Despite millions of years of evolution, the development of the human fetus remains a complex process that is vulnerable to genetic, environmental, and metabolic disruptions. These disruptions could result in developmental abnormalities, starting with one of the first organs to begin developing in the fetus that continues to develop after birth: the brain.

In a routine prenatal ultrasound, the sonographer will flag possible brain abnormalities for additional magnetic resonance imaging (MRI). But imperfect imaging can result in missed or incorrect diagnoses. 

To assist with the early detection and treatment of these abnormalities, researchers at MIT, Boston Children’s Hospital, and Inria have developed and trained a deep learning model called E(3)-Pose that helps image the fetus’s head while it’s in motion to capture a high-resolution image that the radiologist can examine. A paper about the work was presented at the 2026 European Conference on Computer Vision. 

“One of the problems with having the baby move is that the slices are all over the place,” says first author Ramya Muthukrishnan. Muthukrishnan is an MIT PhD student in the lab of Sunlin (1966) and Priscilla Chou Professor of Electrical Engineering and Computer Science Polina Golland, who is a principal investigator at the MIT Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

By slices, Muthukrishnan is referring to a series of 2D images taken during a fetal MRI scan. These 2D planes stacked together effectively make up one high-resolution, 3D image of the fetus’s head. But if the head shifts during imaging, each 2D image “slice” could end up being taken from a different angle, resulting in gaps in the final scan and unusual slice orientation. These problems may cause the physician reviewing the MRI to miss or incorrectly diagnose a pathology in the fetal brain.

“There are very fine details that you need a very good volumetric picture of the brain to see,” explains Muthukrishnan. “If you have coverage gaps, you can’t see critical regions, and you need to be able to see well to detect abnormal development.”

What makes E(3)-Pose particularly good at tracking fetal motion is its focus on physics. Rather than simply training the model to learn physics from the data, the very principles of physics are baked into the neural network: left-right symmetry of the fetal head is embedded in the model architecture, making it easier for the model to accurately identify the brain’s orientation. 

When Muthukrishnan began working on the project at the start of her PhD, she had no background in physics, let alone MRI physics. Most of her experience was in computer science. “I was surprised when I had to go and implement this on the scanner,” she recalls. “I was not prepared for how many times I would crash the scanner because putting things on hardware and getting it to work on hardware is a different beast than training a model to run on data on a GPU.” 

Despite the challenges, Muthukrishnan persisted. She remembers shadowing a radiologist who performed fetal MRI scans at Boston Children’s Hospital at the start of her PhD and observing the shared frustration of the patient and radiologist: the pregnant mother felt uncomfortable after spending an hour in an MRI, only to quit the scan halfway; the radiologist was unable to procure a full, high-quality MRI to monitor the development of the fetus.

“Seeing frustration about it helped me decide what I wanted to do with my PhD, because it felt like this was a pain point,” Muthukrishnan says.

Fortunately, she had help: Co-author Borjan Gagoski, an assistant professor of radiology at Harvard Medical School and a researcher at Boston Children's Hospital, developed a sequence that acquires additional MRI scans to assist with training E(3)-Pose and worked with Muthukrishnan to help troubleshoot the scanner whenever it crashed. Co-author and Boston Children’s Research Assistant Aryn Lee recruited the pregnant volunteers and assisted with acquiring each of the MRI scans. Senior authors who helped guide the project include Elfar Adalsteinsson, MIT professor of electrical engineering and computer science; Ellen Grant, the Käthe Beutler Professor of Pediatrics and professor of radiology at Harvard Medical School; and Golland. Benjamin Billot, a researcher at Inria and a former postdoc in Golland’s group, helped Muthukrishnan get started with the initial method he developed.

“Ramya’s work elegantly combines geometric concepts like equivariance and symmetry with the power of deep learning to change how MRI scanners acquire the images, and to ultimately help the physicians detect and treat problems early in development. It’s an impressive research project that is deep and fundamental in how it models image acquisition, with clear clinical impact,” says Golland.

Grant, who directs the Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC) at Boston Children’s, adds that Muthukrishnan’s work “will automate fetal brain MRI, replacing today's slow, manual process with faster and more comfortable scans for mothers, while also providing higher-quality images for radiologists to interpret.”

E(3)-Pose’s applications could extend beyond motion tracking for fetal MRIs. It could assist with imaging other hard-to-image anatomy, and even autonomous driving applications, where limited sensors need to capture noisy, 3D data in order to track 3D objects.

