On a sunny, warm Sunday MIT students, staff, and faculty spread out across the fields of Hannan Healthy Foods in Lincoln, Massachusetts. Some of these volunteers pluck tomatoes from their vines in a patch a few hundred feet from the cars whizzing by on Route 117. Others squat in the shade cast by the greenhouse to snip chives. Still others slice heads of Napa cabbage from their roots in a bed nearer the woods. Everything being harvested today will wind up in Harvest Boxes, which will be sold at a pop-up farm stand the next day in the lobby of the Stata Center back on the MIT campus.

This initiative — a pilot collaboration between MIT’s Office of Sustainability (MITOS), MIT Anthropology, Hannan Healthy Foods, and the nascent MIT Farm student organization — sold six-pound boxes of fresh, organic produce to the MIT community for $10 per box — half off the typical wholesale price. The weekly farm stands ran from Sept. 15 through Oct. 27.

“There is a documented need for accessible, affordable, fresh food on college campuses,” says Heather Paxson, William R. Kenan, Jr. Professor of Anthropology and one of the organizers of the program. “The problems for a small farmer in finding a sufficient market … are connected to the challenges of food insecurity in even wealthy areas. And so, it really is about connecting those dots.”

Through the six weeks of the project, farm stand shoppers purchased more than 2,000 pounds of fresh produce that they wouldn’t otherwise have had access to. Hannan, Paxson, and the team hope that this year’s pilot was successful enough to continue into future growing seasons, either in this farm stand form or as something else that can equally serve the campus community.

“This year we decided to pour our heart, soul, and resources into this vision and prove what’s possible,” says Susy Jones, senior sustainability project manager at MITOS. “How can we do it in a way that is robust and goes through the official MIT channels, and yet pushes the boundaries of what’s possible at MIT?”

A growing idea

Mohammed Hannan, founder of Hannan Healthy Foods, first met Paxson and Jones in 2022. Jones was looking for someone local who grew vegetables common in Asian cuisine in response to a student request. Paxson wanted a small farm to host a field trip for her subject 21A.155 (Food, Culture and Politics). In July, Paxson and Jones learned about an article in the Boston Globe featuring Hannan as an example of a small farmer hit hard by federal budget cuts.

They knew right away they wanted to help. They pulled in Zachary Rapaport and Aleks Banas, architecture master’s students and the co-founders of MIT Farm, an organization dedicated to getting the MIT community off campus and onto local farms. This MIT contingent connected with Hannan to come up with a plan.

“These projects — when they flow, they flow,” says Jones. “There was so much common ground and excitement that we were all willing to jump on calls at 7 p.m. many nights to figure it out.”

After a series of rapid-fire brainstorming sessions, the group decided to host weekly volunteer sessions at Hannan’s farm during the autumn growing season and sell the harvest at a farm stand on campus.

“It fits in seamlessly with the MIT motto, ‘mind and hand,’ ‘mens et manus,’ learning by doing, as well as the heart, which has been added unofficially — mind, hand, heart,” says Paxson.

Jones tapped into the MITOS network for financial, operational, student, and city partners. Rapaport and Banas put out calls for volunteers. Paxson incorporated a volunteer trip into her syllabus and allocated discretionary project funding to subsidize the cost of the produce, allowing the food to be sold at 50 percent of the wholesale price that Hannan was paid for it.

“The fact that MIT students, faculty, and staff could come out to the farm, and that our harvest would circulate back to campus and into the broader community — there’s an energy around it that’s very different from academics. It feels essential to be part of something so tangible,” says Rapaport.

The volunteer sessions proved to be popular. Throughout the pilot, about 75 students and half a dozen faculty and staff trekked out to Lincoln from MIT’s Cambridge, Massachusetts, campus at least once to clear fields and harvest vegetables. Hannan hopes the experience will change the way they think about their food.

“Harvesting the produce, knowing the operation, knowing how hard it is, it’ll stick in their brain,” he says.

On that September Sunday, second-year electrical engineering and computer science major Abrianna Zhang had come out with a friend after seeing a notification on the dormspam email lists. Zhang grew up in a California suburb big on supporting local farmers, but volunteering showed her a different side of the job.

“There’s a lot of work that goes into raising all these crops and then getting all this manual labor,” says Zhang. “It makes me think about the economy of things. How is this even possible … for us to gain access to organic fruits or produce at a reasonable price?”

