At the end of a tense and scoreless first half of a soccer match between the English men’s team and rival Germany, millions of Brits let out a collective sigh and did what they so often do in moments of stress: They made tea. That wave of electric kettles clicking on, however, caused a different kind of stress: a huge and sudden increase in demand for electricity. But National Grid, which operates the local transmission network, was ready. Just as those kettles started heating up, an AI program sent instructions to a data center in London to slow down some of the facility’s power-hungry chips. This reduction helped make sure there was enough supply to match demand, staving off potential blackouts or damage to electrical hardware. For data centers, which normally guzzle power without consideration for anyone or anything else’s needs, it was a radical departure. It was also a simulation. In December 2025, engineers sought to test a new breed of data center built to be flexible about its electricity needs, so they re-created the energy demand facing the UK’s grid during a match from the 2020 Euro tournament. They wanted to see how their software, called Conductor, would have responded had it been online at the time. Conductor is the signature product of Emerald AI, a firm based in Washington, DC, that’s part of a wave of companies trying to figure out whether data centers can work within the confines of the existing electric grid.
This year, Emerald is set to deploy Conductor in a new facility in the part of Virginia known as Data Center Alley, this time connected to the live grid. When overall demand spikes, Conductor will turn down the power used by the data center, while making sure its servers still carry out their timeliest and most important jobs. Emerald’s partners on the project—which include Nvidia and the giant data-center operator Digital Realty—bill it as one of the world’s first “power-flexible AI factories.” Demonstrating that data centers can participate in this kind of give-and-take could ease what many tech leaders identify as the bottleneck in getting facilities online: It takes far longer to get approval for, construct, and connect new power plants than to build data centers. PJM, the grid operator in Virginia and the largest one in the US, for instance, needs eight years to bring new generation online, according to RMI, an energy research and advocacy group. “We need to solve the energy equation,” says Josh Parker, head of sustainability at Nvidia. “AI factory flexibility is the bridge between the incredible demand for AI and the immediate limitations of our energy grid.”
Speed, though, is only one of the issues. Once facilities do plug in, neighbors often criticize them for drawing too much electricity and contributing to rising prices. They say the data centers generate more noise than they do long-term jobs, contribute to pollution, and threaten to put people out of work. Organizers stalled over $150 billion worth of projects in 2025, according to Data Center Watch, and policymakers alert to the public mood are starting to impose limitations on development. More than a dozen states are considering bans, and local moratoriums are in effect in places like Minneapolis and DeKalb County in Georgia. At the federal level, the GRID Act, a bipartisan bill in the US Senate, proposes to sever new data centers from public grids entirely. Some operators are already moving that way by trying to develop their own power generation. Rather than rushing to build new power plants, companies could find part of the solution to the crunch right under our noses—or, more precisely, in the transmission lines under our feet and above our heads. The existing system operates near its full capacity during only a small number of high-demand hours throughout the year. This means, some grid experts argue, that if data centers can limit the power they draw during those stretches, they won’t need to wait for big infrastructure upgrades or build their own off-grid generation.  Indeed, a growing number of studies have shown there could be plenty of power available for data centers that can flex. A widely discussed 2025 report from researchers at Duke University found that the US grid could offer an additional 76 gigawatts—about 5% of its entire capacity, and about enough to accommodate projected data-center growth in the US through 2030—to facilities that are willing to reduce their usage just 0.25% of the time. That’s about 22 hours a year. And when researchers from Princeton University and two grid-modernization companies looked at locations for new data centers in the PJM region, their report, which was funded by Google, found that a 500-megawatt facility capable of flexing for less than 1% of the year could reach full operation three to five years faster than one that’s inflexible.  Flexible power connections could also help data centers address some of their PR problems. By decreasing their draw at times of grid stress, for instance, they could avoid diverting power from where it’s most needed, thus boosting stability. By using existing capacity, they might be able to reduce the need for new fossil-fuel power plants and spread fixed costs over more electricity users, pushing prices down.  The AI power pinch is attracting resources and research into strategies for grid flexibility overall, which could help negotiate a tricky period: Taken together with electric vehicles, air-conditioning, and other sectors, data centers are helping drive what analysts predict will be a 25% increase in US electricity demand by 2030 compared with 2023 levels. Ideally, flexibility gives grid operators more control over the flow of electrons, making them leaders of a harmonious ensemble rather than hostages to inflexible electricity requirements. That will help them manage demand spikes across the entire system and deal more effectively with the intermittent nature of renewables like wind and solar. “Demand flexibility is incredibly useful for power grids,” says Johanna Mathieu, a grid expert at the University of Michigan. “It helps reduce electricity costs and improve grid reliability.” But while advocates see plenty of benefits, the concept brings complexity. For data centers, compromising on energy needs can be a hard sell. Flexibility requires utilities and grid operators, which tend to be operationally conservative, to change long-held practices. And some skeptics also say that flexibility distracts from the very real need to build more grid infrastructure faster, and could even pose risks to our electricity supply. 