For now, Muthukrishnan hopes to improve E(3)-Pose so that it can help with imaging second-trimester or younger fetuses, as the model is primarily trained on third trimester fetuses. Second-trimester fetuses are “so small, they move around a lot more because there’s more space in the uterus,” Muthukrishnan says. “They’re more important to focus on because the earlier you detect brain abnormalities, the easier it is to intervene.” 

This work is supported by the MIT Jameel Clinic, the MIT Takeda Program, the Chou Family Transformative Research Fund, the National Institute of Biomedical Imaging and Bioengineering, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Exciting news for Safari users: Privacy Badger is now available on Safari for macOS! You’ll need Safari version 26.5 or higher to use it.

Whether you want to protect yourself from data brokers or just don’t want Big Tech profiting off your browsing data, Privacy Badger is here to help. More than 4 million people already use EFF’s free tracker-blocking extension to take a stand against online surveillance. Safari users can now join them and EFF in the fight for a better web.  

Install Privacy Badger

Support the Fight Against Online Tracking

Safari support has been one of Privacy Badger’s most requested features for years. Thanks to recent improvements in Safari's extension support, we’ve finally made it happen for Safari version 26.5 and higher. Privacy Badger is now available on all major desktop browsers. And before you ask, yes, we will look into supporting Safari for iOS once we've ironed out any issues on macOS.

Why Install Privacy Badger on Safari? 

Most websites contain invisible tracking code that lets companies collect, share, and profit from your personal data. Some of those companies are data brokers that sell your information to anyone willing to pay. Creepy ads are just the tip of the iceberg when it comes to the harms of online tracking: Once your information enters the data broker ecosystem, it’s nearly impossible to know who buys it or what they’re doing with it. Privacy Badger blocks online trackers to prevent your browsing data from being used against you.  

Privacy Badger goes beyond Safari’s built-in privacy features to provide additional protection against online tracking. In its default browsing mode, Safari limits the information that trackers can access but still allows them to load. Privacy Badger blocks trackers from loading in the first place, preventing them from tracking you using techniques that bypass Safari’s protections. 

Privacy Badger works well by itself, and will continue to enhance your privacy when installed along side an ad blocker or with Safari’s Advanced settings to block trackers in all windows. Since Privacy Badger automatically learns to block trackers, Privacy Badger will block trackers that other tools don’t know about or choose not to block. 

For example, Privacy Badger blocks tracking from widgets like embedded tweets, comments sections, and video players. These widgets can share your data even if you never click on them. Privacy Badger prevents these trackers from loading and replaces them with click-to-activate placeholders. 

Beyond tracker blocking, Privacy Badger automatically sends the Global Privacy Control (GPC) signal to tell websites not to sell or share your personal information. The GPC signal is already legally binding in a growing number of states, including California, Colorado, New Jersey, and Connecticut.  

All these features (and more) work together to help keep your browsing activity private on Safari. 

Try It Out and Spread the Word 

If you use Safari on macOS, give Privacy Badger a try. You’ll install Privacy Badger through the App Store on your macOS device. Installing extensions is a little more complicated on Safari than other browsers, so follow Apple’s directions here if you’re having trouble.  

This is our first release of Privacy Badger for Safari, and we will keep improving it based on your feedback. If you run into any problems, let us know by emailing extension-devs@eff.org, or by opening an issue on GitHub. And if blocking harmful trackers causes issues on a website you visit, you can disable Privacy Badger for that specific site while keeping it enabled and protecting you everywhere else. You can also let us know about broken sites by using the “Report broken site” button found next to the “Disable for this site” button in Privacy Badger’s popup window. 

When you use Privacy Badger, you join EFF and millions of other users in the fight for a better web. Help spread the word by telling your friends and family who use Safari that they can use Privacy Badger too!  

Install Privacy Badger 

Support the Fight Against Online Tracking 

Free Tracker Blocker Used by Millions Will Protect Even More Users' Privacy

SAN FRANCISCO—Privacy Badger, the award-winning tracker blocker made by the member-supported digital rights nonprofit Electronic Frontier Foundation (EFF), is now available for Safari on macOS.  

Safari users can download the free browser extension today and join the more than 4 million people using Privacy Badger to take a stand against data brokers and online surveillance. Users will need Safari version 26.5 or higher to use it.

Ranked as one of the best ad tracker blockers by The Wirecutter, Consumer Reports, PC Mag and more, Privacy Badger is different from other blocking extensions. Created by EFF to stop companies from spying on you online, Privacy Badger automatically learns to block hidden trackers on the web, along with additional privacy-protecting features. 

