Diana Acconcia and Dimitrios Zevgolis will replace longtime negotiator Jake Werksman.

Energy Minister Tim Hodgson advised his counterparts that Ottawa plans to extend the ask to other partners.

Solar-powered cold rooms, warehouses and cooling hubs allow farmers to preserve perishable goods without relying on expensive and unreliable electricity grids.

Roughly 60 percent of the climate-resilient reefs are located in Australia, the Bahamas, Cuba, Indonesia and the Philippines, scientists said in a study presented Tuesday.

An auto factory worker can remember the storage bin where she left a partly assembled component the night before, and quickly return to that spot to pick it up. But robots that may work side-by-side with her would struggle to develop and access this same type of “spatiotemporal” memory.

Now, MIT researchers have developed a long-term memory framework that allows robots to rapidly form and recall a detailed mental model of complicated, large-scale environments.

In the future, this advance could allow the factory worker to send a robotic assistant to fetch the item, simply by asking it to “go and grab the component we started assembling last night.”

This new method combines advanced map representations with rich descriptions of the environment that the robot gathers as it travels over a long period of time. The robot can quickly access this memory to answer complex queries about its environment in plain language.

This memory framework, which answers questions more accurately than state-of-the-art methods, runs fast enough for a mobile robot to use in real-time.

In addition to its potential uses in robotics, this method could have applications in augmented reality systems that aid maintenance workers in anomaly detection or assist commuters in wayfinding.

“If we want robots to work side-by-side with humans and interact better with humans, they must speak the same language. The robot must be able to reason about time and space the same way humans do. That is essentially what our method is doing. It is turning a traditional map into a language-based map that is easier for the robot to think about and access using language,” says Luca Carlone, an associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), principal investigator in the Laboratory for Information and Decision Systems (LIDS), and director of the MIT SPARK Laboratory.

He is joined on the paper by lead author Nicolas Gorlo, an MIT graduate student; and Lukas Schmid, a former research scientist at MIT and now professor at the University of Technology Nuremberg in Germany. The research was recently presented at the Conference on Computer Vision and Pattern Recognition (CVPR).

Spatiotemporal memory

Memory allows an artificial intelligence system, like a chatbot, to answer complex questions and reason about previous interactions with its user.

“We want to design a new type of memory, a spatiotemporal memory, that enables an AI-powered robot to remember real interactions and sensor observations. Like ChatGPT, but grounded in the real world and capable of answering any question about the environment, like ‘Where did I leave my wallet?’” Carlone says.

To develop such a memory framework, the MIT researchers bridged two lines of work: computer vision and robotic mapping.

Multimodal computer vision models can understand and richly describe the objects in a scene, but they often only process a single annotation at a time. On the other hand, robotic mapping frameworks create 3D maps of an environment, like an entire apartment or university campus, but usually lack detailed descriptions of objects or are computationally expensive.

The method the MIT researchers created, called Describe Anything, Anywhere, Anytime, at Any Moment (DAAAM), takes the best of both approaches.

Using DAAAM, as a robot traverses its environment, it attaches rich descriptions to objects it sees. For instance, the robot may note that a particular building on the MIT campus is called the Stata Center and is designed with a certain type of architecture, or that a bike rack holds five bicycles and the red one has a flat tire. 

It stores this detailed information in a 3D map-based representation that is arranged spatially, so objects will be grouped into separate regions. In this way, the robot can remember that the red bicycle with the flat tire is in the bike rack outside the Stata Center.

But existing techniques that capture such rich descriptions typically take a few seconds to annotate a few objects. This is too slow for real-time performance, since a robot might see hundreds of objects during a few minutes of exploration.

“The faster the robot can form this spatial memory, the more efficient it will be performing actions in the environment,” Carlone adds.

Streamlining the process

To speed things up, DAAAM aggregates nearby objects as it travels and uses an optimization method to select key frames to annotate. These are images with the clearest view of multiple objects, allowing the system to thoroughly describe several items in parallel, speeding up computation tenfold.

As the robot explores the space, it attaches each batch of annotations to multiple objects in a particular location on the 3D map.

“We annotate every object only once, so our framework can run in very large-scale environments in real time. And by clustering objects into regions, it can answer a wide range of queries about objects and locations in the environment,” Gorlo explains.

Once the system builds this spatial memory, it must retrieve information from an enormous database of objects and descriptions in an efficient manner. 

