Nature Climate Change, Published online: 10 June 2026; doi:10.1038/s41558-026-02659-0

Sea-level rise in conjunction with storm surge and tidal variations leads to extreme sea levels that threaten coastal systems. Here the authors use tide-gauge data and models to quantify how anthropogenic climate change has increased the risk of these extreme sea-level events since 1900.

Nature Climate Change, Published online: 10 June 2026; doi:10.1038/s41558-026-02689-8

Author Correction: Rising temperatures increase added sugar intake disproportionately in disadvantaged groups in the USA

Nature Climate Change, Published online: 10 June 2026; doi:10.1038/s41558-026-02633-w

Southern California is rarely affected by tropical cyclones at present. Here the authors show that this could change with warming, leading to an increase in landslide risk that is expected to disproportionately affect low-income households.

The rise of artificial intelligence is riding on the back of an enormous data center expansion. Data centers are projected to account for anywhere from 9 to 17 percent of total electricity usage in the U.S. by the end of the decade. Today, around a third of data center electricity is devoted to cooling the chips that run AI models.

That’s the process Ferveret is working to make more efficient. The startup, founded by Reza Azizian, a former MIT postdoc in nuclear engineering, and Matteo Bucci, MIT’s Esther and Harold E. Edgerton Associate Professor in the Department of Nuclear Science and Engineering, is adapting an approach from nuclear reactors to cool chips using no water and significantly less electricity.

The company’s cooling system submerges computer servers in a specialized liquid that absorbs heat much more efficiently than air from a fan. What makes the solution different from other liquid cooling systems are the bubbles: Ferveret’s Adaptive Phase Cooling (APC) solution produces much smaller bubbles at the surface of the server, which detach more frequently, accelerating the heat transfer process.

Ferveret is already testing its solutions with companies including CleanSpark, the data center developer and operator, as well as FuriosaAI, an AI accelerator company, and Switch, one of the largest data center operators in the U.S.

In a recent study in collaboration with the Samueli Computer Science Department at the University of California at Los Angeles, Ferveret found its APC solution led to a 15 percent improvement in computational power efficiency compared to state-of-the-art liquid cooling solutions. By combining those savings with Ferveret’s power control system to optimize operating conditions, the company says it allows data centers to get 35 percent more tokens — small pieces of text or data — from their AI models with the same amount of power.

“Our goal is to make data centers as sustainable as possible and help them use every single watt of power to generate tokens, which are the most useful outputs,” Azizian says. “Our system enables the operation of more powerful chips, it helps data centers waste a lot less energy, and it accomplishes all that with zero water consumption.”

From nuclear reactors to AI

Azizian was a postdoc at MIT in 2013 when he met Bucci, who was then a research scientist. They worked on heat transfer in nuclear reactors before Azizian went into industry, where he shifted his focus to cooling chips. Azizian first worked on Microsoft’s HoloLens augmented reality headset and then joined Nvidia, which produces the graphical processing units companies use to train and run the latest AI models. Meanwhile, Bucci continued conducting research at MIT, becoming an assistant professor in 2016.

Azizian walked into his first data center in 2017, where he was struck by the massive, noisy fans that filled the building as they cooled.

“I thought, ‘Holy crap, this is not how you cool facilities,’” Azizian recalls, noting air cooling can still take up 40 percent of the power going into a data center. “It was not an efficient way of doing things, but since it wasn’t hurting the performance, no one cared that the cooling technology was 50 years old.”

Azizian began talking with Bucci about applying their knowledge around optimizing heat transfer in nuclear reactors to data centers. Scientists have spent decades finding better ways to move heat in nuclear reactors.

“Heat transfer determines how much energy you can extract from the reactor core, which translates directly to revenue,” Azizian explains.

The founders started Ferveret in 2021. A lot has changed since Azizian walked into his first data center. Chip companies have packed more and more components onto their chips as the explosion in artificial intelligence has put a premium on squeezing as much computing capacity as possible out of limited power supplies.

That has driven data center operators to use liquid to cool chips — often through a technique known as immersion cooling that submerges chips in liquid. The most effective form of immersion cooling brings the liquid to a boil.

