Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity. 

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

The material’s unique magnetic properties also allow for transistors with built-in memory, which would simplify circuit design and unlock new applications for high-performance electronics.

“People have known about magnets for thousands of years, but there are very limited ways to incorporate magnetism into electronics. We have shown a new way to efficiently utilize magnetism that opens up a lot of possibilities for future applications and research,” says Chung-Tao Chou, an MIT graduate student in the departments of Electrical Engineering and Computer Science (EECS) and Physics, and co-lead author of a paper on this advance.

Chou is joined on the paper by co-lead author Eugene Park, a graduate student in the Department of Materials Science and Engineering (DMSE); Julian Klein, a DMSE research scientist; Josep Ingla-Aynes, a postdoc in the MIT Plasma Science and Fusion Center; Jagadeesh S. Moodera, a senior research scientist in the Department of Physics; and senior authors Frances Ross, TDK Professor in DMSE; and Luqiao Liu, an associate professor in EECS, and a member of the Research Laboratory of Electronics; as well as others at the University of Chemistry and Technology in Prague. The paper appears today in Physical Review Letters.

Overcoming the limits

In an electronic device, silicon semiconductor transistors act like tiny light switches that turn a circuit on and off, or amplify weak signals in a communication system. They do this using a small input voltage.

But a fundamental physical limit of silicon semiconductors prevents a transistor from operating below a certain voltage, which hinders its energy efficiency.

To make more efficient electronics, researchers have spent decades working toward magnetic transistors that utilize electron spin to control the flow of electricity. Electron spin is a fundamental property that enables electrons to behave like tiny magnets.

So far, scientists have mostly been limited to using certain magnetic materials. These lack the favorable electronic properties of semiconductors, constraining device performance.

“In this work, we combine magnetism and semiconductor physics to realize useful spintronic devices,” Liu says.

The researchers replace the silicon in the surface layer of a transistor with chromium sulfur bromide, a two-dimensional material that acts as a magnetic semiconductor.

Due to the material’s structure, researchers can switch between two magnetic states very cleanly. This makes it ideal for use in a transistor that smoothly switches between “on” and “off.”

“One of the biggest challenges we faced was finding the right material. We tried many other materials that didn’t work,” Chou says.

They discovered that changing these magnetic states modifies the material’s electronic properties, enabling low-energy operation. And unlike many other 2D materials, chromium sulfur bromide remains stable in air.

To make a transistor, the researchers pattern electrodes onto a silicon substrate, then carefully align and transfer the 2D material on top. They use tape to pick up a tiny piece of material, only a few tens of nanometers thick, and place it onto the substrate.

“A lot of researchers will use solvents or glue to do the transfer, but transistors require a very clean surface. We eliminate all those risks by simplifying this step,” Chou says.

Leveraging magnetism

This lack of contamination enables their device to outperform existing magnetic transistors. Most others can only create a weak magnetic effect, changing the flow of current by a few percent or less. Their new transistor can switch or amplify the electric current by a factor of 10.

They use an external magnetic field to change the magnetic state of the material, switching the transistor using significantly less energy than would usually be required.

The material also allows them to control the magnetic states with electric current. This is important because engineers cannot apply magnetic fields to individual transistors in an electronic device. They need to control each one electrically.

The material’s magnetic properties could also enable transistors with built-in memory, simplifying the design of logic or memory circuits.

A typical memory device has a magnetic cell to store information and a transistor to read it out. Their method can combine both into one magnetic transistor.

“Now, not only are transistors turning on and off, they are also remembering information. And because we can switch the transistor with greater magnitude, the signal is much stronger so we can read out the information faster, and in a much more reliable way,” Liu says.

Building on this demonstration, the researchers plan to further study the use of electrical current to control the device. They are also working to make their method scalable so they can fabricate arrays of transistors.

This research was supported, in part, by the Semiconductor Research Corporation, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), the U.S. Department of Energy, the U.S. Army Research Office, and the Czech Ministry of Education, Youth, and Sports. The work was partially carried out at the MIT.nano facilities.

This post was co-authored by Sheila B. Lalwani, a doctorate student and recent COMPASS Fellow hosted by EFF.

Age verification proposals are often presented as a simple tradeoff: sacrifice a little privacy to better safeguard children online. But that framing overlooks a more fundamental question. What happens to people who cannot verify their age at all? This is particularly a problem when users are required to prove their age with identity documents.

Age-related restrictions are developing quickly around the world. While they differ radically across jurisdictions, in the past year, we’ve witnessed a sharp uptick toward mandatory age assurance for social media access but also for other high-risk digital services.

For example:

• In late 2025, Australia became the first country to implement a minimum age requirement for prohibiting children under age 16 from creating or holding social media accounts. 
• India passed the Digital Personal Data Protection (DPDP) Act that includes mandatory verifiable parental consent and has undertaken ongoing discussions for social media restriction.
• The United Kingdom passed the Online Safety Act requiring age verification across a swath of services hosting content considered harmful to users under 18. More than half the states across the U.S. have enacted age verification laws. 
• An EU Commission’s expert report recommends a ban on social media access for users under 13. It also recommends mandatory age verification for platforms to ensure that users are ‘age appropriate.’ 

The Access Problem 

Age verification laws that are predicated on the necessity of users possessing a current passport, driver’s license, credit card, or similar documents proving their identity exclude critical sections of populations.  And this problem is global in nature: Millions of people lack government-issued identification or encounter regular challenges to obtaining or updating it. 

Roughly 15 million adult U.S. citizens lack a driver’s license, and a further 2.6 million lack any government photo ID; leaving large groups blocked from online content or services. The UK has a similar predicament: proof-of-age checks are often reliant on passports, driver’s licenses, or other recognized alternatives, which can pose unique challenges to people without these documents.

Much of the advocacy around age verification discusses the privacy harms of age verification. Yet these measures also threaten something more fundamental: equal access to information and the ability to exercise the right to freedom of expression. 

Unfortunately, age verification systems foster unequal access to information and provide an asymmetric solution to find essential information, build community, and weigh in on public discourse. As governments and companies increasingly require users to prove their age before accessing online services, these individuals risk being excluded from large parts of the internet altogether. 

Effects on Global Majority Countries 

Age verification laws reshape who can speak, who can access information, and who gets excluded from the digital public sphere. In other words, age verification is not a neutral safety measure: it presents a structural barrier to disproportionately exclude certain groups—particularly those in the global majority—and alters the architecture of global online expression. Some of these groups are already marginalized offline, and age verification extends that exclusion into digital spaces.

For instance, 850 million people globally do not have ID. Most of these individuals exist in primarily low and middle income countries in Sub-Saharan Africa and South Asia. The World Bank points out that many are members of marginalized groups and more than half of those lacking access to identity documentation also have children whose births have not been registered. Women are particularly vulnerable and are 8% less likely than men to have an ID. Other vulnerable groups, such as adults in low income countries, are less likely to have an ID when they fall below 25 years, as are those with a primary school education or less or those in rural areas. 

A policy paper from EDRi points out that age verification laws provide quick tech solutions but overlook longstanding structural challenges and undermine the universality of the internet. The analysis finds that age verification laws have serious human rights implications and ironically harm the very individuals they deem to protect. Moreover, these laws depend on the collection of harmful mass data that human rights organizations, including EFF, is fighting against—and has for decades. 

For example:

• In Morocco, a push to restrict children’s access would ban under-13s from creating accounts on gaming platforms. This could potentially create challenges for those with IDs that have incomplete information concerning the year of birth. In addition, this push would also impact those who attempt to leave Morocco.
• In Egypt, the lack of ID cards has created challenges for minority groups such as the Baha’i.
• Stateless individuals would also struggle under age verification laws. The Rohingya, the world’s largest population of stateless people, often lack IDs. 
• Kuwait’s Bidoon population also lacks proper identification materials. According to Amnesty International, this leads many to rely on standard civil identity cards, which can be restrictive.  
• Nigeria launched a national program to provide ID cards to its population in 2007. Since then, 64.4 million have registered, but that represents just over 30% of the national population.
• The Kafala system, a practice in several countries across the Middle East, also introduces challenges for age verification laws. Under this legal framework, migrant workers’ legal residency and employment status are bound to a specific employer. This potentially leaves stateless persons or migrant workers vulnerable to forced labor and restricted movements. 

No ID, No Access

Age verification laws are less about confirming the age of a user and more about creating barriers to online participation that many people cannot reliably scale. The net result is reduced access, more data collection, and an increased chance of unequal or mistaken exclusion from accessing information online. 

Nobody doubts the importance of protecting children online. While proponents assert that age verification laws protect minors from harmful material, online harassment, and digital addiction, these laws are not the solution. They subvert fundamental freedom of expression rights and pose significant privacy risks.  

EFF has long warned against age-gating the internet. Age verification technology itself is often inaccurate and privacy-invasive, and as more countries considering implementing ID-based checks, the risks move beyond censorship and surveillance toward excluding some people entirely. That’s why we’re working with groups in the U.S. and around the world to push back against these laws, and why we hope you join our effort.

For more information on how to fight back against dangerous age verification laws, visit our resource hub at eff.org/age

Today is DAF Day! This event highlights the millions of donor-advised funds (DAFs) people have set up to make charitable donations and change the world. If you have a DAF, consider supporting EFF today.

Decisions about your privacy, encryption, artificial intelligence, online speech, and digital security will determine whether technology empowers people or concentrates power in the hands of a few. A grant from your DAF to EFF supports our mission to ensure that technology remains a force for freedom, innovation, and human rights.    