Still, some technologists, grid operators, and utilities are hoping to show that flexibility works—not only in white papers or simulations but in real life.  The poster children for data-center growth default toward inflexibility. Hyperscalers like Microsoft and Oracle have proposed enormous new centers, many of which would rely on off-grid, natural-­gas-burning power plants. When xAI wanted to speed up the buildout of the Colossus site outside Memphis, Tennessee, it rolled up with gas turbines on flatbed trucks. The facility, now in operation, is facing blowback from regulators and residents about the spike it’s causing in emissions and other pollution. In any case, there aren’t enough gas turbines worldwide to meet the demand from data-center operators.  One big obstacle for anyone demanding a lot of power is that our grids are mostly rigid. They’re designed to supply enough power to meet total demand when it’s highest, even if that’s for only a relatively small number of hours a year. That conservative approach is a simple route to reliability, but it means that the grid has quite a bit of headroom. “The grid is already overbuilt by a lot. If you were an airline running at 30% utilization, you would not buy more planes,” says Amit Narayan, the cofounder and CEO of GridCare, a company developing flexibility technologies, referring to a 2025 Stanford study of transmission lines in western North America. “If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.”  “If you were an airline running at 30% utilization, you would not buy more planes. If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.” To be fair, the idea of flexibility isn’t entirely foreign to grid operators. For decades, they’ve practiced a technique called demand response: When it looks as if demand will get too close to supply, as it might during a heat wave when many people turn on the AC at the same time, they call large commercial or industrial facilities and ask them to shut down parts of their operations. This method can help avoid the need to fire up so-called peaker plants, which run on fossil fuels, but it’s slow, imprecise, and hard to scale. In the 2000s, as the adoption of technologies like electric cars and solar panels presented new challenges, more internet-­connected grids also provided new means of flexibility. Virtual power plants, or VPPs, offered a smarter, faster, more granular alternative. Electricity customers ranging from factories to homeowners with smart thermostats, solar panels, or big batteries would allow the utility to adjust their draw to help meet demand—often getting paid for their (frequently unnoticed) trouble.  After the generative AI boom began with the release of ChatGPT in 2022, some companies began to see flexibility as a way to get data centers set up more easily, efficiently, and affordably. If they bring AI money into existing grids and reduce or defer the need for expensive upgrades, data centers could actually help spread out fixed costs so as to lower rates for other users. A study from Duke University published this past February, for instance, found that flexibility could reduce rates by 0.5% to 2.8%.  PETRA PÉTERFFY The trick is figuring out how data centers, notorious power hogs, can keep operating when their flexible connections are throttled. Flexibility specialists envision three possible ways. The simplest is for the new data center to install on-site backup power storage or generation to tap when the grid is maxed out—at their own expense, of course. A facility could also fill the gap by drawing on a VPP. The utility would turn down the electricity going to users who signed up for the VPP, and the data center would pay them for their flexibility. This method wouldn’t require any major infrastructure, but it would require the utility to have a big VPP program and to coordinate the exchange at a time when the grid was under stress. While VPPs exist to some extent in nearly 40 states, the rules governing them vary widely, and they are empowered to do more in some areas than in others. 
Finally, a data center could simply use less power at peak times. The conventional wisdom is that they won’t go for such limits, particularly when every number-­crunching server can feel like a goose potentially laying little golden eggs. But some experts are betting that the value of getting up and running quickly is enough to change their minds. “There is a clear and growing trend,” says Ayse Coskun, chief scientist at Emerald AI. “Operators are increasingly willing to trade some level of flexibility for faster grid interconnection.”  GridCare, a startup based in Silicon Valley, was one of the first companies to use flexibility to get data centers online quickly. Instead of looking at grids only in worst-case scenarios when electricity demand is highest, the company analyzes the system under all conditions, explains CEO Narayan, who studied smart grids at Stanford. It feeds every part of the grid—including power plants, lines, substations, and homes—into a generative AI model that creates a “digital twin” for different grid configurations. It then picks out results that could unlock capacity while maintaining reliability, and it feeds those into another model trained on the physics of electrical components like resistors and capacitors to make sure they’re realistic.
