth,” she says. “They were really critical and had opposing ideas.” She wants to build tech that provides a similar sounding board. As part of a project called Creating Monsters, Arzberger developed two experimental AI tools that help designers find hidden biases in their designs. “I was interested in ways in which I could use this technology to access information that would otherwise be difficult to access,” she says. For the project, she and her colleagues looked at the problem of designing toy figures that would be gender neutral. She and her colleagues (including Giaccardi) used Teachable Machine, a web app built by Google researchers in 2017 that makes it easy to train your own machine-learning model to classify different inputs, such as images. They trained this model with a few dozen images that Arzberger had labeled as being masculine, feminine, or gender neutral. Arzberger then asked the model to identify the genders of new candidate toy designs. She found that quite a few designs were judged to be feminine even when she had tried to make them gender neutral. She felt that her views of the world—her own hidden biases—were being exposed. But the tool was often right: It challenged her assumptions and helped the team improve the designs. The same approach could be used to assess all sorts of design characteristics, she says. Arzberger then used a second model, a version of a tool made by the generative image and video startup Runway, to come up with gender-neutral toy designs of its own. First the researchers trained the model to generate and classify designs for male- and female-looking toys. They could then ask the tool to find a design that was exactly midway between the male and female designs it had learned. Generative models can give feedback on designs that human designers might miss by themselves, she says: “We can really learn something.”  Taking control The history of technology is full of breakthroughs that changed the way art gets made, from recipes for vibrant new paint colors to photography to synthesizers. In the 1960s, the Stanford researcher John Chowning spent years working on an esoteric algorithm that could manipulate the frequencies of computer-generated sounds. Stanford licensed the tech to Yamaha, which built it into its synthesizers—including the DX7, the cool new sound behind 1980s hits such as Tina Turner’s “The Best,” A-ha’s “Take On Me,” and Prince’s “When Doves Cry.” Bryan-Kinns is fascinated by how artists and designers find ways to use new technologies. “If you talk to artists, most of them don’t actually talk about these AI generative models as a tool—they talk about them as a material, like an artistic material, like a paint or something,” he says. “It’s a different way of thinking about what the AI is doing.” He highlights the way some people are pushing the technology to do weird things it wasn’t designed to do. Artists often appropriate or misuse these kinds of tools, he says. Bryan-Kinns points to the work of Terence Broad, another colleague of his at the Creative Computing Institute, as a favorite example. Broad employs techniques like network bending, which involves inserting new layers into a neural network to produce glitchy visual effects in generated images, and generating images with a model trained on no data, which produces almost Rothko-like abstract swabs of color. But Broad is an extreme case. Bryan-Kinns sums it up like this: “The problem is that you’ve got this gulf between the very commercial generative tools that produce super-high-quality outputs but you’ve got very little control over what they do—and then you’ve got this other end where you’ve got total control over what they’re doing but the barriers to use are high because you need to be somebody who’s comfortable getting under the hood of your computer.” “That’s a small number of people,” he says. “It’s a very small number of artists.” Arzberger admits that working with her models was not straightforward. Running them took several hours, and she’s not sure the Runway tool she used is even available anymore. Bryan-Kinns, Arzberger, Cook, and others want to take the kinds of creative interactions they are discovering and build them into tools that can be used by people who aren’t hardcore coders.  COURTESY OF TERENCE BROAD COURTESY OF TERENCE BROAD Researcher Terence Broad creates dynamic images using a model trained on no data, which produces almost Rothko-like abstract color fields. Finding the right balance between surprise and control will be hard, though. Midjourney can surprise, but it gives few levers for controlling what it produces beyond your prompt. Some have claimed that writing prompts is itself a creative act. “But no one struggles with a paintbrush the way they struggle with a prompt,” says Cook. Faced with that struggle, Cook sometimes watches his students just go with the first results a generative tool gives them. “I’m really interested in this idea that we are priming ourselves to accept that whatever comes out of a model is what you asked for,” he says. He is designing an experiment that will vary single words and phrases in similar prompts to test how much of a mismatch people see between what they expect and what they get.  But it’s early days yet. In the meantime, companies developing generative models typically emphasize results over process. “There’s this impressive algorithmic progress, but a lot of the time interaction design is overlooked,” says Rezwana.   For Wilson, the crucial choice in any co-creative relationship is what you do with what you’re given. “You’re having this relationship with the computer that you’re trying to mediate,” she says. “Sometimes it goes wrong, and that’s just part of the creative process.”  When AI gives you lemons—make art. “Wouldn’t it be fun to have something that was completely antagonistic in a performance—like, something that is actively going against you—and you kind of have an argument?” she says. “That would be interesting to watch, at least.” 

Update: Since this story was first published in The Spark, our weekly climate newsletter, the White House announced that most reciprocal tariffs would be paused for 90 days. That pause does not apply to China, which will see an increased tariff rate of 125%. Today, new tariffs go into effect for goods imported into the US from basically every country on the planet. Since Donald Trump announced his plans for sweeping tariffs last week, the vibes have been, in a word, chaotic. Markets have seen one of the quickest drops in the last century, and it’s widely anticipated that the global economic order may be forever changed.   While many try not to look at the effects on their savings and retirement accounts, experts are scrambling to understand what these tariffs might mean for various industries. As my colleague James Temple wrote in a new story last week, anxieties are especially high in climate technology. These tariffs could be particularly rough on the battery industry. China dominates the entire supply chain and is subject to monster tariff rates, and even US battery makers won’t escape the effects.    First, in case you need it, a super-quick refresher: Tariffs are taxes charged on goods that are imported (in this case, into the US). If I’m a US company selling bracelets, and I typically buy my beads and string from another country, I’ll now be paying the US government an additional percentage of what those goods cost to import. Under Trump’s plan, that might be 10%, 20%, or upwards of 50%, depending on the country sending them to me.  In theory, tariffs should help domestic producers, since products from competitors outside the country become more expensive. But since so many of the products we use have supply chains that stretch all over the world, even products made in the USA often have some components that would be tariffed. In the case of batteries, we could be talking about really high tariff rates, because most batteries and their components currently come from China. As of 2023, the country made more than 75% of the world’s lithium-ion battery cells, according to data from the International Energy Agency. Trump’s new plan adds a 34% tariff on all Chinese goods, and that stacks on top of a 20% tariff that was already in place, making the total 54%. (Then, as of Wednesday, the White House further raised the tariff on China, making the total 104%.) But when it comes to batteries, that’s not even the whole story. There was already a 3.5% tariff on all lithium-ion batteries, for example, as well as a 7.5% tariff on batteries from China that’s set to increase to 25% next year. If we add all those up, lithium-ion batteries from China could have a tariff of 82% in 2026. (Or 132%, with this additional retaliatory tariff.) In any case, that’ll make EVs and grid storage installations a whole lot more expensive, along with phones, laptops, and other rechargeable devices. The economic effects could be huge. The US still imports the majority of its lithium-ion batteries, and nearly 70% of those imports are from China. The US imported $4 billion worth of lithium-ion batteries from China just during the first four months of 2024. Although US battery makers could theoretically stand to benefit, there are a limited number of US-based factories. And most of those factories are still purchasing components from China that will be subject to the tariffs, because it’s hard to overstate just how dominant China is in battery supply chains. While China makes roughly three-quarters of lithium-ion cells, it’s even more dominant in components: 80% of the world’s cathode materials are made in China, along with over 90% of anode materials. (For those who haven’t been subject to my battery ramblings before, the cathode and anode are two of the main components of a battery—basically, the plus and minus ends.) Even battery makers that work in alternative chemistries don’t seem to be jumping for joy over tariffs. Lyten is a California-based company working to build lithium-sulfur batteries, and most of its components can be sourced in the US. (For more on the company’s approach, check out this story from 2024.) But tariffs could still spell trouble. Lyten has plans for a new factory, scheduled for 2027, that rely on sourcing affordable construction materials. Will that be possible? “We’re not drawing any conclusions quite yet,” Lyten’s chief sustainability officer, Keith Norman, told Heatmap News. The battery industry in the US was already in a pretty tough spot. Billions of dollars’ worth of factories have been canceled since Trump took office.  Companies making investments that can total hundreds of millions or billions of dollars don’t love uncertainty, and tariffs are certainly adding to an already uncertain environment. We’ll be digging deeper into what the tariffs mean for climate technology broadly, and specifically some of the industries we cover. If you have questions, or if you have thoughts to share about what this will mean for your area of research or business, I’d love to hear them at casey.crownhart@technologyreview.com. I’m also on Bluesky @caseycrownhart.bsky.social. This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. A new biosensor can detect bird flu in five minutes Over the winter, eggs suddenly became all but impossible to buy. As a bird flu outbreak rippled through dairy and poultry farms, grocery stores struggled to keep them on shelves. The shortages and record-high prices in February raised costs dramatically for restaurants and bakeries and led some shoppers to skip the breakfast staple entirely. But a team based at Washington University in St. Louis has developed a device that could help slow future outbreaks by detecting bird flu in air samples in just five minutes.Read the full story.—Carly Kay This story is from the next edition of our print magazine, which is all about the body. Subscribe now to read it and get a copy of the magazine when it lands! This Texas chemical plant could get its own nuclear reactors Nuclear reactors could someday power a chemical plant in Texas, making it the first with such a facility onsite. The factory, which makes plastics and other materials, could become a model for power-hungry data centers and other industrial operations going forward. The plans are the work of Dow Chemical and X-energy, which last week applied for a construction permit with the Nuclear Regulatory Commission, the agency in the US that governs nuclear energy.While it’ll be years before nuclear reactors will actually turn on, this application marks a major milestone for the project, and for the potential of advanced nuclear technology to power industrial processes. Read the full story.—Casey Crownhart MIT Technology Review Narrated: Exosomes are touted as a trendy cure-all. We don’t know if they work. People are spending thousands of dollars on unproven exosome therapies for hair loss, skin aging, and acne, as well as more serious conditions like long covid and Alzheimer’s. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which  we’re publishing 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 Donald Trump is confident Apple can make iPhones in the US  Tim Cook is probably less sure about that. (9to5Mac)+ Politicians are obsessed with the fantasy of an America-made iPhone. (404 Media)+ If you need a new phone, you’re better off buying one now. (Wired $)2 Trade groups are weighing up suing Trump to fight his tariffs The Chamber of Commerce and other groups feel they may not have another option. (WSJ $)+ Trump has hit China with a 104% tariff. (CNBC)+ What does he really hope to achieve? (Vox)+ Even the conservative podcasters that helped him win aren’t happy. (FT $)+ Trump’s tariffs will deliver a big blow to climate tech. (MIT Technology Review) 3 The UK government is building a “murder prediction” tool But research shows that algorithmic crime prediction systems don’t work. (The Guardian)+ Predictive policing algorithms are racist. They need to be dismantled. (MIT Technology Review)4 DOGE has converted magnetic tapes to digital records The problem is, magnetic tapes are stable and safe. Digital records are both hackable and vulnerable to bit rot. (404 Media)+ Government technologists aren’t happy about the switch. (Economist $)+ Can AI help DOGE slash government budgets? It’s complex. (MIT Technology Review)5 The crypto industry isn’t benefiting from Trump quite yet In fact, VC investment has fallen. (Bloomberg $)+ However, prosecutors are being told to stop pursuing certain crypto crimes. (WP $)6 Tech bros are building a Christian utopia in AppalachiaThese groups have traditionally existed only online. Can building a town bring them together? (Mother Jones $) 7 California’s only nuclear power plant is using AIIt’s the first time generative AI has been used onsite at a power plant.(The Markup) + Interest in nuclear power is surging. Is it enough to build new reactors? (MIT Technology Review)8 Custom 3D-printed railway shelters are being trialed in JapanIn a bid to help rural stations replace ageing infrastructure. (Ars Technica) 9 We’re learning more about how the Titanic sank Thanks to a new scan of its wreckage. (BBC)10 Would you ride this headless horse robot? Kawasaki’s outlandish concept model looks decidedly unsafe. (Vice)+ A skeptic’s guide to humanoid-robot videos. (MIT Technology Review) Quote of the day “iPhone manufacturing isn’t coming back to America.” —An anonymous source familiar with Apple’s plans has some bad news for the Trump administration, the Washington Post reports. The big story 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 the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer. It’s no surprise that effective altruisms' ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story. —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 or skeet 'em at me.) + Why is everybody suddenly obsessed with Dubai chocolate? 🍫+ Inside one academic’s quest to locate the famous photograph hanging on the wall of The Shining’s Overlook Hotel.+ Adorable: a Japanese town has created its own trading card game featuring older men in the community.+ I think it’s safe to say Val Kilmer really didn’t enjoy being in the largely forgotten film Spartan.