If you’ve never heard of a DAF, just think of it as a bank account for your giving with some special benefits. 

Grants from DAFs allow you to: 

• Simplify your taxes by receiving an upfront single deduction for your multiple charitable donations 
• Receive immediate tax benefits of multi-year gifts
• Avoid capital gains tax on long-term appreciated assets like stocks
• Boost your giving by investing your DAF funds 

While allowing EFF to: 

• Defend encryption, privacy, and security that protect users and developers 
• Challenge unlawful surveillance and censorship that threaten democracy 
• Shape technology policy to safeguards civil liberties while enabling innovation 
• Build free privacy-preserving tools that strengthen digital autonomy 
• Protect the rights of creators, researchers, and builders in the digital ecosystem 

Your support helps ensure that the next generation of technology will strengthen our freedom. Consider a DAF gift today. 

LEARN MORE

This essay was written with Seva Gunitsky, and originally appeared in Foreign Affairs.

Two weeks after Moscow’s full-scale invasion of Ukraine in March 2022, the Russian TV Channel One editor Marina Ovsyannikova burst onto the set of the evening newscast. She held up a hand-drawn sign behind the anchor’s head that read: “Stop the war. Don’t believe propaganda. They’re lying to you!” She shouted, “No to war!” until she was dragged away.

No one has protested the war on Russian television since then, partly as a result of tighter security and a general climate of fear. But in October 2024, Margarita Simonyan, one of Russia’s chief propagandists, gave another explanation. A growing number of the RT network’s anchors, she explained to an interviewer, are not real. “That face doesn’t exist. We generated the voice and everything else.” They were, she meant, produced by artificial intelligence. In a follow-up interview with the newspaper ...

The global building boom of power-hungry data centers is straining electrical grids, causing greater reliance on energy from polluting fossil fuels.

Christina Delimitrou, a newly tenured associate professor at MIT, is fighting this environmental threat by rethinking how the computer servers and networking equipment inside those data centers operate. 

She and her group apply machine learning to make large-scale data centers more efficient, secure, and reliable. They redesign outdated cloud computing systems, develop methods to manage shared hardware resources, and create streamlined server architectures. 

These advances allow data center operators to coax more computational power out of existing hardware.

“If data centers are not utilized to the best of their capabilities, then they will burn much more power than they need to meet growing user demand,” says Delimitrou, the KDD Career Development Associate Professor in Communications and Technology in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). “There is a lot of bloating, especially on the software side of these systems. If we can remove that bloating in a way that doesn’t compromise performance, then we won’t need to build as many new data centers.”

She also harnesses AI to help programmers find and fix problems in cloud-based applications, like music-streaming services or video conferencing systems. This eliminates application downtime that hampers performance and drains computational resources.

“By managing resources more effectively in the cloud, the end user gets more predictable performance from the application running on their smartphone,” she adds.

Mathematical beginnings

Delimitrou grew up in a midsized town within the vast plains of northern Greece. Her early interest in math and science was sparked, in part, by the ancient history of her homeland, where Euclid and Pythagoras studied mathematical problems more than 2,000 years ago. 

“In Greece, there is a long tradition of geometry,” she says.

She also drew scientific inspiration from her parents. Her mother worked as a chemical engineer and her father as a pharmacist — and both encouraged their daughter’s innate curiosity.

Her early affinity for math led Delimitrou to study computer engineering at the National Technical University of Athens, even though she didn’t know much about the field. She quickly gravitated toward courses that focused on the applied science of engineering.

For her diploma thesis — a project all students complete during their fifth and final year of study — she studied resource management in a computer when multiple applications are running at once. 

“A lot of the challenges I was looking at then would get much harder if, instead of a single system, you had 100,000 of these systems. That was a problem that piqued my interest,” she says.

Seeking to make a bigger impact as a researcher, Delimitrou pursued a graduate degree at Stanford University. She began tackling inefficiencies in cloud computing systems and large-scale data centers, which was a rapidly growing area of research. 

Through that work, Delimitrou and her research mentor, Christos Kozyrakis, the Leonard Bosack and Sandy K. Lerner Professor of Engineering, realized many large computing systems were underutilized.

“You would expect, with all the demand for these systems, that they should be running close to 100 percent capacity. But we found that most were running at only about 15 percent capacity,” she says. “This is not a resource-efficient or sustainable way of scaling these systems.”

Applying AI

To push that utilization closer to 100 percent, she began investigating machine-learning solutions to streamline cumbersome computational processes. Machine learning could automate resource management operations in the cloud, identifying solutions that developers might miss on their own.

“Applying machine learning to solve a large-scale system problem was a novel approach at the time. It was a bit risky because people had not yet shown that these techniques would work,” Delimitrou says. “But empirical approaches require a lot of expertise, and the scale of the system is so large that it is difficult for users to manage. This is why machine learning is often the best solution.”

After earning her PhD, Delimitrou continued this line of work as an assistant professor at Cornell University.

One tool her group developed, Seer, uses deep learning to anticipate and prevent problems in web applications before they happen. This averts widespread slowdowns that may occur if a developer tries to fix a problem manually.   

As she delved deeper into cloud computing, Delimitrou observed that cloud applications were changing. Developers were now splitting applications into smaller pieces to spread across multiple servers, which increases the speed of deployment.

“But the servers were not built for this new style of application design. So, I rethought some of my earlier work to build machine-learning systems for this new class of applications,” she says.

To tackle these new challenges, she found herself collaborating more often with faculty members who had different software and hardware expertise. Those collaborations opened exciting new research areas.

A few years later, she decided to join MIT because of the opportunity to collaborate with researchers at the top of their fields in hardware and software engineering. She became an assistant professor in EECS in 2022.

Creative approaches

At MIT, Delimitrou also enjoys the teaching aspect of her role. One of her favorite courses to teach is 6.191 (Computation Structure), a popular undergraduate class with about 350 students each semester. 

While it’s challenging to keep the course material fresh when the field constantly evolves, she strives to inspire creativity in her students.

“I want the students to learn how to think and learn on their own. Part of that involves shifting away from formulaic assignments and making classes more open-ended. I’d rather give the students something to make them think more deeply,” she says.

In the lab, a creative mindset helps Delimitrou and her team identify novel solutions to problems in cloud computing that others might overlook.

For instance, she extended prior work on debugging problems in cloud applications to encompass not just errors in the code, but also security issues that can make user data vulnerable to hackers.

She also uses AI to redesign software systems so they better fit the capabilities of existing hardware.

“One of the challenges when it comes to applying AI to these systems is that the AI is not interpretable,” she says. “A lot of the work we are doing now involves adding explainability into these AI tools so people can get useful feedback from the system.”

That not only helps developers ensure AI is giving the right answer, but also provides insights into how to design systems better in the future.

She finds that studying these large-scale cloud computing systems is becoming more challenging because tech companies that operate data centers use proprietary hardware, unlike the commodity equipment of early cloud computing days, as well as software systems that can’t be accessed by academic teams. A solution that works in the lab might not work in the real world.

To that end, Delimitrou and her group create clones of proprietary systems and applications. One tool they developed, called Ditto, mimics an application’s structure and performance characteristics, enabling a wide range of studies.

She expects her work to continue shifting as machine-learning models become more advanced, opening new possibilities to boost application performance and hardware efficiency.

“But you still have to use AI carefully. While it can greatly accelerate the application development side, we still need to audit it and be especially careful about how these models are applied so we don’t lose the ability to gain insights out of the solutions AI is giving,” she says.

Outside the lab, Delimitrou enjoys spending time with her husband and 1-year-old daughter.

While she doesn’t have as much time for hobbies these days, she also enjoys gardening and building an electrical toy train track for her daughter, as well as playing classical piano and painting nature scenes. She became interested in painting at Cornell, where she would often paint the many waterfalls near the campus. 

Whether she is working in the garden or painting, Delimitrou says she finds spending time outdoors to be a relaxing escape from the technical nature of her work, but also an important reminder of the role her research plays in sustainability. 

Margaret Hamilton, a profoundly influential computer scientist best known for leading the software engineering team at MIT’s Instrumentation Lab during NASA’s Apollo program, died on Sep. 30. She was 90.

A computing pioneer who authored over 130 publications, Hamilton helped to establish software engineering as a dedicated discipline. She worked at MIT from 1959 until the mid-1970s, after which she became a successful computing entrepreneur and CEO.

Her life’s work was recognized with many awards and honors, including the 2016 Presidential Medal of Freedom from President Barack Obama, whose citation noted: “Hamilton defined new forms of software engineering and helped launch an industry that would forever change human history. Her software architecture led to giant leaps for humankind, writing the code that helped America set foot on the moon.”

“To say Margaret Hamilton was a pioneer — to say she was ahead of her time — would be a dramatic understatement. She was a software engineer at a time when that field was in its infancy, and she not only developed advanced code herself but also led a team in using that nascent technology to develop one of the most complex systems humanity had ever achieved,” says Olivier de Weck, the Apollo Program Professor and interim head of the MIT Department Aeronautics and Astronautics. 

“The Apollo program still stands as one of our greatest testaments to the power of collaboration, ingenuity, and engineering, and Margaret Hamilton was a fundamental contributor to that program’s success. And for her that was just the beginning! She went on to become an entrepreneur and remained on the cutting edge of systems software throughout an extraordinary career, while acting as an advocate, mentor, and inspiration to millions.”