GridCare found its first customer in the Silicon Forest, an area in the Pacific Northwest named for the trees that dominate the landscape and the IT industry that has more recently sprouted up there. The local grid needed more capacity to support more data centers. “Data centers wanted ‘speed to power,’” says Isaac Barrow, a manager of data-center relations at Portland General Electric, or PGE, the local power generator and distributor, “but transmission buildout is a long process that’s very costly.” In 2024, Aligned Data Centers came to PGE wanting to expand its operation in Hillsboro, Oregon, and PGE followed a recommendation from GridCare. Aligned will install a 31-megawatt battery, set to be in service in May 2027, and decrease its draw by up to that amount when the grid becomes congested. Bundled with other flexibility measures, that battery has allowed PGE to increase the capacity it can offer Aligned and other nearby operators by 80 megawatts without any new power plants. Though the buildout of data centers in Hillsboro has faced plenty of pushback from locals, Barrow points out that it could have the knock-on effect of lowering costs for ratepayers, because it spreads out the tab. Other companies are promoting different flavors of flexibility. Google has been moving processing loads from facilities in areas experiencing demand spikes to those in less stressed spots since 2023. It’s signed agreements with five utilities, including the Tennessee Valley Authority and Indiana Michigan Power, that add as much as a gigawatt of flexibility.  Voltus, a major VPP provider across the US and Canada, markets a “bring your own capacity” program in which a data-­center company can fund a VPP nearby. The grid operator can use the VPP to decrease demand at busy times, and participants get a financial thank-you. “We can spin up new VPPs on the order of months,” says Emily Orvis, Voltus’s vice president of energy markets. In June, the company signed their first such data-center deal: a three-year plan in which Google will bankroll a VPP in the PJM interconnection. Of all the approaches to flexibility, Emerald AI’s may be the most ambitious: asking data centers to dial into the grid’s needs. The company’s Conductor software, which can run on premises or in the cloud, builds on the research of chief scientist Coskun. Her group at Boston University showed in a pair of 2013 papers that a data center could watch the grid and help balance big power fluctuations, such as the intermittent effects of solar and wind power. By 2022, she and her colleagues had tested their methods on a cluster of 36 research servers and shown that the system could respect power limits without breaking the processes it was running.  One of the most important questions for Conductor is deciding which AI processes can be slowed down to save energy without kneecapping performance. A lot of companies label their jobs by priority—a real-time chatbot query, for instance, might outrank something like a web search that’s part of a deep research project. When they don’t, Emerald AI tries to infer priority from the nature of the job. Conductor then analyzes the AI workload to determine how tweaking the power to a given processor will affect the performance and help meet the usage limits set by the grid operator.
“The performance curve changes for different kinds of workloads,” says Coskun. “Each AI job is going to have a different location on that curve. Our intelligence is figuring out where you are on that curve.”  PETRA PÉTERFFY Last year, Emerald AI began assessing the technology’s readiness for real-world use in a series of tests, raising the difficulty each time. The trials were carried out in partnership with the Data Center Flexible Load Initiative—a collaboration among tech companies like Google and Nvidia, utilities like Duke Energy, and grid operators like PJM that aims to help establish a repeatable framework for power-­flexible data centers. The first challenge was in Phoenix, a fast-growing computing hub. For the test, Conductor took control of a group of server racks laden with 256 Nvidia A100 GPUs—hardware that can use about as much power as around 170 US homes. When presented with a simulation of a busy grid, Conductor reduced the power to the chips by 25% for three hours, while maintaining acceptable computing performance. Emerald AI and its partners reported the results in a paper in Nature Energy in December 2025. The next trial forced the system to juggle surprise grid fluctuations without advance warning and redirect AI jobs from a data center in Virginia to a less busy one in Chicago. Then, in London, Conductor took the reins of equipment beyond the main GPU processors and faced a more complicated mix of fluctuations, including very short and long bouts of congestion—plus the notorious teakettle effect.
The progress so far shows that flexibility can work, at least in some situations, but only a small fraction of operators have pursued it as yet. “We’re just in the beginning innings of the game,” says Jesse Jenkins, one of the authors of the 2025 Princeton study and cofounder of Firma, a startup that works on data-center flexibility. “People are recognizing that this is a potential solution. The motivation is there; there are some bespoke examples. But there’s no uniform solution set that’s the default option, which is where we need to get.” While data centers are going up across the US, no place on Earth comes close to the accumulated computing muscle in Northern Virginia’s Data Center Alley. The region is home to around 500 compute-crunching facilities, which represent 13% of the entire world’s capacity; the next two hot spots, Beijing and Oregon, contain 6% each. There are proposals to build hundreds more facilities in Virginia, but a government study found that the state’s electricity demand will increase 183% (around 26 gigawatts) by 2040 if they all go forward, and supporting even half would be difficult. The power-flexible data center that Emerald AI, Nvidia, Digital Realty, and their partners are building in the suburb of Manassas could demonstrate how data centers can squeeze the power they need out of existing capacity. The facility, slated to come online later this year, is intended to give Conductor the chance to manage power at the largest scale yet and to respond to conditions on a live grid for the first time. In the UK demonstration, Conductor managed a 130-kilowatt AI cluster; in Manassas, it will pull the strings of a 96-megawatt hyperscale AI factory.  Some degree of flex will play a key role as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars. For PJM, the Manassas facility points to a potential path through the current power crunch. “We think data-center flexibility, in different forms, will be essential for the reliable integration of data-center load over the short to mid term,” says Scott Baker, who manages demand-side markets at PJM.  