Nature Climate Change, Published online: 05 June 2026; doi:10.1038/s41558-026-02656-3

Global warming boosts freshwater methane production. Now, a study shows that methane oxidizing bacteria cannot increase their methane consumption rates enough in response to warming-induced enhancement of methane availability, leading to higher emissions.

Nature Climate Change, Published online: 05 June 2026; doi:10.1038/s41558-026-02643-8

Blue carbon brings new interest in the land and sea rights of coastal communities, small-scale fishers and Indigenous peoples. While promises of climate mitigation, conservation and economic benefits are compelling, blue carbon projects must uphold local agency and rights as a legal and ethical duty, not just as conditional for project approval.

Nature Climate Change, Published online: 05 June 2026; doi:10.1038/s41558-026-02649-2

How the balance of microbial methane production and oxidation in freshwater systems will change with warming is unclear. This study uses natural warming experiments to demonstrate that methane emissions increase because oxidation keeps pace with, but cannot exceed, warming-accelerated production.

Nature Climate Change, Published online: 05 June 2026; doi:10.1038/s41558-026-02651-8

Blue carbon projects are expanding, yet their implications for tenure security remain uncertain. Analysis of 122 guidance documents reveals that rights are narrowly interpreted and key international obligations are overlooked, leaving rightsholders vulnerable to dispossession and exclusion.

When you picture a worker at a retail store, you probably think of someone at a cash register or helping a customer. But employees also spend a lot of their time combing through stockrooms and shop floors, fulfilling requests or online orders and generally trying to keep track of all their inventory.

Keeping track of inventory takes so much time, in part, because retailers don’t always know where everything is located. That’s why when you ask a store associate to check if they have a shirt in your size, it may take them 20 minutes to get back to you.

Cartesian is helping retailers keep track of inventory with a technology invented at MIT. The system uses wireless signals from radio frequency identification (RFID) tags attached to items to find their precise location in a store, from the stockroom to the shop floor.

Last year, Cartesian did a study with a retailer and found its platform delivered meaningful annual savings at the store level by streamlining inventory tracking, optimizing workflows, and improving customer experiences.

“The big problem we’re solving is that about 50 percent of working hours in retail stores go to managing inventory,” says co-founder Fadel Adib SM ’13, PhD ’17, an associate professor at MIT. “That is roughly a $15 billion problem in the U.S. alone. We use algorithms to decipher indoor locations using wireless signals. The core technology enables a new level of indoor localization.”

Cartesian is already deployed in more than 700 stores across 15 countries and is working with one of the world’s largest fashion groups, Inditex, which is the parent company to brands like ZARA, Pull&Bear, and Oysho.

Beyond retailers and warehouses, Cartesian’s platform could also improve indoor location tracking for manufacturers, logistics operators, and robotics companies.

“The broad vision for what we are doing is spatial AI,” says Adib. “Today, AI does extremely well in the digital world. Now it has to move into the physical world. That means allowing machines to perceive their environment in such a way that they can interact with it. That’s where spatial AI comes in and where Cartesian sits.”

From technology to product

Adib, who holds a joint appointment in MIT’s Media Lab and Department of Electrical Engineering and Computer Science, has been studying wireless signals at the Institute for more than 15 years, dating back to research during his master’s degree.

“My group today researches how to use wireless signals to sense the world in ways that were not possible before,” Adib says. “We develop the fundamental technology and then we build systems around them. Our goal is to see these systems deployed in the real world for impact.”

When Adib joined MIT’s faculty, the first project he worked on was indoor localization using RFID tags. Isaac Perper ’20, MEnG ’21 later joined his lab as a student, and together they developed machine-learning algorithms to process RFID data to translate them into location patterns, with an initial focus on helping robots locate RFIDs indoors.

In 2021, Adib went through the National Science Foundation’s I-Corps program, which challenges researchers to interview potential customers to find the right problems to solve with their technologies. That’s when he realized how big of a problem inventory management is for retailers.

Cartesian was officially founded by Adib and Perper in the beginning of 2023, after they received a small business award from the National Science Foundation. The pair worked with MIT’s Technology Licensing Office to license patents from Adib’s lab. They also received support from MIT’s Venture Mentoring Service.