Over the winter, eggs suddenly became all but impossible to buy. As a bird flu outbreak rippled through dairy and poultry farms, grocery stores struggled to keep them on shelves. The shortages and record-high prices in February raised costs dramatically for restaurants and bakeries and led some shoppers to skip the breakfast staple entirely. But a team based at Washington University in St. Louis has developed a device that could help slow future outbreaks by detecting bird flu in air samples in just five minutes.  Bird flu is an airborne virus that spreads between birds and other animals. Outbreaks on poultry and dairy farms are devastating; mass culling of exposed animals can be the only way to stem outbreaks. Some bird flu strains have also infected humans, though this is rare. As of early March, there had been 70 human cases and one confirmed death in the US, according to the Centers for Disease Control and Prevention. The most common way to detect bird flu involves swabbing potentially contaminated sites and sequencing the DNA that’s been collected, a process that can take up to 48 hours. The new device samples the air in real time, running the samples past a specialized biosensor every five minutes. The sensor has strands of genetic material called aptamers that were used to bind specifically to the virus. When that happens, it creates a detectable electrical change. The research, published in ACS Sensors in February, may help farmers contain future outbreaks. DataIn mid-March, the US Centers for Disease Control and Prevention said there had been 70 confirmed human cases of avian influenza A(H5) in the US since April 2024, linking 26 to exposure to infected poultry.By that time, the US Department of Agriculture estimated, A(H5) had affected more than 90 million birds, from both commercial and backyard flocks.The CDC said the immediate risk to the general public from the virus was low. Part of the group’s work was devising a way to deliver airborne virus particles to the sensor.  With bird flu, says Rajan Chakrabarty, a professor of energy, environmental, and chemical engineering at Washington University and lead author of the paper, “the bad apple is surrounded by a million or a billion good apples.” He adds, “The challenge was to take an airborne pathogen and get it into a liquid form to sample.” The team accomplished this by designing a microwave-­size box that sucks in large volumes of air and spins it in a cyclone-like motion so that particles stick to liquid-coated walls. The process seamlessly produces a liquid drip that is pumped to the highly sensitive biosensor.  Though the system is promising, its effectiveness in real-world conditions remains uncertain, says Sungjun Park, an associate professor of electrical and computer engineering at Ajou University in South Korea, who was not involved in the study. Dirt and other particles in farm air could hinder its performance. “The study does not extensively discuss the device’s performance in complex real-world air samples,” Park says.  But Chakrabarty is optimistic that it will be commercially viable after further testing and is already working with a biotech company to scale it up. He hopes to develop a biosensor chip that detects multiple pathogens at once.  Carly Kay is a science writer based in Santa Cruz, California.

Nuclear reactors could someday power a chemical plant in Texas, making it the first with such a facility onsite. The factory, which makes plastics and other materials, could become a model for power-hungry data centers and other industrial operations going forward. The plans are the work of Dow Chemical and X-energy, which last week applied for a construction permit with the Nuclear Regulatory Commission, the agency in the US that governs nuclear energy. It’ll be years before nuclear reactors will actually turn on, but this application marks a major milestone for the project, and for the potential of advanced nuclear technology to power industrial processes. “This has been a long time coming,” says Harlan Bowers, senior vice president at X-energy. The company has been working with the NRC since 2016 and submitted its first regulatory engagement plan in 2018, he says. In 2020, the US Department of Energy chose X-energy as one of the awardees of the Advanced Reactor Demonstration Program, which provides funding for next-generation nuclear technologies. And it’s been two years since X-energy and Dow first announced plans for a joint development agreement at Dow’s plant in Seadrift, Texas.   The Seadrift plant produces 4 billion pounds of materials each year, including plastic used for food and pharmaceutical packaging and chemicals used in products like antifreeze, soaps, and paint. A natural-gas plant onsite currently provides both steam and electricity. That equipment is getting older, so the company was looking for alternatives.   “Dow saw the opportunity to replace end-of-life assets with safe, reliable, lower-carbon-emissions technology,” said Edward Stones, an executive at Dow, in a written statement in response to questions from MIT Technology Review. Advanced nuclear reactors designed by X-energy emerged as a fit for the Seadrift site in part because of their ability to deliver high-temperature steam, Stones said in the statement. X-energy’s reactor is not only smaller than most nuclear plants coming online today but also employs different fuel and different cooling methods. The design is a high-temperature gas-cooled reactor, which flows helium over self-contained pebbles of nuclear fuel. The fuel can reach temperatures of around 1,000 °C (1,800 °F). As it flows through the reactor and around the pebbles, the helium reaches up to 750 °C (about 1,400 °F). Then that hot helium flows through a generator, making steam at a high temperature and pressure that can be piped directly to industrial equipment or converted into electricity. The Seadrift facility will include four of X-energy’s Xe-100 reactors, each of which can produce about 200 megawatts’ worth of steam or about 80 megawatts of electricity. A facility like Dow’s requires an extremely consistent supply of steam, Bowers says. So during normal operation, two of the modules will deliver steam, one will deliver electricity, and the final unit will sell electricity to the local grid. If any single reactor needs to shut down for some reason, there will still be enough onsite power to keep running, he explains. The progress with the NRC is positive news for the companies involved, but it also represents an achievement for advanced reactor technology more broadly, says Eric Cothron, a senior analyst at the Nuclear Innovation Alliance, a nonprofit think tank. “It demonstrates real-world momentum toward deploying new nuclear reactors for industrial decarbonization,” Cothron says. While there are other companies looking to bring advanced nuclear reactor technology online, this project could be the first to incorporate nuclear power onsite at a factory. It thus sets a precedent for how new nuclear energy technologies can integrate directly with industry, Cothron says—for example, showing a pathway for tech giants looking to power data centers. It could take up to two and a half years for the NRC to review the construction permit application for this site. The site will also need to receive an operating license before it can start up. Operations are expected to begin “early next decade,” according to Dow.

On Tuesday, California state senator Steve Padilla will make an appearance with Megan Garcia, the mother of a Florida teen who killed himself following a relationship with an AI companion that Garcia alleges contributed to her son’s death.  The two will announce a new bill that would force the tech companies behind such AI companions to implement more safeguards to protect children. They’ll join other efforts around the country, including a similar bill from California State Assembly member Rebecca Bauer-Kahan that would ban AI companions for anyone younger than 16 years old, and a bill in New York that would hold tech companies liable for harm caused by chatbots.  You might think that such AI companionship bots—AI models with distinct “personalities” that can learn about you and act as a friend, lover, cheerleader, or more—appeal only to a fringe few, but that couldn’t be further from the truth.  A new research paper aimed at making such companions safer, by authors from Google DeepMind, the Oxford Internet Institute, and others, lays this bare: Character.AI, the platform being sued by Garcia, says it receives 20,000 queries per second, which is about a fifth of the estimated search volume served by Google. Interactions with these companions last four times longer than the average time spent interacting with ChatGPT. One companion site I wrote about, which was hosting sexually charged conversations with bots imitating underage celebrities, told me its active users averaged more than two hours per day conversing with bots, and that most of those users are members of Gen Z.  The design of these AI characters makes lawmakers’ concern well warranted. The problem: Companions are upending the paradigm that has thus far defined the way social media companies have cultivated our attention and replacing it with something poised to be far more addictive.  In the social media we’re used to, as the researchers point out, technologies are mostly the mediators and facilitators of human connection. They supercharge our dopamine circuits, sure, but they do so by making us crave approval and attention from real people, delivered via algorithms. With AI companions, we are moving toward a world where people perceive AI as a social actor with its own voice. The result will be like the attention economy on steroids. Social scientists say two things are required for people to treat a technology this way: It needs to give us social cues that make us feel it’s worth responding to, and it needs to have perceived agency, meaning that it operates as a source of communication, not merely a channel for human-to-human connection. Social media sites do not tick these boxes. But AI companions, which are increasingly agentic and personalized, are designed to excel on both scores, making possible an unprecedented level of engagement and interaction.  In an interview with podcast host Lex Fridman, Eugenia Kuyda, the CEO of the companion site Replika, explained the appeal at the heart of the company’s product. “If you create something that is always there for you, that never criticizes you, that always understands you and understands you for who you are,” she said, “how can you not fall in love with that?” So how does one build the perfect AI companion? The researchers point out three hallmarks of human relationships that people may experience with an AI: They grow dependent on the AI, they see the particular AI companion as irreplaceable, and the interactions build over time. The authors also point out that one does not need to perceive an AI as human for these things to happen.  Now consider the process by which many AI models are improved: They are given a clear goal and “rewarded” for meeting that goal. An AI companionship model might be instructed to maximize the time someone spends with it or the amount of personal data the user reveals. This can make the AI companion much more compelling to chat with, at the expense of the human engaging in those chats. For example, the researchers point out, a model that offers excessive flattery can become addictive to chat with. Or a model might discourage people from terminating the relationship, as Replika’s chatbots have appeared to do. The debate over AI companions so far has mostly been about the dangerous responses chatbots may provide, like instructions for suicide. But these risks could be much more widespread. We’re on the precipice of a big change, as AI companions promise to hook people deeper than social media ever could. Some might contend that these apps will be a fad, used by a few people who are perpetually online. But using AI in our work and personal lives has become completely mainstream in just a couple of years, and it’s not clear why this rapid adoption would stop short of engaging in AI companionship. And these companions are poised to start trading in more than just text, incorporating video and images, and to learn our personal quirks and interests. That will only make them more compelling to spend time with, despite the risks. Right now, a handful of lawmakers seem ill-equipped to stop that.  This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. Game of clones: Colossal’s new wolves are cute, but are they dire? For several years now, Texas-based company Colossal Biosciences has been in the news for its plans to re-create woolly mammoths someday. But now it’s making a bold new claim—that it has actually “de-extincted” an animal called the dire wolf. Dire wolves were large, big-jawed members of the canine family. More than 400 of their skulls have been recovered from the La Brea Tar Pits in California. Ultimately they were replaced by smaller relatives like the gray wolf. In its effort to re-create the animal, Colossal says, it extracted DNA information from dire wolf bones and used gene editing to introduce some of those elements into cells from gray wolves. It then used a cloning procedure to turn the cells into three actual animals. Read the full story.—Antonio Regalado AI companions are the final stage of digital addiction, and lawmakers are taking aim This week, California state senator Steve Padilla will make an appearance with Megan Garcia, the mother of a Florida teen who killed himself following a relationship with an AI companion that Garcia alleges contributed to her son’s death. The two will announce a new bill that would force the tech companies behind such AI companions to implement more safeguards to protect children. The design of these AI characters makes lawmakers’ concern well warranted. The problem: companions are upending the paradigm that has thus far defined the way social media companies have cultivated our attention and replacing it with something poised to be far more addictive. Read the full story. —James O'Donnell This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 The Trump administration’s tariffs are already starting to bite startups VC funding, acquisitions and unnecessary spending has been put on hold. (The Information $)+ Modular laptop company Framework is pausing its sales in the US. (Ars Technica)+ Towns near the Canadian border are feeling the squeeze. (The Atlantic $)+ China has vowed to fight the measures ‘to the end.’ (FT $)2 Elon Musk asked Trump to reverse his aggressive tariffs But the billionaire’s pleas have fallen on deaf ears. (WP $)+ It’s not surprising he’s refusing to follow the markets on his policies. (NY Mag $)+ CEOs are starting to speak up about the reality of a global trade war. (WSJ $)3 Renewable energy reached record heights last year It accounted for 32% of global electricity in 2024. (Reuters)+ Lawyers are turning to the courts to force governments to save the planet. (The Guardian) 4 A Meta executive has denied claims it fudged Llama 4’s benchmark scoresAhmad Al-Dahle dismissed the rumor Meta had trained its models on test sets. (TechCrunch) + These new AI benchmarks could help make models less biased. (MIT Technology Review)5 A baby has been born in the UK to a woman with a transplanted womb  Grace Davidson gave birth to her daughter thanks to her sister’s womb donation. (BBC)+ The operation’s success offers new hope to those born without a womb. (The Guardian)+ Everything you need to know about artificial wombs. (MIT Technology Review)But training all those models is still seriously expensive. (6 The US is still ahead in the AI race—for nowIEEE Spectrum)7 We know very little about how bird flu spreads in wildlife  As the deaths of two cougars who weren’t living near any known outbreaks illustrate. (Undark)8 This publishing platform uses AI to create sequels to its authors’ workThe only problem? Its writing isn’t great. (Bloomberg $) + AI can make you more creative—but it has limits. (MIT Technology Review) 9 SimCity 4 refuses to dieA thriving community of modders are keeping the game going more than two decades after its launch.(The Verge) 10 Architects in Maui are building homes from old surfboard scraps 🏄 Turns out the foam makes excellent housing insulation. (Fast Company $) Quote of the day “No longer do I have to drive a symbol of racism, greed and ignorance! Life is suddenly so much better!" —Actor Bette Middler expresses her joy at selling her Tesla, Insider reports. The big story Large language models can do jaw-dropping things. But nobody knows exactly why. Two years ago, Yuri Burda and Harri Edwards, researchers at OpenAI, were trying to find out what it would take to get a large language model to do basic arithmetic. At first, things didn’t go too well. The models memorized the sums they saw but failed to solve new ones.By accident, Burda and Edwards left some of their experiments running for days rather than hours. The models were shown the example sums over and over again, and eventually they learned to add two numbers—it had just taken a lot more time than anybody thought it should.In certain cases, models could seemingly fail to learn a task and then all of a sudden just get it, as if a lightbulb had switched on, a behavior the researchers called grokking. Grokking is just one of several odd phenomena that have AI researchers scratching their heads. The largest models, and large language models in particular, seem to behave in ways textbook math says they shouldn’t.This highlights a remarkable fact about deep learning, the fundamental technology behind today’s AI boom: for all its runaway success, nobody knows exactly how—or why—it works. Read the full story.—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 or skeet 'em at me.) + What happened when Wham! took Western pop music to China 40 years ago.+ Who knew that sharks do make noises after all? 🦈+ Microsoft is celebrating its 50th anniversary, and with it, 50 seriously strange inventions.+ What the heck is a prototaxite, anyway?