Early life and projects at MIT

Born in Paoli, Indiana, in 1936, Hamilton began studying mathematics at the University of Michigan in 1955 before transferring to Earlham College, where she earned a BA in mathematics with a minor in philosophy in 1958. She moved to Boston, Massachusetts, in 1959 with her husband while he pursued a law degree. 

Hamilton soon found a temporary position in the meteorology department at MIT, working with professor of meteorology Edward N. Lorenz SM ’43, ScD ’48 on weather prediction software. This was her first entry point into computer programming, and her work would go on to inform Lorenz’s future publications on chaos theory.

From there, Hamilton took a role as a programmer at MIT Lincoln Laboratory in 1961, working on the Semi-Automatic Ground Environment (SAGE) project, the United States’ first air defense system. Hamilton wrote software for the prototype AN/FSQ-7 computer (XD-1), used by the U.S. Air Force to search for potentially unfriendly aircraft. During this time, Hamilton began to take an interest in software reliability — a new and largely unexplored concept at the time.

In 1965 Hamilton was preparing to pursue graduate studies when her husband saw an advertisement in the newspaper: The Instrumentation Lab at MIT was seeking people to develop software to “send man to the moon.” The lab had won the contract from NASA to build the onboard flight software for the Apollo program. Intrigued by the challenge, Hamilton applied, and was hired as the first programmer for the Apollo project at MIT, as well as the first female programmer in the project. 

Hamilton worked first on the software for the uncrewed Apollo missions and then was promoted into leading the team developing the on-board flight software for the crewed missions. By 1968 she was assistant director in charge of the Command and Service Module team, and more than 400 people were working on Apollo’s software. 

“From my own perspective, the software experience itself (designing it, developing it, evolving it, watching it perform and learning from it for future systems) was at least as exciting as the events surrounding the mission,” Hamilton told MIT News in 2009. “There was no second chance. We knew that. We took our work seriously, many of us beginning this journey while still in our 20s. Coming up with solutions and new ideas was an adventure. Dedication and commitment were a given. Mutual respect was across the board. Because software was a mystery, a black box, upper management gave us total freedom and trust. We had to find a way, and we did. Looking back, we were the luckiest people in the world; there was no choice but to be pioneers.”

“Defensive” programming and priority-driven software take humans to the moon

Hamilton discovered a talent for leadership, as well as a keen instinct for problem-solving and critical thinking that would prove to save Project Apollo several times over. 

There was the incident that became known as “the Lauren error”: One day, her daughter Lauren, then four years old, was playing with the command module simulator at the Instrumentation Lab when she somehow activated a pre-launch program, called P01, while the simulator was in midflight — which crashed the simulator altogether. Hamilton created a program add-on in the technical documentation warning users not to launch P01 during flight. 

She also proposed a software fix to prevent the error happening during a real mission, but she was overruled on the grounds that the highly trained astronauts were never going to make that same mistake. Yet during the Apollo 8 mission in 1968, that’s exactly what happened: Jim Lovell inadvertently launched P01 during the flight, causing the on-flight navigational data to vanish. Hamilton and her team were called in to solve the error, and after that her proposed changes were integrated into the program. This was an early example of “defensive” programming, the practice of building software that could anticipate or fix errors on its own. 

Hamilton’s most famous contribution to the Apollo program came during the pivotal Apollo 11 mission to land on the moon in July of 1969. Moments before the Eagle module was set to land on the lunar surface, the onboard computer raised the alarm. It had detected a 1202 error: The computer was overloaded due to a fault in a hardware switch, and it was possible the system would not be able to handle the complex landing procedure. 

But Hamilton and her team had engineered priority-driven software, able to shut down unnecessary background tasks in order to prioritize mission-critical tasks. Houston trusted Hamilton’s software and allowed the mission to proceed, and two men walked on the moon for the first time. 

Later career and legacy

Hamilton continued to work at the Instrumentation Lab into the 1970s. As the Apollo program wound down, the Instrumentation Lab spun out of MIT to become the independent Draper Laboratory.

“Margaret left an indelible mark on Draper, and we will be forever grateful,” says Jerry M. Wohletz SM ’97, PhD ’00, president and CEO at Draper. “Through her leadership and contributions to the development of the onboard flight software for NASA’s Apollo Guidance Computer, she helped ensure that Apollo astronauts landed safely on the lunar surface and safely returned home. We will honor her legacy at Draper forever.”

Hamilton went on to create her first software company, Higher Order Software, in 1976. The firm was based on Hamilton’s software engineering approach of error prevention and fault tolerance. 

A decade later, Hamilton founded another software company, Hamilton Technologies, “to provide products and services to modernize the planning, system engineering and software development process in order to maximize reliability, lower cost and accelerate time to market.” 

Hamilton Technologies’ flagship product is the Universal Systems Language (USL), a systems modeling language and methodology for engineering complex software systems that prioritize error prevention and defensive programming. 

Throughout her career, Hamilton worked to achieve recognition for software engineering as a dedicated discipline. 

“I fought to bring the software legitimacy so that it — and those building it — would be given its due respect, and thus I began to use the term ‘software engineering’ to distinguish it from hardware and other kinds of engineering, yet treat each type of engineering as part of the overall systems engineering process,” Hamilton told El Pais in 2018. “When I first started using this phrase, it was considered to be quite amusing. It was an ongoing joke for a long time. They liked to kid me about my radical ideas. Software eventually and necessarily gained the same respect as any other discipline.”

Among her many awards and honors, Hamilton was recognized with the NASA Exceptional Space Act Award for scientific and technical contributions in 2003; the Computer History Museum Fellow Award in 2017; the Intrepid Lifetime Achievement Award in 2019; and induction into the National Aviation Hall of Fame in 2022.

Later in life, Hamilton become an icon for women in science and technology, especially after a now-famous photo, showing her next to a printout of her MIT team’s Apollo code, began circulating online. In 2015, the Apollo software she helped to develop was added in its entirety to the code-sharing site GitHub. And in 2017, she became an official Lego Minifigure after a set originally designed by MIT science communicator Maia Weinstock, honoring her and several other women of NASA history, became available worldwide. 

“Margaret Hamilton has been an inspiration to generations of computer scientists and engineers. Hers was a career dedicated to preventing errors and what she called ‘handling the unknown,’” says de Weck. “She personified leadership by example, and established a practice of software engineering based on problem-solving and systems engineering that we all benefit from.” 

Hamilton is survived by her daughter, Lauren Hamilton; her son-in-law, Richard Selesnick; two grandsons; four great grandchildren; and her siblings John, David, and Kathryn. A memorial service will take place in the spring in Cambridge, Massachusetts.

Artificial intelligence has become part of the zeitgeist. And while it’s a polarizing topic, Linda Rabieh has a unique take on AI: “It’s good for business. Our business, of humanistic thinking.” As senior lecturer in the Concourse program, one of MIT’s first-year learning communities, Rabieh has been introducing students to the “business” since 2010. 

“What AI has been useful for is making very vivid to students today the question of what it means to be human,” she adds. “They’re meeting this question with a new urgency. What is intelligence? Is it only mathematical intelligence? Is it only an aggregation of information? Or is human intelligence something different?”

AI is just one of countless thorny topics that bubble up in Concourse, which offers first-year MIT students a foundation in the humanities, alongside math and science General Institute Requirement courses taught by Concourse faculty. Studying “great books” and literary luminaries — Plato, Homer, Aristotle, Wordsworth and Coleridge, to name a few — provides a springboard for rich conversations and spirited debates.

A “mini-liberal arts college within MIT”

Concourse was founded in 1970 to enable humanities, engineering, and science faculty to collaborate on curriculum, cultivating a “concourse” of ideas. Now it’s a place, Rabieh says, “where students who come primarily to MIT for world-class science, math, and engineering can also have a traditional liberal education, exploring fundamental questions of human existence, reading the great books, engaging in intense, vigorous debate about these questions.”

“I often describe Concourse as a mini-liberal arts college within MIT,” says Assistant Director Sasha Rickard ’19, an alumna of the program. “A lot of students tell us that Concourse is a big part of the reason they decided on MIT instead of [other schools].”

Concourse accepts 50 first-year students each year. Johnnie Jones VI, a senior in mathematics and Concourse teaching assistant (TA) and debate fellow, marvels at the diversity of students the program attracts — “athletes, people who are interested in humanities, people who have no experience in humanities,” he says. “Somehow, 50 people every year self-select into this space, and magic happens.”

Connection and “cross-pollination”

Part of that magic is the sense of community that Concourse fosters. The program has a dedicated space in Building 16 with a classroom, seminar room, lounge, and kitchen. Students receive advising and participate in community events throughout the year. Since they overlap in their humanities, math, and science classes, as well as outside the classroom, they get to know each other and their instructors well. “There’s a lot of cross-pollination of conversation and ideas,” Rabieh says. 

During the weekly Friday advising seminar, students gather over lunch to discuss assigned texts or hold debates. In the fall, topics focus broadly on the human condition, and in the spring, students consider practical political or moral issues such as gene therapy, immigration, and gun control. Several debates are held in conjunction with the MIT Civil Discourse Project, which has collaborated with Concourse since 2023.

Many students stay involved in the program after their first year. Some serve as TAs, debate fellows, or associate advisors. 

“There’s very much a sense of wanting to be guides and supports and set an example for the incoming students,” Rickard says. Upper-level students also take Concourse electives, hang out in the lounge, and participate in community events.

Learning to think things through

Taking multiple classes together, sharing meals, and spending time together outside the classroom — these common experiences build a level of trust that allows students to hold deep conversations. The result is a transformative experience.