“Our goal was to reduce the cost of the technology to make it scalable,” Adib recalls. “Isaac focused on simplifying the product, leveraging progress in machine learning, and making it fast. It was a lot of iterating and testing early on.”

Retail workers spend much of their time locating items for a number of reasons. They might get an online order to fulfill, need to restock store shelves, or get a customer inquiry about items in the back.

Stores differ in how they organize their inventory. Most separate items by categories in specific shelves and bins then use barcodes or inventory systems that tend to get outdated fast.

“It’s a big problem for stores because customers may just leave before asking an employee to look for their size, or customers may get frustrated and leave if it takes too long,” Adib says. “The associate also wastes time looking for items they could spend doing higher-value work.”

Cartesian’s platform works with retailers’ existing handheld RFID readers, which store associates already use to manage inventory. Each store installs Cartesian’s software into their existing inventory apps or uses a custom app for employees to access directly.

“The RFID readers are how stores tell what’s in stock and what’s out of stock,” Perper says. “We figured out a way to leverage the same scans they’re already using with the reader, put the data they generate into our machine-learning algorithms, and generate maps of where all the items are.”

Customers can build analytics on top of Cartesian’s technology to keep track of inventory levels, show customers maps of where each item is located, and create other services.

“They use our location intelligence platform and build different products on top,” Adib says. “We can work with any device, any store, any type of RFID. It’s a simple interface. All the sophisticated location algorithms sit in the cloud.”

Beyond retail

Cartesian signed its first big contract in 2025 and soon expanded to several hundred stores. One of Cartesian’s advantages is its ability to quickly scale. Perper says they can add a store in about one minute. Cartesian’s team doesn’t even have to travel to a new store to turn on its system if it’s already working with the company.

“It’s as simple as flipping a switch, preparing the data, and sending it to our customers,” Perper says. “One of our first big bets was, ‘Can we build this entirely on existing hardware?’ That bet is starting to pay off.”

Cartesian’s models can also work with Wi-Fi and Bluetooth signals, which the company plans to use with customers in other verticals.

“Right now, we’re focused on applications in retail, but this technology has a lot of value in manufacturing, warehouses, and other locations,” Adib says.

Cartesian’s team aims to be deployed in tens of thousands of stores over the next year and then begin expanding beyond retail into industries like manufacturing and robotics.

“What’s most exciting about Cartesian to me is we’ve built a lot of the technology foundation, and now that we have the fundamentals in place, we hope to build specific application layers,” Perper says. “Then we can ask customers in different verticals about their problems and apply our technology in different ways to solve it.”

California lawmakers are again considering A.B. 412, a bill that would require AI developers to identify and disclose copyrighted works used to train generative AI systems.

The problem this year is the same as last year: it’s practically impossible to comply with this law. The bill demands information that often does not exist, and cannot realistically be obtained. 

EFF submitted an opposition letter to the California Senate Privacy Committee explaining why we continue to believe A.B. 412 is simply unworkable. To the extent developers do follow this law, it will have the effect of locking in the power of the largest companies in AI. 

A Burden That Can’t Be Met

A.B. 412 sounds simple: just have AI developers create and keep a list of all the registered copyrighted works they use in AI training. 

That may seem straightforward. In practice, it’s anything but. 

There is no machine-readable “list” of copyrighted works at the U.S. Copyright Office. And many copyright holders can get a copyright without even depositing a publicly viewable sample of the work—for example, software companies may register copyright on proprietary code without revealing it to the public. 

And on the open internet, copyright information is often incomplete, unavailable, or impossible to verify. One image may be registered with the copyright office, while the next is licensed under a free Creative Commons license (like the images that EFF creates), and the next is public domain. A message forum user might post an original story, photograph, or poem without any indication of ownership or registration status. 

The bill effectively asks developers to continuously cross-reference massive batches of online data against a copyright system that simply wasn’t designed to do so. If California passes A.B. 412, its impact will go far beyond the large AI companies we read about in the headlines. 

Not Just Big Tech

Supporters often frame this bill as a way to help creative workers have some leverage against Big Tech, but the bill reaches much further than the big AI companies. 

Its definition of “developer” extends to anyone who makes a generative AI model available to Californians. That includes indie developers tinkering with an existing model, open-source initiatives, nonprofits, and other non-commercial efforts. Recent amendments added exemptions for universities and government entities, which is important, but that still leaves out a vast swathe of non-commercial tech work that’s done by people without full-time jobs in government or academia. 