“Liquid is a better heat transfer medium than air. That’s why when you stick your hand into room temperature water it still feels cold,” Bucci explains. “When liquid is boiling, it becomes even better at removing heat because the phase change requires a lot of energy, which is the energy you remove from the chip. That lets you transfer large quantities of heat with minimal temperature differences between the chips and the liquid.”

Unfortunately, boiling liquid adds complexity to the system because it forces operators to capture and reliquefy the bubbles while controlling for pressure, temperature, and fluid inventory.

Ferveret’s system is adapted from a process in nuclear reactors called subcooled boiling. It uses a liquid with a low boiling point and none of the toxic PFAS “forever chemicals” that other approaches rely on. At the surface of the chip, Ferveret’s liquid produces smaller bubbles than other immersion cooling approaches. Those bubbles detach more frequently and quickly recondense in the surrounding liquid, accelerating the bubble-rewetting cycle at the surface of the chip to hasten heat transfer.

Ferveret delivers its APC system in small boxes, each of which houses one server. The founders say their modular systems make it easier to deploy the system and simplify maintenance.

“The physics enable us to get to form factors that weren’t possible in the past,” Azizian says. “Most immersion cooling solutions are large tanks that people submerge the servers in. We have a smaller, modular rack-mounted solution that makes it adaptable to the current infrastructure, so it’s easier for people to deploy our technology.”

Ferveret also offers control software that adjusts the power going to each server in real-time to further improve efficiency.

“We deliver full-stack systems that include the cooling box, the rack, the cooling distribution units, and sensors that measure the temperature and pressure,” Bucci says. “Our software monitors those sensors and optimizes the operating condition inside each box to ensure that energy consumption is minimized in the system.”

AI with fewer resources

In addition to helping data centers to run more efficiently, Ferveret is also improving sustainability by making it easier to operate data centers in remote regions with more renewable energy.

“The sun shines in places where you don’t have much water, so the advantage of us being water-free is we allow you to build data centers where you have solar energy but nothing to cool the data center down,” Bucci says. “This technology can help deploy data centers in regions where normally you wouldn’t have the resources to do so, including Africa, the Middle East, and of course parts of America. It’s a huge unlock.”

Ferveret is in talks with the large cloud computing companies known as hyperscalers, and is currently part of Nvidia’s Inception program for startups. The company plans to announce expanded partnerships later this year. From there, the founders plan to quickly scale their technology to help the AI industry continue to grow without further straining the planet.

“The computing industry is facing a huge challenge in the form of access to power, and they have a problem with access to water in many regions,” Azizian says. “That will only become more limiting as the industry grows. The main goal for these data center operators would be to get more tokens from the power they have. We’ve shown we can do that.”

The Senate Judiciary Committee is set to consider and vote on the Nurture Originals, Foster Art, and Keep Entertainment Safe Act (NO FAKES). Instead of targeting the real privacy harms posed by AI-generated replicas, this law would create another layer of internet censorship on top of the already existing legal and voluntary takedown systems. Congress should reject NO FAKES.

Take action

Tell Congress to Say No to NO FAKES

As currently written, NO FAKES proposes to tackle the problems of misleading AI-generated replicas by creating a broad property right in someone's look, voice, and general style. However, there are all kinds of First Amendment-protected expression that would be swept under the NO FAKES regime—think about parody, news, criticism.

NO FAKES also does a laughable job of protecting artists from use of their image in misleading ways. It doesn’t create a privacy right, but rather a property right that can easily be signed away—as major studios and record labels are almost certain to require in their contracts with artists. As a result, NO FAKES actually creates a new avenue for the exploitation of artists by companies instead of protection from misleading replicas. 

The bill also makes it trivially easy for protected speech to be censored. It is a supercharged version of the already flawed copyright takedown regime. It would essentially require platforms to institute filters that don't just look for exact matches of copyrighted material, as current filters do, but anything that might be a digital replica. Even though the latest version of this bill adds some forms of redress for bad faith takedowns, those provisions lack the teeth required to deter a malicious actor. 

NO FAKES targets speech, tools, and innovation instead of focusing on the real concern posed by these replicas: privacy. This bill was a bad idea when it was introduced, and got even worse when it was amended last year. Tell Congress to just say no to NO FAKES.