Rickard has noticed that incoming first-years tend to fall into two categories: those who think they already know the answers to political or philosophical questions, and those who have no opinion because they think there’s no definitive answer. Over time, she explains, “some students come to understand that they need to learn from others, and others learn that they really can think for themselves, and they do have something to say.”

“Students learn the importance of judgment in non-quantitative areas,” Rabieh says. MIT students excel at quantitative reasoning, she adds, but “you can’t just show which political policy is right and which is wrong … and one reason I think MIT students shy away from those kinds of issues is because they don’t see a way to think through them. Concourse teaches them a way to think about moral and political questions in a rigorous way that isn’t quantitative.”

That rings true for Jones. “Overwhelmingly, the greatest skill Concourse has given me, more than just teaching me things, is teaching me how to work through ideas myself — really making possible the ability to, even after a long day of work, sit down with a great book and have a conversation with someone who was alive 300 years ago about things that matter to me,” he says.

Stewarding the “ethos of Concourse” into its next chapter

As Concourse continues into its next half-century, a new leader has taken the helm. Ford Professor of Political Science Lily Tsai was recently named director after Anne McCants, the Ann F. Friedlaender Professor of History, stepped down.

Colleagues laud McCants for 14 years of steady leadership; cultivating a robust, collaborative advising program; advocating for a whole-student approach; and for her passion for teaching.

McCants says she relished interacting with Concourse students in a sustained way — often for all four years — and learning not only from them, but also colleagues. “Having a group of committed educators from different disciplines in sustained conversation is a remarkable feature of Concourse. In our normal faculty roles, we are siloed off from those whose fields of study are not ours. I will miss those interactions as much as I do the ones with the students.”

Tsai assumes the role as the Institute expands efforts to broaden connections between the School of Humanities, Arts, and Social Sciences (SHASS) and other fields. Those efforts include the Compass Initiative, which Tsai co-leads with other faculty from across SHASS; the MIT Human Insight Collaborative; and the creation of shared faculty positions within the MIT Schwarzman College of Computing.

“The ethos of Concourse is thrilling to me,” Tsai says. “Through reflection and debate about what we value individually and collectively, Concourse students cultivate the skills and habits of mind that prepare them to be not only excellent engineers and scientists, but also responsible citizens and leaders. At a time when the whole world is seeking to ground our use of powerful technologies in thoughtful, principled judgment, Concourse seems all the more vital, and I’m eager to champion the teaching and learning that the program does so well.”

Until recently, when a Massachusetts shellfish warden needed to know how much rain had fallen overnight before deciding whether to close a shellfishing area, the process might look something like this: call a local resident who happened to own a rain gauge, ask for the measurement, write it down, and use that number to make the call. Heavy rain may cause a closure due to stormwater runoff that can carry pollutants from land to water. If the area closed, the public found out the same low-tech way: a paper notice at the boat ramp, a phone call, or word passed along at the marina.

It’s a system built on trust between neighbors, but it doesn’t scale particularly well. According to the Massachusetts Division of Marine Fisheries’ 2024 Annual Report, Massachusetts shellfisheries yielded an ex-vessel value of over $441 million. This number includes shellfish spread across 738 classified growing areas along the coast that fall under a tangle of overlapping state and municipal jurisdictions. Add in thousands of recreational permit holders, and the old system starts to show its age.

With support from MIT’s Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), MIT Sea Grant researchers have spent the past several years trying to close the gap between the data that exist and the data people can actually use. The effort was proposed to J-WAFS by Michael Triantafyllou, the Henry L. and Grace Doherty Professor in Ocean Science and Engineering and director of MIT Sea Grant, under the title “Cloud-Based Data Applications for Streamlining Natural Resource Management.” 

The original aim of the proposal was to build a web-based system to help decision-making among managers and their stakeholders in order to support productivity of shellfisheries, safe human consumption, and vitality of coastal economies. The team wanted the platform to be scalable enough to serve the entire decision-making pipeline, from the state agency managing hundreds of growing areas down to an individual permit holder deciding whether it’s worth the drive to the water that day. 

The result is a platform called Seashell. The team describes it as sitting at the intersection of big data, natural resource management, and what’s often called the blue economy — the sustainable use of ocean and coastal resources for economic growth — a phrase increasingly common in state and federal policy circles, and one Massachusetts has staked real ground on. Food security is a large part of the equation too. Many of these towns don’t just issue permits for sport; these areas are open so residents have shellfish to eat. When permit holders can trust a platform to tell them, in real time, whether an area is safe to harvest, that’s not just convenience. It’s local food supply staying reliable.

An old bottleneck, a new pipeline

The project’s origins trace back to 2020, when MIT Sea Grant Research Scientist Carolina Bastidas and her colleagues built a shellfish restoration webpage and noticed that propagation data was scattered and often misrepresented. Propagation isn’t a minor detail; it’s how many coastal towns support food security for residents, a fact that came into sharper focus during the Covid-19 pandemic, when recreational shellfishing demand rose sharply enough that some towns limited permit sales just to protect their beds.

That early work led to an informal working group with the Massachusetts Division of Marine Fisheries (DMF) and towns of Falmouth, Mashpee, and Nantucket well before any formal funding existed. “We already had engagement,” says Ben Bray, geospatial applications developer at MIT. “We already had a very real starting point.” 

By the time J-WAFS awarded the team a seed grant in 2022, letters of support from DMF and all three towns were already in hand, each describing the same underlying problem: a lack of an efficient, shared way to track and communicate shellfishing area status.

Bray’s path to this work goes back two decades. He joined MIT Sea Grant in 2005 to help build an internal grant management system, and the job pulled him toward an idea he’d recently encountered in Thomas Friedman’s book “The World Is Flat”: that data tend to sit stranded on disconnected “islands,” reachable only through the right application programming interface (API).

The underlying architecture reflects that same philosophy of connecting, rather than replacing, existing systems. Seashell runs on a PostgreSQL database and Amazon Web Services cloud infrastructure, designed from the outset to be exportable — towns or states that want to run it on their own servers can do so. Rather than asking DMF or municipalities to abandon the tools they already use, the system pulls in data through APIs from a long list of sources: National Oceanic and Atmospheric Administration tide stations, satellite feeds for sea surface temperature and chlorophyll-a, local weather networks, and DMF’s own geographic information system.

Built with towns, not for them

If Seashell has a defining trait, it’s that the towns using it had a hand in shaping nearly every piece of it. In 2023, the research team ran a regional assessment of the Massachusetts shellfishing community that drew responses from more than 312 people, 122 of whom volunteered for follow-up focus groups. In 2025, dedicated focus groups for both the public and administrative interfaces — described by Bastidas as involving anywhere from one to a handful of participants at a time — drove a final round of revisions before launch.

What the team learned sometimes cut against their own assumptions. “How little the end user wants to see and interact with” the data was the biggest surprise, Bray says. Focus group participants didn’t want a comprehensive dashboard of every growing area in the state; they wanted their own location, loaded automatically, with the fewest clicks possible. More simply, users wanted answers to questions such as: Is an area open? Is it high or low tide? What’s the water temperature? That preference reshaped the public interface around geolocation and minimal menu navigation, particularly for mobile use, allowing permit holders to check the system on their way out the door.

The towns themselves turned out to have sharply different needs, shaped largely by how many people they have on staff and who’s showing up at their docks. Many of these departments run on a skeleton crew with one or two staff, managing the entire permitting and enforcement operation. “All the organizations we work with are all understaffed,” Bray says. “I didn’t realize that going into this.”

That imbalance shaped something called the “Ways to Water” feature. Towns popular with seasonal and vacationing residents who buy a permit without knowing the local geography asked for a tool that could route users to the nearest shellfishing access points. They also wanted the tool to show parking availability, boat ramps, and travel time. This detail captures the blue economy dimension of the project well. Both tourism and traditional shellfishing for food security call for differing groups to share the same water and the same system, without necessarily sharing the same local knowledge.

Other requests were smaller, but no less telling. One shellfish officer asked simply whether the interface could be offered in different languages, a request the team is now addressing through built-in translation. It’s the kind of feature that doesn’t show up in a funding proposal’s list of objectives, but that turned out to matter a great deal to the people actually using the tool.

The relationship with DMF followed a different shape than the one with the towns. Where individual towns had fewer resources but could move quickly once they decided to adopt something, DMF moved more deliberately. “They had more ability than they had power,” Bray says of DMF staff, describing an agency with existing institutional constraints that limited the design approach the researchers could take. That distinction ultimately reshaped the project’s strategy: rather than building one system meant to unify DMF and every town under a single workflow, the team shifted toward treating towns and DMF as separate entities with distinct needs, while still syncing DMF’s official closure data into the platform automatically. Bray describes the process as investing effort where towns have the flexibility to adopt something new, rather than waiting on slower-moving state processes to catch up.

Rules, real-time data, and respecting jurisdiction

The system’s handling of jurisdiction is arguably its core technical achievement. DMF manages the baseline layer of the state’s 738 growing areas; individual towns manage sub-areas on top of that layer, closing sections for reasons ranging from water quality to family-designated harvesting zones reserved for local residents. Early on, the team assumed DMF would want to manage its polygons directly inside Seashell. DMF preferred to keep working in an existing ArcGIS system. So the MIT team adjusted, syncing Seashell to DMF’s existing records via API instead, and building in automatic alerts whenever DMF’s underlying data changed. It’s a small design decision with an outsized effect: DMF keeps full control of its own data while towns still benefit from updated, synced data.