Setting up shop

Since mid-September, Monday has been Farm Stand day at MIT. Tables covered in green gingham tablecloths strike through the Stata Center lobby, holding stacks of cardboard boxes filled with produce. Customers wait in line to claim their piece of the fresh harvest — carrots, potatoes, onions, tomatoes, herbs, and various greens.

Many of these students typically head to off-campus grocery stores to get their fresh produce. Katie Stabb, a sophomore civil and environmental engineering major and self-proclaimed “crazy plant lady,” grows her own food in the summer, but travels far from campus to shop for her vegetables during the school year. Having this stand right at MIT gives her time back, and she’s been spreading the news to her East Campus dorm mates — even picking boxes up for them when they can’t make it themselves and helping them figure out what to do with their excess ingredients.

“I have encountered having way too many chives before, but that’s new for some folks,” she says. “Last week we pooled all of our chives and I made chive pancakes, kind of like scallion pancakes.”

Stabb is not alone. In a multi-question customer survey conducted at the close of the Farm Stand season, 62 percent of respondents said the Harvest Box gave them the chance to try new foods and 49 percent experimented with new recipes. Seventy percent said this project helped them increase their vegetable intake.

Nearly 60 percent of the survey respondents were graduate students living off campus. Banas, one of the MIT Farm co-leads, is one of those grad students enjoying the benefits.

“I was cooking and making food that I bought from the farm stand and thought, ‘Oh, this is very literally influencing my life in a positive way.’ And I’m hoping that this has a similar impact for other people,” she says.

The impact goes beyond the ability of students to nourish themselves with fresh vegetables. New communities have grown from this collaboration. Jones, for example, expanded her network at MITOS by tapping into expertise and resources from MIT Dining, the Vice President for Finance Merchant Services, and the MIT Federal Credit Union.

“There were just these pockets of people in every corner of MIT who know how to do these very specific things that might seem not very glamorous, but make something like this possible,” says Jones. “It’s such a positive, affirming moment when you’re starting from scratch and someone’s like, ‘This is such a cool idea, how can I help?’”

Strengthening community

Inviting people from MIT to connect across campus and explore beyond Cambridge has helped students and employees alike feel like they’re part of something bigger.

“The community that’s grown around this work is what keeps me so engaged,” says Rapaport. “MIT can have a bit of a siloing effect. It’s easy to become so focused on your classes and academics that your world revolves around them. Farm club grew out of wanting to build connections across the student body and to see ourselves and MIT as part of a larger network of people, communities, and relationships.”

This particular connection will continue to grow, as Rapaport and Banas will use their architectural expertise to lead a design-build team in developing a climate-adaptive and bio-based root cellar at Hannan Healthy Foods, to improve the farm’s winter vegetable storage conditions. 

Community engagement is an ethos Hannan has embraced since the start of his farming journey in 2018, motivated by a desire to provision first his family and then others with healthy food.

“One thing I have done over the years, I was not trying to do farming by myself,” he says. “I always reached out to as many people as I could. The idea is, if community is not involved, they just see it as an individual business.”

It’s why he gifts his volunteers huge bags of tomatoes at the end of a shift, or donates some of his harvest to food banks, or engages an advisory committee of local residents to ensure he’s filling the right needs.

“There’s a reciprocal dimension to gifting that needs to continue,” says Paxson. “That is what builds and maintains community — it’s classic anthropology."

And much of what’s exchanged in this type of reciprocity can’t be charted or graded or marked on a spreadsheet. It’s cooking pancakes with dorm mates. It’s meeting and appreciating new colleagues. It’s grabbing a friend to harvest cabbage on a beautiful autumn Sunday.

“Seeing a student who volunteered over the weekend harvesting chives come to the market on Monday and then want to take a selfie with those chives,” says Jones. “To me, that’s a cool moment.”

Democracy is colliding with the technologies of artificial intelligence. Judging from the audience reaction at the recent World Forum on Democracy in Strasbourg, the general expectation is that democracy will be the worse for it. We have another narrative. Yes, there are risks to democracy from AI, but there are also opportunities.