Take action

Tell Congress to Say No to NO FAKES

It’s no secret that the last few years have seen a massive explosion in the use of artificial intelligence for general information-gathering. An even more recent trend, though, is how large language models (LLMs) like ChatGPT, Claude, and Gemini are increasingly being used for verifying and consuming news; reports from the Pew Research Center over the last year found that one-in-five U.S. teens regularly use LLMs to get their news, while one-in-four young adults have reported using them for that purpose at least once. 

A new open-access study from the MIT Media Lab should give some of those users pause: Researchers found that, over the course of a month, participants who relied on AI systems to verify facts actually got worse at detecting misinformation on their own when their chatbots were taken away.

This phenomenon, which is often referred to as the “AI dependency paradox,” has been observed in a wide range of knowledge domains, like the 2025 study that found that doctors who used AI got worse at detecting cancer on their own. The dynamic mirrors broader tech trends around so-called “deskilling” (or “cognitive offloading”) that have been well-documented for decades, from calculators weakening our math skills to Global Positioning System (GPS) technologies impacting our natural sense of direction.

In the new Media Lab study, which tracked 67 people over four weeks as they evaluated news headline-image pairs, participants were 21 percent more accurate in detecting fake news when assisted by an AI chatbot during a session — confirming previous research out of the MIT Sloan School of Management demonstrating that AI can be an effective tool in reducing people’s beliefs in false information.

However, the study showed that a new wrinkle emerged when the AI was no longer present: By week four, participants’ unassisted performance on new news items declined by 15 percentage points compared to before the study started. (Roughly a quarter of all participants actually reported feeling that they were getting better at detection, even as their performance declined.)

Dunning-Kruger creeps in

“Users get excited about these ‘magical’ LLMs, but forget that they’re just statistical models that predict the next ‘token’ in a sequence [of letters/words],” says MIT media arts and sciences (MAS) PhD student Anku Rani, co-lead author of a new paper about the research, alongside fellow MAS PhD student Valdemar Danry. “Many impressive behaviors emerge from scaling this, but it comes with real limitations, both in what the model can reliably generate and in its broader impact on the people using it.”

Qualitative analysis identified distinct behavioral patterns, with the team labeling one-fifth of all participants as "Dependency Developers” who gradually shifted from active self-reliance to passive acceptance of AI guidance.

In the post-experiment survey, one respondent explicitly acknowledged this transition, noting their passive role in the process. “While [the chatbots] did emphasize that you must check across multiple sources to make sure a story is true, they didn’t teach me much about exploring the context of the images themselves,” the participant said.

The research team said that these AI models are particularly vulnerable to mistakes in the midst of emotionally charged breaking news, as exhibited by the widespread misinformation that accompanied President Trump’s recent assassination attempt and major events during the Iranian war. (The authors also point out that the original human-created news content that’s used to train the AI models is increasingly unreliable and/or biased, further exacerbating the problem.)

The paper, which Danry and Rani presented at the 2026 CHI Conference on Human Factors in Computing Systems, was co-authored by Assistant Professor Paul Pu Liang, Senior Research Scientist Andrew Lippman, and senior author Pattie Maes, the Germeshausen Professor of Media Arts and Sciences. 

The solution: Being a coach, not a crutch

The researchers say that the results of their project suggest that the specific way in which an AI interacts with a user determines whether its impact will be “as a coach, versus as a crutch.” The study found a clear distinction between conversational strategies that simply help in the moment and those that actually support active learning and skill development.

For the latter, the Media Lab team uncovered several strategies associated with stronger independent detection later on, even if the strategies initially slowed down performance during the interaction. This included the Socratic method of the AI asking guided questions, as well as so-called “deep probing,” where the system provides gently persuasive statements if the user appears to be veering away from the correct response.

“AIs that ‘tell’ by providing direct answers are more likely to foster reliance, while those that ‘ask’ via Socratic questioning are better at engaging someone to actually learn how to discern the truth on their own,” says Danry. “But it’s very much a trade-off between speed and effort.”