But not all grid experts are so sanguine. PJM’s market monitor, which oversees the grid operator, says there are no workarounds when it comes to adding capacity. “The notion that large amounts of data-center load can be added without adding new generation is magical thinking,” says Joseph Bowring, an economist and the head of PJM’s market monitor since 1999. One problem, he says, is that there’s no way to guarantee that a data center will actually take less power when demand is high. That is, absent any legal or regulatory push for flexibility or compliance, the utility won’t be able to step in to help prevent, say, a blackout. Utilities can rely on resources like power plants, but they can’t control or rely on data centers. “They do not want to be fully interruptible,” Bowring says of the facilities. Stephen Empedocles, an advisor for technology companies, views flexibility as more of a tool than a silver bullet. “These approaches are excellent for improving grid reliability and getting more out of the infrastructure we already have,” he says, “but they are optimization tools.” They’re not substitutes for the “generation, transmission, and distribution expansion that will still be required,” he continues. Flexibility advocates agree that over the long term, whether or not AI continues to boom, electrification will drive a need for more generation and transmission. Some degree of flex will play a key role in using grid infrastructure better as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars. A report published by the International Renewable Energy Agency in January 2026 found that grids around the world will need three times as much flexibility in 2030 as they had in 2019—and 10 times as much by 2050—to balance increasing demand with fluctuating supplies of renewable energy.  The challenge of powering AI could provide just the spark we need to do the work of designing and building smarter, more flexible grids, says Coskun. “I think with a crisis like this, there’s no quick solution,” she says. “Sometimes a crisis like this creates an opportunity to do something differently.”  Amos Zeeberg is a freelance science and technology journalist based in Bucharest. He’s developing a book about technology networks, including electric grids.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. When I landed in Seoul after a grueling 12-hour flight from San Francisco, I walked through an unmanned immigration checkpoint, where a machine scanned my face and passport. On the subway home, people were glued to their phones (powered by flawless 5G even underground), as we raced past platforms lined with LED screens of ads celebrating K-pop idols’ birthdays. When I got off the station in Gangnam, a cartoon-eyed robot on wheels was waiting patiently at a crosswalk to deliver someone’s dinner. Internet cafés dotted the sidewalks, crammed with teenagers playing computer games, maybe hoping to become the next legendary pro gamer. I stood at a bus stop with interactive touch screens showing real-time bus schedule updates. It will soon become an “AI bus stop,” the Gangnam district announced in June, with a kiosk that answers riders’ questions in multiple languages. The news didn’t surprise me. Having grown up in the city, I’ve watched Seoul transform from a scrappy boomtown into the gleaming tech capital it is today. South Korea loves AI.
While a public backlash against AI is brewing across the US, South Koreans are optimistic. Only 16% say they are more concerned than excited about AI—the lowest of any of the 25 countries surveyed by the Pew Research Center—while 50% of Americans were more worried than excited. A majority of Koreans use AI every day, either as a sort of personal assistant or to do tasks at work, according to surveys by the Ministry of Culture, Sports, and Tourism and Korea Chamber of Commerce and Industry. One of the most wired countries in the world, South Korea loves to street-test every new technology on the block—AI webcomics, virtual K-pop idols, and humanoid monks. And the appetite for experimentation doesn’t stop with ordinary citizens. Government agencies are early adopters too, deploying AI textbooks in schools and AI eldercare robots in welfare centers. South Koreans share a deep conviction that embracing technology is integral to modernizing the country and cementing its place in the global order. Their fascination with AI is just the latest incarnation of that ethos—and it’s making them anxious to stay ahead.
Engineered enthusiasm All this techno-optimism has largely been engineered by South Korea’s national agenda to make AI a motor of economic growth. “The South Korean government has designated an AI-powered Fourth Industrial Revolution as the country’s path forward and aggressively promoted and invested in it,” says Chihyung Jeon, a professor of science and technology policy at the Korea Advanced Institute of Science and Technology. “South Koreans have consistently and relentlessly been told by the government about AI’s potential to create a better future.” As South Korea rose from the ashes of the Korean War, technology lifted the nation from poverty into an economic powerhouse. In the 1970s, South Korea manufactured steel and ships, then semiconductors in the 1980s, broadband in the 1990s, and smartphones in the 2000s. Today, Samsung and SK Hynix supply most of the world’s high-bandwidth memory chips, which power the cutting-edge Nvidia hardware used to train AI models. South Korea’s economy now orbits these two semiconductor giants: The country’s main equity index, Kospi, surged to record highs in 2026, powered by the soaring share prices of both companies, each valued above $1 trillion. Lee Jae-myung, president of South Korea, has pledged to vault the country into the ranks of the “top three AI powers” alongside the US and China. After taking office in 2025, he launched the Presidential Council on National AI Strategy to help buy massive amounts of computing power and a sovereign AI foundation model project that funds Korean companies to develop homegrown AI models. The government has also supported semiconductor titans, including Samsung and SK Hynix, through generous tax credits and low-interest financing.  South Korea’s policy posture also prioritizes accelerating AI development over safety considerations. In 2024, South Korea’s legislature passed the AI Basic Act, one of the world’s first comprehensive AI laws, to promote AI development and establish light-touch regulatory guardrails. Seventy percent of South Koreans say advancing science and medicine through AI innovation is a bigger priority than protecting industries through regulation, according to the 2026 Stanford AI Index. All of that effort might be paying off. The same index ranked South Korea as having the third largest number of notable AI models in the world, based on criteria such as state-of-the-art advancements or high citation rates. For many small countries like South Korea, AI is a chance to punch above their weight. The blind spots But that single-mindedness can crowd out critical reflection on AI’s broader societal impacts. “Because the national agenda on AI prioritizes economic development,” says Jeon, the professor of science and technology policy, “there isn’t much reflection on the social, political, ethical dimensions of the technology.” In 2025, the South Korean government faced a fierce backlash for rolling out AI textbooks riddled with factual inaccuracies and data privacy risks without testing them first in a pilot program to evaluate how they affect student learning. And despite their optimism, South Koreans are still worried that AI could displace them from their jobs. After Hyundai announced in January that it will deploy Atlas humanoid robots across its car factories, the Hyundai Motor Group union protested vehemently. “Without labor-management agreement, not a single robot using new technology will be allowed to enter the workplace,” the union said. Sixty-four percent of South Koreans fear AI could displace human labor and exacerbate inequality, although 52% believe it could also increase productivity.  On a recent Friday night in the Seoul Central Market, I went out with my cousins to a pocha, a late-night restaurant that serves fish cakes stacked in neat pyramids. As we clinked our cups of soju cut with beer—the scrappy staple cocktail of every Korean night out—one cousin asked me if I’d asked ChatGPT about my saju, a traditional Korean fortune-telling practice. A 29-year-old insurance agent in Seoul praying for a new job and a boyfriend, she said asking ChatGPT about work and dating was her favorite pastime. She pulled up her phone and punched my birth date into the chatbot. 