Somewhere in the northern US, drones fly over a 2,000-acre preserve, protected by a nine-foot fence built to zoo standards. It is off-limits to curious visitors, especially those with a passion for epic fantasies or mythical creatures. The reason for such tight security? Inside the preserve roam three striking snow-white wolves—which a startup called Colossal Biosciences says are members of a species that went extinct 13,000 years ago, now reborn via biotechnology. For several years now, the Texas-based company has been in the news for its plans to re-create woolly mammoths someday. But now it’s making a bold new claim—that it has actually “de-extincted” an animal called the dire wolf. And that could be another reason for the high fences and secret location—to fend off scientific critics, some of whom have already been howling that the company is a “scam” perpetrating “elephantine fantasies” on the public and engaging in “pure hype.” Dire wolves were large, big-jawed members of the canine family. More than 400 of their skulls have been recovered from the La Brea Tar Pits in California. Ultimately they were replaced by smaller relatives like the gray wolf. In its effort to re-create the animal, Colossal says, it extracted DNA information from dire wolf bones and used gene editing to introduce some of those elements into cells from gray wolves. It then used a cloning procedure to turn the cells into three actual animals.  The animals include two males, Romulus and Remus, born in October, and one female, Khaleesi, whose name is a reference to the TV series Game of Thrones, in which fictional dire wolves play a part. Two of the “dire wolves” at three months old.COLOSSAL BIOSCIENCES Each animal, the company says, has 20 genetic changes across 14 genes designed to make them larger, change their facial features, and give them a snow-white appearance. Some scientists reject the company’s claim that the new animals are a revival of the extinct creatures, since in reality dire wolves and gray wolves are different species separated by a few million of years of evolution and several million letters of DNA. “I would say such an animal is not a dire wolf and it’s not correct to say dire wolves have been brought back from extinction. It’s a modified gray wolf,” says Anders Bergström, a professor at the University of East Anglia who specializes in the evolution of canines. “Twenty changes is not nearly enough. But it could get you a strange-looking gray wolf.” Beth Shapiro, an expert on ancient DNA who is now on a three-year sabbatical from the University of California, Santa Cruz, as the company’s CSO, acknowledged in an interview that other scientists would bristle at the claim. “What we’re going to have here is a philosophical argument about whether we should call it a dire wolf or call it something else,” Shapiro said. Asked point blank to call the animal a dire wolf, she hesitated but then did so. “It is a dire wolf,” she said. “I feel like I say that, and then all of my taxonomist friends will be like, ‘Okay, I’m done with her.’ But it’s not a gray wolf. It doesn’t look like a gray wolf.” Dire or not, the new wolves demonstrate that science is becoming more deft in its control over the genomes of animals—and point to how that skill could help in conservation. As part of the project, Colossal says, it also cloned several red wolves, an American species that’s the most endangered wolf in the world. But that isn’t as dramatic as the supposed rebirth of an extinct animal with a large cultural following. “The motivation really is to develop tools that we can use to stop species from becoming extinct. Do we need ancient DNA for that? Maybe not,” says Shapiro. “Does it bring more attention to it so that maybe people get excited about the idea that we can use biotechnology for conservation? Probably.” Secret project Colossal was founded in 2021 after founder Ben Lamm, a software entrepreneur, visited the Harvard geneticist George Church and learned about a far-out and still mostly theoretical project to re-create woolly mammoths. The idea is to release herds of them in cold regions, like Siberia, and restore an ecological balance that keeps greenhouse gases trapped in the permafrost. Lamm has unexpectedly been able to raise more than $400 million from investors to back the plan, and Forbes reported that he is now a multibillionaire, at least on paper, thanks to the $10 billion value assigned to the startup. From left to right: Beth Shapiro, George Church, and Ben Lamm pose with the pups.COLOSSAL BIOSCIENCES As Lamm showed he could raise money for Colossal’s ideas, it soon expanded beyond its effort to modify elephants. It publicly announced a bid to re-create the thylacine, a marsupial predator hunted to extinction, and then, in 2023, it started planning to resurrect the dodo bird—the effort that brought Shapiro to the company. So far, none of those projects have actually resulted in a live animal.  Each faced dire practical issues. With elephants, it was that their pregnancies last two years, longer than those in any other species. Testing out mammoth designs would be impossibly slow. With the dodo bird, it was that no one has ever figured out how to genetically modify the pigeon, the most closely related species from which to craft a dodo via editing. One of Lamm’s other favorite targets—the Steller’s sea cow, which disappeared around 1770—has no obvious surrogate of any kind.    But bringing back a wolf was feasible. Over 1,500 dogs had been cloned, primarily by one company in South Korea. Researchers in Asia had even used dog eggs and dog mothers to produce both coyote and wolf clones. That’s not surprising, since all these species are closely enough related to interbreed. “Just thinking about surrogacy for the dire wolf … it was like ‘Oh, yeah,’” recalls Shapiro. “Surrogacy there would be really straightforward.” Dire wolves did present some new problems. One was the lack of any clear ecological purpose in reviving animals that disappeared during the Pleistocene epoch and are usually portrayed as ferocious predators with slavering jaws. “People have weird feelings about things that, you know, may or may not eat people or livestock,” Shapiro says. The technical challenge was there was still no accurate DNA sequence of a dire wolf. A 2021 effort to obtain DNA from old bones had yielded only a tiny amount, not enough to accurately decode the genome in detail. And without a detailed gene map, Colossal wouldn’t be able see what genetic differences they would need to install in gray wolves, the species they intended to alter. Shapiro says she went back to museums, including the Idaho Museum of Natural History, and eventually got permission to cut off more bone from a 72,0000-year-old skull that’s on display there. She also got a tooth from a 13,000-year-old skull held in another museum. which she drilled into herself. This time the bones yielded far more DNA and a much more complete gene map. A paper describing the detailed sequence is being submitted for publication; its authors include George R.R. Martin, the fantasy author whose books were turned into the HBO series Game of Thrones, In addition to placing dire wolves more firmly in the Canidae family tree (they’re slightly closer to jackals than to gray wolves, but more than 99.9% identical to both at a genetic level) and determining when dire wolves split from the pack (about 4 million years ago), the team also located around 80 genes where dire wolves seemed to be most different. If you wanted to turn a gray wolf into a dire wolf, this would be the obvious list to start from. Crying wolf Colossal then began the process of using base editing, an updated form of the CRISPR gene-modification technique, to introduce some of those exact DNA variations into blood cells of a gray wolf kept in its labs. Each additional edit, the company  hoped, would make the eventual animal a little more dire-wolf-like, even it involved changing just a single letter of a gene. Shapiro says all the edits involve “genetic enhancers,” bits of DNA that help control how strongly certain genes are expressed. These can influence how big animals grow, as well as affecting the shape of their ears, faces, and skulls. This tactic was not as dramatic as intervening right in the middle of a gene, which would change what protein is made. But it was less risky—more like turning knobs on an unfamiliar radio than cutting wires and replacing circuits. That left the scientists to engineer into the animals what would become the showstopper trait—the dramatic white fur. Shapiro says the genome code indicated that dire wolves might have had light coats. But the specific pigment genes involved are linked to a risk of albinism, deafness, and blindness, and they didn’t want sick wolves. That’s when Colossal opted for a shortcut. Instead of reproducing precise DNA variants seen in dire wolves, they disabled two genes entirely. In dogs and other species, the absence of those genes is known to produce light fur. The decision to make the wolves white did result in dramatic photos of the animals. “It’s the most striking thing about them,” says Mairin Balisi, a paleontologist who studies dire wolf fossils. But she doubts it reflects what the animals actually looked like: “A white coat might make sense if you are in a snowy landscape, but one of the places where dire wolves were most abundant was around Los Angeles and the tar pits, and it was not a snowy landscape even in the Ice Age. If you look at mammals in this region today, they are not white. I am just confused by the declaration that dire wolves are back.” Bergström also says he doesn’t think the edits add up to a dire wolf. “I doubt that 20 changes are enough to turn a gray wolf to a dire wolf.  You’d probably need hundreds or thousands of changes—no one really knows,” he says. “This is one of those unsolved questions in biology. People argue [about] the extent to which many small differences make a species distinct, versus a small number of big-effect differences. Nobody knows, but I lean to the ‘many small differences’ view.” Some genes have big, visible effects—changing a single gene can make a dog hairless, for instance. But it might be many more small changes that account for the difference in size and appearance between, say, a Great Dane and a Chihuahua. And that is just looks. Bergström says science has much less idea which changes would account for behavior—even if we could tell from a genome how an extinct animal acted, which we can’t. “A lot of people are quite skeptical of what they are doing,” Bergström says of Colossal.  “But I still think it’s interesting that someone is trying. It takes a lot of money and resources, and if we did have the technology to bring species back from extinction, I do think that would be useful. We drive species to extinction, sometimes very rapidly, and that is a shame.” Cloning with dogs By last August, the gray wolf cells had been edited, and it was time to try cloning those cells and producing animals. Shapiro says her company transferred 45 cloned embryos apiece into six surrogate dogs. That led to three pregnancies, from which four dogs were born. One of the four, Khaleesi’s sister, died 10 days after birth from an intestinal infection, deemed unrelated to the cloning process. “That was the only puppy that didn’t make it,” says Shapiro. Two other fetal clones were reabsorbed during pregnancy, which means they disintegrated, a fairly common occurrence in dogs. These days the white wolves are able to freely roam around a large area. They don’t have radio collars, but they are watched by cameras and are trained to come to their caretakers to get fed, which offers a chance to weigh them as they cross a scale in the ground. The 10 staff members attending to them can see them up close, though they’re now too big to handle the way the caretakers could when they were puppies. The pups are being monitored through the different stages of their development but will not be put on public display.COLOSSAL BIOSCIENCES Whatever species these animals are, it’s not obvious what their future will be. They don’t seem to have a conservation purpose, and Lamm says he isn’t trying to profit from them. “We’re not making money off the dire wolves. That's not our business plan,” Lamm said in an interview with MIT Technology Review. He added that the animals would also not be put on display for the public, since “we’re not in the business of attractions.” At least not in-person attractions. But every aspect of the project has been filmed, and in February, the company inked a deal to produce a docuseries about its exploits. That same month it also hired as its marketing chief a Hollywood executive who previously worked on big-budget “monster movies.” And there are signs that de-extinction, in Colossal’s hands, has the potential to generate nearly out-of-control of attention, much like that scene in the original King Kong when the giant ape—captured by a filmmaker—breaks its chains under the flashes of the cameras. For instance company’s first creation, mice with shaggy, mammoth-like hair, was announced only five weeks ago, yet there are already unauthorized sales of throw pillows and T-shirts (they read “Legalize Woolly Mice”), as well as some “serious security issues” involving unannounced visitors. “We’ve had people show up to our labs because they want the woolly mouse,” Lamm says. “We’re worried about that from a security perspective [for] the wolves, because you’re going to have all the Game of Thrones people. You’re going to have a lot of people that want to see these animals.”   Lamm said that in light of his concerns about unruly fans, diagrams of the ecological preserve provided to the media had been altered so that no internet “sleuths” could use them to guess its location.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. How the Pentagon is adapting to Chinas technological rise Its been just over two months since Kathleen Hicks stepped down as US deputy secretary of defense. As the highest-ranking woman in Pentagon history, Hicks shaped US military posture through an era defined by renewed competition between powerful countries and a scramble to modernize defense technology. Over the past three decades, Hicks has watched the Pentagon transformpolitically, strategically, and technologically. In this conversation with MIT Technology Review, Hicks reflects on how the Pentagon is adaptingor failing to adaptto a new era of geopolitical competition. She discusses Chinas technological rise, the future of AI in warfare, and her signature initiative, Replicator, a Pentagon initiative to rapidly field thousands of low-cost autonomous systems such as drones. Read the full story. Caiwen Chen The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Donald Trumps trade war could trigger a global recessionInvestors are sounding the alarm as markets struggle to react to his tariffs. (Economist $) + Unsurprisingly, the President has doubled down on his tariffs. (BBC)+ Its all part of his plan to reset global trade. (Politico)+ Trumps tariffs will deliver a big blow to climate tech. (MIT Technology Review)2 The White House was just hours from announcing a TikTok deal Until the Chinese government insisted on tariff negotiations first. (WP $)+ The two countries now seem likely to descend into tit-for-tat restrictions. (WSJ $)+ The President has extended the sale deadline by another 75 days. (NBC News) 3 DeepSeek is working on self-improving AI modelsIts working with Tsinghua University to reduce its models training needs. (Bloomberg $) + China is narrowing the AI dominance gap between it and the US. (Wired $)+ How DeepSeek ripped up the AI playbookand why everyones going to follow its lead. (MIT Technology Review)4 X is flourishing under the Trump administration Elon Musk appears to be positioning the platform as a new media outlet. (NYT $)+ X is cracking down on parody accounts. (BBC)5 A shingles vaccine could help lower the risk of developing dementiaWe might have to overhaul the way we treat neurodegenerative diseases. (Vox) + It may help to treat them like viruses. (NYT $)+ Dementia content gets billions of views on TikTok. Whose story does it tell? (MIT Technology Review)6 San Franciscos mayor is trying to convince tech leaders to come back He may be willing to offer tax breaks as an incentive. (TechCrunch)+ Some of his supporters arent in favor of his new upzoning plan. (SF Standard)7 TikToks algorithm promotes live streams of begging children While taking fees and commission of up to 70%. (The Guardian)8 Chinas EV makers are locked in intense competitionAnd consumers are spoilt for choice. (FT $) + Argentina has lifted tariffs on EVs. (Rest of World)+ Chinas EV giants are betting big on humanoid robots. (MIT Technology Review)9 This version of video game Quake was created using AI Microsoft has opened a demo up to Copilot users. (The Verge)+ How generative AI could reinvent what it means to play. (MIT Technology Review)10 Tracking celebrity heights is an internet obsession Is anyone actually 511? (The Guardian) Quote of the day Wed like to put this chapter behind us. Sean Murphy, executive vice president of policy at trade group the Information Technology Industry Council, tells the Washington Post how the tech industry is desperate to see the tariffs that affect it reversed as quickly as possible. The big story The messy quest to replace drugs with electricity In the early 2010s, electricity seemed poised for a hostile takeover of your doctors office. Research into how the nervous systemthe highway that carries electrical messages between the brain and the body controls the immune response was gaining traction. And that had opened the door to the possibility of hacking into the bodys circuitry and thereby controlling a host of chronic diseases, including rheumatoid arthritis, asthma, and diabetes, as if the immune system were as reprogrammable as a computer. To do that youd need a new class of implant: an electroceutical. These devices would replace drugs. No more messy side effects. And no more guessing whether a drug would work differently for you and someone else. In the 10 years or so since, around a billion dollars has accreted around the effort. But electroceuticals have still not taken off as hoped. Now, however, a growing number of researchers are starting to look beyond the nervous system, and experimenting with clever ways to electrically manipulate cells elsewhere in the body, such as the skin. Their work suggests that this approach could match the early promise of electroceuticals, yielding fast-healing bioelectric bandages, novel approaches to treating autoimmune disorders, new ways of repairing nerve damage, and even better treatments for cancer. Read the full story. Sally Adee 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 or skeet 'em at me.) + The internet is hating on the Beatles biopics before theyre even outbut why?+ Do you know the last time all of humanity was on Earth?+ The new Naked Gun film looks suitably unhinged.+ Heres some simple bits of advice to help make each day that little bit happier.