Rani noted a few key limitations to the one-month study, from the small dataset of roughly 50 validated news items to the demographic focus on the United States and the United Kingdom. In the future, she says that the team hopes to do similar experiments with more geographically diverse cohorts, including low-resource communities, and is also eager to explore whether other multi-modal interaction strategies — like interacting with culturally adaptive digital twins instead of text-based chatbots — help people improve their abilities to detect misinformation. 

At a higher level, the researchers hope that the project will be something that educators can examine as they develop teaching plans that incorporate AI tools into their school curricula.

“It’s especially important to raise awareness in our schools and academic communities about the shortcomings of using AI as learning tools,” says Maes. “People need to know that if they ‘delegate’ their thinking, they’re not going to get better at that particular brand of problem-solving. Ultimately, the ability to question and analyze information is important for everyone, because it empowers us to solve problems and form our own independent opinions about the world.”

Danry adds that the rapidly-evolving field of machine learning and deep learning will require continuous education on the benefits and drawbacks of LLMs.

“There’s a lot of work to do in making sure that we don’t just fully offload critical tasks that we want to be able to keep on doing to these models,” he says. “We need to develop a new kind of AI literacy.”

The research project was supported, in part, by the Media Lab Consortium, an MIT Tata Center Technology and Design Fellowship, and a Google PhD Fellowship in Human–Computer Interaction.

This is interesting:

The U.S. military has likely been quietly broadcasting codes for its global encryption network using public GPS for nearly 20 years, turning each satellite into a hidden “numbers station,” according to Steven Murdoch…

That means every device that uses GPS has been receiving hidden government information for years, and nobody outside the military knew it until now.

[…]

Murdoch discovered that this particular sentinel was transmitted by all 31 operational satellites within a window of a few hours on May 26, 2011, potentially heralding the activation of a new operational system. He confirmed that this timeline coincided with the rollout of the military’s Over-the-Air Distribution (OTAD) and the Over-the-Air Rekeying (OTAR) by cross-referencing declassified documents, including a 2015 presentation about the dates of the operation...

Chris Zegras, professor of mobility and urban planning and the current head of the MIT Department of Urban Studies and Planning (DUSP), has been appointed chief executive officer and director of the Singapore-MIT Alliance for Research and Technology (SMART), effective Sept. 1. Zegras succeeds Bruce Tidor, professor of biological engineering and computer science, who has served as interim CEO and director since January 2025.

Established in collaboration with the National Research Foundation of Singapore in 2007, SMART is MIT’s only research center outside the United States​. Housed within the Campus for Research Excellence and Technological Enterprise, SMART serves as a key platform for collaboration between MIT and Singapore’s research ecosystem, bringing together leading experts and institutions from the United States, Singapore, and the region for world-class research and innovation.

“Professor Zegras brings a distinguished track record of interdisciplinary leadership and a deep understanding of SMART’s mission and impact,” says Anantha Chandrakasan, MIT’s provost, who announced Zegras’ appointment in a letter to the MIT community today. “His appointment reinforces MIT’s commitment to the alliance, which has advanced innovation and driven global impact, and which remains as important as ever in a time of accelerating technological and global change.” 

Zegras joined the MIT faculty in 2005 and has served as the head of DUSP since 2020. His own research spans interrelated areas critical to tackling metropolitan mobility challenges: leveraging computational technologies for understanding and modeling human behaviors and enhancing strategic planning capabilities.

Zegras brings extensive experience in interdisciplinary research and leadership and a long-standing connection to SMART, where he led collaborative research on next-generation mobility sensing and simulation systems. From 2010 to 2020, he was a principal investigator on the Future Urban Mobility interdisciplinary research group; from 2016 to 2020, he was the group’s lead principal investigator. During this time, the group spearheaded Singapore’s first-ever public autonomous vehicle trials, developed and deployed large-scale urban simulation and visualization systems, and conducted research that evolved into spinoff companies, among other activities. 

“Bringing together leading experts from the U.S., Singapore, and around the world, SMART has established itself as a unique hub for interdisciplinary collaboration and innovation that addresses pressing societal issues,” says Zegras. “Having experienced firsthand what this distinctive model can achieve, I look forward to building on this strong foundation to deepen collaboration, strengthen our innovation ecosystem, and accelerate the translation of research into meaningful real-world impact.”