Addicted to their screens, trapped between unemployment and dead-end jobs, and priced out of marriage and homeownership, 46% of South Koreans in their 20s have used a chatbot to read their fortunes, according to a survey by Korea Gallup.  My cousin said she also asks ChatGPT for tips on trading stocks, dreaming big about making bank on her investment accounts into which she’s been pouring her salary. ChatGPT, she believes, is her portal out of reality into a better future. Despite how fond she is of the chatbot as her shaman and financial advisor, she fears losing her job to AI. She still uses ChatGPT feverishly at work, as all her coworkers do, afraid of falling behind.  “I sometimes fear AI, but for now, it’s just so useful,” she said.

EXECUTIVE SUMMARY Casey Harrell has had a set of electrodes embedded in his brain for almost three years. Harrell, who has amyotrophic lateral sclerosis (ALS) and is paralyzed, first used his brain-computer interface (BCI) to “speak” sentences with the help of a research team in 2023. Since then, Harrell has clocked thousands of hours of use. He can use the device largely independently, once he’s been “plugged in” with the help of a carer. His team has added new features to it, and Harrell also uses it to surf the web and perform his job. “Living with a disease like ALS, you are supposed to have diminished dreams. I do not,” Harrell tells MIT Technology Review. “Any one of these things would be an absolute godsend of improvement. To have all of them, and many, many more, is truly revolutionary.”  Within the first 22.6 months after the device was implanted, Harrell had used it for more than 3,800 hours at home without any researchers present, the team reported today in the journal Nature Medicine. “He’s the first power user of a speech BCI,” says team member Sergey Stavisky, a neuroengineer at the University of California, Davis.
Decoding speech Three years ago, Harrell entrusted David Brandman, an associate professor of neurological surgery at the University of California, Davis, and his colleagues with his brain. Harrell, who was 45 at the time, had already been diagnosed with ALS, a degenerative disease that robs people of the use of their muscles. Harrell was dependent on others to control his wheelchair and to dress and feed him. He had difficulty speaking; people struggled to understand what he was saying. Then Brandman and his colleagues asked if he’d like to trial a brain implant that might help him communicate. “The industry was [on the] cusp of a transformation, and I wanted to be part of it,” says Harrell. He signed up.
In July 2023, during a five-hour operation, doctors implanted four arrays of 64 electrodes each into his brain. Each pair of arrays was wired to a “pedestal” connection point—creating two docking locations on the exterior of his skull to connect the electrodes to a computer. The team had long been working on developing algorithms to decode brain activity into speech. Their system works by recording activity from the speech motor cortex—a region of the brain responsible for the movements that allow us to speak. “There are 39 phonemes that make up all the sounds in the [American] English language,” says Nicholas Card, a neuroengineer at UC Davis and member of the team. Mapping neural activity related to producing each of those phonemes can allow the team to create a personalized speech decoder and software that can “speak” those words. “We first go from brain data to phonemes, and then from phonemes to words,” he says. They started using the device around a month after the surgery. The team got Harrell’s speech decoder working on the first day, says Card. On that day in August, Harrell used the device to speak with a 50-word vocabulary, and 99.6% of the words were as he’d intended. That vocabulary was later expanded to 125,000 words with 97.5% accuracy. At the time, it was unclear how long the device might last. Brain-computer interfaces are still new—not many people have had them implanted for long periods of time. Scar tissue can form around electrodes in a person’s brain, interfering with their ability to pick up neural activity, for example. But that doesn’t seem to be the case for Harrell. Power user In another advance, Harrell is now able to use the device more independently. In 2023, members of the research team would have to visit Harrell at his home and physically connect and disconnect him from the device on the days he wanted to use it. Not anymore. The team has since automated more of the system—today, Harrell’s care partner can don and doff it for him. “He’ll wake up, get plugged in, and just get going,” says Stavisky. This is important, says Mariska Vansteesel, a BCI researcher at Utrecht Medical Center who was not involved in the trial. “For these technologies to be relevant for patients, we really need to test them in settings in which they will eventually be used … to demonstrate that it has value, that it’s usable, and that it functions well without the constant involvement of a research team,” she says.