Large companies will hire compliance teams and lawyers to navigate these requirements. Smaller organizations and independent developers usually can’t. The result will be fewer opportunities for startups and new entrants. Faced with this massive compliance burden, some won’t even try. 

Courts Are Already Deciding These Questions

The bill is premised on the idea that copyright owners currently don’t have good remedies if they’re mistreated by AI companies. That simply isn’t true. And the growing wave of federal court filings in this space prove it. Content companies that want to sue tech companies, large or small, have no problem doing so. Those courts are still working through important questions about fair use and transformative use. Some courts have already concluded that many AI training activities qualify as fair use. Others continue to evaluate the issue.

California lawmakers should not rush to impose new state regulation while those questions remain unresolved. This is why copyright is governed at the federal level: both creators and fair users benefit from a single set of nationwide rules. 

At this point, the bill remains a solution in search of a problem. Rights holders already have powerful tools to protect their interests under existing federal law. What this bill adds isn’t clarity or transparency, but a costly and essentially impossible compliance burden that will discourage small developers and researchers. 

California has been able to support both artistic creativity and tech innovation for decades now.  But A.B. 412 does not strike the right balance. 

If you are a California resident and interested in speaking out about this bill, you can find and contact your representatives through this website. 

President Trump’s highly politicized appointment of an entirely unqualified acting Director of National Intelligence (DNI) underscores why the government’s warrantless mass spying power must be reformed. 

Congress now faces a deadline of Friday, June 12 to reauthorize Section 702 of the Foreign Intelligence Surveillance Act, an unconstitutional program rife with problems, loopholes, and compliance issues. Section 702 allows the National Security Agency to collect communications from targets overseas – including communications with Americans in the U.S. – and stores them in massive databases. The NSA then allows other agencies, including the Federal Bureau of Investigation, to access untold amounts of that information.  

Under current practice, the FBI can query and even read the U.S. side of that communication without a warrant. What’s more, victims won’t even know and have very few ways of finding out that their communications have been surveilled. EFF and other civil liberties advocates have been trying for years to know how data collected through Section 702 is used in domestic investigations and prosecutions.  

Our advocacy to reform Section 702 has been consistent across administrations, including when the federal Intelligence Community was run by people with experience in the relevant agencies. In fact, the 2004 law creating the position of DNI – which coordinates America’s 18 spy agencies – requires those who hold it to have “extensive national security expertise.” 

Enter Bill Pulte. 

Trump on Tuesday named Pulte – currently director of the Federal Housing Finance Agency (FHFA) and chairman of Fannie Mae and Freddie Mac – to replace current DNI Tulsi Gabbard, who announced her resignation last month. Pulte lacks any intelligence, military, or congressional experience.  

“William has deep experience managing the most sensitive matters in America, the safety and soundness of the Markets, and over 10 Trillion Dollars at Fannie Mae/Freddie Mac, a substantial increase from where it was just 12 months ago,” Trump wrote on his Truth Social platform.

Pulte isn't a qualified intelligence administrator. He does, however, seem to be unquestioningly loyal to President Trump and willing to use his position to attack and smear the President’s political foes.   

Because Trump named him acting DNI, Pulte isn’t subject to Senate confirmation. And under the Vacancies Act, Pulte could remain in the role for about seven months. 

This is particularly concerning because of Pulte’s history of using private information held by the government as a political weapon. In his FHFA role, he has accused several of the President’s political foes and targets – including New York State Attorney General Letitia James, U.S. Sen. Adam Schiff, D-Calif., and Federal Reserve governor Lisa Cook – of mortgage fraud based on private data held by his agency.  

All these targets and others have denied wrongdoing. A federal criminal complaint filed against James in Virginia imploded after a judge found prosecutor Lindsey Halligan had been unlawfully appointed, and prosecutors twice failed to convince a grand jury to indict James. Pulte’s accusations against Schiff, Cook, and others have not led to criminal charges. 

Pulte also used his FHFA pulpit to attack then-Federal Reserve Chair Jerome Powell and dismantle internal oversight. 

