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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. AI labs are buying data from dead startups to train their models When Keelan Miskell began winding down his crypto startup, he didn’t think its data was worth much. But he’s since turned the company’s digital archives into tens of thousands of dollars, selling its codebase and workspace data. He’s part of a growing market in which companies that help shut down startups sell their data to AI labs. Demand has grown as training labs hit the limits of public and synthetic datasets, with buyers seeking real-world records to help train AI agents. But the sales raise legal and ethical questions. Read the full story on the AI labs buying up the remains of failed startups.
—Matthew King Are we there yet? Interspecies communication  Humans are far from the only species with a gift for gab, and our furry, feathered, and finned friends could have a lot to tell us. 
Decoding how animals communicate with one another could reveal the inner lives of other species—and give humans a window onto how they see the world. A growing arsenal of devices and advances in AI have made it easier to study their howls, squeaks, and clicks, but making sense of it all remains complex. Find out how close we are to interspecies communication. —Cassandra Willyard This story is part of “Are we there yet?”, our series that takes stock of six technologies that have long promised to change the world—and scores them on a progress meter. We’re exploring each one in The Download, so stay tuned, and subscribe to read the rest of the stories in our new Impossible issue. MIT Technology Review Narrated: what it would take to build a city on the moon The US and China are racing to build bases on the moon, with NASA hoping to establish a small lunar city by the end of the century. But the moon is a tremendously hostile place to set up camp. A sprawling lunar base must be safe for its inhabitants, protected from falling asteroids, endless cosmic radiation, razor-sharp lunar dust, and torturous temperature swings. It also must be somewhat self-sustaining. That will require autonomous robots, nuclear power, and a way to use the moon’s resources to keep the base operating. But the chief obstacle may be one of political will. This is our latest story to become an MIT Technology Review Narrated podcast, which we publish each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Hackers have disrupted the US Federal Election Commission’s websiteThe FEC filing system went offline a week before the midterms. (Reuters $)+ The attack is hiding spending data during the costliest midterms ever. (Gizmodo)+ Social media platforms are struggling to contain AI election lies. (Guardian)+ Software flaws in US voting machines threaten election security. (Axios)+ A blueprint for using AI to strengthen democracy. (MIT Technology Review) 2 Starlink restrictions have driven US allies to rethink their dependenceRestrictions in Ukraine have spooked officials across Europe. (Bloomberg $)+ And given European firms a new pitch for their rival services. (Axios)+ An Israeli spy firm allegedly targeted Starlink users. (Reuters $)+ Stratospheric internet could take off this year. (MIT Technology Review) 3 Greenhouse gas levels keep reaching new records worldwideCarbon dioxide, methane, and nitrous oxide are all on the up. (New Scientist $)+ Trump is making it easier for fossil fuel companies to leak methane. (Verge)+ The IPCC is fighting for survival. (Nature)+ How to study a swiftly melting climate disaster. (MIT Technology Review) 4 Monkeys’ brains have revealed new clues about consciousnessTheir neural activity encodes images that escape their awareness. (Nature)+ Bees’ feelings are also changing views of consciousness. (New Scientist $)+ Debates over AI consciousness are a trap. (MIT Technology Review) 5 Chinese scientists have developed a catalyst to make Mars rocket fuelIt converts Martian atmospheric carbon dioxide into liquid methanol. (SCMP) 6 Tech billionaires have teamed up against California’s wealth taxSergey Brin, Eric Schmidt, and others have funded a major campaign. (NYT $)
7 Delaware plans to let AI agents run entire businessesThe proposal could let owners evade responsibility for harm. (Ars Technica)+ A better web for AI agents could hurt humans. (MIT Technology Review) 8 Palmer Luckey has unveiled plans for American-made military laptopsAnduril will build rugged PCs in Ohio using Qualcomm chips. (WSJ $)
9 Gen Z is turning away from the social media it grew up withYoung people are fueling a boom in digital detox tools. (Guardian) 10 Trump now wants to ban the term “artificial intelligence”He’s demanding we all start using “Super Intelligence.” (Gizmodo) Quote of the day “For the next two years, we’re going to be living in a state where, on average, every week there is a critical, internet-wide vulnerability.” —Matthew Prince, Cloudflare’s chief executive, tells the New York Times that AI is currently finding software vulnerabilities quicker than they can be patched. One more thing Inside the controversial tree farms powering Apple’s carbon-neutral goal In 2020, Apple set a goal to become net zero by the end of the decade. To hit that target, the company is offsetting its emissions by planting millions of eucalyptus trees in Brazil.