The administrative interface goes a step further, pulling in real-time environmental data and using it to recommend closure decisions based on rules that towns configure themselves. It’s a direct stand-in for the old rain-gauge phone call, and it’s built to shrink the gap between when DMF issues a closure notice and when the public actually learns about it.

A rare bipartisan corner of ocean policy

Seashell officially launched at the 2026 Northeast Aquaculture Conference and Exposition in Portland, Maine, this past January. The team is scheduled to present at the Massachusetts Shellfish Officers Association’s meeting this October, betting that broader town-level adoption will reduce the confusion that crops up when neighboring towns operate on entirely different systems. Some towns’ shellfish officers are using Seashell while the next town over might still be working on paper.

Bray sees something durable in the subject matter itself, apart from the technology. “Shellfishing is one of the few things, in terms of the ocean, in terms of cultural communities, that is bipartisan,” he says. Bastidas points to the layered value of the resource, not just its economic footprint, but its role in food security and in traditions, including Indigenous shellfishing practices, that predate Massachusetts’ current regulatory system by centuries.

Looking ahead, the team is exploring an extension into commercial fisheries and landing-data reporting, building on related, town-driven effort. More broadly, the researchers see little about the underlying framework that’s specific to shellfishing. The same architecture, they argue, could serve any natural resource management problem with a geospatial and jurisdictional dimension: wildlife management, water quality, coastal permitting.

For Bray, who led his first funded research project through this J-WAFS grant, the work has doubled as a lesson in institutional collaboration as much as software design. The project helped him understand how fast and how much a large state agency can move versus a small town, and where to put the effort to balance both sides. “You have to figure out what an organization is capable of providing, and work within that,” he says, “while still trying to push things forward.”

Apple just released a system called “Reference Image.” It can verify the image is exactly as taken by an iPhone—new models only—without tying it to a specific iPhone or photographer. It can also verify that multiple images came from the same iPhone.

Other industry solutions require a photographer or institution to vouch for an image using their own credentials. We are concerned this puts some photographers, such as those operating in conflict zones, in a difficult position; it should not be necessary to forgo anonymity in order to prove image authenticity. We built Apple Reference Image to avoid using an explicit, public credential for photographers, and to avoid even implicit public association between different photos taken by the same sensor. The final reference image is instead signed by Apple’s signing service, after validation by PCC. That signature is backed by Apple’s strongest technical guarantees...

Uncrewed aerial vehicles (UAVs) could fly deep into the heart of a raging wildfire, avoiding sudden flare-ups and dodging falling tree branches to gather critical information for rescuers. But in this dangerous situation, the UAV could easily be damaged or destroyed by falling debris.

The UAV — and the rescuers who rely on it — would benefit from a new, autonomous navigation system that is guaranteed to avoid collisions, even in completely unfamiliar surroundings. 

Developed by MIT researchers, this method plans a flight path for a UAV that eludes unknown obstacles that may move in unpredictable ways. It charts an efficient course through an unmapped environment that is mathematically proven to be safe from collisions.

Many popular navigation systems can only offer formal safety guarantees when the environment is static, or when the obstacles are known in advance.

By enabling the UAV to avoid moving obstacles while it is discovering its environment, this trajectory planner, which the researchers call “SANDO” (for “Safe AutoNomous trajectory planning for Dynamic unknOwn environments”) could be especially useful for applications like search and rescue missions into collapsed buildings, mine explorations through networks of hidden tunnels, or package delivery across a crowded neighborhood.

“In the hardest possible environment, where the UAV has no map of the area and there are unknown obstacles moving around, we established a mathematical guarantee of safety. The only thing the planner needs to know is the top speed the obstacles could reach. Given that, you could use it in any environment, without a map, and you know the UAV is not going to crash into anything,” says Kota Kondo SM ’23, PhD ’26, who recently earned his doctorate in aeronautics and astronautics at MIT and is lead author of a paper on this new system.

He is joined on the paper by Jesús Tordesillas PhD ’22, an assistant professor at Comillas Pontifical University in Madrid; MIT graduate students Juan Rached, Lili Sun, and Yixuan Jia; and senior author Jonathan P. How, a Ford Professor of Aeronautics and Astronautics and a principal investigator in the Laboratory for Information and Decision Systems (LIDS) and the Aerospace Controls Laboratory (ACL) at MIT. The research appears in the IEEE Transactions on Robotics.

Safety first

Trajectory planners use images and data from a UAV’s onboard cameras and sensors to chart a flight path that reaches the vehicle’s goal. 

Most existing planners are either designed for unknown static environments, where the obstacles don’t move, or they loosely avoid dynamic obstacles without providing a formal guarantee that the robot won’t crash. 

Formal safety guarantees are important in high-stakes situations, such as if a UAV were delivering medical supplies to the site of a remote natural disaster. But trying to compute every possible crash in a dynamic environment would take too long for real-world deployments.

“In an unknown dynamic environment, you don’t have many assumptions to rely on. In those types of environments, researchers haven’t yet been able to mathematically guarantee that a trajectory is safe,” Kondo explains.

The MIT researchers used a rigorous mathematical approach to develop SANDO, their safe trajectory planner. They theoretically proved the algorithm always computes trajectories which are guaranteed to avoid collisions with moving obstacles in unknown environments.

SANDO starts by mapping out a safety corridor through the robot’s environment. This corridor is a series of connected regions of 3D space the robot can travel through, which are guaranteed not to contain any obstacles. 

But unlike other systems, SANDO creates a time-sensitive safety corridor that considers the possible future movements of dynamic obstacles. It employs a special module that detects, groups, and monitors dynamic obstacles to estimate where they will move next.

While the system doesn’t know exactly where an obstacle will move in the future, it uses that obstacle’s maximum velocity to compute how far it could possibly go in a certain timespan. It puts a sphere around the obstacle that captures the farthest distance it could travel in all directions.

SANDO builds the safety corridor around these spheres to ensure the UAV will not collide with a moving object.

“In the real world, obstacles are going to move, so the safety corridor you create at one point won’t be useful as things move into the corridor. But because we consider this time component, we can now guarantee safety into the future,” Kondo says.

The system uses a heat-map based planner to identify “hot” regions of the environment with many obstacles and guides the UAV away from these dangerous areas. This helps the robot chart a more efficient course around danger zones.

Fast reactions

Once it has established a collision-free safety corridor, SANDO optimizes the trajectory within that corridor to find the fastest path to reach the goal. 

As the robot travels, SANDO adjusts the safety corridor and reformulates the trajectory to ensure the robot’s path remains collision-free until it reaches its goal. 

The researchers employed a few tricks to make the optimization easier to solve so the UAV can rapidly recalculate trajectories using its onboard computer, quickly reacting to sudden changes.

“The most difficult part of developing SANDO was the math,” Kondo says. “When you try to guarantee safety, you need to be rigorous and ensure your theory covers every possible case, even edge cases. Once we had that mathematical guarantee, it was very easy to fly the UAVs.”

In simulations, SANDO reached the robot’s goal faster than several state-of-the-art systems while completely avoiding collisions in all environments. 

SANDO also avoided all dynamic obstacles in 12 test flights with a real UAV, using the robot’s onboard computer and sensors to rapidly replan safe trajectories. 

In the future, researchers could make SANDO more computationally efficient and combine the system with machine-learning models that allow the user to give instructions to a robot using plain language.

A central challenge in autonomous flight is that a path that is safe when it is planned may become unsafe as the environment changes. SANDO addresses this challenge with time-varying safe flight corridors and hard-constrained trajectory optimization that supports frequent onboard replanning. Its combination of spatiotemporal planning, formal safety analysis, and hardware validation provides a practical approach to autonomous flight in complex dynamic environments,” says Fei Gao, an associate professor at Zhejiang University in China, who was not involved with this research.

This research is funded, in part, by the Defense Science and Technology Agency of Singapore.

Nature Climate Change, Published online: 07 October 2026; doi:10.1038/s41558-026-02768-w

Climate change is already causing widespread losses and damages, and these impacts will intensify as human and natural systems exceed their capacity to adapt. Recent research allows us to understand if and how countries are prioritizing this issue in national policies.

As artificial intelligence transforms industries and national security, understanding the latest hardware capabilities is important for maintainind technological advantage.

AI accelerators — specialized systems designed to speed up capabilities such as neural networks, deep learning, and machine learning — have been a major area of development for nearly a decade. Since 2018, team from the Lincoln Laboratory Supercomputing Center (LLSC) has been conducting the Lincoln AI Computing Survey (LAICS, pronounced "lace"). Six papers later, LAICS continues to summarize current commercial AI accelerators and compare their peak performance and peak power.

"About eight years ago, we saw a sharp rise in the number of research AI accelerators described in research papers and commercial accelerators being announced, and we started to get questions about them from government sponsors of the laboratory's work. That was motivation enough to start the survey," says Albert Reuther, a staff member at the LLSC, which operates and optimizes the high-performance computing systems used by thousands of laboratory research staff.

Although AI accelerators are frequently used for processes such as machine learning, they also can enable other parallel applications, such as modeling the functions of molecules and speeding up simulations of fluid dynamics — processes that are very computationally expensive.

AI accelerator technology can come in a number of forms: central processing units (CPUs), graphics processing units (GPUs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and dataflow accelerators. Each type of accelerator has slightly different capabilities. CPUs can be used for general-purpose computing, while ASICs can perform only very specific tasks. Dataflow accelerators, FPGAs, and GPUs are more flexible and can be configured for a variety of workloads. Efficiency and performance vary across the different types of accelerators depending on how they are designed. The goal of LAICS is to survey the technologies currently on the market and compare them to find the best accelerators for certain needs.