We have just published the book Rewiring Democracy: How AI will Transform Politics, Government, and Citizenship. In it, we take a clear-eyed view of how AI is undermining confidence in our information ecosystem, how the use of biased AI can harm constituents of democracies and how elected officials with authoritarian tendencies can use it to consolidate power. But we also give positive examples of how AI is transforming democratic governance and politics for the better...

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Nature Climate Change, Published online: 25 November 2025; doi:10.1038/s41558-025-02501-z

Research on climate change requires continued support from funding agencies. Nature Climate Change spoke to experts from different organizations across the world to discuss how funding agencies can better promote future climate research and actions regarding interdisciplinary studies, international collaborations, supporting young scholars and more.

Nature Climate Change, Published online: 25 November 2025; doi:10.1038/s41558-025-02506-8

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It is important to understand the combined effects of multiple changes on the ocean. Here the authors use time of emergence to highlight the increases in impacts of individual and compound changes globally from the surface to the deeper ocean, identifying areas most affected.

At a high level, ammonia seems like a dream fuel: It’s carbon-free, energy-dense, and easier to move and store than hydrogen. Ammonia is also already manufactured and transported at scale, meaning it could transform energy systems using existing infrastructure. But burning ammonia creates dangerous nitrous oxides, and splitting ammonia molecules to create hydrogen fuel typically requires lots of energy and specialized engines.

The startup Amogy, founded by four MIT alumni, believes it has the technology to finally unlock ammonia as a major fuel source. The company has developed a catalyst it says can split — or “crack” — ammonia into hydrogen and nitrogen up to 70 percent more efficiently than state-of-the-art systems today. The company is planning to sell its catalysts as well as modular systems including fuel cells and engines to convert ammonia directly to power. Those systems don’t burn or combust ammonia, and thus bypass the health concerns related to nitrous oxides.

Since Amogy’s founding in 2020, the company has used its ammonia-cracking technology to create the world’s first ammonia-powered drone, tractor, truck, and tugboat. It has also attracted partnerships with industry leaders including Samsung, Saudi Aramco, KBR, and Hyundai, raising more than $300 million along the way.

“No one has showcased that ammonia can be used to power things at the scale of ships and trucks like us,” says CEO Seonghoon Woo PhD ’15, who founded the company with Hyunho Kim PhD ’18, Jongwon Choi PhD ’17, and Young Suk Jo SM ’13, PhD ’16. “We’ve demonstrated this approach works and is scalable.”

Earlier this year, Amogy completed a research and manufacturing facility in Houston and announced a pilot deployment of its catalyst with the global engineering firm JGC Holdings Corporation. Now, with a manufacturing contract secured with Samsung Heavy Industries, Amogy is set to start delivering more of its systems to customers next year. The company will deploy a 1-megawatt ammonia-to-power pilot project with the South Korean city of Pohang in 2026, with plans to scale up to 40 megawatts at that site by 2028 or 2029. Woo says dozens of other projects with multinational corporations are in the works.

Because of the power density advantages of ammonia over renewables and batteries, the company is targeting power-hungry industries like maritime shipping, power generation, construction, and mining for its early systems.

“This is only the beginning,” Woo says. “We’ve worked hard to build the technology and the foundation of our company, but the real value will be generated as we scale. We’ve proved the potential for ammonia to decarbonize heavy industry, and now we really want to accelerate adoption of our technology. We’re thinking long term about the energy transition.”

Unlocking a new fuel source

Woo completed his PhD in MIT’s Department of Materials Science and Engineering before his eventual co-founders, Kim, Choi, and Jo, completed their PhDs in MIT’s Department of Mechanical Engineering. Jo worked on energy science and ran experiments to make engines run more efficiently as part of his PhD.

“The PhD programs at MIT teach you how to think deeply about solving technical problems using systems-based approaches,” Woo says. “You also realize the value in learning from failures, and that mindset of iteration is similar to what you need to do in startups.”

In 2020, Woo was working in the semiconductor industry when he reached out to his eventual co-founders asking if they were working on anything interesting. At that time, Jo was still working on energy systems based on hydrogen and ammonia while Kim was developing new catalysts to create ammonia fuel.

“I wanted to start a company and build a business to do good things for society,” Woo recalls. “People had been talking about hydrogen as a more sustainable fuel source, but it had never come to fruition. We thought there might be a way to improve ammonia catalyst technology and accelerate the hydrogen economy.”