Apple is betting that the strategy will lead to a greener future. But critics warn that the industrial tree farms will do more harm than good. Here’s why the plans have sparked a backlash. —Gregory Barber 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.) + Ugly shoes have become beautifully mainstream.+ Scientists have built a stunning new simulation of the early universe.+ Guitarist Kent Nishimura has stripped Thriller back to a mesmerising acoustic performance.+ A photographer who snapped punks and mods in 1980 has tracked them down for an emotional reunion 46 years later.

AcknowledgementsGenie 4 was made possible by core contributions from Hang Qi, Diego Rivas, Aleksander Hołyński, Inbar Mosseri, Jack Parker-Holder, Shlomi Fruchter, Tejas Kulkarni, James Assiene, Philip Ball, Jakob Bauer, Eddie Cao, Lucy Chai, Harris Chan, Kleopatra Chatziprimou, Hao Chen, Yoni Choukroun, Mark Collier, Enric Corona, Kurtis David, Ariel Ephrat, Maxime Gazeau, Ruiqi Gao, Chelsee Glover-Odom, Liangke Gui, Swaroop Guntupalli, Shan Han, Tingbo Hou, Jiri Hron, Hui Huang, Drew A. Hudson, Zhouyuan Huo, Linyi Jin, Christos Kaplanis, Dhrupad Karwa, Eunyoung Kim, Congtao Kuang, Eliot Laidlaw, José Lezama, Hao Li, Shuang Li, Yuchen Liu, Hanzi Mao, Mark Matthews, Matt McGill, Kay McKinney, Ricardo Monti, Mark Murphy, Joseph Ortiz, Roni Paiss, Frank Perbet, Ben Poole, Tal Reiss, Konstantinos Rematas, Guy Scully, Jeremy Shar, Shashank Shastry, Sri S, Omer Tov, Ruben Villegas, Andrey Voynov, Hongjie Wang, Luyu Wang, Kaustubh Sridhar, Mo Samsami, Stephen Spencer, Yufei Wang, Will Whitney, Rundi Wu, Joyce (Jingjing) Xie, Jesse Yin, Shiran Zada, Serena Zhang, Xiaofan Zhang, Zhengqi Li, Zhixing Zhang, Yuan Zhong, Shuo-yiin Chang, Dmitry Lagun, Ronny Huang, Yao Su, Ankush Gupta, Genzhi Ye, Haolin Jia, Weiqin Wang, Xi Xiong, Salah Zaiem, Carol Zheng, .Genie 4 also required close collaborations across partner teams, we thank all our cross-functional partners that made this launch possible: Dina Bashkirova, Emil Bergner, Greta Borisko, Irina Blok, Melissa Byun, Gabe Clapper, Viral Carpenter, Michael Y. Chang, Maximo Cudich-Sieburger, Chloe Doan, Alisa Fortin, Shivani Ghanta, Vikram Gopali, Ezra Gorman, Khyatti Gupta, Sam Hasinoff, Philipp Henzler, Hector Hinestroza, Ed Hirst, Tyler Holland, Kristian Holsheimer, Tiffany Hu, Kapil Joshi, Randeep Katari, Pavan Kumar, Vikhyat Kumeria, Sam Kvaalen, Matthew Levine, Yinxiao Li, Yuchi Liu, Miao Luo, Nick Matarese, Kangfu Mei, Signe Nørly, Moises Oliveira, Eric Paskie, Manika Puri, Susanna Ricco, Andrey Ryabtsev, Cai Schumann, Nicole Brichtova, Andy Sekyere, Grace Shih, Melissa Smith, Duncan Noble Smith, Kenda Stewart, Rod Strougo, Jenn Sturgeon, Amy Zeng, Gaby Pearl, Eleanor Tomlinson, Kenyon Watson, Inês Ayer, Luke Talbot, Han-Yun Tsao, Guillaume Vernade, Karen Wang, Changchang Wu, Ian Wilkinson, Weijuan Xi, Jennifer Yick, Yunhan Zhao, Eric Zhang, Jason Zhang, Annie Zhou, James Zhou, Chris Walker, Alan Yam, Alex Chen, Cliff Lungaretti, Dan Motzenbecker, Kaloyan Kolev, Matthew Carey, Nate Zucker, Sam Lawton, Shashwath Santosh, Suz Chambers.Thanks to Raia Hadsell, Aäron van den Oord, Josh Woodward, Steve Seitz, Carlos Hernandez, Elias Roman, Jung E. Kim, Abhishek Bapna, Eli Collins, Tulsee Doshi, Carolina Parada, Jie Tan, Koray Kavukcuoglu and Demis Hassabis for their insightful guidance and support throughout the research process.Lastly, we thank our trusted tester and early access users that have provided feedback to help guide our research forward.