Led by Reuther, the LAICS team includes LLSC members Michael Jones, Peter Michaleas, Jeremy Kepner, and Vijay Gadepally. The team also collaborates with researchers across Lincoln Laboratory, including in the Advanced Technology Division and Intelligence, Surveillance, and Reconnaissance and Tactical Systems Division, to learn how accelerators support research and development for their missions.

The first paper in their series studied 57 accelerators, while the latest one looked at more than 120 accelerators. The main metrics the team uses to compare accelerators are the peak performance and power; then they sort accelerators by whether they're on a chip, card, or system. All the data in the papers are drawn from public sources, which can be challenging because some companies prefer to keep their performance and power data private. To keep up to date on the latest in the field, Reuther runs daily news and citation searches that report new technical press articles, company announcements, and industry presentations.

"It continues to surprise me how each year another five to 10 startups get funded and announced, and then release new AI accelerators," Reuther says. "One might think that the landscape is saturated enough, but then another batch of innovative accelerators is introduced."

In addition to summarizing the performance versus peak power of the current accelerators, each paper explores a new aspect of the field. For example, the paper published in 2022 investigated sources of performance increases, finding that they stem from smaller, denser transistor designs and the use of lower numerical precision (i.e., calculating fewer significant digits). The latest paper examined different architectural choices available, analyzing how the addition of certain components, such as more cores per processor or parallel performance, would change the system.

Reuther plans to continue the survey for the foreseeable future, stating that, in just the past few months, six new startups have announced their first AI accelerators.

"AI and the hardware it runs on are such hot topics, and it is important for Lincoln Laboratory to be an unbiased technical advisor for choosing and pursuing the right technologies," Reuther says. "Our AI accelerator surveys have helped many sponsors and government colleagues gain a better understanding of the AI accelerator landscape and make better research and acquisition decisions about them. This survey has also been very valuable to determine which GPUs we should consider for upcoming LLSC system purchases so it not only benefits our sponsors and mission programs, but also benefits all LLSC users."

The full set of papers and the accompanying datasets can be found here.

Chris Bourg, who has served as director of the MIT Libraries since 2015, has been named vice provost and Barbara K. Ostrom (1978) Director of the Libraries, MIT Provost Anantha Chandrakasan announced today.

“The title ‘vice provost’ signals the enduring importance of the MIT Libraries in the digital age,” said Chandrakasan. “While the ways in which the libraries meet the needs of our community might change as technology changes, their mission of protecting access to knowledge and information is as vital as ever.”

Thanks to a generous gift from Barbara K. Ostrom ’78, SM ’78, the position of the director of the libraries now has an endowment to help fund it in perpetuity. Bourg noted that the gift is especially meaningful for her, due to the sense of service she shares with Ostrom: they both completed Reserve Officers' Training Corps (ROTC) during their time as undergraduates — Bourg at Duke University and Ostrom at MIT — before going on to active military service.

“Barbara’s gift is an incredible acknowledgment of the progress the entire MIT Libraries staff has made toward our vision,” said Bourg, who noted that Ostrom had also supported an MIT Libraries initiative to highlight MIT’s women faculty by acquiring, preserving, and making accessible their personal archives. “Her generosity advances the libraries’ ability to support teaching, learning, and community-building at MIT well into the future.”

During her tenure, Bourg has emphasized digital access to content, a more open and equitable scholarly publishing landscape, and expanded support for data-intensive and computational research. She has helped both the libraries and the Institute adapt to AI-driven changes: she co-chaired the Working Group on Scholarly Content and Generative AI, charged with helping the MIT community navigate the legal, technical, and ethical issues involved when scholarly content is used to develop and train generative AI models. And she was a member of the Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, which issued its final report in August.

Promoting open scholarship has been a longstanding focus of Bourg’s career. In 2018, the libraries launched the Center for Research on Equitable and Open Scholarship, with Bourg serving as founding director. She co-chaired the 2017 MIT Ad Hoc Task Force on Open Access to MIT’s Research; its recommendations led to the creation of the MIT Prize for Open Data, co-sponsored by the School of Science, and the development of the MIT Framework for Publisher Contracts. Guided by the framework, MIT became one of the first major U.S. institutions to cancel a journals contract with Elsevier in 2020, standing by its open scholarship principles while saving the Institute millions of dollars.

Bourg co-chaired the 2016 Ad Hoc Task Force on the Future of Libraries and has guided the MIT Libraries toward the vision laid out by the task force report. Under her leadership, the libraries completed a major renovation of Hayden Library and the Building 14 Courtyard and launched MIT Reads, an Institute-wide reading and discussion program designed to foster empathy and belonging within the MIT community.

Prior to joining MIT, Bourg worked for 12 years in the Stanford University Libraries. Before Stanford, she spent 10 years as an active-duty U.S. Army officer, including three years on the faculty at the United States Military Academy at West Point. She received a BA from Duke, an MA from the University of Maryland, and an MA and PhD in sociology from Stanford. 

Bourg is a member of the board of the Center for Open Science, the external advisory board of the Stanford Data Science Institute’s Center for Open and Reproducible Science, and the board of Annual Reviews, a premier publisher of open review journals in 51 disciplines. She also currently serves on the national academies of Science and Engineering, and the Medicine Corrections and Retractions Committee, tasked with upgrading the scientific record.

MIT is launching a new strategic initiative today: MIT for America, which seeks to strengthen STEM education nationally, at many levels of learning. 

Addressing a critical national need, the initiative ranges across STEM fields and will engage students from kindergarten through community college, preparing them to live and work in a world increasingly shaped by science and technology. MIT for America’s programs will develop new opportunities for student achievement in mathematics, hands-on design and fabrication, and constructive engagement with artificial intelligence. 

President Sally Kornbluth made the announcement today in a letter to the Institute community.

“A natural extension of the Institute’s long record of national service, MIT for America is grounded in our deep belief in potential over pedigree, of the transformative power of learning by doing and in the open sharing of knowledge,” Kornbluth wrote.

The initiative represents an Institute-wide effort to address the national challenge of improving STEM education and helping it adapt to shifting societal needs. MIT for America will leverage the Institute’s longstanding strengths to develop new programs and expand existing projects, while amplifying MIT’s impact on national education.

MIT for America’s faculty leaders emphasize that the initiative will support programs that can be scaled up and that provide direct, face-to-face guidance for learners and educators. 

“The goal is to provide programs that are both scalable and high-touch, and make an impact across the country,” says Professor Eric Klopfer, a faculty co-director of MIT for America and director of the Scheller Teacher Education Program and the Education Arcade at MIT. “All our programs take advantage of things we are well-positioned to do at MIT, and can be distributed around the country. That’s our guiding light.” 

Cynthia Breazeal, faculty co-director of MIT for America, professor of media arts and sciences, and the Benesse Professor of Research in Education, says the initiative “is about bringing high-quality access to STEM and AI education, from kindergarten to community college, across the United States. We live in an innovation-driven world, and it’s important to have an education that gives you access to it, whether that’s so you can be a fully engaged citizen or have the opportunity for economic mobility.”

Breazeal adds: “Talent is everywhere. We think opportunity should be, too.” 

The initiative is addressing large-scale needs in STEM education. Only 29 percent of U.S. students in grades 9-12 build circuits, and only 6 percent of students enroll in computer science classes, even though about 60 percent of high schools offer such courses. MIT for America intends to substantially help communities across the country build the bandwidth needed to further develop STEM knowledge and workplace skills. 

“This effort is about really rolling up sleeves and getting out there and engaging communities, and helping to build capacity across the United States,” Breazeal adds.

MIT for America features programs addressing three high-priority areas:

Mathematical thinking and problem solving: Work here builds on an existing program, the MIT for America Calculus Project, launched a year ago, in which MIT students and alumni volunteer to help provide calculus tutoring to students in school districts across the country. 

Living, learning, and working with AI: This area addresses multiple issues revolving around AI, including teacher education that helps instructors integrate AI into classroom learning in productive ways, and programs that enhance AI skills and STEM education in technical-vocational schools and community colleges. The MIT RAISE program (Responsible AI for Social Empowerment and Education) is a leader in this domain. 

Designing, making, and innovating: MIT for America plans to build out programs that encourage hands-on learning, design work, use of fab labs and makerspaces, and experiential learning, sometimes deploying tools such as national design challenges. 

“Across the U.S., we want to unlock opportunities and experiences where students are,” says Claudia Urrea, head of MIT for America and head of the MIT pK-12 Initiative. “We want to find people who have not had the opportunity to discover their talent.”

In the first case, the MIT for America Calculus Project provides a ready model of outreach with growth potential. About half of U.S. school districts offer calculus, but many of those districts may be under-resourced. The MIT for America Calculus Project has been growing in partnership with an increasing number of school districts, while MIT undergraduates and alumni have enjoyed participating in the program.  

“People have been really excited about the MIT for America Calculus Project, seeing both the impact that it has, and its model, which I think has resonated,” Klopfer says. “That’s really representative of what other programs could look like.”

In the second topic area, MIT for America can leverage burgeoning efforts such as MIT RAISE. The program helps educate teachers and engage students about implementing AI in ways that can complement the developing skills of students, enabling them to use AI in productive ways.

“RAISE is about providing materials and training for teachers that helps them have conversations and productive activities around AI,” Klopfer says. “It’s about understanding how AI works and discussing what the values are in your school. It has to be active, involving the students. If you try to force things, about AI one way or the other, that will fail.”