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Casey Harrell uses his BCI to speak in “private mode.”
The team has also worked to improve the system itself. It is now 99% accurate, says Stavisky. Harrell can also control a cursor—a game changer that enables him to use his personal computer to send text messages and emails, surf the web, and keep up with his job as an environmental activist.

Over the years, the team has updated the system to accommodate specific requests from Harrell. He is now able to switch on a “privacy mode”—when active, any decoded text will be automatically deleted. He can also opt to use a “profanity filter” while he’s talking to his young daughter. “We have been able to add on to the software side of the device … improving the accuracy and adding more bells and whistles to enable me to be more independent when using the device,” says Harrell. “We are making the road as we walk it, or roll it, so to speak.” Nothing short of revolutionary Vansteesel cautions that while the device is working well for Harrell, there’s no guarantee it will work as well, or as long, for other people with ALS. Over the last decade, she has worked with a woman with ALS who used a fully implanted device to communicate using “brain clicks”—cursor clicks made using brain activity. The woman used her BCI for seven years, but it stopped working toward the end of that period, apparently due to brain degeneration. At any rate, not everyone with ALS will be willing to undergo invasive brain surgery, says Jane Huggins, who is developing noninvasive BCIs at the University of Michigan and was not involved in the trial. “Long-term, independent use with efficient and accurate communication is kind of the holy grail of BCI,” she says. “But we have been finding a consistent aversion to hospital stays among people with progressive conditions like ALS.” Harrell, however, calls the device “nothing short of revolutionary.” “This has allowed me to keep working and earn money and insurance for my family. This is reconnecting me with friends and family who are too shy or too afraid to come over and not be able to understand me,” Harrell says. “With my seven-year-old daughter, I am able to create a bond that I wasn’t before able to forge. Now I can read to them and help them sharpen their own reading skills. By doing so, I am able to share the responsibility of parenting with my wife, who does so much caregiving for me and also our daughter.” Stavisky and his colleagues hope to improve the device further still. “We’re never satisfied,” he says. One aim is to eventually restore Harrell’s “full voice.” They are working on a “brain-to-voice” system that could directly decode brain activity to a speaking voice, complete with natural-sounding cadence, inflection and intonation—a voice that could sound happy, angry, or sarcastic, for example. “I was quietly confident that I could get some personal benefit from the system,” says Harrell. “Never in a million years would I think that I would achieve this much.” 

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. These new solid-state ACs promise a cool future. Scientists aren’t so sure. After three years of record-­breaking heat and another scorcher underway, air-conditioning isn’t going anywhere. That’s good for our health, but bad for the planet: it already accounts for 7% of global electricity use and 3% of greenhouse-gas emissions.  Feeling the heat, scientists and startups are hoping to amp up solid-­state cooling. These systems move heat through conductive materials, which could cool spaces and surfaces with fewer messy side effects. The catch is whether it can match the efficiency of traditional AC. Find out how the unconventional coolers aim to dial down AC emissions.
—Sara Kiley Watson This story is from the next edition of our magazine, which is all about engineering. Subscribe now to get a copy when it lands! 