"Most websites contain invisible tracking code that lets companies collect, share, and profit from your personal data," said Lena Cohen, Staff Technologist at EFF. "Creepy ads are just the tip of the iceberg when it comes to the harms of online tracking: Once your information enters the data broker ecosystem, it’s nearly impossible to know who buys it or what they’re doing with it. Safari support has long been one of Privacy Badger’s most requested features and EFF is excited to be able to make this important tool available to Safari users to fight back for a better web." 

On Safari, Privacy Badger goes beyond the browser’s built-in privacy features to provide additional protection against online tracking. In its default browsing mode, Safari limits the information that trackers can access, but it still allows them to load. Privacy Badger blocks online trackers from loading in the first place, preventing them from tracking you using techniques that bypass Safari’s protections. 

With today's launch, Privacy Badger is now available on all major desktop browsers. 

As the leading nonprofit defending online civil liberties, EFF is committed to fighting mass surveillance in the courts, through activism, and by making free, privacy-protecting tools like Privacy Badger. Now, even more people can join the movement against online tracking, by installing Privacy Badger themselves, telling their friends and family who use Safari about it, or by supporting Privacy Badger today. 

For more on Privacy Badger for Safari on macOS: https://www.eff.org/deeplinks/2026/10/announcing-privacy-badger-safari-macos

For more on the dangers of online tracking: https://www.eff.org/deeplinks/2025/03/online-tracking-out-control-privacy-badger-can-help-you-fight-back 

For more on how Privacy Badger works: https://privacybadger.org/ 

Contact: press@eff.org

Tags: Privacy BadgerAd trackersSurveillance Advertising

Interesting research:

Abstract: Vision-language models (VLMs) can solve visual CAPTCHAs without task-specific training, but the agents built on them approach every challenge from scratch. For such an agent, the hundredth instance of a familiar puzzle costs as much time and compute as the first. Specialized detectors invert the trade-off, answering in milliseconds but only for categories they were trained on. Neither improves with exposure. We study what changes when a solver improves with use. Our system pairs a fine-tuned YOLOv8 detector with an open-weight VLM behind a confidence-based router, and runs entirely from screenshots and operating-system input events, with no browser automation or DOM access. It reaches 85.4% overall and 84.2% macro accuracy across 16 classes, exceeding either component alone. Every answer VLM produces also serves as a training label, so the detector absorbs categories it was never trained for, typically after one or two encounters and without human annotation. The same loop also repairs it. A CAPTCHA operator can perturb images against the publicly released detector and drive its accuracy to 0%, but the perturbations leave VLM untouched, and its labels let the detector recover. Under a year-long simulated arms race in which the CAPTCHA operator re-crafts its perturbations each month, the solver recovers every round, and a cheap ~70%-accurate open-weight teacher hardens it as effectively as a perfect oracle. Visual CAPTCHA defenses that assume a failing bot stays failing therefore understate how quickly an adaptive solver returns...

Nature Climate Change, Published online: 19 October 2026; doi:10.1038/s41558-026-02770-2

A resilient society must prepare not only for common harms but also for uncommon vulnerabilities, such as rare disease where the consequences leave no room for failure. Ensuring that people with rare diseases have reliable access to essential care is crucial for fairness and safety in a changing climate.

In principle, artificial intelligence could make finding the right material for an application as simple as ordering dinner: Scientists would tell a large language model what they want, and it would serve them a perfectly designed crystal for the job.

Unfortunately, that approach doesn’t work well yet, and the problem comes down to data: Most materials consist of crystals, which are 3D periodic arrangements of atoms whose structures are stored in specialized formats, not the text streams that today’s large language models are trained on. The experimental literature is also heavily biased toward a few popular classes of crystals, making AI outputs skew toward those materials.

Now MIT researchers have created a multimodal AI model that tackles these problems. The model combines 3D atomic structures with natural language descriptions to create rich linguistic descriptions about the structures from experimental research papers and first-principles computational databases. The unified description outlines not just the chemical composition and structure, but also its properties, processing considerations, and potential applications, helping AI learn more about what makes materials impactful.

In a new paper in Nature Communications, the researchers showed their system could identify better material designs than models trained on text streams alone by allowing the model to “see” the atomic arrangements and bonding patterns. For example, when the researchers asked the model to identify materials suited for solid-state lithium-ion battery electrolytes, its top results included materials that had been independently identified as promising candidates. The researchers also showed their model learned geometric representations of material structures in ways text-only models could not.