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. Will the real Anthropic please stand up? After weeks of frenzied speculation, Anthropic has filed its IPO prospectus. The 335-page document (100 pages or so are focused on risks) lays out the company’s unique view of the technology it is building and how it believes it will change the world. But Anthropic has been honing its storytelling skills for years. Its public messaging is a master class in narrative capture, presenting it as different things to different people: an AI safety organization, a profit-driven megacorp, and a group hell-bent on creating superhuman technology. These roles come with huge tensions. Will the IPO reveal the company behind the mask, or lean deeper into the myth-making? Take a new glimpse inside Anthropic.
—Will Douglas Heaven This story is from The Algorithm, our weekly AI newsletter. Sign up to receive it in your inbox every Monday.
How solid-state transformers could help power the AI boom Transformers are a crucial but nearly invisible part of the US grid, helping efficiently move power across long distances. But they’re complicated and in short supply, and their basic design hasn’t changed much in about a century. As electricity demand rises from EVs, data centers, and more, researchers and companies are looking to modernize these grid staples. Solid-state versions could help ease supply concerns and cut power losses. The technology is still in development, but it could become a crucial part of our future grid. Find out how solid-state transformers could help meet rising electricity demand. —Casey Crownhart Are we there yet? Exercise in a pill We all know exercise is good for us. It builds muscle, strengthens bones, lowers blood pressure, and boosts mood. By deciphering how movement benefits the body, researchers hope to develop medicines that can offer some of the same perks, without the workout. The idea isn’t to replace exercise but to bring its upsides to people who struggle with frailty, disability, or chronic illness. Discover how close researchers are to developing an exercise pill.

—Cassandra Willyard This story is part of “Are we there yet?”  from the new Impossible issue of MIT Technology Review. The series takes stock of six technologies that have long promised to change the world—and scores them on a progress meter. Over the next six days, we’ll explore each one in The Download. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Anthropic has filed for its blockbuster IPOThe listing could determine the future of the AI investment boom. (CNBC)+ The filing warns of catastrophic AI risks and huge compute costs. (BBC)+ And exposes safety failures and a month-long training pause. (Reuters $)+ The prospectus reveals soaring revenues but also staggering losses. (NYT $)+ Anthropic’s founders will retain voting control after the IPO. (Verge)  2 Solar is quietly overtaking nuclear as a global power sourceCheap panels and batteries are accelerating the shift. (BBC)+ The balcony solar boom is coming to the US. (MIT Technology Review) 3 OpenAI has announced three new science discoveriesThey span mathematics, computer science, and physics. (Verge)+ It’s enlisted expert “shepherds” to publish its breakthroughs. (Gizmodo) 4 Microsoft is offering buyouts to a quarter of staff amid rising AI costsAround 60,000 employees are eligible for the buyout program. (Bloomberg $)+ Microsoft plans $190 billion in AI spending this year. (NYT $)
5 The plastics industry knew microplastics could enter the body decades agoCompany documents reveal concerns dating back to 1974. (LA Times $)+ No part of the globe is free of human fingerprints. (MIT Technology Review) 6 A demonstration of lighting Earth from space has sparked alarmStartup Reflect Orbital used space mirrors for the California test. (Guardian)+ The tech could jeopardize the night sky. (MIT Technology Review)
7 The US has designated helium a critical materialThe move is due to its importance to semiconductor production. (AP) 8 Hundreds of Boston Dynamics staff have protested its ICE dealThey’ve called for a halt to sales of the robot dogs. (Ars Technica) 9 Treatments for age-related infertility are being developed at lastTwo startups aim to reduce chromosome errors in eggs. (Economist $)+ Here’s how tech transformed babymaking. (MIT Technology Review) 10 Grok says its AI-generated Odyssey is “not historically accurate”The bot itself admitted Elon Musk’s filmmaking plan has failed. (Wired $) Quote of the day “It’s as if they’re making a promise and crossing their fingers behind their backs.”  —Kate Brennan, who leads policy at the AI Now Institute, tells the New York Times that the voluntary safety pledges AI executives recently made are toothless and unenforceable.