Pulte isn't a qualified intelligence administrator. He does, however, seem to be unquestioningly loyal to President Trump and willing to use his position to attack and smear the President’s political foes. As acting DNI, Pulte would have access to every scrap of classified information the Intelligence Community holds, and under Section 702, that includes massive amounts of information about Americans. 

Even lawmakers who are typically friendly to the intelligence community acknowledge that this is a disaster in the making. U.S. Sen. Mark Warner, D-Va., who is the Senate Intelligence Committee’s ranking Democrat, told NPR that Pulte has "no experience in the military, no experience in Congress, no experience in the intel community or law enforcement" and was chosen because he is "100% loyal to doing anything and everything President Trump demands." 

And Senate Majority Leader John Thune, R-S.D., told reporters “we don’t need a weaponized” national intelligence director. Asked about fears that Pulte might pursue Trump’s political opponents, Thune said: “We need professionals there.” 

Congress already has had trouble reauthorizing Section 702 as Freedom Caucus Republicans and many Democrats joined forces to demand reforms including the common-sense requirement that federal agencies get a probable cause warrant from a judge before searching any data involving Americans. Pulte’s appointment exemplifies why no administration should have the power granted by Section 702 without the independent judicial review required in seeking a warrant. 

Governments must not adopt emerging and powerful AI technologies without also adopting strong and clear safeguards to protect Constitutional rights, EFF Senior Policy Analyst Dr. Matthew Guariglia testified today to the House Homeland Security Subcommittee on Cybersecurity and Infrastructure Protection. 

During the hearing on “The AI Security Landscape: How Frontier Models, Agentic AI, and AI Coding Tools Are Reshaping Cybersecurity and Critical Infrastructure Resilience,” he explained that he use of generative AI for the purposes of mass government surveillance would supercharges unconstitutional violations of civil liberties. He also highlighted how government secrecy, in addition to the black box of for-profit proprietary technology, prevents the public and lawmakers from knowing when AI models make mistakes, including errors that seriously impact the cybersecurity of critical infrastructure and the lives of individuals.  

“AI also has a track record of getting things wrong—from false citations on legal briefs to a major AI mistake that sent DHS recruits to the field without proper training. There are likely more consequential examples that we do not even know about because of classification that would prevent a more thorough accounting," he said in his opening remarks.

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“At this level the question is not how do we rein in AI, it’s how do we rein in the agencies that would unleash AI on the American public,” Matthew said in response to a question by Subcommittee Ranking Member Delia Ramirez, D-Ill.  

You can read his full testimony as prepared here. 

Carbon capture is an important climate change mitigation strategy, but it faces technological barriers and can be energy-intensive and expensive. To help make necessary advances in this area, a team of MIT researchers, with support from the MIT Climate and Sustainability Consortium (MCSC), are exploring energy-efficient and scalable alternatives to conventional carbon dioxide (CO2) capture methods. 

Conventional amine scrubbing, which is the current standard for CO2 capture, is energy-intensive and difficult to scale, limiting its impact despite the urgent need to reduce carbon emissions and upgrade CO2 into valuable products. In a new article published in Nature Energy, MIT researchers — graduate students Fang-Yu Kuo of the Department of Chemical Engineering, and Gi Hyun Byun of the Department of Mechanical Engineering (MechE); Professor Betar Gallant of MechE; and former MCSC postdoctoral Impact Fellows Glen Junor and Akachukwu Obi — investigate a promising alternative to these conventional CO2 capture methods. Their findings could move the needle on achieving efficient and flexible carbon capture and removal.

In their paper, the team explores an alternative, electrochemically mediated CO2 capture (EMCC). This approach enables electrification of CO2 separation — driven ideally by renewables — but currently faces challenges, such as relying on sorbents that require highly reducing potentials, where oxygen reduction side reactions become significant. This can compromise both efficiency and long-term performance. To tackle this shortcoming of EMCC, the MIT team researched whether N-heterocyclic imines (NHIs) is a useful new class of EMCC sorbent.

“NHIs have shown promise in recent years as CO2 sorbents because of the ease of NHI molecular modifications for tuning basicity,” says Fang-Yu Kuo. “Our work translates these NHIs for the first time into the EMCC application space, and demonstrates that NHI-based sorbents can be modulated electrochemically for CO2 separation by a unique separation mechanism that avoids the need of applying highly reducing potentials.”