Job titles of the future: nature’s drug designer In 2018, after nearly two decades working in Big Pharma, chemist Tim Cernak was ready to put his skills to a new use.  As a lifelong nature lover, he had become concerned that animals are often treated with human pharmaceuticals that can be harmful or even lethal. He decided to address this with a new approach: “conservation chemistry.”  Using AI tools and robots, he’s now rapidly designing and testing drugs for animals. Here’s what it takes to treat nature’s patients. —Anna Gibbs The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Anthropic has shut down access to its top models after a US directiveThe US barred foreigners from using Fable 5 and Mythos 5 on Friday. (NYT $)+ Anthropic disabled access globally as it can’t filter users in real time.(BBC)+ Talks with Amazon’s CEO apparently prompted the ban. (WSJ $)+ Cybersecurity experts have called for the ban to end. (Axios)+ But the White House’s war against Anthropic has previously backfired. (MIT Technology Review) 2 The UK is banning social media for under-16sDetails are scant, but the measure is due to take effect in early 2027. (The Guardian)+ The ban covers Snapchat, TikTok, YouTube, Instagram, Facebook, and X. (BBC)+ Many countries are curbing children’s social media access. (Reuters $)

3 New space data suggests black holes formed before galaxiesIt could resolve cosmology’s chicken-and-egg dilemma. (New Scientist $)+ Odd tricks have formed a massive black hole. (MIT Technology Review) 4 Skepticism around AI layoffs is increasingThere are growing doubts that AI is really the culprit. (TechCrunch)+ We need a reality check on AI jobs hysteria. (MIT Technology Review) 5 A coalition of states has opened an investigation into OpenAIOver matters including user data, child safety and advertising. (NYT $) 6 Tesla has been accused of misleading regulators over “full self-driving”By exaggerating its safety statistics. (Reuters $) 7 NASA’s “quiet supersonic” plane has hit critical new milestonesThe X-59 reached 924 mph and 55,000 feet. (Scientific American) + Which are essential for flying over populated areas. (Engadget)+ It’s designed to take the boom out of supersonic travel. (BBC)8 Deepfakes are getting harder to spot—and weirder—in the midtermsThanks to improvements in free AI tools. (WSJ $) 9 AI is revealing the secret lives of animalsBy tracing their movements, landmarks, and social practices. (Nature)  10 Where did Earth get its oceans? Maybe it made them itself.Scientists now suspect that Earth’s waters are homegrown. (Quanta)  Quote of the day
“This action has taken the best models away from defenders, created market uncertainty, and risked America’s AI leadership without any real risk to justify it.”  —Cybersecurity leaders urge the Trump administration to reverse restrictions on Anthropic’s most advanced AI models in an open letter. One More Thing
CHRISTIE HEMM KLOK How scientists want to make you young again A little over 15 years ago, scientists at Kyoto University made a remarkable discovery. When they added just four proteins to a skin cell and waited about two weeks, some of the cells underwent an unexpected and astounding transformation: they became young again. Now, after more than a decade of developing this cellular reprogramming, biotech companies and research labs have tantalising hints that the process could be the gateway to an unprecedented new technology for human age reversal. 

After three years of record-­breaking heat, this one is set to be yet another scorcher. Air-conditioning? Not going anywhere. The International Energy Agency projects that the number of AC units will triple by 2050. That’s good for health—one Lancet study estimated that AC prevented nearly 200,000 premature deaths in 2019 alone—but bad for the planet. Artificial chill already accounts for 7% of global electricity use and 3% of greenhouse-gas emissions, and if improperly disposed of, the units can leak refrigerants with more global-­warming potential than carbon dioxide. Feeling the heat, a number of scientists and startups are hoping to amp up solid-­state cooling, which is currently used at a small scale for things like mini fridges, EV batteries, and some high-end gaming computers. Traditional ACs transfer heat by using a compressor and a fan to circulate a refrigerant and turn it from liquid to gas. Solid-state systems, on the other hand, move heat through conductive materials like gadolinium and bismuth telluride—which could theoretically cool spaces and surfaces with fewer messy side effects. 
The catch is whether they can match the efficiency of conventional AC. “One of the key questions that remain is why are the solid-state coolers not as efficient as typical thermodynamic cycles?” says Pramod Reddy, a professor of mechanical engineering at the University of Michigan who studies heat transfer.  Research and pilot programs are underway to test a range of approaches. Brooklyn-based Mimic Systems uses thermo­electric cooling, which passes a current through semiconductive materials to shift heat from one side to another. Its room-scale climate control system is being piloted in an apartment in Vancouver.
The German company Magnotherm is set to test its system, which relies on a magneto­caloric setup that transfers heat by magnetizing and demagnetizing materials, in a chain of supermarkets. A team in Hong Kong has announced that its elastocaloric device, whose material heats and cools as it expands and contracts, can dip below 0 °C. And the UK’s Barocal is betting on barocaloric systems, which change temperature in response to shifts in pressure.  But experts, especially in thermoelectrics, have doubts about how well any solid-­state scheme can compete. For most modern HVAC systems, the coefficient of performance (COP) is 3, explains Jeff Snyder, a professor at Northwestern University who studies electrical and thermal conductivity. That essentially means the system moves three units of heat for every unit of energy that goes into it. Thermoelectrics in particular tend to have a much lower performance at high levels of temperature change, Snyder says, which means they’re best suited for niche uses such as cooling the back of a car seat.  Mimic’s room-scale thermoelectric HVAC unit is being tested in a Vancouver apartment.COURTESY OF MIMIC SYSTEMS, INC Efficiency, however, isn’t everything, argues Lindsay Rasmussen, a manager at the Rocky Mountain Institute’s climate tech accelerator Third Derivative, which supports both Magnotherm and Mimic. In the US, most ACs currently in use employ a refrigerant called R410A, which has a global-­warming potential more than 2,000 times that of carbon dioxide. Plus, their moving parts can make them less durable, especially compared with a solid-state model that’s less mechanically complex. Still, a dearth of units makes it hard to answer the efficiency question. To understand how well alternatives work, says Rasmussen, researchers need to compare their long-term energy consumption with that of conventional models instead of simply looking at COP. Mimic claims, for example, that its room-scale model should match the draw of a typical AC unit over the course of a year. Elastocaloric and barocaloric systems also have promise, Rasmussen adds, but room-scale prototypes are probably two to three years away.  In the end, the likelihood that solid-state cooling could replace compressor-based AC is slim. But as the planet warms and places like India install tens of millions of new AC units over the next decade, supplanting even a small number could make a dent. “If [solid-state] could take over even a 5% market share,” Rasmussen says, “that is a really large potential impact.”  Sara Kiley Watson is a science journalist specializing in climate and sustainability. She’s based in The Hague.