One more thing The problem with thinking you’re part Neanderthal There’s a theory that many of us have an “inner Neanderthal.” The idea is that Homo sapiens and its cousin species once bred, leaving some people today with a trace of Neanderthal DNA.  This DNA is arguably the 21st century’s most celebrated discovery in human evolution. But in 2024, a pair of French geneticists called into question the theory’s very foundations.  They proposed that what scientists interpret as interbreeding could instead be explained by population structure—the way genes concentrate in smaller, isolated groups.

Provided byMicrosoft Every manufacturer has its own industrial intelligence. Some is documented, and some resides in the knowledge of experienced workers. Consider an experienced operator preparing to restart a line after a changeover. The machine settings matter, but so does knowing how a particular material behaves, what happened during the previous shift, and when an apparently minor variation deserves a closer look. A procedure can describe the sequence, but successful execution depends on the judgment that comes from experience and the organization’s accumulated know-how. That combination is industrial intelligence: a manufacturer’s accumulated know-how, operating practices, production data, and understanding of its own business. The opportunity now is to make more of that intelligence available wherever decisions are made, then connect it to the physical world of manufacturing. The strategic destination is not more agents, but rather to turn the existing business intelligence into an engine for profitable growth.
Individual knowledge can be translated into organizational advantage Expertise has limited reach when it stays with one person, inside one system, or within one plant. Leaders now must determine how to extend that reach without stripping away the context that makes the knowledge useful. For example, an engineer evaluating a process change needs more than a production record. They need to understand the circumstances behind it: the equipment configuration, the quality requirements, and the trade-offs an operator made. Connecting those elements can help people apply experience beyond the place where it originated.
When individual knowledge becomes widely accessible, innovation can spread to the maintenance workshop, the planning office, the engineering team, and the production floor. More people can contribute because more people can work with what the organization knows. But access to knowledge is only part of the opportunity. Manufacturing ultimately is physical, and it depends on materials, machines, and products. When intelligence participates in action Physical AI describes systems that can perceive conditions, reason about them, and take action within the physical world. By connecting machines and processes, manufacturers get a clearer view of what is happening on the factory floor. Agents can then reason on top of that information to identify patterns, predict problems, and determine the best course of action. Physical AI brings business intelligence into the physical process, allowing machines and systems to respond to changing conditions. Consider a robotic-handling operation encountering variation in the parts arriving at its station. Vision can help the system assess a part’s position. A model informed by the material and task can help determine an appropriate movement. Connected controls can then execute an adjustment within validated limits. The value is not merely seeing the variation; it is responding appropriately. The same principle applies to quality operations. When Toyota Industries connected previously fragmented paint shop data, engineering and operations teams were given the context needed to understand defect drivers. The company reports that analysis cycles fell from five days to under four hours, while its pilot reduced relevant paint defects by about 25%. The breakthrough was not simply identifying another signal; it was helping people understand why defects were occurring and respond before the outcome was locked in. This is the type of situation where industrial intelligence has become essential. Data may reveal what is happening, but industrial intelligence provides the context for what should happen, which constraints cannot be breached, and when uncertainty requires human judgment. Simulation offers a way to examine proposed actions before applying them to equipment. Manufacturers can explore how a change might affect a process in a digital environment. That does not remove the need for physical validation, but it creates room to learn without treating the production line as the first experiment. Responsible deployment, therefore, begins with operational discipline. Leaders need to establish clear authority or what systems may change, reliable connections to equipment, defined safety boundaries, and a record of decisions and actions. People must be able to recognize uncertainty, intervene, and bring equipment to a safe state. Trust rests on those practical arrangements, not on confidence in a model alone.