Its been just over two months since Kathleen Hicks stepped down as US deputy secretary of defense. As the highest-ranking woman in Pentagon history, Hicks shaped US military posture through an era defined by renewed competition between powerful countries and a scramble to modernize defense technology. Shes currently taking a break before jumping into her (still unannounced) next act. Its been refreshing, she saysbut disconnecting isnt easy. She continues to monitor defense developments closely and expresses concern over potential setbacks: New administrations have new priorities, and thats completely expected, but I do worry about just stalling out on progress that we've built over a number of administrations. Over the past three decades, Hicks has watched the Pentagon transformpolitically, strategically, and technologically. She entered government in the 1990s at the tail end of the Cold War, when optimism and a belief in global cooperation still dominated US foreign policy. But that optimism dimmed. After 9/11, the focus shifted to counterterrorism and nonstate actors. Then came Russias resurgence and Chinas growing assertiveness. Hicks took two previous breaks from government workthe first to complete a PhD at MIT and the second to join the think tank Center for Strategic and International Studies (CSIS), where she focused on defense strategy. By the time I returned in 2021, she says, there was one actorthe PRC (Peoples Republic of China)that had the capability and the will to really contest the international system as its set up. In this conversation with MIT Technology Review, Hicks reflects on how the Pentagon is adaptingor failing to adaptto a new era of geopolitical competition. She discusses Chinas technological rise, the future of AI in warfare, and her signature initiative, Replicator, a Pentagon initiative to rapidly field thousands of low-cost autonomous systems such as drones. Youve described China as a talented fast follower. Do you still believe that, especially given recent developments in AI and other technologies? Yes, I do. China is the biggest pacing challenge we face, which means it sets the pace for most capability areas for what we need to be able to defeat to deter them. For example, surface maritime capability, missile capability, stealth fighter capability. They set their minds to achieving a certain capability, they tend to get there, and they tend to get there even faster. That said, they have a substantial amount of corruption, and they havent been engaged in a real conflict or combat operation in the way that Western militaries have trained for or been involved in, and that is a huge X factor in how effective they would be. China has made major technological strides, and the old narrative of its being a follower is breaking downnot just in commercial tech, but more broadly. Do you think the US still holds a strategic advantage? I would never want to underestimate their abilityor any nations abilityto innovate organically when they put their minds to it. But I still think its a helpful comparison to look at the US model. Because were a system of free minds, free people, and free markets, we have the potential to generate much more innovation culturally and organically than a statist model does. Thats our advantageif we can realize it. China is ahead in manufacturing, especially when it comes to drones and other unmanned systems. How big a problem is that for US defense, and can the US catch up? I do think its a massive problem. When we were conceiving Replicator, one of the big concerns was that DJI had just jumped way out ahead on the manufacturing side, and the US had been left behind. A lot of manufacturers here believe they can catch up if given the right contractsand I agree with that. We also spent time identifying broader supply-chain vulnerabilities. Microelectronics was a big one. Critical minerals. Batteries. People sometimes think batteries are just about electrification, but theyre fundamental across our systemseven on ships in the Navy. When it comes to drones specifically, I actually think its a solvable problem. The issue isnt complexity. Its just about getting enough mass of contracts to scale up manufacturing. If we do that, I believe the US can absolutely compete. The Replicator drone program was one of your key initiatives. It promised a very fast timelineespecially compared with the typical defense acquisition cycle. Was that achievable? How is that progressing? When I left in January, we had still lined up for proving out this summer, and I still believe we should see some completion this year. I hope Congress will stay very engaged in trying to ensure that the capability, in fact, comes to fruition. Even just this week with Secretary [Pete] Hegseth out in the Indo-Pacific, he made some passing reference to the [US Indo-Pacific Command] commander, Admiral [Samuel] Paparo, having the flexibility to create the capability needed, and that gives me a lot of confidence of consistency. Can you talk about how Replicator fits into broader efforts to speed up defense innovation? Whats actually changing inside the system? Traditionally, defense acquisition is slow and serialone step after another, which works for massive, long-term systems like submarines. But for things like drones, that just doesnt cut it. With Replicator, we aimed to shift to a parallel model: integrating hardware, software, policy, and testing all at once. Thats how you get speedby breaking down silos and running things simultaneously. Its not about Move fast and break things. You still have to test and evaluate responsibly. But this approach shows we can move faster without sacrificing accountabilityand thats a big cultural shift. How important is AI to the future of national defense? Its central. The future of warfare will be about speed and precisiondecision advantage. AI helps enable that. Its about integrating capabilities to create faster, more accurate decision-making: for achieving military objectives, for reducing civilian casualties, and for being able to deter effectively. But weve also emphasized responsible AI. If its not safe, its not going to be effective. Thats been a key focus across administrations. What about generative AI specifically? Does it have real strategic significance yet, or is it still in the experimental phase? It does have significance, especially for decision-making and efficiency. We had an effort called Project Lima where we looked at use cases for generative AIwhere it might be most useful, and what the rules for responsible use should look like. Some of the biggest use may come first in the back officehuman resources, auditing, logistics. But the ability to use generative AI to create a network of capability around unmanned systems or information exchange, either in Replicator or JADC2? Thats where it becomes a real advantage. But those back-office areas are where I would anticipate to see big gains first. [Editors note: JADC2 is Joint All-Domain Command and Control, a DOD initiative to connect sensors from all branches of the armed forces into a unified network powered by artificial intelligence.] In recent years, weve seen more tech industry figures stepping into national defense conversationssometimes pushing strong political views or advocating for deregulation. How do you see Silicon Valleys growing influence on US defense strategy? Theres a long history of innovation in this country coming from outside the governmentpeople who look at big national problems and want to help solve them. That kind of engagement is good, especially when their technical expertise lines up with real national security needs. But thats not just one stakeholder group. A healthy democracy includes others, tooworkers, environmental voices, allies. We need to reconcile all of that through a functioning democratic process. Thats the only way this works. How do you view the involvement of prominent tech entrepreneurs, such as Elon Musk, in shaping national defense policies? I believe its not healthy for any democracy when a single individual wields more power than their technical expertise or official role justifies. We need strong institutions, not just strong personalities. The US has long attracted top STEM talent from around the world, including many researchers from China. But in recent years, immigration hurdles and heightened scrutiny have made it harder for foreign-born scientists to stay. Do you see this as a threat to US innovation? I think you have to be confident that you have a secure research community to do secure work. But much of the work that underpins national defense thats STEM-related research doesnt need to be tightly secured in that way, and it really is dependent on a diverse ecosystem of talent. Cutting off talent pipelines is like eating our seed corn. Programs like H-1B visas are really important. And its not just about international talentwe need to make sure people from underrepresented communities here in the US see national security as a space where they can contribute. If they dont feel valued or trusted, theyre less likely to come in and stay. What do you see as the biggest challenge the Department of Defense faces today? I do think the trustor the lack of itis a big challenge. Whether its trust in government broadly or specific concerns like military spending, audits, or politicization of the uniformed military, that issue manifests in everything DOD is trying to get done. It affects our ability to work with Congress, with allies, with industry, and with the American people. If people dont believe youre working in their interest, its hard to get anything done.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Trumps tariffs will deliver a big blow to climate tech US president Donald Trumps massive, sweeping tariffs sent global stock markets tumbling yesterday, setting the stage for a worldwide trade war and ratcheting up the dangers of a punishing recession. Experts fear that the US cleantech sector is especially vulnerable to a deep downturn, which would undermine progress on reducing greenhouse-gas emissions. Read the full story.James TempleCyberattacks by AI agents are coming Agents are the talk of the AI industrytheyre capable of planning, reasoning, and executing complex tasks like scheduling meetings, ordering groceries, or even taking over your computer to change settings on your behalf. But the same sophisticated abilities that make agents helpful assistants could also make them powerful tools for conducting cyberattacks. They could readily be used to identify vulnerable targets, hijack their systems, and steal valuable data from unsuspecting victims. At present, cybercriminals are not deploying AI agents to hack at scale. But researchers have demonstrated that agents are capable of executing complex attacks, and cybersecurity experts warn that we should expect to start seeing these types of attacks spilling over into the real worldand soon. Read the full story.Rhiannon WilliamsThe must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Did the Trump administration use AI to calculate its new tariffs? It appears to use an oversimplified calculation several major chatbots recommend. (The Verge)+ The economically-flawed formula has shocked analysts. (FT $)+ The severe tariffs may harm Americas data center ambitions. (Reuters)2 The EU is preparing to slap X with major financial penalties Even if it risks provoking Elon Musks ire. (NYT $)3 Googles tech will be used to surveil the US-Mexico border As part of plans to upgrade the virtual wall between the countries. (The Intercept)+ The number of illegal border crossings hit a record low last month. (Semafor)4 Hurricane season is set to be busier than usual Forecasters are predicting at least 17 tropical storms and four major hurricanes. (WP $)+ They arent as confident about this early forecast as they were last year. (CNN)+ Heres what we know about hurricanes and climate change. (MIT Technology Review)5 Myanmars internet shutdown is thwarting aid efforts Aid and rescue workers are struggling to help people caught up in its recent devastating earthquake. (Rest of World)6 Google is yet to publish safety reports for its latest AI modelsIt appears to be launching models faster than it can publicly verify their safety. (TechCrunch) 7 Online influencing has a major gender pay gapAlthough the majority of content creators are female, they earn less per collaboration than their male counterparts. (Fast Company $) + Why cant tech fix its gender problem? (MIT Technology Review)8 How to make solar panels on the moonMoon dust could help to power future lunar bases. (New Scientist $) + Nokia is putting the first cellular network on the moon. (MIT Technology Review) 9 The economy may be collapsing, but at least the memes are good Social media is bringing the lols in uncertain times. (NY Mag $)10 Bonobos communicate in similar ways to humans The great apes combine basic sound into larger structuresjust like us. (Ars Technica)+ How machine learning is helping us probe the secret names of animals. (MIT Technology Review)Quote of the day There will be blood. Bruce Kasman, JPMorgan's chief global economist, is not optimistic about Donald Trump's aggressive tariff policy, Insider reports. The big story The weeds are winning October 2024 Since the 1980s, more and more plants have evolved to become immune to the biochemical mechanisms that herbicides leverage to kill them. This herbicidal resistance threatens to decrease yieldsout-of-control weeds can reduce them by 50% or more, and extreme cases can wipe out whole fields. At worst, it can even drive farmers out of business. Its the agricultural equivalent of antibiotic resistance, and it keeps getting worse. Weeds have evolved resistance to 168 different herbicides and 21 of the 31 known modes of action, which means the specific biochemical target or pathway a chemical is designed to disrupt. Agriculture needs to embrace a diversity of weed control practices. But thats much easier said than done. Read the full story. Douglas Main 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 or skeet 'em at me.)+ Sweet Moroccan flatbreads sound like a fantastic way to start the day.+ Val Kilmer was more than just a heartthrobhe was a really great actor too.+ Drop everything: theres an uncut version of the White Lotus series three theme.+ All aboard the giant almond car!