To enable this, the researchers used an LLM that calls on various tools, which can quickly retrieve specific information in a way that reduces hallucinations. This allows DAAAM to answer a user query accurately in only a few seconds. 

For instance, if one asks a robot about a certain sculpture it saw near an MIT campus building, DAAAM can use a semantic search tool to retrieve information based on the word “sculpture” or a different tool to retrieve information based on the location of the building.

When tested and compared with other methods, DAAAM was between 21 percent and 53 percent more accurate, depending on the question type. 

In the future, the researchers want to expand DAAAM so the system can capture significant events that happened in the environment. They are also working to incorporate confidence levels into the system’s responses.

“Ultimately, we want to have robots that can help with any sort of tasks. With this framework, we are trying to create the foundations to enable a generalist agent that can do anything you ask,” Gorlo says.

This research was funded, in part, by the U.S. Army Research Laboratory and the Office of Naval Research. Carlone is currently on sabbatical as an Amazon Scholar; this article describes work performed at MIT and is not associated with Amazon.

Nature Climate Change, Published online: 17 June 2026; doi:10.1038/s41558-026-02693-y

Author Correction: Priority science can accelerate agroforestry as a natural climate solution

Nature Climate Change, Published online: 17 June 2026; doi:10.1038/s41558-026-02654-5

Greenhouse gas emissions are typically attributed to where they are produced or consumed. A recent analysis traces them to capital owners, revealing a stronger concentration and offering new perspectives on how they are distributed — and why it matters.

Nature Climate Change, Published online: 17 June 2026; doi:10.1038/s41558-026-02677-y

The biophysical effects of forests on climate are important for mitigation, but the impacts of climate change on these effects are unclear. This study shows that vapour pressure deficit is the primary driver of trends in forest biophysical cooling, regulated by plant anisohydricity.

Nature Climate Change, Published online: 17 June 2026; doi:10.1038/s41558-026-02662-5

An ownership-based approach to carbon accounting is emerging alongside production- and consumption-based frameworks. This study provides global estimates, identifies which countries are net owners of emissions abroad and traces the concentration of ownership emissions among top wealth groups.

In May, the Initiative for New Manufacturing (INM) marked its first anniversary with MIT Manufacturing Week, four days of events that attracted more than 800 registrants including students, faculty, industry leaders, investors, entrepreneurs, and government officials to explore topics ranging from how companies are using AI on factory floors to the role of startups in introducing innovation to new workforce solutions to address the worker shortage.

“INM launched a year ago with the premise that strengthening the industrial base needed a coordinated response, and MIT has a responsibility to lead it,” says Paula T. Hammond, dean of MIT’s School of Engineering and co-chair of INM’s Steering Committee. “The response and participation level has been huge. MIT Manufacturing Week proved that the appetite for change — from students to chief executives — is real and urgent.”

The week opened with a cybersecurity workshop co-led by INM and Google Cloud for the initiative’s industry members. It continued with the MIT MIMO (Machine Intelligence for Manufacturing Operations) symposium focused on deploying artificial intelligence on factory floors, alongside discussions on workforce development, emerging technologies, startups, and industrial transformation. The week closed with a regional research showcase and competition that drew more than 140 graduate students and postdocs from across New England.

Over the past year, INM has also continued its distinguished speaker series featuring manufacturing leaders including Keith Flynn, senior vice president of manufacturing at Anduril; Roland Busch, president and CEO of Siemens; and Venky Alagirisamy, COO of Nike.

Inspiring a new generation of manufacturing startups

A central goal of INM is to help more students see manufacturing as a frontier for scientific discovery, technological innovation, entrepreneurship, and societal impact.

To support that effort, INM is launching and leading programs to help move early-stage ideas and new technologies from the lab to real-world development, and to catalyze new manufacturing companies. 

This year, INM partnered with NSF I-Corps New England, which helps researchers turn their startup ideas into companies, to host its first manufacturing research showcase. More than 140 teams from 17 universities across New England applied to participate. Forty finalist teams received mentorship on their ideas and advanced to the final competition, where eight teams shared $50,000 in prize funding.

The top prize in the category “most transformative innovation” went to MIT PhD student Jake Read for “The End of G Code,” a project focused on modular machine control architectures designed to accelerate the development of new manufacturing equipment and processes. Vatsal Patel from MIT and Joshua Grace from Yale University won the top prize in the research excellence category, for “VisFT,” scalable six-axis force-torque sensors.