The team’s initial research establishes a novel bis(NHI) structure that can enable a theoretical CO2 modulation of two molecules per electron during cell operation. The initial published result also indicates that with further molecular engineering of bis(NHI) structures to strengthen CO2 binding affinity, the bis(NHI) could operate in more diverse electrolyte environments, opening new possibilities to optimize system performance in terms of electron efficiency, energy efficiency, and operational flexibility.

“A critical future direction of our work involves gaining deeper mechanistic insight into the stability and degradation pathways of the bis(NHI) radical cation,” says Kuo. “Understanding these pathways will inform the rational design of next-generation bis(NHI) molecules, enabling longer operational lifetimes and enhanced cycling durability for practical deployment.”

Meta has deployed facial recognition code to millions of their always-on surveillance glasses, according to new reporting by Wired. EFF’s Threat Lab was able to confirm that the facial recognition code is present through static analysis of the application. 

This dangerous new Meta functionality stores faceprints as a series of 2,048 numbers uniquely representing the positioning of a person’s facial features. When this feature is activated, it will convert every new face in the sightlines of the surveillance glasses into a series of numbers, and compare it to all the existing faceprints in the user’s database.

Wired and EFF confirmed that the code is present and active, though not yet exposed to consumers. Another researcher confirmed that when they manually added a face to the app database by connecting the phone to a computer in debug mode and issuing a few commands, the glasses would subsequently detect that face when it came into view. 

Meta has already paid $650 million to settle a BIPA lawsuit challenging mass facial recognition of every photo posted to its platform, a feature which it has since shut down. 

Despite the billions of reasons not to, Meta seems to have created the capacity to turn their customers into a distributed surveillance machine. This is just one more reason to think twice before buying or using Meta’s surveillance glasses. 

Considering that Meta previously wrote in an internal document that they want to launch facial recognition “during a dynamic political environment where many civil society groups that we would expect to attack us would have their resources focused on other concerns," this invasive new feature doesn't come as a surprise. But Meta's surveillance plans won't escape public scrutiny that easily, and we'll be watching if this feature is rolled out to the public. 

MIT, in collaboration with Georgia State University and a growing network of educational institutions, has announced expanded work under PATH (Pathways for AI Training and Hiring) — a multiyear initiative designed to scale effective, affordable, industry-aligned AI training for entry-level and current workers, with a particular focus on transforming community colleges into engines powering an AI-enabled workforce for the nation. 

“In the era of AI, economic opportunity and mobility will increasingly depend on whether people can develop practical, industry-relevant AI skill sets and mindsets, not just familiarity with tools,” says Cynthia Breazeal, principal investigator (PI) of PATH and professor of media arts and sciences at MIT. “That means combining hands-on, work-learn experiences with strong technical foundations and the responsible design, professional, and human skills that employers are looking for.”

To make that possible, the initiative is building state-based hubs anchored by research universities and community colleges. Each hub works with regional employers to design curricula that reflect local industry needs. The program also provides professional development for instructors and develops modular, open educational materials that institutions can adapt and share.

“Artificial intelligence is shaping every sector of the economy, and the United States will need far more people who understand how to build with these technologies and apply them responsibly,” says MIT President Sally Kornbluth. “Through PATH, MIT RAISE is using our convening power to bring community colleges, industry, research universities, and government together to build human-centered AI pathways that lead to shared prosperity. When research universities contribute their expertise to expand access and economic mobility, we strengthen both the nation’s workforce and our collective capacity for innovation.”

Unlike many large-scale online training efforts, PATH emphasizes in-person, collaborative learning. Students work in teams to address real problems brought by industry collaborators. These projects mirror the kinds of challenges graduates will face in the workplace, helping them build technical skills alongside the judgment, communication, collaboration, and ethical awareness that employers increasingly value.

The initiative’s first two hubs launched earlier this year in Massachusetts and Georgia.