The founders started experimenting with Jo’s technology for ammonia cracking, the process in which ammonia (NH3) molecules split into their nitrogen (N2) and hydrogen (H2) constituent parts. Ammonia cracking to date has been done at huge plants in high-temperature reactors that require large amounts of energy. Those high temperatures limited the catalyst materials that could be used to drive the reaction.

Starting from scratch, the founders were able to identify new material recipes that could be used to miniaturize the catalyst and work at lower temperatures. The proprietary catalyst materials allow the company to create a system that can be deployed in new places at lower costs.

“We really had to redevelop the whole technology, including the catalyst and reformer, and even the integration with the larger system,” Woo says. “One of the most important things is we don’t combust ammonia — we don’t need pilot fuel, and we don’t generate any nitrogen gas or CO2.”

Today Amogy has a portfolio of proprietary catalyst technologies that use base metals along with precious metals. The company has proven the efficiency of its catalysts in demonstrations beginning with the first ammonia-powered drone in 2021. The catalyst can be used to produce hydrogen more efficiently, and by integrating the catalyst with hydrogen fuel cells or engines, Amogy also offers modular ammonia-to-power systems that can scale to meet customer energy demands.

“We’re enabling the decarbonization of heavy industry,” Woo says. “We are targeting transportation, chemical production, manufacturing, and industries that are carbon-heavy and need to decarbonize soon, for example to achieve domestic goals. Our vision in the longer term is to enable ammonia as a fuel in a variety of applications, including power generation, first at microgrids and then eventually full grid-scale.”

Scaling with industry

When Amogy completed its facility in Houston, one of their early visitors was MIT Professor Evelyn Wang, who is also MIT’s vice president for energy and climate. Woo says other people involved in the Climate Project at MIT have been supportive.

Another key partner for Amogy is Samsung Heavy Industries, which announced a multiyear deal to manufacturing Amogy’s ammonia-to-power systems on Nov. 12.

“Our strategy is to partner with the existing big players in heavy industry to accelerate the commercialization of our technology,” Woo says. “We have worked with big oil and gas companies like BHP and Saudi Aramco, companies interested in hydrogen fuel like KBR and Mitsubishi, and many more industrial companies.”

When paired with other clean energy technologies to provide the power for its systems, Woo says Amogy offers a way to completely decarbonize sectors of the economy that can’t electrify on their own.

“In heavy transport, you have to use high-energy density liquid fuel because of the long distances and power requirements,” Woo says. “Batteries can’t meet those requirements. It’s why hydrogen is such an exciting molecule for heavy industry and shipping. But hydrogen needs to be kept super cold, whereas ammonia can be liquid at room temperature. Our job now is to provide that power at scale.”

There is growing attention on the links between artificial intelligence and increased energy demands. But while the power-hungry data centers being built to support AI could potentially stress electricity grids, increase customer prices and service interruptions, and generally slow the transition to clean energy, the use of artificial intelligence can also help the energy transition.

For example, use of AI is reducing energy consumption and associated emissions in buildings, transportation, and industrial processes. In addition, AI is helping to optimize the design and siting of new wind and solar installations and energy storage facilities.

On electric power grids, using AI algorithms to control operations is helping to increase efficiency and reduce costs, integrate the growing share of renewables, and even predict when key equipment needs servicing to prevent failure and possible blackouts. AI can help grid planners schedule investments in generation, energy storage, and other infrastructure that will be needed in the future. AI is also helping researchers discover or design novel materials for nuclear reactors, batteries, and electrolyzers.

Researchers at MIT and elsewhere are actively investigating aspects of those and other opportunities for AI to support the clean energy transition. At its 2025 research conference, MITEI announced the Data Center Power Forum, a targeted research effort for MITEI member companies interested in addressing the challenges of data center power demand.

Controlling real-time operations

Customers generally rely on receiving a continuous supply of electricity, and grid operators get help from AI to make that happen — while optimizing the storage and distribution of energy from renewable sources at the same time.

But with more installation of solar and wind farms — both of which provide power in smaller amounts, and intermittently — and the growing threat of weather events and cyberattacks, ensuring reliability is getting more complicated. “That’s exactly where AI can come into the picture,” explains Anuradha Annaswamy, a senior research scientist in MIT’s Department of Mechanical Engineering and director of MIT’s Active-Adaptive Control Laboratory. “Essentially, you need to introduce a whole information infrastructure to supplement and complement the physical infrastructure.”