Project themes presented by participating teams included AI tools for manufacturing, semiconductor manufacturing and process control, robotics and autonomous assembly, digital twins and simulation, new materials, additive manufacturing, next-generation shipbuilding, and biomanufacturing. 

“Entrepreneurship is a transformative pathway to take research to market, and to drive faster innovation and scale-up,” says John Hart, INM faculty co-director and head of MIT’s Department of Mechanical Engineering. “At INM’s inaugural research showcase, we had tremendous interest from universities across New England, along with enthusiastic participation from industry, investors, and experienced founders across the ecosystem. We are excited to build on this success and work toward a nationwide program and platform for entrepreneurship and translation in manufacturing.” 

The Cheng Wu Foundation supported the showcase. 

Growing industry membership

During MIT Manufacturing Week, First Solar became INM’s eighth industry member, joining Amgen, Autodesk, GE Vernova, Flex, PTC, Sanofi and Siemens. 

The growth of INM’s consortium reflects a broader recognition that the challenges facing modern manufacturing — from supply chain resilience to workforce development and industrial competitiveness — are too complex for any single sector or company to address alone. 

This reflects renewed interest in manufacturing at a moment when advances in artificial intelligence, robotics, energy systems, and advanced materials are transforming industrial production. INM provides a platform to convene and provide solutions.

INM’s industry consortium model brings industry, researchers, and educators together around shared manufacturing challenges, with a focus on emerging technologies, workforce transformation, and commercialization pathways. Members participate in workshops and working groups on topics including cybersecurity and digital twins, implementing automated systems, AI agents in regulatory environments, and AI and continuous innovation. INM helps them connect with students, meet with startups, and learn from one another.

“Our members see MIT as a partner that can help them both address today’s challenges and think far into the future,” says Rick Locke, dean of the MIT Sloan School of Management and co-chair of INM’s steering committee. “This kind of multi-industry engagement is unusual and powerful.”

A year of rapid progress

When MIT launched INM a year ago, the goal was to create stronger connections between research, industry, workforce development, and entrepreneurship — helping accelerate how new manufacturing technologies move from the laboratory into real-world development.

Since then, the initiative has expanded quickly across research, industry, workforce training, and student engagement. INM issued a call for proposals focused on artificial intelligence and automation, receiving an incredible response from faculty and researchers, and funding eight seed research projects. In June, the initiative plans to publish eight white papers as part of a broader study examining the future of manufacturing. 

During MIT’s Independent Activities Period (IAP) in January 2026, INM collaborated with NSF I-Corps to guide 13 early-stage teams through customer discovery as part of the I-Corps Spark program.

Workforce development has also been a major focus. This fall, MIT launched the Technologist Advanced Manufacturing Program (TechAMP), led by Principal Research Scientist John Liu, to create a new generation of shop floor leaders and drivers of productivity — becoming“‘technologists” — at six sites across New England, including three community colleges. 

“INM has the potential to transform the national manufacturing workforce,” says Liu. “It will require deep engagement between how people learn and lead, and how firms adopt new technologies and transform. We’re just getting started.” 

INM is now exploring a national rollout of TechAMP, along with expansion into areas including biomanufacturing and semiconductor manufacturing.

On campus, INM supported student engagements including an AI and automation lunch series that Professor Faez Ahmed and colleagues organized, and visited factories through its Factory Observatory program that Ben Armstrong and the MIT Industrial Performance Center led. This spring, students also founded MIT’s first manufacturing club, holding its launch event during MIT Manufacturing Week. “We’re thrilled students are taking the lead,” says Sloan associate professor and INM faculty co-director Karen Zheng. “It was really exciting to see a full room of 80-plus students across campus coming together for the kickoff event during the busiest final period of a semester. This speaks to the students’ enthusiasm.” 

An eye toward the long term

While maintaining a deep focus on strengthening domestic manufacturing, INM aims to have a global reach. For example, the initiative is collaborating with NAMTECH, a new education institute in Ahmedabad, India, where students are now taking an adaptation of MIT’s well-known “yo-yo course,” or 2.008 (Design and Manufacturing II), focused on the fundamentals of manufacturing processes.

Next year, INM plans to bring more manufacturing leaders to campus, offer additional programming for emerging entrepreneurs, graduate the first cohort of TechAMP students, bring TechAMP to new states, grow the consortium to include new industries, and deepen research into manufacturing productivity. 