“As PIs for the Georgia PATH hub, we are very excited with the significant early momentum, with over 1,000 GSU students enrolled in PATH courses,” says Arun Rai, regents’ professor, Howard S. Starks Distinguished Chair, and director of the Center for Digital Innovation at Georgia State University (GSU), with Balasubramaniam Ramesh, regents’ professor and the George E. Smith Eminent Scholar’s Chair at GSU. “Our curriculum, co-designed with MIT RAISE and spanning AI foundations, data science, deep learning, and agentic AI systems, is now being shared with partner institutions including Georgia Gwinnett College, GSU Perimeter College, and Clark Atlanta University. By leveraging the University System of Georgia’s FinTech Academy to expand work-based learning opportunities, we are building a collaborative ecosystem that rapidly advances the state’s AI workforce capabilities and creates tangible, job-ready skills for our diverse student population.” 

GSU President Brian Blake says, “Our collaboration with MIT reflects a shared commitment to strengthening the nation’s AI talent pipeline. Georgia State University brings a distinctive strength to this effort — the ability to prepare students from all backgrounds for AI-enabled careers at scale. By combining academic rigor with strong industry partnerships and work-based learning, we are translating advances in AI into practical skills and expanding access to opportunities in this transformative era.”

In Massachusetts, students at Quinsigamond Community College are participating in Data Science in Action, a course that introduces AI-enabled data analysis and engineering. The class includes a hands-on Action Lab, modeled after experiential learning programs at the MIT Sloan School of Management. David Birnbach, lecturer at MIT Sloan, leads the design framework for the PATH Action Labs. Working with industry partners, students tackle real data challenges while building portfolio projects and professional connections. 

Beyond individual courses, PATH is building clearer pathways for students to turn AI learning into real job opportunities. Through industry-informed micro-credentials and a shared set of workforce skills, students will gain practical abilities that employers are actually looking for, along with the human skills needed to succeed at work, like communication, problem-solving, and collaboration. 

The MIT skills taxonomy team, led by Katerina Bagiati in collaboration with Professor Tom Malone from the MIT Sloan Center for Collective Intelligence, is mapping the skills and roles emerging in AI across fields such as financial technology (fintech), information technology, and business operations, with plans to expand into areas such as health care, manufacturing, and creative media. The goal is to help students build skills that are relevant, recognized, and directly connected to growing career paths.

The initiative is supported by a grant to MIT from Google.org, which is helping MIT and its collaborators build a multi-state network for AI workforce development.

“MIT’s PATH initiative offers a blueprint for expanding opportunity in the age of AI,” says Shanika Hope, director of Google.org. “By connecting research universities, community colleges, and industry partners, it helps translate innovation into real jobs and sustainable career pathways.”

PATH is led by Breazeal, who has brought together a cross-MIT team with expertise in AI literacy, workforce pedagogy, educator professional development, open education, research, and the future of work. Breazeal is a professor and director of the MIT RAISE Initiative. Eric Klopfer, director of the STEP Lab and co-director of the MIT RAISE Initiative, serves as a co-PI on this award. The GSU leadership team includes PIs Arun Rai and Balasubramaniam Ramesh.

Hackers are convincing Meta’s AI support chatbot to let them take over other peoples’ accounts:

A video posted on X showed the step-by-step process to hack someone’s Instagram account. The hacker allegedly used a VPN to spoof the targets’ presumed location to avoid triggering Instagram’s automated account protections. Then, the hacker opened a chat with Meta AI Support Assistant and asked the bot to add a new email address to the target’s account. The chatbot can be seen sending a verification code to the email address provided by the hacker; the hacker then shares the verification code with the chatbot, which prompts the chatbot to show a button to “Reset Password.” The hacker enters a new password and takes over the victim’s account...

The agency's regulatory rollback for grocery refrigerators has sparked a backlash from U.S. manufacturers.

The National Center for Atmospheric Research is the latest example of how the Trump administration’s efforts to chain saw the federal government can happen too fast for the courts or Congress to counter.

The far-reaching measure also would launch a study of the state’s 2050 carbon-neutrality target — a move that could set the stage for its demise.

The country's climate pollution climbed 2 percent this year because wind and solar power weren't integrated into the grid.

The South Texas city is trying to navigate a potential water shortage that could affect refineries and residents.

A combination of climate change, urbanization and inflation mean disasters are getting more costly when they hit.

The findings underscore the economic toll of climate change and the opportunities it creates for companies that help customers mitigate and adapt to its effects.

With the center of the storm at sea, the cyclone posed no immediate threat to land.