SMART is built around interdisciplinary research groups, all headed by senior MIT faculty members. At present, there are six groups, focused on antimicrobial resistance; the use of living cells as personalized medicines to treat and prevent diseases; social and institutional challenges arising from the proliferation of AI and emerging technologies; new agricultural technologies; wafer-scale 3D sensing technologies; and wearable ultrasound imaging. SMART is also home to the SMART Innovation Center, which aims to get research ideas from lab to market.

The agency is reorganizing and hiring for hundreds of positions left unfilled by last year's staffing cuts.

The proposal from NV Energy comes as the West grapples with the twin challenges of rising wildfire risk and growing electricity costs.

The justices ordered a lower bench to take a second look at a challenge against DOE rules for water heaters and furnaces.

The shift expands the number of assistant administrator-level positions and refocuses their responsibilities among other changes.

Gov. Mikie Sherrill predecessor's administration spent years crafting a rule package to increase regulations to cope with more extreme flooding.

Still, scientists warn that this will be the most polluting World Cup to date, largely because of the air travel required.

The U.S. withdrawal means Europe is a lifeline for ocean research, although a poorer one.

The British king’s commercial property and land manager, which controls the seabed in England and Wales, will re-tender a planned wind farm site, previously known as Morgan.

The Nigeria-based company secured $76 million in a first round of fundraising for its Successor Fund.

Nature Climate Change, Published online: 09 June 2026; doi:10.1038/s41558-026-02683-0

As climate change impacts are increasingly apparent, there are changes in society and the political landscape that need to be considered.

MIT researchers have demonstrated a low-cost design of specialized electronic nozzles, called triaxial electrospray emitters, that could be used to manufacture time-release drug-delivery particles or self-healing materials efficiently and at scale.

Triaxial electrospray emitters use electricity to precisely dispense three liquids from microscopic nozzles to generate a steady stream with three distinct fluid layers. The liquid forms multilayered droplets, which can solidify into layered microparticles.

For instance, an array of triaxial electrospray emitters can be used to make three-layer drug-delivery nanoparticles. The outer layer might slowly erode in the stomach, revealing a second material that controls the release of a core material, which delivers medicine to a specific area of the intestines.

Developing a tiny array of electrospray emitters typically requires expensive and time-consuming microfabrication processes inside semiconductor cleanrooms, which limits their use. To overcome these drawbacks, the MIT researchers 3D-printed arrays of triaxial electrospray emitters that have 16 nozzles in an area of about one square centimeter. Each device contains an intricate network of three-dimensional microchannels that uniformly supply liquid to the nozzles. 

Their one-step fabrication process takes only a few hours to produce complex emitter arrays. 

When tested, the 3D-printed arrays generated uniform, three-layered droplets at scale. Such uniformity is key for high-throughput manufacturing of layered microparticles for applications like biosensors that detect chemical substances or artificial cells to aid in tissue regeneration.

“We couldn’t make a device like this in a semiconductor cleanroom. This is only possible because they are 3D-printed,” says Luis Fernando Velásquez-García, a principal research scientist in MIT’s Microsystems Technology Laboratories (MTL) and senior author of a paper describing this advance. “The particles these devices generate, whether they are used for a self-healing composite or to deliver medicine, can have a big impact in many applications. We want to democratize this technology so the benefits can touch many more people.”

Velásquez-García is joined on the paper by lead author Bryan Ivan Quintanar-Abarca of the Technological Institute of Monterrey in Mexico. The research appears in Virtual and Physical Prototyping.

A precise process

Electrospray emitters apply a high voltage to a liquid as it exits the device’s nozzle, producing a steady stream of extremely tiny droplets. 

Triaxial devices contain arrays of three concentric nozzles that emit three immiscible, or non-mixable, liquids simultaneously into layered droplets, which can be used to generate compound microparticles with distinct layers.

For instance, one could use a triaxial electrospray emitter to create a biosensing particle that contains three different chemical markers, one in each layer. Electrospray emitters can make smaller microdroplets much faster than other techniques.

Miniaturization is key for electrospray devices, since the smaller the emitter, the lower the voltage required to generate droplets. The output of a single electrospray emitter is modest, so arrays of emitters are required to boost droplet production without sacrificing uniformity. 