“INM aims to be a catalyst for transforming manufacturing across the nation to drive innovation, economic growth, and new types of jobs,” says Chris Love, faculty co-director of INM. “MIT’s work on the PIE (Production in the Innovation Economy) study in 2013 highlighted the value of proximity between production and innovation. INM seeks to rekindle this relationship in manufacturing across the country.”

After 26 years, today is my last day at EFF. It's been a terrific and wild ride — the organization has grown from a tiny band of fighty people trying to plant a flag for freedom and justice in the coming digital world into a large, established band of fighty people doing, well, much the same. The world around us has changed enormously. Our core values haven't budged.

I'm proud of what we've achieved: freeing encryption, defending coders, pushing to rein in government and corporate surveillance and ensure the right to have a private conversation online, standing up for free speech and anonymous speech, fighting for network neutrality and safe voting machines, busting stupid patents, and making sure copyright didn't become the one law that rules the internet. That's only the start. We've stopped more bad legislative, regulatory, and legal ideas than I can count, built tools that millions rely on to protect their privacy, and helped encrypt the web. I've long said EFF is the plumber of the internet — finding the clogs and barriers that prevent technology from serving freedom, justice, and innovation for everyone.  

In addition to presenting cases in courts across the land, testifying in Congress and in California, in the European Parliament and at the United Nations, I went onto the internet with Stephen Colbert and engaged in a healthy disagreement with Jon Stewart.  I wrote a lot of it down in a book, hoping to recruit others to the cause.  The work has been hard and often frustrating at times.  But looking back, the fun parts are what I remember most.   

None of it would have been possible without EFF’s stalwart members. More than 30,000 people, some with big wallets and some with small ones, give us what we need to stand up to bullies and fight for the long haul. EFF has always served as a beacon for people who know that for technology to support freedom, justice, and innovation for all the people of the world, we need a dedicated band of folks working overtime on behalf of users, innovators, and creators. 

There's still plenty left to do. We haven't killed the third-party doctrine, tamed the surveillance business model, or gotten metadata the constitutional protection it deserves. Stupid patents persist as does the overreach of DMCA section 1201 and the Computer Fraud and Abuse Act. The government is now the largest purchaser of data from shady brokers, communities everywhere are fighting license plate readers and other street-level surveillance, and we haven't reined in NSA and FBI spying nearly enough. Meanwhile, the rise of AI is supercharging problems we've fought against for years. 

But I'm proud of what we've built together. I'm grateful to every EFFer — past, present, and future — who threw in with us when the odds were long and the pay was much better elsewhere. I'm grateful to the EFF Board and especially to my mentors and friends Pam Samuelson and Shari Steele, along with my longtime partner in justice, Lee Tien, who has been working with me since the Bernstein case. Fighting for justice is easier when you have a posse: coworkers, co-counsel, coalitions, interns, volunteers, and the heroic clients who trusted us to steward their cases in ways that bent the law toward everyone's benefit. Twenty-six years later, EFF is part of a global diaspora of organizations defending internet freedom — and I'm proud of that too. 

I'm stepping down because good leaders should make way for new ones, and the time feels right. EFF is strong and full of fight. My successor Nicole Ozer — a longtime friend and collaborator — is exactly the right person for this moment. She understands EFF's role and values at a deep level and will protect them while helping the organization rise to meet what's coming. 

As for me, I'm not going far. After a few months off to reflect and walk dogs, I plan to get back into the fight for justice — likely heading back into the courtroom. And I'll be watching, cheering, donating, and wearing the merch from EFF, just like the rest of you.

There are over a dozen cases around the country where police officers are using the Flock surveillance camera system to obsessively and illegally stalk people.

Alternate link.

Oklahoma Republicans are embracing a tougher regulatory stance once considered untouchable in a primary race to be insurance commissioner.

A tax law phasing out solar incentives imperiled projects already underway.

Federal judges granted Interior’s bid to voluntarily drop its appeal of a ruling against the administration's pause on new wind approvals.

AM Best warns that the power-hungry, fire-prone facilities will need more coverage than the property insurance market has ever experienced.

Alaska Republican Sen. Lisa Murkowski joined Democrats in both chambers urging the National Science Foundation to reconsider.

The attack on the Emissions Trading System is among industry’s most direct calls yet for the EU to change course on climate.

The European Commission is drawing flak for offering fiscal leeway to contend with skyrocketing fuel prices.

Other targets include more than 80 percent electrification on fixed short‑haul routes in key regions and 18 percent of highway freight volumes carried by such vehicles.