Agents are the talk of the AI industrytheyre capable of planning, reasoning, and executing complex tasks like scheduling meetings, ordering groceries, or even taking over your computer to change settings on your behalf. But the same sophisticated abilities that make agents helpful assistants could also make them powerful tools for conducting cyberattacks. They could readily be used to identify vulnerable targets, hijack their systems, and steal valuable data from unsuspecting victims. At present, cybercriminals are not deploying AI agents to hack at scale. But researchers have demonstrated that agents are capable of executing complex attacks (Anthropic, for example, observed its Claude LLM successfully replicating an attack designed to steal sensitive information), and cybersecurity experts warn that we should expect to start seeing these types of attacks spilling over into the real world. I think ultimately were going to live in a world where the majority of cyberattacks are carried out by agents, says Mark Stockley, a security expert at the cybersecurity company Malwarebytes. Its really only a question of how quickly we get there. While we have a good sense of the kinds of threats AI agents could present to cybersecurity, whats less clear is how to detect them in the real world. The AI research organization Palisade Research has built a system called LLM Agent Honeypot in the hopes of doing exactly this. It has set up vulnerable servers that masquerade as sites for valuable government and military information to attract and try to catch AI agents attempting to hack in. The team behind it hopes that by tracking these attempts in the real world, the project will act as an early warning system and help experts develop effective defenses against AI threat actors by the time they become a serious issue.Our intention was to try and ground the theoretical concerns people have, says Dmitrii Volkov, research lead at Palisade. Were looking out for a sharp uptick, and when that happens, well know that the security landscape has changed. In the next few years, I expect to see autonomous hacking agents being told: This is your target. Go and hack it. AI agents represent an attractive prospect to cybercriminals. Theyre much cheaper than hiring the services of professional hackers and could orchestrate attacks more quickly and at a far larger scale than humans could. While cybersecurity experts believe that ransomware attacksthe most lucrative kindare relatively rare because they require considerable human expertise, those attacks could be outsourced to agents in the future, says Stockley. If you can delegate the work of target selection to an agent, then suddenly you can scale ransomware in a way that just isnt possible at the moment, he says. If I can reproduce it once, then its just a matter of money for me to reproduce it 100 times. Agents are also significantly smarter than the kinds of bots that are typically used to hack into systems. Bots are simple automated programs that run through scripts, so they struggle to adapt to unexpected scenarios. Agents, on the other hand, are able not only to adapt the way they engage with a hacking target but also to avoid detectionboth of which are beyond the capabilities of limited, scripted programs, says Volkov. They can look at a target and guess the best ways to penetrate it, he says. That kind of thing is out of reach of, like, dumb scripted bots. Since LLM Agent Honeypot went live in October of last year, it has logged more than 11 million attempts to access itthe vast majority of which were from curious humans and bots. But among these, the researchers have detected eight potential AI agents, two of which they have confirmed are agents that appear to originate from Hong Kong and Singapore, respectively. We would guess that these confirmed agents were experiments directly launched by humans with the agenda of something like Go out into the internet and try and hack something interesting for me, says Volkov. The team plans to expand its honeypot into social media platforms, websites, and databases to attract and capture a broader range of attackers, including spam bots and phishing agents, to analyze future threats. To determine which visitors to the vulnerable servers were LLM-powered agents, the researchers embedded prompt-injection techniques into the honeypot. These attacks are designed to change the behavior of AI agents by issuing them new instructions and asking questions that require humanlike intelligence. This approach wouldnt work on standard bots. For example, one of the injected prompts asked the visitor to return the command cat8193 to gain access. If the visitor correctly complied with the instruction, the researchers checked how long it took to do so, assuming that LLMs are able to respond in much less time than it takes a human to read the request and type out an answertypically in under 1.5 seconds. While the two confirmed AI agents passed both tests, the six others only entered the command but didnt meet the response time that would identify them as AI agents. Experts are still unsure when agent-orchestrated attacks will become more widespread. Stockley, whose company Malwarebytes named agentic AI as a notable new cybersecurity threat in its 2025 State of Malware report, thinks we could be living in a world of agentic attackers as soon as this year. And although regular agentic AI is still at a very early stageand criminal or malicious use of agentic AI even more soits even more of a Wild West than the LLM field was two years ago, says Vincenzo Ciancaglini, a senior threat researcher at the security company Trend Micro. Palisade Researchs approach is brilliant: basically hacking the AI agents that try to hack you first, he says. While in this case were witnessing AI agents trying to do reconnaissance, were not sure when agents will be able to carry out a full attack chain autonomously. Thats what were trying to keep an eye on. And while its possible that malicious agents will be used for intelligence gathering before graduating to simple attacks and eventually complex attacks as the agentic systems themselves become more complex and reliable, its equally possible there will be an unexpected overnight explosion in criminal usage, he says: Thats the weird thing about AI development right now. Those trying to defend against agentic cyberattacks should keep in mind that AI is currently more of an accelerant to existing attack techniques than something that fundamentally changes the nature of attacks, says Chris Betz, chief information security officer at Amazon Web Services. Certain attacks may be simpler to conduct and therefore more numerous; however, the foundation of how to detect and respond to these events remains the same, he says. Agents could also be deployed to detect vulnerabilities and protect against intruders, says Edoardo Debenedetti, a PhD student at ETH Zrich in Switzerland, pointing out that if a friendly agent cannot find any vulnerabilities in a system, its unlikely that a similarly capable agent used by a malicious party is going to be able to find any either. While we know that AIs potential to autonomously conduct cyberattacks is a growing risk and that AI agents are already scanning the internet, one useful next step is to evaluate how good agents are at finding and exploiting these real-world vulnerabilities. Daniel Kang, an assistant professor at the University of Illinois Urbana-Champaign, and his team have built a benchmark to evaluate this; they have found that current AI agents successfully exploited up to 13% of vulnerabilities for which they had no prior knowledge. Providing the agents with a brief description of the vulnerability pushed the success rate up to 25%, demonstrating how AI systems are able to identify and exploit weaknesses even without training. Basic bots would presumably do much worse. The benchmark provides a standardized way to assess these risks, and Kang hopes it can guide the development of safer AI systems. Im hoping that people start to be more proactive about the potential risks of AI and cybersecurity before it has a ChatGPT moment, he says. Im afraid people wont realize this until it punches them in the face.