Multi-emitter electrospray devices are typically manufactured in semiconductor cleanrooms, but traditional processes limit the shapes and sizes of device components. The researchers could not find any previous reports of a miniaturized triaxial electrospray array in the open literature, highlighting the novelty of this work.

“When you build a triaxial array, you need to find a way to create geometries that have many integrated parts and extremely fine structures in the smallest footprint possible. And you need to ensure the devices will work uniformly,” Velásquez-García explains.

To do this, he and his collaborators used a 3D-printing technique called vat photopolymerization, which utilizes light to solidify extremely thin layers of liquid resin, fabricating a complex device one layer at a time. 

This extremely precise process enabled the researchers to print layers that were only 25 micrometers tall, just a fraction of the width of a human hair. In this way, they could generate the complex internal geometry needed for a triaxial electrospray emitter.

Refining the design

The array, which is slightly larger than a U.S. penny, contains a network of internal coiled channels that carry liquid to 16 nozzles. These helical microchannels help maintain a uniform spray of microdroplets across all nozzles, while keeping the device as compact as possible. 

“In a sense, the emitters in the array never learn they have company, or otherwise there would be cross-talking and causing interference between them. We achieved uniformity because of the work that went into our designs,” Velásquez-García says.

They also needed to fabricate extremely tiny channels without support structures, which could clog the device, and ensure all uncured resin was removed before the array was used.

The microchannels funnel liquid to the concentric nozzles, which must be perfectly aligned to properly emit microdroplets in a consistent manner.

“We were able to aggressively optimize the design because we could iterate in a much timelier manner. This ability to exquisitely refine designs is a key advantage of 3D printing,” Velásquez-García says.

The researchers tested multiple architectures to determine the ideal combination of liquid flow rates to maximize the stability and consistency of emitted microdroplets. They were surprised to find that the viscosity of the middle liquid plays the most important role in achieving stability in a microdroplet, since it preserves the thickness of each layer. 

In addition, the researchers found that by adjusting flow rates and voltages, they could precisely tailor the thickness of each microdroplet layer. This would allow scientists to design drug-delivery particles with ideal layers so medicine releases at exactly the right time.

“By making such intricate devices more practical, we can empower others to pursue entrepreneurial and scientific advances,” Velásquez-García says. 

In the future, the researchers want to continue refining their fabrication process and designs to achieve even smaller dimensions and integrate conductive or dielectric materials to the devices to make more advanced electrospray emitter arrays.

This research was funded, in part, by the Tecnológico de Monterrey – MIT Nanotechnology Program. 

Just days after a damning WIRED report exposed that Meta had quietly embedded facial recognition technology (FRT) code into millions of phones, the tech giant has quietly acquiesced in demands to reverse course.

Last week, researchers identified code in Meta AI, a companion app for its line of smart glasses, that could convert images of faces into unique biometric signatures to identify strangers in public. EFF’s Threat Lab verified these findings through static analysis, and reminded consumers to think twice before buying or using Meta’s surveillance glasses. 

Just as quietly as Meta embedded this code, the app’s June 5th app update appears to have quietly removed all those features and systems. Gone is the face-recognition technology, the code meant to trigger “Person recognized” alerts, and the machine learning models and databases  designed to detect, digitize, and store the biometric signatures of people users engage with.

When WIRED broke the news last week, Meta’s executives immediately went on the defensive. Yet, their actions speak louder than their tweets: less than 48 hours after the public caught wind of their plans, Meta quietly launched an update to scrub nearly all traces of the FRT system from their app.

But this quiet deletion of code does not equal a permanent change of heart. Meta previously used face recognition, and stopped only after it faced the legal and financial consequences. Now the company has refused to answer WIRED’s inquiries on whether it plans to bring the NameTag system back in the future, or what they did with any data they may have already collected during internal testing. 

There are billions of reasons not to turn Meta’s customers into a distributed surveillance machine. This whiplash behavior proves exactly why we cannot rely on the "good will" of Big Tech to protect our digital rights. We need robust, enforceable consumer privacy laws, complete with a private right of action that allows everyday people to sue companies that violate their biometric privacy.

While we won this round, Meta's FRT ambitions probably aren't going away. EFF will keep watching.