More capable machines, more capable people Manufacturing has long combined human ingenuity with increasingly capable tools. Physical AI extends that relationship. Intelligent equipment can take on suitable repetitive or physically demanding tasks, while agent-assisted operations can help people navigate information-intensive decisions and changing conditions. The aim is not to make machines smarter; it is to see what people can build when knowledge can travel, intelligence can act, and ambition has more room to become reality. Rockwell Automation illustrates the point. At its Singapore plant, technicians use a maintenance copilot that combines manufacturing data, machine manuals, and knowledge captured from experienced workers. This system has reduced the time required for new workers to learn how to troubleshoot hundreds of machines from nine months to three. An engineer could explore more process alternatives before committing to a change. An operator could help improve the system’s response rather than repeatedly managing the same exception. This type of progress requires investment in equipment but also in people: training, time to learn, and playing a meaningful role in shaping how systems work. Machines become more capable so people can become more capable. Industrial Intelligence is the answer to sustainable growth Industrial intelligence connects what a manufacturer knows: the experience of its people, the signals from its operations, and the lessons accumulated over time. Physical AI gives that intelligence a way to act in the physical world, turning knowledge into decisions and decisions into action. The next challenge for industry is not simply to produce more, but to grow without adding complexity at the same rate. Intelligence can help manufacturers turn experience into scalable capability—improving productivity, accelerating innovation, expanding capacity, and enabling people to solve problems that were previously difficult to tackle. The next frontier of industry is not smarter machines or more automated factories; it is businesses that can continuously learn, adapt, and act. The opportunity is to turn the intelligence embedded in every operation into a compounding advantage for growth.
Watch the video series to learn how industrial customers are unlocking intelligence across the value chain, and join Microsoft at Microsoft Ignite to see what’s next for Industrial Intelligence. This content was produced by Microsoft. It was not written by MIT Technology Review’s editorial staff.

EXECUTIVE SUMMARY Transformers are a crucial but nearly invisible part of our grid. The devices help efficiently move power across long distances, but they’re complicated and in short supply. And given that their basic design hasn’t changed much for about a century, they could use an upgrade.  As the world races to meet rising electricity demand from EVs, data centers, and more, researchers and companies are looking to modernize transformers. New, solid-state versions could help relieve some of the supply concerns and make sure the grid can handle the growing pressure. Conventional transformers generally rely on huge amounts of specialized steel alloys and miles of copper wire to do their work of transferring electricity between circuits. Solid-state models, in comparison, combine magnetic components with high-power semiconductors, making them more compact and allowing for more control over the flow of electricity.  These devices are still in development, and can’t replace all traditional transformers today, especially the largest ones that work at the high voltages necessary for long-distance transmission. But a new generation of transformer technology could be a crucial part of our future grid.
The grid’s backbone Moving electricity through the grid isn’t perfectly efficient: As electricity flows through power lines, some gets lost as heat. How much varies—the higher the voltage, the lower the current, and the less electricity gets lost. So a key function for the grid is stepping voltage up and down.  Consider, for example, your local solar plant. For that electricity to efficiently travel to your home hundreds of miles away, it needs to reach a higher voltage than what’s generated by the solar plant. Enter transformers. 
In its path from the power plant to your outlets, electricity might go through one transformer at the solar farm and another at a substation nearby, stepping up the voltage twice to reach a high enough level to travel on high-voltage transmission lines. Solar panels also produce direct current (DC) electricity, which needs to be converted to alternating current (AC) via an inverter before it flows into a transformer. Closer to its destination, the voltage will be stepped down again, probably at least twice: once at another substation and again at a smaller transformer in your neighborhood. If you’re in the US, electricity from a solar plant might be converted to AC by an inverter at around 480 volts, get stepped up to 115,000 volts for the transmission lines, and finally get stepped back down to 120 volts and 240 volts for your home. Conventional transformers do this work using what essentially amount to loops of wire. The core of a transformer is typically made of a special type of steel called grain-oriented electrical steel. Coils of copper wire sit on either end of that core.  The number of loops in each coil determines the voltage on either end of the transformer: If there are more loops on the secondary coil than the primary, the voltage steps up, and if there are fewer, it steps down. When incoming electricity passes through loops on the upstream end of the transformer, that forms a magnetic field in the core. That field induces a voltage in the loops on the other side of the device, which is what allows the energy to continue flowing at a new voltage. This process is called magnetic induction. Transformers form the backbone of electricity transmission and distribution, says Srdjan Lukic, a professor of electrical and computer engineering at North Carolina State University. In addition to doing the job of stepping up and down voltage, transformers also often provide what’s called galvanic isolation, meaning there’s no direct electrical path flowing through them. That can help limit disturbances from moving through the grid, improving safety. The problem is that today’s transformers are big and bulky, and they’re also difficult and expensive to replace, Lukic says. A solid option Solid-state transformers essentially add so-called power electronics—semiconductors that convert and control electricity to the typical blueprint of today’s transformers. While a conventional transformer operates at the frequency of the part of the grid it’s connected to, a solid-state transformer actually controls the frequency of the current. Typically, a solid-state transformer first converts incoming AC power from the grid to DC power, and then to a higher-frequency AC power using switches made of a semiconductor like silicon carbide. 