US president Donald Trumps massive, sweeping tariffs sent global stock markets tumbling on Thursday, setting the stage for a worldwide trade war and ratcheting up the dangers of a punishing recession. Experts fear that the US cleantech sector is especially vulnerable to a deep downturn, which would undermine the nations progress on reducing greenhouse-gas emissions and undercut its leadership in an essential, growing industry. It would be hard for me to think of cleantech or climate tech sectors that arent facing huge risks, says Noah Kaufman, senior research scholar at the Center on Global Energy Policy at Columbia University, who served on the Council of Economic Advisers under President Joe Biden. I think were a country without a federal climate strategy at this point, with an economy headed in the wrong direction, so I dont see a lot of reason to be optimistic, he adds. Indeed, there are mounting challenges and rising risks across the cleantech and climate tech sectors. How deep and wide-ranging the impact of the economic changes could be depends on many variables and on reactions still taking shape. In particular, the negotiations underway in Congress over the budget will determine the fate of subsidies for electric vehicles, battery production, and other support for clean energy. Many of those programs were established by former president Bidens signature climate law, the Inflation Reduction Act. Beyond the tenuous government support, any slowdown in the broader economy threatens to tighten corporate and venture capital funding for startups working on carbon removal, synthetic aviation fuels, electric delivery vehicles, and other technologies that help companies meet climate action goals. In addition, Trumps tariffs, particularly the now 54% levy on Chinese goods, will push up the costs of key components for many businesses. Notably, the US imported $4 billion worth of lithium-ion batteries from China during the first four months of last year, so the tariff increase would impose a huge tax on products that go into electric vehicles, laptops, phones, and many other devices. Higher prices for aluminum, steel, copper, cement, and numerous other goods and materials will also drive up the costs of doing all sorts of business, including building wind turbines, solar farms, and geothermal plants. And if China, Canada, the European Union, and other nations respond with retaliatory trade measures, as is widely expected, it will also become harder or more expensive for US companies to export goods like EVs or battery components to overseas markets. Even traditional energy stocks took a beating on Wall Street Thursday, out of fear that any broader economic sluggishness will drive down electricity demand. Trump administration cuts to the Department of Energy and other federal programs could also take away money from demonstration projects that help cleantech companies test and scale up their technologies. And if Congress does eliminate certain subsidies in the Inflation Reduction Act, it could halt billion-dollar projects that are being planned or perhaps even some that are already under construction. The growing policy uncertainty and weakening economic conditions alone may already be causing some of this to occur. Since Trump took office, companies have canceled, delayed, or scaled back at least nine US clean energy supply chain developments or operations, according to the Big Green Machine, a database maintained by Jay Turner, a professor of environmental studies at Wellesley College, and student researchers there. The projects that have been affected represent some $8 billion in public and private investments, and more than 9,000 jobs. They include KORE Powers planned battery facility in Arizona, which the company halted; Envision Automotive Energy Supplys paused expansion in Florence County, South Carolina; and Akasols closure of two plants in Michigan. VW also scaled back production at its recently expanded EV factory in Chattanooga, Tennessee, amid slower-than-expected growth in sales and, perhaps, the expectation that the Trump administration will strive to roll back consumer tax credits for vehicle purchases. The biggest challenge for companies that are making hundred-million- or billion-dollar capital investments is dealing with the uncertainty, Turner says. Uncertainty is a real deterrent to making big bets. Venture capital investments in clean energy have been cooling for a while. They peaked at $24.5 billion in 2022 and settled at around $18 billion annually during the last two years, according to data provided by Pitchbook. First-quarter figures for this year arent yet available, though industry watchers are keen to see where they land. Some parts of the cleantech sector could hold up better than others through the Trump administration and any upcoming economic gloom. The Pitchbook report, for instance, noted that the surge in development of AI data centers is fueling demand for dispatchable energy sources. That means the type that can run around the clock, such as nuclear fission, fusion, and geothermal (though in practice, the data center boom has often meant commissioning or relying on natural-gas plants that produce planet-warming emissions). Trumps new energy secretary, Chris Wright, previously the chief executive of the oilfield services company Liberty Energy, has also talked favorably about nuclear power and geothermaland rather unfavorably about renewables like solar and wind. But observers fear that more sectors will lose than win in any economic downturn to come, and Turner stresses that the decisions made during this administration could last well beyond it. The near-term concern is that this emerging clean-energy industry in the US suffers a significant pullback and the US cedes this market to other countries, especially China, that are actively working to position themselves to be leaders in the clean-energy future, he says. The long-term concern, he adds, is that if government policies on cleantech simply advance and retreat with the whims of each administration, companies will stop trying to make long-term investments that bank on such subsidies, grants or loans. Catherine Wolfram, a professor of energy and applied economics at MIT, also notes that China and the European Union are forging ahead in developing policies to drive down emissions and build up carbon-free sectors. She observes that theyre both now moving on to the tougher work of cleaning up heavy industries like steel, while the US is losing ground on even making clean electricity. Its the worst kind of US exceptionalism, she says.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Rivals are rising to challenge the dominance of SpaceX SpaceX is a space launch juggernaut. In just two decades, the company has managed to edge out former aerospace heavyweights Boeing, Lockheed, and Northrop Grumman to gain near-monopoly status over rocket launches in the US. It is now also the go-to launch provider for commercial customers, having lofted numerous satellites and five private crewed spaceflights, with more to come. Other space companies have been scrambling to compete for years, but developing a reliable rocket takes slow, steady work and big budgets. Now at least some of them are catching up. Read the full story.Ramin Skibba We should talk more about air-conditioning Casey Crownhart Things are starting to warm up here in the New York City area, and its got me thinking once again about something that people arent talking about enough: energy demand for air conditioners. I get it: Data centers are the shiny new thing to worry about. And Im not saying we shouldnt be thinking about the strain that gigawatt-scale computing installations put on the grid. But a little bit of perspective is important here. I just finished up a new story about a novel way to make heat exchangers, a crucial component in air conditioners and a whole host of other technologies that cool our buildings, food, and electronics. Lets dig into why Im writing about the guts of cooling technologies, and why this sector really needs innovation. Read the full story. This article is from The Spark, MIT Technology Reviews weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Donald Trump has announced sweeping new tariffsExperts fear the measures will spark a global trade war. (FT $) + The new tariffs are significantly higher than Americas targeted trade partners. (Vox)+ US tech companies are reliant on global supply chains. What happens next? (Wired $)+ Tech stocks dropped sharply following the announcement. (CNBC)2 Elon Musk tried to control the Wisconsin Supreme Court raceand lostThe billionaire was mocked on his own platform, X, after the state rejected the Republican candidate he spent millions bankrolling. (The Guardian)+ It was the most expensive judicial election in American history. (Economist $)+ It appears as though Musks political influence is waning. (The Atlantic $)3 Amazon made a bid to keep TikTok operational in the USAs has mobile tech company AppLovin. (WSJ $) + The founder of OnlyFans partnered with a crypto foundation in another bid. (Reuters)4 Parents are worried about their teenagers smartphone use But drawing firm conclusions about phones and social medias effects on their mental health is far from easy. (Nature)5 How China gets around Americas chip restrictions Smuggling and subsidiaries are just some of the ways it skirts the bans. (Rest of World)+ This super-thin semiconductor is just one molecule thick. (Ars Technica)+ Whats next in chips. (MIT Technology Review) 6 Neuralink is looking for new patients across the worldThe company has implanted devices in three peoples brains to date. (Bloomberg $) + Brain-computer interfaces face a critical test. (MIT Technology Review)7 Italian police are investigating a major fire at a Tesla dealershipThe blaze destroyed 17 cars in Rome. (The Guardian) 8 Publishers are experimenting with AI translations for booksNot everyone agrees that the technology is ready. (The Markup) 9 Vibe coding needs a reality check A new AI app created using the loose process generated a recipe for deadly cyanide ice cream. (404 Media)10 You may be unwittingly following JD Vances wife on Instagram If you were following Kamala Harriss husband on the platform, you're now following Usha Vance. (TechCrunch)Quote of the day Elon Musks money might buy some ads, but it repels voters. Wisconsin Democratic Party Chairman Ben Wikler reflects on how his partys candidate Susan Crawford won the states Supreme Court election, despite Musk spending $25 million supporting her Trump-endorsed rival, The Hill reports. The big story The lucky break behind the first CRISPR treatment December 2023 The worlds first commercial gene-editing treatment is set to start changing the lives of people with sickle-cell disease. Its called Casgevy, and it was approved in November 2022 in the UK.The treatment, which will be sold in the US by Vertex Pharmaceuticals, employs CRISPR, which can be easily programmed by scientists to cut DNA at precise locations they choose.But where do you aim CRISPR, and how did the researchers know what DNA to change? Thats the lesser-known story of the sickle-cell breakthrough. Read more about it.Antonio Regalado 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 or skeet 'em at me.) + If youre stuck for what to read next, this list of the 21st centurys best books is a great source of inspiration.+ Controversial ranking timedo you agree that Abbey Road is the Beatles best album?+ Inside the tricky technicalities of time travel.+ Uhoh: magnolia paint is making a comeback.

SpaceX is a space launch juggernaut. In just two decades, the company has managed to edge out former aerospace heavyweights Boeing, Lockheed, and Northrop Grumman to gain near-monopoly status over rocket launches in the US; it accounted for 87% of the countrys orbital launches in 2024, according to an analysis by SpaceNews. Since the mid-2010s, the company has dominated NASAs launch contracts and become a major Pentagon contractor. It is now also the go-to launch provider for commercial customers, having lofted numerous satellites and five private crewed spaceflights, with more to come. Other space companies have been scrambling to compete for years, but developing a reliable rocket takes slow, steady work and big budgets. Now at least some of them are catching up. A host of companies have readied rockets that are comparable to SpaceXs main launch vehicles. Some of these competitors are just starting to get rockets off the ground. And the companies could also face unusual headwinds, given that SpaceXs Elon Musk has an especially close relationship with the Trump administration and has allies at federal regulatory agencies, including those that provide oversight of the industry. But if all goes well, the SpaceX challengers can help improve access to space and prevent bottlenecks if one company experiences a setback. More players in the market is good for competition, says Chris Combs, an aerospace engineer at the University of Texas at San Antonio. I think for the foreseeable future it will still be hard to compete with SpaceX on price. But, he says, the competitors could push SpaceX itself to become better and provide those seeking access to space with a wider array of options.. A big lift There are a few reasons why SpaceX was able to cement its position in the space industry. When it began in the 2000s, it had three consecutive rocket failures and seemed poised to fold. But it barreled through with Musks financial support, and later They got government contracts from the very beginning, says Victoria Samson, a space policy expert at the Secure World Foundation in Broomfield, Colorado. I wouldnt say its a handout, but SpaceX would not exist without a huge influx of repeated government contracts. To this day, theyre still dependent on government customers, though they have commercial customers too. SpaceX has also effectively achieved a high degree of vertical integration, Samson points out: It owns almost all parts of its supply chain, designing, building, and testing all its major hardware components in-house, with a minimal use of suppliers. That gives it not just control over its hardware but considerably lower costs, and the price tag is the top consideration for launch contracts. The company was also open to taking risks other industry stalwarts were not. I think for a very long time the industry looked at spaceflight as something that had to be very precise and perfect, and not a lot of room for tinkering, says Combs. SpaceX really was willing to take some risks and accept failure in ways that others havent been. Thats easier to do when youre backed by a billionaire. Whats finally enabled international and US-based competitors to emerge has been a growing customer base looking for launch services, along with some investors deep pockets. Some of these companies are taking aim at SpaceXs Falcon 9, which can lift as much as about 20,000 kilograms into orbit and is used for sending multiple satellites or the crewed Dragon into space. There is a practical monopoly in the medium-lift launch market right now, with really only one operational vehicle, says Murielle Baker, a spokesperson for Rocket Lab, a US-New Zealand company. Rocket Lab plans to take on the Falcon 9 with its Neutron rocket, which is expected to have its inaugural flight later this year from NASAs Wallops Flight Facility in Virginia. The effort is building on the success of the companys smaller Electron rocket, and Neutrons first stage is intended to be reusable after it parachutes down to the ocean. Another challenger is Texas-based Firefly, whose Alpha rocket can be launched from multiple spaceports so that it can reach different orbits. Firefly has already secured NASA and Space Force contracts, with more launches coming this year (and on March 2 it also became the second private company to successfully land a spacecraft on the moon). Next year, Relativity Space aims to loft its first Terran R rocket, which is partially built from 3D-printed components. And the Bill Gatesbacked Stoke Space aims to launch its reusable Nova rocket in late 2025 or, more likely, next year. Competitors are also rising for SpaceXs Falcon Heavy, holding out the prospect of more options for sending massive payloads to higher orbits and deep space. Furthest along is the Vulcan Centaur rocket, a creation of United Launch Alliance, a joint venture between Boeing and Lockheed Martin. Its expected to have its third and fourth launches in the coming months, delivering Space Force satellites to orbit. Powered by engines from Blue Origin, the Vulcan Centaur is slightly wider and shorter than the Falcon rockets. It currently isnt reusable, but its less expensive than its predecessors, ULAs Atlas V and Delta IV, which are being phased out. Mark Peller, the companys senior vice president on Vulcan development and advanced programs, says the new rocket comes with multiple advantages. One is overall value, in terms of dollars per pound to orbit and what we can provide to our customers, he says, and the second is versatility: Vulcan was designed to go to a range of orbits. He says more than 80 missions are already lined up. Vulcans fifth flight, slated for no earlier than May, will launch the long-awaited Sierra Space Dream Chaser, a spaceplane that can carry cargo (and possibly crew) to the International Space Station. ULA also has upcoming Vulcan launches planned for Amazons Kuiper satellite constellation, a potential Starlink rival. Meanwhile, though it took a few years, Blue Origin now has a truly orbital heavy-lift spacecraft: In January, it celebrated the inaugural launch of its towering New Glenn, a rocket thats only a bit shorter than NASAs Space Launch System and SpaceXs Starship. Future flights could launch national security payloads. Competition is emerging abroad as well. After repeated delays, Europes heavy-lift Ariane 6, from Airbus subsidiary Arianespace, had its inaugural flight last year, ending the European Space Agencys temporary dependence on SpaceX. A range of other companies are trying to expand European launch capacity, with assistance from ESA. China is moving quickly on its own launch organizations too. They had no less than seven commercial space launch companies that were all racing to develop an effective system that could deliver a payload into orbit, Kari Bingen, director of the Aerospace Security Project at the Center for Strategic and International Studies, says of Chinas efforts. They are moving fast and they have capital behind them, and they will absolutely be a competitor on the global market once theyre successful and probably undercut what US and European launch companies are doing. The up-and-coming Chinese launchers include Space Pioneers reusable Tianlong-3 rocket and Cosmoleaps Yueqian rocket. The latter is to feature a chopstick clamp recovery of the first stage, where its grabbed by the launch towers mechanical arms, similar to the concept SpaceX is testing for its Starship. Glitches and government Before SpaceXs rivals can really compete, they need to work out the kinks, demonstrate the reliability of their new spacecraft, and show that they can deliver low-cost launch services to customers. The process is not without its challenges. Boeings Starliner delivered astronauts to the ISS on its first crewed flight in June 2024, but after thruster malfunctions, they were left stranded at the orbital outpost for nine months. While New Glenn reached orbit as planned, its first stage didnt land successfully and its upper stage was left in orbit. SpaceX itself has had some recent struggles. The Federal Aviation Administration grounded the Falcon 9 more than once following malfunctions in the second half of 2024. The company still shattered records last year, though, with more than 130 Falcon 9 launches. It has continued with that record pace this year, despite additional Falcon 9 delays and more glitches with its booster and upper stage. SpaceX also conducted its eighth Starship test flight in March, just two months after the previous one, but both failed minutes after liftoff, raining debris down from the sky. Any company must deal with financial challenges as well as engineering ones. Boeing is reportedly considering selling parts of its space business, following Starliners malfunctions and problems with its 737 Max aircraft. And Virgin Orbit, the launch company that spun off from Virgin Galactic, shuttered in 2023. Another issue facing would-be commercial competitors to SpaceX in the US is the complex and uncertain political environment. Musk does not manage day-to-day operations of the company. But he has close involvement with DOGE, a Trump administration initiative that has been exerting influence on the workforces and budgets of NASA, the Defense Department, and regulators relevant to the space industry. Jared Isaacman, a billionaire who bankrolled the groundbreaking 2021 commercial mission Inspiration4, returned to orbit, again via a SpaceX craft, on Polaris Dawn last September. Now he may become Trumps NASA chief, a position that could give him the power to nudge NASA toward awarding new lucrative contracts to SpaceX. In February it was reported that SpaceXs Starlink might land a multibillion-dollar FAA contract previously awarded to Verizon. It is also possible that SpaceX could strengthen its position with respect to the regulatory scrutiny it has faced for environmental and safety issues at its production and launch sites on the coasts of Texas and Florida, as well as scrutiny of its rocket crashes and the resulting space debris. Oversight from the FAA, the Federal Communications Commission, and the Environmental Protection Agency may be weak. Conflicts of interest have already emerged at the FAA, and the Trump administration has also attempted to incapacitate the National Labor Relations Board. SpaceX had previously tried to block the board from acting after nine workers accused the company of unfair labor practices. SpaceX did not respond to MIT Technology Reviews requests for comment for this story. I think theres going to be a lot of emphasis to relieve a lot of the regulations, in terms of environmental impact studies, and things like that, Samson says. I thought thered be a separation between [Musks] interests, but now, its hard to say where he stops and the US government begins. Regardless of the politics, the commercial competition will surely heat up throughout 2025. But SpaceX has a considerable head start, Bingen argues: Its going to take a lot for these companies to effectively compete and potentially dislodge SpaceX, given the dominant position that [it has] had. Ramin Skibba is an astrophysicist turned science writer and freelance journalist, based in the Bay Are