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. Why “reprogramming” is the buzziest approach to reversing aging right now Earlier this week, Life Biosciences, a biotech company focused on reversing age-related diseases, announced that it had dosed its first volunteer. A person with glaucoma has had an experimental treatment injected straight into their eyeball. The idea is to treat the disease by regenerating healthy nerves in the eye—but the company already hopes to go further. If the treatment can reverse glaucoma, similar treatments could reverse other diseases of aging. Maybe, just maybe, they could reverse aging altogether. The approach relies on “reprogramming” cells to a younger state. It’s one of many strategies being explored by biotech companies looking to slow and reverse aging. But of all of them, it seems to be the one that is truly taking off.
Read the full story on the pursuit of reprogramming for rejuvenation. —Jessica Hamzelou
This story is from The Checkup, our weekly newsletter giving you the inside track on all things biotech. Sign up to receive it in your inbox every Thursday. Inside Interoception: The hidden sense of how you feel inside Scientists have a word for how we sense ourselves from the inside: interoception. Today, thanks to a 2021 Nobel Prize and new tools that can map internal signaling across the body, research into interoception is taking off. As researchers decode how signals move between body and brain, a clearer picture is starting to take shape—with implications for how we understand and treat conditions from obesity to chronic pain to anxiety. Find out how it’s leading to a “new continent of awareness.” —Katherine W. Isaacs This story is part of MIT Technology Review Explains, our series untangling the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here.  The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 SpaceX has officially delivered the largest IPO in historyIt’s raised a record $75 billion at a $1.77 trillion valuation. (Axios)+ Making Elon Musk the world’s first trillionaire (on paper). (Reuters $)+ The IPO will now put his “extreme ownership” to the test. (Wired $)+ While China attempts to build a Starlink rival. (Rest of World)+ And other challenges to SpaceX emerge. (MIT Technology Review) 2 Jeff Bezos wants to build an “artificial general engineer”Through his new industrial AI startup, Prometheus. (NYT $)+ Which just raised $12 billion, valuing it at $41 billion. (TechCrunch)+ Meanwhile, OpenAI is building a fully automated researcher. (MIT Technology Review) 3 Chinese regulators are dramatically intensifying tech enforcementA spell of relative restraint has ended. (SCMP)+ Regulators have admonished e-commerce giants Alibaba and JD.com. (FT $)+ And blocked Meta’s acquisition of Chinese AI startup Manus. (BBC) 4 Google says Chinese cybercriminals used Gemini to scam AmericansIt’s suing the network over the alleged AI-powered scams.(NYT $)+ “Supercharged scams” are one of our 10 Things That Matter in AI Right Now. (MIT Technology Review) 5 Ukraine’s defense AI chief predicts a “new paradigm” of warfareHe expects AI systems to unify into a single battlefield network. (Reuters $)+ AI chatbots could be used for targeting decisions. (MIT Technology Review) 6 Anthropic has rankled users with its safety-first Fable modelStringent safety rules and refusals to help have sparked a backlash. (NBC)+ Anthropic has backtracked on some policies. (Wired $) 7 Pokémon Go data trained AI that could assist military dronesIt could help them locate themselves in war zones. (Guardian)+ Pokémon Go data is also training delivery robots. (MIT Technology Review) 8 Orbital data centers are harder than Silicon Valley thinksShedding heat in space requires ingenious new designs. (IEEE Spectrum)+ We need a few things to put data centers in space. (MIT Technology Review)
9 A toy universe shows time could be a quantum illusionIt could emerge from quantum interactions, rather than just existing by default. (New Scientist $) 10 Chatbots keep telling stories about a lighthouse keeper called EllaAnd now we may finally know why. (404 Media)
Quote of the day “People are paying a trillion dollars for Elon.”  —Ross Gerber, the CEO of Gerber Kawasaki, which owns SpaceX stock, tells the New York Times why he believes the company’s IPO is overvalued. One More Thing GEORGE WYLESOL How generative AI could reinvent what it means to play I was immediately attracted to open-world games, in which you’re free to explore a vast simulated world and choose what challenges to accept. To make them feel alive, these games are inhabited by crowds of “nonplayer characters” (NPCs). But the illusion starts to weaken when you spend enough time with them. It may not always be like that. Just as it’s upending other industries, generative AI is opening the door to entirely new kinds of in-game interactions that are open-ended, creative, and unexpected. The game may not always have to end. Discover how generative AI could make games—and other worlds—deeply immersive.
—Niall Firth 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.) + My feet have fallen for the Crocs x Super Mario collection.+ Denmark’s 2026 Mullet Championship is the hottest hairdo contest of the year.+ Hungry at half-time? Here are seven mouth-watering international recipes inspired by the World Cup.+ Feast your eyes on a helicopter bound for Mars and a flowery Milky Way frame in Nature’s top images from last month.