The electricity grid is a complex system that requires meticulous control on time scales ranging from decades all the way down to microseconds. The challenge can be traced to the basic laws of power physics: electricity supply must equal electricity demand at every instant, or generation can be interrupted. In past decades, grid operators generally assumed that generation was fixed — they could count on how much electricity each large power plant would produce — while demand varied over time in a fairly predictable way. As a result, operators could commission specific power plants to run as needed to meet demand the next day. If some outages occurred, specially designated units would start up as needed to make up the shortfall.

Today and in the future, that matching of supply and demand must still happen, even as the number of small, intermittent sources of generation grows and weather disturbances and other threats to the grid increase. AI algorithms provide a means of achieving the complex management of information needed to forecast within just a few hours which plants should run while also ensuring that the frequency, voltage, and other characteristics of the incoming power are as required for the grid to operate properly.

Moreover, AI can make possible new ways of increasing supply or decreasing demand at times when supplies on the grid run short. As Annaswamy points out, the battery in your electric vehicle (EV), as well as the one charged up by solar panels or wind turbines, can — when needed — serve as a source of extra power to be fed into the grid. And given real-time price signals, EV owners can choose to shift charging from a time when demand is peaking and prices are high to a time when demand and therefore prices are both lower. In addition, new smart thermostats can be set to allow the indoor temperature to drop or rise —  a range defined by the customer — when demand on the grid is peaking. And data centers themselves can be a source of demand flexibility: selected AI calculations could be delayed as needed to smooth out peaks in demand. Thus, AI can provide many opportunities to fine-tune both supply and demand as needed.

In addition, AI makes possible “predictive maintenance.” Any downtime is costly for the company and threatens shortages for the customers served. AI algorithms can collect key performance data during normal operation and, when readings veer off from that normal, the system can alert operators that something might be going wrong, giving them a chance to intervene. That capability prevents equipment failures, reduces the need for routine inspections, increases worker productivity, and extends the lifetime of key equipment.

Annaswamy stresses that “figuring out how to architect this new power grid with these AI components will require many different experts to come together.” She notes that electrical engineers, computer scientists, and energy economists “will have to rub shoulders with enlightened regulators and policymakers to make sure that this is not just an academic exercise, but will actually get implemented. All the different stakeholders have to learn from each other. And you need guarantees that nothing is going to fail. You can’t have blackouts.”

Using AI to help plan investments in infrastructure for the future

Grid companies constantly need to plan for expanding generation, transmission, storage, and more, and getting all the necessary infrastructure built and operating may take many years, in some cases more than a decade. So, they need to predict what infrastructure they’ll need to ensure reliability in the future. “It’s complicated because you have to forecast over a decade ahead of time what to build and where to build it,” says Deepjyoti Deka, a research scientist in MITEI.

One challenge with anticipating what will be needed is predicting how the future system will operate. “That’s becoming increasingly difficult,” says Deka, because more renewables are coming online and displacing traditional generators. In the past, operators could rely on “spinning reserves,” that is, generating capacity that’s not currently in use but could come online in a matter of minutes to meet any shortfall on the system. The presence of so many intermittent generators — wind and solar — means there’s now less stability and inertia built into the grid. Adding to the complication is that those intermittent generators can be built by various vendors, and grid planners may not have access to the physics-based equations that govern the operation of each piece of equipment at sufficiently fine time scales. “So, you probably don’t know exactly how it’s going to run,” says Deka.

And then there’s the weather. Determining the reliability of a proposed future energy system requires knowing what it’ll be up against in terms of weather. The future grid has to be reliable not only in everyday weather, but also during low-probability but high-risk events such as hurricanes, floods, and wildfires, all of which are becoming more and more frequent, notes Deka. AI can help by predicting such events and even tracking changes in weather patterns due to climate change.

Deka points out another, less-obvious benefit of the speed of AI analysis. Any infrastructure development plan must be reviewed and approved, often by several regulatory and other bodies. Traditionally, an applicant would develop a plan, analyze its impacts, and submit the plan to one set of reviewers. After making any requested changes and repeating the analysis, the applicant would resubmit a revised version to the reviewers to see if the new version was acceptable. AI tools can speed up the required analysis so the process moves along more quickly. Planners can even reduce the number of times a proposal is rejected by using large language models to search regulatory publications and summarize what’s important for a proposed infrastructure installation.