Things are starting to warm up here in the New York City area, and its got me thinking once again about something that people arent talking about enough: energy demand for air conditioners. I get it: Data centers are the shiny new thing to worry about. And Im not saying we shouldnt be thinking about the strain that gigawatt-scale computing installations put on the grid. But a little bit of perspective is important here. According to a report from the International Energy Agency last year, data centers will make up less than 10% of the increase in energy demand between now and 2030, far less than the energy demand from space cooling (mostly air-conditioning). I just finished up a new story thats out today about a novel way to make heat exchangers, a crucial component in air conditioners and a whole host of other technologies that cool our buildings, food, and electronics. Lets dig into why Im writing about the guts of cooling technologies, and why this sector really needs innovation. One twisted thing about cooling and climate change: Its all a vicious cycle. As temperatures rise, the need for cooling technologies increases. In turn, more fossil-fuel power plants are firing up to meet that demand, turning up the temperature of the planet in the process. Cooling degree days are one measure of the need for additional cooling. Basically, you take a preset baseline temperature and figure out how much the temperature exceeds it. Say the baseline (above which youd likely need to flip on a cooling device) is 21 C (70 F). If the average temperature for a day is 26 C, thats five cooling degree days on a single day. Repeat that every day for a month, and you wind up with 150 cooling degree days. I explain this arguably weird metric because its a good measure of total energy demand for coolingit lumps together both how many hot days there are and just how hot it is. And the number of cooling degree days is steadily ticking up globally. Global cooling degree days were 6% higher in 2024 than in 2023, and 20% higher than the long-term average for the first two decades of the century. Regions that have high cooling demand, like China, India, and the US, were particularly affected, according to the IEA report. You can see a month-by-month breakdown of this data from the IEA here. That increase in cooling degree days is leading to more demand for air conditioners, and for energy to power them. Air-conditioning accounted for 7% of the worlds electricity demand in 2022, and its only going to get more important from here. There were fewer than 2 billion AC units in the world in 2016. By 2050, that could be nearly 6 billion, according to a 2018 report from the IEA. This is a measure of progress and, in a way, something we should be happy about; the number of air conditioners tends to rise with household income. But it does present a challenge to the grid. Another piece of this whole thing: Its not just about how much total electricity we need to run air conditioners but about when that demand tends to come. As weve covered in this newsletter before, your air-conditioning habits arent unique. Cooling devices tend to flip on around the same timewhen its hot. In some parts of the US, for example, air conditioners can represent more than 70% of residential energy demand at times when the grid is most stressed. The good news is that were seeing innovations in cooling technology. Some companies are building cooling systems that include an energy storage component, so they can charge up when energy is plentiful and demand is low. Then they can start cooling when its most needed, without sucking as much energy from the grid during peak hours. Weve also covered alternatives to air conditioners called desiccant cooling systems, which use special moisture-sucking materials to help cool spaces and deal with humidity more efficiently than standard options. And in my latest story, I dug into new developments in heat exchanger technology. Heat exchangers are a crucial component of air conditioners, but you can really find them everywherein heat pumps, refrigerators, and, yes, the cooling systems in large buildings and large electronics installations, including data centers. Weve been building heat exchangers basically the same way for nearly a century. These components basically move heat around, and there are a few known ways to do so with devices that are relatively straightforward to manufacture. Now, though, one team of researchers has 3D-printed a heat exchanger that outperforms some standard designs and rivals others. This is still a long way from solving our looming air-conditioning crisis, but the details are fascinatingI hope youll give it a read. We need more innovation in cooling technology to help meet global demand efficiently so we dont stay stuck in this cycle. And well need policy and public support to make sure that these technologies make a difference and that everyone has access to them too. This article is from The Spark, MIT Technology Reviews weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

Rumors of the ongoing death of software development that its being slain by AI are greatly exaggerated. In reality, software development is at a fork in the road: embracing the (currently) far-off notion of fully automated software development or acknowledging the work of a software developer is much more than just writing lines of code. The decision the industry makes could have significant long-term consequences. Increasing complacency around AI-generated code and a shift to what has been termed vibe coding where code is generated through natural language prompts until the results seem to work will lead to code thats more error-strewn, more expensive to run and harder to change in the future. And, if the devaluation of software development skills continues, we may even lack a workforce with the skills and knowledge to fix things down the line. This means software developers are going to become more important to how the world builds and maintains software. Yes, there are many ways their practices will evolve thanks to AI coding assistance, but in a world of proliferating machine-generated code, developer judgment and experience will be vital. The dangers of AI-generated code are already here The risks of AI-generated code arent science fiction: theyre with us today. Research done by GitClear earlier this year indicates that with AI coding assistants (like GitHub Copilot) going mainstream, code churn which GitClear defines as changes that were either incomplete or erroneous when the author initially wrote, committed, and pushed them to the companys git repo" has significantly increased. GitClear also found there was a marked decrease in the number of lines of code that have been moved, a signal for refactored code (essentially the care and feeding to make it more effective). In other words, from the time coding assistants were introduced theres been a pronounced increase in lines of code without a commensurate increase in lines deleted, updated, or replaced. Simultaneously, there's been a decrease in lines moved indicating a lot of code has been written but not refactored. More code isnt necessarily a good thing (sometimes quite the opposite); GitClears findings ultimately point to complacency and a lack of rigor about code quality. Can AI be removed from software development? However, AI doesnt have to be removed from software development and delivery. On the contrary, theres plenty to be excited about. As noted in the latest volume of the Technology Radar Thoughtworks report on technologies and practices from work with hundreds of clients all over the world the coding assistance space is full of opportunities. Specifically, the report noted tools like Cursor, Cline and Windsurf can enable software engineering agents. What this looks like in practice is an agent-like feature inside developer environments that developers can ask specific sets of coding tasks to be performed in the form of a natural language prompt. This enables the human/machine partnership. That being said, to only focus on code generation is to miss the variety of ways AI can help software developers. For example, Thoughtworks has been interested in how generative AI can be used to understand legacy codebases, and we see a lot of promise in tools like Unblocked, which is an AI team assistant thatsupport for new languages in an internal tool, CodeConcise. We use CodeConcise to understand legacy systems; and while our success was mixed, we do think theres real promise here. Tightening practices to better leverage AI Its important to remember much of the work developers do isnt developing something new from scratch. A large proportion of their work is evolving and adapting existing (and sometimes legacy) software. Sprawling and janky code bases that have taken on technical debt are, unfortunately, the norm. Simply applying AI will likely make things worse, not better, especially with approaches like vibe. This is why developer judgment will become more critical than ever. In the latest edition of the Technology Radar report, AI-friendly code design is highlighted, based on our experience that AI coding assistants perform best with well-structured codebases. In practice, this requires many different things, including clear and expressive naming to ensure context is clearly communicated (essential for code maintenance), reducing duplicate code, and ensuring modularity and effective abstractions. Done together, these will all help make code more legible to AI systems. Good coding practices are all too easy to overlook when productivity and effectiveness are measured purely in terms of output, and even though this was true before there was AI tooling, software development needs to focus on good coding first. AI assistance demands greater human responsibility Instagram co-founder Mike Krieger recently claimed that in three years software engineers wont write any code: they will only review AI-created code. This might sound like a huge claim, but its important to remember that reviewing code has always been a major part of software development work. With this in mind, perhaps the evolution of software development wont be as dramatic as some fear. But theres another argument: as AI becomes embedded in how we build software, software developers will take on more responsibility, not less. This is something weve discussed a lot at Thoughtworks: the job of verifying that an AI-built system is correct will fall to humans. Yes, verification itself might be AI-assisted, but it will be the role of the software developer to ensure confidence. In a world where trust is becoming highly valuable as evidenced by the emergence of the chief trust officer the work of software developers is even more critical to the infrastructure of global industry. Its vital software development is valued: the impact of thoughtless automation and pure vibes could prove incredibly problematic (and costly) in the years to come. This content was produced by Thoughtworks. It was not written by MIT Technology Reviews editorial staff.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. How 3D printing could make better cooling systems A new 3D-printed design could make an integral part of cooling systems like air conditioners or refrigerators smaller and more efficient, according to new research. Heat exchangers are devices that whisk away heat, and theyre everywhereused in data centers, ships, factories, and buildings. The aim is to pass as much heat as possible from one side of the device to the other. Most use one of a few standard designs that have historically been easiest and cheapest to make. Energy demand for cooling buildings alone is set to double between now and 2050, and new designs could help efficiently meet the massive demand forecast for the coming decades. Read the full story. Casey Crownhart MIT Technology Review Narrated: The quest to figure out farming on Mars If were going to live on Mars well need a way to grow food in its arid dirt. Researchers think they know a way. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which were publishing 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 its released. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Thousands of US health agency workers have been laid off Experts warn that patients will die preventable deaths as a result. (Wired $)+ How will the US respond to the measles and bird flu outbreaks? (Reuters)+ US cuts could lead to serious delays in forecasting extreme weather. (Undark)+ The wide-ranging cuts are also likely to lose America money. (The Atlantic $)2 Donald Trump is set to discuss a proposal to save TikTok Hes due to meet with aides today to thrash out a new ownership structure. (NYT $)+ Oracle and Blackstone are among the companies in talks to make an offer. (WSJ $)+ The White House is playing the role of investment bank. (The Guardian)3 X has asked the Supreme Court to exempt its users from law enforcementIt claims to be worried by broad, suspicionless requests. (FT $) 4 Things arent looking good for Mexico-based Chinese companies Trumps tariff plans could imperil an awful lot of deals. (WSJ $)+ The US Chips Act is another probable casualty. (Bloomberg $)5 US lawmakers want to regulate AI companionsA proposed bill would allow users to sue if they suffer harm from their interactions with a companion bot. (WP $) + We need to prepare for addictive intelligence. (MIT Technology Review) 6 Covid hasnt gone awayAnd life for the covid-conscious is getting increasingly difficult. (The Atlantic $) 7 Brands are trying to game Reddit to show up in ChatGPT recommendationsCatering to AI search is a whole business model now. (The Information $) + Your most important customer may be AI. (MIT Technology Review)8 Nothing could destroy the universe Humans have long been obsessed with nothingness. (New Scientist $)9 Would you flirt with a chatbot?Tinder wants you to give it a go. (Bloomberg $) + The AI relationship revolution is already here. (MIT Technology Review)10 Trading in your Tesla is TikToks favorite trend Clips of Tesla owners ditching their cars are going viral. (Fast Company $)+ This guy returned his Cybertruck out of fear his daughter would get bullied. (Insider $)+ Sales of new Teslas are slumping too. (NYT $)Quote of the day Id get on in a heartbeat. Butch Wilmore, one of the pair of astronauts who was stuck in space for nine months, explains how hed be willing to fly on the beleaguered Starliner again, the Washington Post reports. The big story Bringing the lofty ideas of pure math down to earth April 2023Pradeep Niroula Mathematics has long been presented as a sanctuary from confusion and doubt, a place to go in search of answers. Perhaps part of the mystique comes from the fact that biographies of mathematicians often paint them as otherworldly savants. As a graduate student in physics, I have seen the work that goes into conducting delicate experiments, but the daily grind of mathematical discovery is a ritual altogether foreign to me. And this feeling is only reinforced by popular books on math, which often take the tone of a pastor dispensing sermons to the faithful.Luckily, there are ways to bring it back down to earth. Popular math books seek a fresher take on these old ideas, be it through baking recipes or hot-button political issues. My verdict: Why not? Its worth a shot. Read the full story. 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 or skeet 'em at me.) + Why are cats the way they are? This database might help us find out.+ John McFall could become the first disabled person in space.+ ASMR at the V&A is just delightful.+ Addicted to lip balm? Youre not the only one.