In an outgrowth of RAISE, MIT also launched a related program, Pathways for AI Training and Hiring (PATH), on Oct. 1. Starting with a partnership with Georgia State University, PATH aims to bring AI training to two-year and four-year colleges, to help students gain AI skills useful for workplaces. 

“RAISE has had a lot of success with scaling already,” Breazeal says, noting that about 1 million students were involved with RAISE’s Day of AI event earlier this year. “At MIT, we want to empower youth voices to shape the future. It’s an excellent example of our ability to do that.”

And in the third topic area, MIT for America can help produce substantial growth in programs aimed at hands-on learning. That may include more projects such as MIT’s Regenerative Futures Challenge, a global program stemming from MIT’s pK-12 Initiative, which give students the opportunity to create climate and sustainability solutions. Additionally, the Fab Foundation, which grew out of MIT’s Center for Bits and Atoms Fab Lab program, offers tools and curriculum to learners at 300 fab labs across the U.S.

“It’s about coming together in places where there are people who can work together, mentor each other, and learn by example,” Klopfer says. “That’s the kind of thing we want to be creating at scale. We want to build on that.”

All told, MIT for America represents a vigorous all-campus effort to enhance education through sustained outreach and knowledge-sharing. At MIT, partners in creating the initiative include the MIT Media Lab; MIT RAISE; the MIT pK-12 Initiative; the Office of the Vice President for Resource Development; and the Office of Innovation and Strategy.

The leaders of MIT for America presented an overview of the program in September at MIT’s Alumni Leadership Conference, and they say alumni activity around the new initiative will be another key to its success. 

“We really appreciate the support and engagement of our alumni,” Breazeal says. “We know they care about K-12 education and access to community colleges.” More broadly, she adds, “We do think this message will resonate with people all across the country.”

“I look forward to watching these programs flourish, evolve, and grow,” Kornbluth wrote to the community. 

404Media is reporting (alternate link) that a cyber-weapons arms manufacturer is exploiting a vulnerability in iOS to bypass its automatic reboot security feature. This is the feature that automatically puts an iPhone into a more secure state if it hasn’t been used for 72 hours.

The new technology to get around inactivity reboot was developed by Magnet Forensics, the company behind GrayKey, a popular tool sold to law enforcement agencies that allows them to unlock and access data stored in iPhones and Android smartphones. Magnet has developed a new device called GrayKey Preserve and a feature for its regular GrayKey devices called Evidence Preservation Mode, according to the video...

Like Earth, most planetary bodies circle their star in stable, detached orbits. These companionable systems can suddenly change when a planet comes too close to its star. In such a close encounter, a star can pull the planet in and swallow it whole. 

Across the galaxy, astronomers have seen plenty of stable, detached planetary systems. They have also observed a handful of stars quickly engulfing their planet. Now, for the first time, scientists have spotted a system that is striking a curious balance between the two extremes. And it’s revealing a new way that stars can interact with planetary companions. 

In a paper appearing today in Nature Astronomy, scientists at MIT and elsewhere have discovered a star leisurely snacking on a closely orbiting brown dwarf — a planet-like object that is more massive than a planet yet not quite as big as a star. 

The new system, named ZTF J0440+2325, is within the Milky Way galaxy, roughly 300 light years from Earth, and represents the first observation of a low-mass object that is slowly and steadily consuming material from another low-mass object. 

The rate at which the star is feeding from the brown dwarf suggests that this slow stellar cannibalism could carry on for hundreds of thousands, or even billions of years.

“When we think of stars interacting with planets or brown dwarfs, the picture is always that the star eventually swallows the other thing,” says Kevin Burdge, assistant professor of physics at MIT. “This is what will happen to the Earth when the sun becomes a red giant. But here, we’ve found an alternative: Instead of swallowing the thing up, the star can gradually eat it, for billions of years.”

The study’s MIT co-authors include Aaron Householder, Kaitlyn Shin, Saul Rappaport, Joheen Chakraborty, and Emma Chickles, along with collaborators from Caltech, the University of Hawaii, the Instituto de Astrofísica de Canarias and the Universidad de La Laguna in Spain, and the Harvard and Smithsonian Center for Astrophysics.

A “weird triangle”

The new system was spotted initially by the Zwicky Transient Facility. The ZTF uses a camera as part of a telescope at the Palomar Observatory, in California, to scan the sky for rapid changes in brightness, which could signal the presence of a supernova, a gamma-ray burst, or colliding neutron stars. 

Several years ago, Burdge was looking through ZTF data when he noticed a strange light curve, or pattern in brightness. Light curves for supernova resemble a bell curve, signaling the gradual brightening and then fading of a star as it bursts. But what Burdge picked out looked more like a triangle, that didn’t appear once, but again and again.

“I remember first looking at this and thinking: Stars don’t make triangular waveforms like this,” he recalls. 

At the time, he and his colleagues were focused on a different signal, which they identified as a “black widow binary” — a system in which an extremely dense, spinning neutron star is slowly consuming a much smaller companion star, similar to how its arachnid namesake plays with its prey. 

Burdge wondered whether the triangle signal might also be from a black widow. But the light from the signal was puzzling. In black widow binaries, the light appears to wobble, as a result of a very light, low-mass object, such as a small companion star, whipping around a much heavier object, such as a neutron star. 

“We weren’t seeing that whipping back and forth here,” Burdge says. “It didn’t make any sense. We couldn’t explain what this was.” 

But they had a hunch: Could the signal be coming not from a wobbly, David-and-Goliath system, but from a more balanced pair of objects, each with a similarly low mass? 

“If you have less mass in the system overall, things can gently orbit each other without whipping back and forth,” Burdge says. “That was the idea. But we never had any proof. And this weird triangle just sat for years.”

A slow and steady fireball

Recently, Burdge and Householder, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences, decided to revisit the triangle mystery. From the original ZTF signal, they determined the location of its source to be within the Milky Way galaxy, around 300 light years from Earth. They focused multiple telescopes on the source, named ZTF J0440+2325. From these observations, they measured various properties of the source, including its wobble. Compared to black widows and other similar binaries, the wobbling from ZTF J0440+2325 was much smaller — but not insignificant. 

“That was the real clincher for this system,” Householder says. “When we measured that wobble, we found we were not seeing a black widow. This was a low-mass star that’s orbited by a brown dwarf. The wobble was too small in amplitude to be anything else.”

They determined that the star and the brown dwarf are extremely close, with the brown dwarf circling the star every 87 minutes, in an orbit that could fit within the diameter of the sun. Both objects are small by stellar standards. The star is around 85 times as massive as Jupiter, while the brown dwarf is around 25 times as massive. 

With two low-mass objects circling at such close range, the scientists wondered if one object could be pulling material from the other. Such a process, known as accretion, is most often seen around objects that are extremely massive, though small in actual size, such as black holes and neutron stars. When a black hole accretes, or draws material from a much smaller nearby object, it pulls the matter around it in a disk.

“The difference here is: The thing absorbing matter is not a tiny black hole but a star, which is relatively big in size,” Burdge explains. “So matter just pummels directly onto the surface, at very high speeds, like an asteroid hitting the moon.”

The team carried out simulations of possible accretion in ZTF J0440+2325. Taking into account the properties of the star and the brown dwarf, they simulated particles of matter on the brown dwarf, and how these particles should behave within the system over time, according to the laws of physics and equations of motion. 

“When we track those test particles, we see they indeed fall right onto the surface of the star,” Householder says. “This is the first time we’ve caught a low-mass star actively accreting from another low-mass object.”

What’s more, the team calculated that the brown dwarf must be feeding material to its star at a rate of about 1/100,000 of an Earth’s mass each year. That’s about 40 million dump trucks’ worth of material, or roughly 1.3 trillion one-pound burritos every second. While that may seem like a lot of matter to be losing, it is in fact a very small fraction of the brown dwarf. This rate, the researchers estimate, is actually quite slow and steady. Given the size of the system, they say the star could continue leisurely snacking on the brown dwarf, for billions of years. 

This slow accretion, they say, would resemble a steady stream from the brown dwarf, onto the star. The researchers realized that if they were to view the system from afar, the brightness from the system would chart as a triangle, as the brown dwarf and its stream of matter circles its star. 

“It’s like you’ve got this continuous fireball onto one of the objects, and as one orbits the other, that hotspot comes in and out of view, and the peak of the triangle signal is when you’re looking right at the fireball,” Burdge explains. 

With the mystery of the triangle light curve solved, the team hopes to spot similar slow-feeding systems nearby. 

“It’s inspiring a lot of new searches on our part,” Householder says. “I think we’re going to learn a lot about a different kind of way that planets and brown dwarfs interact with their host stars.”

This research was supported, in part, by the National Science Foundation.

This one is from 1809, written by Napoleon’s nephew.

The EU is recommending import controls to combat unregulated squid fishing in the Southwest Atlantic. I’m not optimistic.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Blog moderation policy.

MIT formally dedicated its newly transformed Met Warehouse (Building W41) on Wednesday, in an energetic evening ceremony heralding the start of a new era for the practice of design on campus. 

The ceremony highlighted “the essential vision of the Met: connecting people, disciplines, and ideas, and inviting everyone to see where those connections might be,” said Mark Gorenberg ’76, chair of the MIT Corporation, during introductory remarks.