Harnessing AI to discover and exploit advanced materials needed for the energy transition

“Use of AI for materials development is booming right now,” says Ju Li, MIT’s Carl Richard Soderberg Professor of Power Engineering. He notes two main directions.

First, AI makes possible faster physics-based simulations at the atomic scale. The result is a better atomic-level understanding of how composition, processing, structure, and chemical reactivity relate to the performance of materials. That understanding provides design rules to help guide the development and discovery of novel materials for energy generation, storage, and conversion needed for a sustainable future energy system.

And second, AI can help guide experiments in real time as they take place in the lab. Li explains: “AI assists us in choosing the best experiment to do based on our previous experiments and — based on literature searches — makes hypotheses and suggests new experiments.”

He describes what happens in his own lab. Human scientists interact with a large language model, which then makes suggestions about what specific experiments to do next. The human researcher accepts or modifies the suggestion, and a robotic arm responds by setting up and performing the next step in the experimental sequence, synthesizing the material, testing the performance, and taking images of samples when appropriate. Based on a mix of literature knowledge, human intuition, and previous experimental results, AI thus coordinates active learning that balances the goals of reducing uncertainty with improving performance. And, as Li points out, “AI has read many more books and papers than any human can, and is thus naturally more interdisciplinary.”

The outcome, says Li, is both better design of experiments and speeding up the “work flow.” Traditionally, the process of developing new materials has required synthesizing the precursors, making the material, testing its performance and characterizing the structure, making adjustments, and repeating the same series of steps. AI guidance speeds up that process, “helping us to design critical, cheap experiments that can give us the maximum amount of information feedback,” says Li.

“Having this capability certainly will accelerate material discovery, and this may be the thing that can really help us in the clean energy transition,” he concludes. “AI [has the potential to] lubricate the material-discovery and optimization process, perhaps shortening it from decades, as in the past, to just a few years.” 

MITEI’s contributions

At MIT, researchers are working on various aspects of the opportunities described above. In projects supported by MITEI, teams are using AI to better model and predict disruptions in plasma flows inside fusion reactors — a necessity in achieving practical fusion power generation. Other MITEI-supported teams are using AI-powered tools to interpret regulations, climate data, and infrastructure maps in order to achieve faster, more adaptive electric grid planning. AI-guided development of advanced materials continues, with one MITEI project using AI to optimize solar cells and thermoelectric materials.

Other MITEI researchers are developing robots that can learn maintenance tasks based on human feedback, including physical intervention and verbal instructions. The goal is to reduce costs, improve safety, and accelerate the deployment of the renewable energy infrastructure. And MITEI-funded work continues on ways to reduce the energy demand of data centers, from designing more efficient computer chips and computing algorithms to rethinking the architectural design of the buildings, for example, to increase airflow so as to reduce the need for air conditioning.

In addition to providing leadership and funding for many research projects, MITEI acts as a convenor, bringing together interested parties to consider common problems and potential solutions. In May 2025, MITEI’s annual spring symposium — titled “AI and energy: Peril and promise” — brought together AI and energy experts from across academia, industry, government, and nonprofit organizations to explore AI as both a problem and a potential solution for the clean energy transition. At the close of the symposium, William H. Green, director of MITEI and Hoyt C. Hottel Professor in the MIT Department of Chemical Engineering, noted, “The challenge of meeting data center energy demand and of unlocking the potential benefits of AI to the energy transition is now a research priority for MITEI.”

The International Association of Cryptologic Research—the academic cryptography association that’s been putting conferences like Crypto (back when “crypto” meant “cryptography”) and Eurocrypt since the 1980s—had to nullify an online election when trustee Moti Yung lost his decryption key.

For this election and in accordance with the bylaws of the IACR, the three members of the IACR 2025 Election Committee acted as independent trustees, each holding a portion of the cryptographic key material required to jointly decrypt the results. This aspect of Helios’ design ensures that no two trustees could collude to determine the outcome of an election or the contents of individual votes on their own: all trustees must provide their decryption shares...

At least 15 coal-fired plants are being kept online to power artificial intelligence as the administration rolls back pollution rules.

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