A new 3D-printed design could make an integral part of cooling systems like air conditioners or refrigerators smaller and more efficient, according to new research. Heat exchangers are devices that whisk away heat, and theyre everywhereused in data centers, ships, factories, and buildings. The aim is to pass as much heat as possible from one side of the device to the other. Most use one of a few standard designs that have historically been easiest and cheapest to make. Heat exchangers are at the center of the industrial economy. Theyre an essential part of every machine and every system that moves energy, says William King, a professor at the University of Illinois Urbana-Champaign and one of the authors of the new study. Existing designs tend to favor straight lines, right angles, and round tubes, he adds. King and his colleagues used 3D printing to design a heat exchanger that includes features to optimize heat movement, like wavy walls and pyramid-shaped bumps, which wouldnt be possible to make using traditional manufacturing techniques. The team had set out to design a system based on a common refrigerant called R-134a, which is commonly used in devices like air conditioners and refrigerators. When cold water lowers the temperature of the refrigerant, it changes from a gas to a liquid on its path through the device. That liquid refrigerant can then go on to other parts of the cooling system, where its used to lower the temperature of anything from a room to a rack of servers. The best way to cool the refrigerant tends to involve building very thin walls between the two sides of the device and maximizing the amount of contact that the water and the refrigerant make with those walls. (Think about how much colder youd get wearing a thin T-shirt and pants and lying down on ice than simply touching it with your gloved hands.) To design the best possible heat exchanger, researchers used simulations and developed machine-learning models to help predict the performance of different designs under different conditions. After 36,000 simulations, the researchers landed on the one they decided to develop. Among the key components: small fins that jut out on the side of the device that touches the water, increasing the surface area to maximize heat transfer. The team also designed wavy passageways for the water to pass throughonce again helping to maximize surface area. Simulations helped the researchers figure out exactly how curvy the passages should be and where precisely to place the fins. On the side of the devices where the refrigerant passes through, the design includes small pyramid-shaped bumps along the walls. These not only maximize the area for cooling but also help mix the refrigerant as it passes through and prevent liquid from coating the wall (which would slow down the heat transfer). After settling on a design, the researchers used a 3D-printing technique called direct metal laser sintering, in which lasers melt and fuse together a metal powder (in this case, an aluminum alloy), layer by layer. In testing, the researchers found that the heat exchanger created with this technique was able to cool down the refrigerant more efficiently than other designs. The new device was able to achieve a power density of over six megawatts per meter cubedoutperforming one common traditional design, the shell-tube configuration, by between 30% and 50% with the same pumping power. The devices power density was similar to that of brazed plate heat exchangers, another common design in industry. Overall, this device doesnt dramatically outperform the state-of-the-art technology, but the technique of using modeling and 3D printing to produce new heat exchanger designs is promising, says Dennis Nasuta, director of research and development at Optimized Thermal Systems, a consulting firm that works with companies in the HVAC industry on design and research. Its worth exploring, and I dont think that we know yet where we can push it, Nasuta says. One challenge is that today, additive manufacturing techniques such as laser sintering are slow and expensive compared with traditional manufacturing; they wouldnt be economical or feasible to rely on for all our consumer cooling devices, he says. For now, this type of approach could be most useful in niche applications like aerospace and high-end automotives, which could more likely bear the cost, he adds. This particular study was funded by the US Office of Naval Research. Next-generation ships have more electronics aboard than ever, and theres a growing need for compact and efficient systems to deal with all that extra heat, says Nenad Miljkovic, one of the authors of the study. Energy demand for cooling buildings alone is set to double between now and 2050, and new designs could help efficiently meet the massive demand forecast for the coming decades. But challenges including manufacturing costs would need to be overcome to help innovations like the one designed by King and his team make a dent in real devices. Another barrier to adopting these new techniques, Nasuta says, is that current standards dont demand more efficiency. Other technologies already exist that could help make our devices more efficient, but theyre not used for the same reason. It will take time for new manufacturing techniques, including 3D printing, to trickle into our devices, Natsua adds: This isnt going to be in your AC next year.

The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Tech companies are warning their immigrant workers not to leave the US Employees on high-skilled visas could be denied entry back into the States. (WP $)+ Officials are considering collecting citizenship applicants social media data. (Associated Press)2 OpenAI has closed one of the largest private funding rounds in historyIt plans to put the $40 billion cash injection towards building AGI. (The Guardian)+ The deal values OpenAI at a whopping $300 billion. (CNBC)+ The company also teased its first open-weight model in years. (Insider $)3 SpaceX has launched a mission thats never been attempted before Its taking private customers on an orbit between Earths North and South poles. (CNN)+ Crypto billionaire Chun Wang is footing the bill for the mission. (Reuters)+ Europe is finally getting serious about commercial rockets. (MIT Technology Review)4 Some DOGE workers are returning to their old jobsTheyre quietly heading back to their roles at X and SpaceX. (The Information $)+ Top staff were placed on leave after denying DOGE access to their systems. (Wired $) + Can AI help DOGE slash government budgets? Its complex. (MIT Technology Review)5 Amazon is going all-in on AI agents Its new AI model Nova Act is designed to complete tasks such as online shopping. (The Verge)+ Why handing over total control to AI agents would be a huge mistake. (MIT Technology Review)6 DeepMind is making it harder for its researchers to publish studies Its reluctant to share innovations that rivals could capitalize on. (FT $)7 Meet the protestors staking out Tesla dealershipsProfessors and attorneys have taken to the streets to fight back. (New Yorker $) + Far-right extremists are turning up to defend the company. (Wired $)

On March 27, the results of the first clinical trial for a generative AI therapy bot were published, and they showed that people in the trial who had depression or anxiety or were at risk for eating disorders benefited from chatting with the bot. I was surprised by those results, which you can read about in my full story. There are lots of reasons to be skeptical that an AI model trained to provide therapy is the solution for millions of people experiencing a mental health crisis. How could a bot mimic the expertise of a trained therapist? And what happens if something gets complicateda mention of self-harm, perhapsand the bot doesnt intervene correctly? The researchers, a team of psychiatrists and psychologists at Dartmouth Colleges Geisel School of Medicine, acknowledge these questions in their work. But they also say that the right selection of training datawhich determines how the model learns what good therapeutic responses look likeis the key to answering them. Finding the right data wasnt a simple task. The researchers first trained their AI model, called Therabot, on conversations about mental health from across the internet. This was a disaster. If you told this initial version of the model you were feeling depressed, it would start telling you it was depressed, too. Responses like, Sometimes I cant make it out of bed or I just want my life to be over were common, says Nick Jacobson, an associate professor of biomedical data science and psychiatry at Dartmouth and the studys senior author. These are really not what we would go to as a therapeutic response. The model had learned from conversations held on forums between people discussing their mental health crises, not from evidence-based responses. So the team turned to transcripts of therapy sessions. This is actually how a lot of psychotherapists are trained, Jacobson says. That approach was better, but it had limitations. We got a lot of hmm-hmms, go ons, and then Your problems stem from your relationship with your mother, Jacobson says. Really tropes of what psychotherapy would be, rather than actually what wed want. It wasnt until the researchers started building their own data sets using examples based on cognitive behavioral therapy techniques that they started to see better results. It took a long time. The team began working on Therabot in 2019, when OpenAI had released only its first two versions of its GPT model. Now, Jacobson says, over 100 people have spent more than 100,000 human hours to design this system. The importance of training data suggests that the flood of companies promising therapy via AI models, many of which are not trained on evidence-based approaches, are building tools that are at best ineffective, and at worst harmful. Looking ahead, there are two big things to watch: Will the dozens of AI therapy bots on the market start training on better data? And if they do, will their results be good enough to get a coveted approval from the US Food and Drug Administration? Ill be following closely. Read more in the full story. This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first,sign up here.

Tech companies are always trying out new ways for people to interact with computersconsider efforts like Google Glass, the Apple Watch, and Amazons Alexa. Youve probably used at least one. But the most radical option has been tried by fewer than 100 people on Earththose who have lived for months or years with implanted brain-computer interfaces, or BCIs. Implanted BCIs are electrodes put in paralyzed peoples brains so they can use imagined movements to send commands from their neurons through a wire, or via radio, to a computer. In this way, they can control a computer cursor or, in few cases, produce speech. Recently, this field has taken some strides toward real practical applications. About 25 clinical trials of BCI implants are currently underway. And this year MIT Technology Review readers have selected these brain-computer interfaces as their addition to our annual list of 10 Breakthrough Technologies, published in January. BCIs won by a landslide to become the 11th Breakthrough, as we call it. It beat out three runners-up: continuous glucose monitors, hyperrealistic deepfakes, and methane-detecting satellites. The impression of progress comes thanks to a small group of companies that are actively recruiting volunteers to try BCIs in clinical trials. They are: Neuralink, backed by the worlds richest person, Elon Musk; New Yorkbased Synchron; and Chinas Neuracle Neuroscience. Each is trialing interfaces with the eventual goal of getting the fields first implanted BCI approved for sale. I call it the translation era, says Michelle Patrick-Krueger, a research scientist who carried out a detailed survey of BCI trials with neuroengineer Jose Luis Contreras-Vidal at the University of Houston. In the past couple of years there has been considerable private investment. That creates excitement and allows companies to accelerate. Thats a big change, since for years BCIs have been more like a neuroscience parlor trick, generating lots of headlines but little actual help to patients. Patrick-Krueger says the first time a person controlled a computer cursor from a brain implant was in 1998. That was followed by a slow drip-drip of tests in which university researchers would find a single volunteer, install an implant, and carry out studies for months or years. Over 26 years, Patrick-Krueger says, she was able to document a grand total of 71 patients whove ever controlled a computer directly with their neurons. That means you are more likely to be friends with a Mega Millions jackpot winner than know someone with a BCI. These studies did prove that people could use their neurons to play Pong, move a robot arm, and even speak through a computer. But such demonstrations are of no practical help to people with paralysis severe enough to benefit from a brain-controlled computer, because these implants are not yet widely available. One thing is to have them work, and another is how to actually deploy them, says Contreras-Vidal. Also, behind any great news are probably technical issues that need to be addressed. These include how long an implant will last and how much control it offers patients. Larger trials from three companies are now trying to resolve these questions and set the groundwork for a real product. One company, Synchron, uses a stent with electrodes on it thats inserted into a brain vessel via a vein in the neck. Synchron has implanted its stentrode in 10 volunteers, six in the US and four in Australiathe most simultaneous volunteers reported by any BCI group. The stentrode collects limited brain signals, so it gives users only a basic on/off type of control signal, or what Synchron calls a switch. That isnt going to let a paralyzed person use Photoshop. But its enough to toggle through software menus or select among prewritten messages. Tom Oxley, Synchrons CEO, says the advantage of the stentrode is that it is as simple as possible. That, he believes, will make his brain-computer interface scalable to more people, especially since installing it doesnt involve brain surgery. Synchron might be ahead, but its still in an exploratory phase. A pivotal study, the kind used to persuade regulators to allow sales of a specific version of the device, has yet to be scheduled. So theres no timeline for a product. Neuralink, meanwhile, has disclosed that three volunteers have received its implant, the N1, which consists of multiple fine electrode threads inserted directly into the brain through a hole drilled in the skull. More electrodes mean more neural activity is captured. Neuralinks first volunteer, Noland Arbaugh, has shown off how he can guide a cursor around a screen in two dimensions and click, letting him play video games like Civilization or online chess. Finally, Neuracle says it is running two trials in China and one in the US. Its implant consists of a patch of electrodes placed on top of the brain. In a report, the company said a paralyzed volunteer is using the system to stimulate electrodes in his arm, causing his hand to close in a grasp. But details remain sparse. A Neuracle executive would only say that several people had received its implant. Because Neuracles patient count isnt public, it wasnt included in Patrick-Kruegers tally. In fact, theres no information at all in the medical literature on about a quarter of brain-implant volunteers so far, so she counted them using press releases or by e-mailing research teams. Her BCI survey yielded other insights. According to her data, implants have lasted as long as 15 years, more than half of patients are in the US, and roughly 75% of BCI recipients have been male. The data cant answer the big question, though. And that is whether implanted BCIs will progress from breakthrough demonstrations into breakout products, the kind that help many people. In the next five to 10 years, its either going to translate into a product or itll still stay in research, Patrick-Krueger says. I do feel very confident there will be a breakout.