MIT President Sally Kornbluth called the new building “a testament to the transformative power of design, which has been central to MIT from the very beginning.” She also heralded the building as a cornerstone of MIT’s “magnetic new West Campus district for art and design,” which includes the Edward and Joyce Linde Music Building (W18) and the MIT Theater Arts building (W97). 

Hashim Sarkis, dean of MIT’s School of Architecture and Planning, delivered keynote remarks at the event, linking together many themes of the evening and recounting the project’s development in the late 2010s.

In envisioning moving into the Met Warehouse, Sarkis said, the “building spoke to us. It offered us possibilities that we could clearly envision both outside and inside the thick brick walls. … It helped us imagine how we can live and work together as a campus and as a school. Over the months of discussions among the faculty and students across the school, it became clear that it was an idea whose time had come.”

Many members of the MIT Corporation were in attendance for the event, held in the Met Warehouse’s Sidara Auditorium. The ceremony was also an occasion for giving thanks to those who made the new Met Warehouse possible: campus leaders, donors, faculty, architects and designers, contractors and specialized builders, and many others who worked on the remarkable structure in different ways. 

“The list, I promise you, runs longer than the credits at the end of “The Odyssey,” and what an odyssey this has been,” Sarkis quipped. 

From fortress to workshop

The Met Warehouse was originally constructed from 1884 to 1923, as a massive private storage facility with 2-foot thick brick walls, a corner turret, slit-like windows, and other features making it look like a fortress. About 500 feet long, with five stories, the building was long an imposing local curiosity.

MIT acquired the Met Warehouse in the 1970s and in the 2010s began exploring possible new uses for it. By 2018, the idea of making it the new home of MIT’s School of Architecture and Planning had gained enough traction to move forward. 

The high-profile firm Diller Scofidio + Renfro won the competition to become the project architects, and created a variety of solutions to bring natural light into the warehouse and revamp its interior. With permission from the Cambridge Historical Commission, the designers replaced four segments of brick wall on the building’s north side with top-to-bottom glass sheets, which along with skylights bring in abundant light.

At the same time, the architects — led by Elizabeth Diller and Benjamin Gilmartin, who were at the dedication last night — overhauled the building’s interior, while working within many of its structural features. The refurbished Met Warehouse now features double-height design studios, an auditorium, a large entrance lobby, a ground-floor café, offices, and many flexible, reconfigurable classroom spaces designed to help faculty and students collaborate on an immense array of projects. 

The Met Warehouse also features building-long open corridors on all five floors and a central staircase connecting all of them, as elements designed to enhance circulation and connectivity within the building.

In her remarks, Kornbluth heralded the Met Warehouse’s educational potential, noting the challenges artificial intelligence presents for education, as highlighted in an MIT-wide report released in August. 

That report, she outlined, emphasized that education comes from “helping students to value the process of learning as a ‘productive struggle’ and from engaging them in ‘human settings where they … learn how to work with others, communicate their ideas, receive criticism constructively, build confidence, develop judgment, and act as members of a community.’”

With that in mind, Kornbluth said, “that sounds exactly like the kind of hands-on, in-person, collaborative problem-solving the new Met was made for. … This community is not only ready to withstand the educational challenges of AI … it’s also primed to help the rest of MIT meet the moment. And that is very good news for us all!”

Diller also addressed the audience, highlighting some of the key design challenges involved in the project and thanking many of those who worked on it, including Leers Weinzapfel Associates, the project’s associate architects, and Shawmut Design and Construction. The Met Warehouse, she emphasized, is meant to be used in many ways in the future, and was designed with enough flexibility so that it can continue to evolve. 

“This building should remain a work in progress,” Diller said, adding that she would continue to regard it as “definitively unfinished.” 

Professors John Ochsendorf, Caroline Jones, and Lawrence Vale — MIT faculty who are all associate deans in the School of Architecture and Planning — also spoke at the ceremony, outlining the implications of the building for the school’s many forms of research and collaborative work. 

“It’s working,” Ochsendorf said, now that the building is inhabited on an everyday basis by students, faculty, and staff. 

Giving more thanks

As with almost any large, long-term project, credit can be spread in many directions, and the speakers at the dedication ceremony gave ample thanks to those involved — and to the important supporters of the project. 

“Hashim Sarkis has been its greatest champion,” Kornbluth said. “His leadership and imagination shaped not only this building, but the ambitious future it makes possible for the school.” She also thanked MIT President Emeritus L. Rafael Reif, a project supporter during his tenure, “for your foresight, your perseverance, and your insistence that the music, theater, and design communities at MIT deserve facilities worthy of the quality of their world-class work.”

For his part, Sarkis also gave credit to former MIT Corporation Chair Robert Millard ’73, saying, “Without Bob and his wife Bethany, this building would not be here today.” Gorenberg, in his remarks, also made a point of thanking the City of Cambridge for its extensive cooperation with MIT on the project. 

Gorenberg also expressed his deep “gratitude to the Morningside Foundation,” the philanthropic arm of the T.H. Chan family. He cited the “extraordinary generosity” of the founding gift, from family members Gerald and Beryl Chan and Ronnie and Barbara Chan, establishing the Morningside Academy for Design (MAD), a major interdisciplinary center at MIT located in the Met Warehouse. 

Speaking of Gerald L. Chan, Gorenberg added, “We cherish his wisdom and belief in MIT as a leading institution that can do good for the world.”

In a statement sent to MIT News, Chan said: “In this day and age when disciplinary boundaries are ever dissolving, it is important to have initiatives that tie all departments of the Institute together so that students can be facilitated to have broad exposures. Design provides such a possibility, and MAD is the venue.”

Sidara (formerly the Dar Group), a global collaborative of specialist design, engineering, and consulting firms owned by Maha and Talal Shair, supported the establishment of two central public spaces in the building, the Sidara Auditorium, and the Sidara Gallery, on the ground floor. 

“At Sidara, we share MIT’s commitment to improving lives, solving critical challenges, and making room for cultures to shine,” Talal Shair said in a statement to MIT News. “We feel a profound resonance with SA+P across all three dimensions — so it was only fitting that we would support the transformation of the MET into a hub for education, research, and innovation. We trust the Sidara Auditorium and the Sidara Gallery will serve as spaces for idea exchange, inspiring future generations to think broadly and act boldly.”

The LUMA Foundation, a Zurich-based nonprofit founded by Maja Hoffmann in 2004 to support artistic production and the organization behind LUMA Arles, an interdisciplinary creative campus in southern France, also gave an establishing gift for the MIT LUMA Lab, based in the Met Warehouse, for projects combining art, science, technology, conservation, and design. 

“LUMA Foundation has always been grounded in the belief that meaningful change begins by creating the field and conditions for people, disciplines, and forms of knowledge to encounter one another freely, critically, and with mutual respect,” Hoffmann said in a statement for MIT News. “The MET gives this principle a remarkable new context. To see faculty, students, researchers, artists, designers, scientists, and technologists connected through the MIT-LUMA Lab working alongside one another is a powerful expression of what such a place can enable. I am excited and proud to be contributing to this journey and be part of the MIT community and its future.”

Referencing MIT’s motto, “mens et manus,” which is Latin for “mind and hand,” Gorenberg wrapped up the dedication ceremony last night with an additional thought: “This is ‘mens et manus’ at its finest.” 

The Massachusetts Institute of Technology Investment Management Company (MITIMCo) announced today that MIT’s unitized pool of endowment and other MIT funds generated an investment return of 10.3 percent during the fiscal year ending June 30, 2026, as measured using valuations received within one month of fiscal year end. At the end of the fiscal year, MIT’s endowment funds totaled $29.2 billion, excluding pledges. Over the 10 years ending June 30, 2026, MIT generated an annualized return of 11.7 percent.

The endowment is the bedrock of MIT’s finances, made possible by gifts from alumni and friends for more than a century. The use of the endowment is governed by a state law that requires MIT to maintain each endowed gift as a permanent fund, preserve its purchasing power, and spend it as directed by its original donor. Most of the endowment’s funds are restricted and must be used for a specific purpose. MIT uses the bulk of the income these endowed gifts generate to support financial aid, research, and education.

The endowment supports about half of undergraduate tuition, helping to enable the Institute’s need-blind and full-need undergraduate admissions policy, which ensures that an MIT education is accessible to the most talented students in the nation and the world regardless of their financial resources. 

In fiscal 2026, MIT enhanced undergraduate financial aid, ensuring that all students from families with incomes below $200,000 and typical assets have tuition fully covered by scholarships, and that families with incomes below $100,000 and typical assets owe nothing toward their students’ MIT education. Eighty-eight percent of the Class of 2026 graduated with no debt. With our investments in financial aid, parents of MIT undergraduates receiving financial aid now pay on average 10 percent less on a real basis than at the end of the Great Recession.

MIT Student Financial Services works closely with all families of undergraduates who need financial aid to make MIT affordable for them. In 2025-26, the average need-based MIT undergraduate scholarship was $66,155. Fifty-eight percent of MIT undergraduates received need-based financial aid, and 44 percent of MIT undergraduate students received scholarship funding from MIT and other sources sufficient to cover the total cost of tuition.

MIT’s endowment enables it to do more cutting-edge research. Fueled by funding from the endowment, the Institute more than matches the amount of campus-based research funded by the U.S. government and other sponsors — expanding its beneficial impact without asking more from taxpayers. 

MITIMCo is a unit of MIT, created to manage and oversee the investment of the Institute’s endowment, retirement, and operating funds.

MIT’s Report of the Treasurer for fiscal year 2026, which details the Institute’s annual financial performance, was made available publicly today.