From there, a magnetic component changes the voltage. Because the advanced semiconductors allow transformers to exert so much control over the frequency and stability of the current, the magnetic core can be much smaller than in a conventional transformer. Some come in at roughly one-tenth the size but have the same capacity, Lukic says. Finally, additional power electronics convert the electricity from high-frequency AC to its required form—generally back to DC power and finally to lower-frequency AC. Today, stepping voltage up and down is many transformers’ only job. But solid-state transformers can do much more. They absorb the jobs of devices like rectifiers and inverters (which convert AC to DC power and vice versa), shrinking the total footprint of the electrical equipment and potentially cutting the amount of power lost in the system. In August, the New York Power Authority and the Electric Power Research Institute (EPRI) tested a one-megawatt solid-state transformer under realistic utility conditions at EPRI’s test site. The device was built in Lukic’s lab, and it was the first such test for a transformer of that capacity, he says.  The prototype was roughly 98% efficient—meaning it lost only 2% of the energy fed in. An equivalent conventional transformer and rectifier, by comparison, would be about 96% efficient together, Lukic says. A difference of 2% might seem small, but it is significant, since it means the solid-state transformer could cut power losses from conventional equipment in half, Lukic says.  One major goal of the project was to help utilities gain more confidence in these new components, Lukic says. That’s crucial, since these devices could be used on the power grid in the future. In the near term, solid-state transformers could be used within data centers to provide electricity for server racks.  The prototype is still a relatively low-voltage system, operating at about 15,000 volts. Industrial facilities like larger data centers often require higher-voltage connections, and transmission lines typically operate at hundreds of thousands of volts. Adapting solid-state transformers to these higher voltages will require further engineering development. But the test was a successful demonstration that solid-state transformers can work under real conditions, Lukic says.  Companies developing solid-state transformers are largely focused on data centers right now, Lukic says. There’s an influx of money to support developing the new technology, and the voltage requirements aren’t as high as they will be for larger transformers that will be needed for long-distance transmission. 
In February, Heron Power raised $140 million to commercialize its solid-state transformer, which the company calls the Heron Link. The technology could be used in data centers, solar power arrays, and grid batteries, says Drew Baglino, the founder and CEO. The company is starting to test its technology at larger scales now, Baglino says. Ten megawatt-hours’ worth of batteries at Heron’s headquarters in Scotts Valley, California, will soon undergo testing with Heron transformers. The company is also planning a pilot with a nearby solar farm, Baglino says. One challenge for solid-state transformers is that their power electronics have more failure modes than conventional transformers. In a traditional device, a failure means that the entire device will typically be taken offline, resulting in power interruptions. But Heron designs with that in mind, Baglino says: The company uses a modular design, with many small devices that work together. If one fails, the rest of the system keeps working until the affected bit can be replaced, which doesn’t require shutting the whole thing down.
Heron Power is currently building a $100 million factory in California to make advanced transformers. The facility should begin production in 2027 and reach its full production rate of 40 gigawatts’ worth of transformers per year in 2029.   The future of the grid In recent years, companies that make grid equipment have put $1.7 billion into the US supply chain for power transformers, which are used in high-voltage transmission, says Benjamin Boucher, a supply chain analyst at Wood Mackenzie. There’s been an additional $1.3 billion invested for distribution transformers, the smaller devices that help transform power for homes and businesses, he adds.  But even this investment isn’t keeping pace with the rapid growth of the grid. Wait times for large conventional transformers—the kind needed to connect new power plants, long-distance transmission, and high-demand sites like data centers—are stretching as long as five years. “Transformers have become one of the biggest bottlenecks for utilities, generation developers, and even data centers,” Boucher says. The big challenge is that it’s difficult to get new transformer manufacturing up and running, because it’s a quite technical process that requires a lot of specialized labor. So even facilities announced years ago are still years from opening, Boucher says. Solid-state transformers could help ease some of that pressure. But high-voltage devices needed for power plant connections and transmission lines are the holy grail for solid-state transformers, Lukic says. Existing solid-state technology can’t be used for those applications yet, so the industry will need to develop new materials and designs to support high voltages and handle electricity safely in a compact device. “We’re facing a big risk related to grid infrastructure,” Boucher says. “Without the transformers, you don’t really have an electrical grid.”