“Structure is really at the heart of the materials science field,” says Ju Li, the Carl Richard Soderberg Professor in Power Engineering in the Department of Materials Science and Engineering (DMSE). “If you understand the structure, you can infer quite a lot about the properties and performance of materials. We wanted to build the connection between a material’s atomic structure and its properties and processing for the model.”

Joining Li on a paper about the model are Yang Jeong Park, first author and former MIT postdoc; Mayank Kumaran, a recent University of Illinois Urbana-Champaign computer engineering graduate; Chia-Wei Hsu SM ’26; and Elsa Olivetti, the Jerry McAfee (1940) Professor in Engineering in DMSE.

Getting models to see in 3D

Materials scientists are always on the hunt for new crystals that will lead to the products of the future. Over the last decade, AI has reshaped that process, proposing and designing new crystalline structures, which have highly ordered atomic structures and make up more than 90 percent of solid materials on Earth. Most of those models treat solid crystalline materials as 3D graphs.

The rise of large language models has given researchers another tool for innovation. But existing large language models rely heavily on text from published papers and books, limiting their knowledge of the physical world, since many potential crystal structures are stored in computational databases. Text-based models also lack understanding of visual geometry.

To overcome those challenges, the researchers decided to create a vision-language model for crystalline materials.

They trained a language model to create textual descriptions of crystal structures using an approach known as contrastive learning, in which models compare similar and dissimilar examples of structures and textual descriptions to achieve a unified understanding. This is similar to aligning the visual and language regions of the brain.

Following training, the researchers compared the predictions of two versions of the model: one trained on a dataset containing the AI-generated descriptions and the other trained on a dataset containing text from papers only. They found that the model trained on AI-generated descriptions successfully learned how to align geometric structures with text descriptions while the other did not.

“We wanted to create an AI model that works broadly across materials,” Li says. “That’s why we decided to synthesize narratives rather than rely solely on existing papers. We found when we used that narrative dataset, the models are better at predicting the function.”

Accelerating materials science

The researchers then showed their model could be given a natural language query describing a property and identify crystalline materials with that property, outperforming a baseline.

“There are sometimes these step changes within materials science around algorithmic integration toward useful tools, which the community uses to further advance the field,” Olivetti says. “This approach helps us see more deeply into three-dimensional structures and link structures to property and processing. I hope this can be one of those step changes.”

Li compares the model to AlphaFold, an AI model that links protein structures with function that has helped advance biological research and drug development.

The researchers believe their new approach can work with many crystalline materials, and they hope other material scientists will use it to accelerate their work.

“Being able to see a three-dimensional crystal and how its atoms are connected is super foundational,” Li says. “I think this will be useful to anyone who practices materials science.”

The work was supported, in part, by the U.S. Defense Threat Reduction Agency through the University Research Alliance; the U.S. Defense Advanced Research Projects Agency; and the National Research Foundation of Korea.

New research shows that squid lived all around the globe even before the Cretaceous-Paleogene mass extinction event.

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.

Kendall Square in Cambridge, Massachusetts, is often cited as the most innovative square mile in the world. But when the Kendall Square Association gathered local stakeholders for its 18th Annual Meeting Thursday, the conversation focused on innovation primarily in the context of community.

The event, which took place at the nonprofit startup incubator The Engine, attracted people from across Cambridge, including business leaders, elected officials, local residents, and students, for a night of local food and conversation about the advance of technologies like artificial intelligence and what they mean for society.

“How can we make AI not an enemy of work, but a tool for workers to expand their capabilities and build new expertise or do new things?” asked MIT Institute Professor Daron Acemoglu in a keynote talk. “The world is at a point in time where we need new innovations and new adaptations to growing challenges.”

Acemoglu’s keynote was one of several presentations at the event, which also featured music from the Kendall Square Orchestra, a vote on new KSA board members, and awards for organizations making a positive impact through innovation.

KSA is a nonprofit made up of over 150 organizations across Kendall Square, from major companies to universities, research organizations, and the independent shops and restaurants that give Kendall Square its distinct character.

“People come to Kendall Square to make the world better,” said KSA Executive Director Beth O’Neill Maloney in her opening remarks. “People come here to improve the human condition, people come here to solve big problems, and people come here to innovate for good.”

Acemoglu, who shared the Nobel Prize in economics in 2024 for his work studying how institutions affect prosperity, spoke on the subject of his new book, “What Happened to Liberal Democracy?”

Acemoglu says liberal democracy is under siege as trust in liberal institutions decline, political polarization rises, and people lose faith in elected officials. He acknowledged that the shared prosperity liberal democracy promised has not always been delivered, especially over the last 50 years, but insisted it is the best path forward and in need of renewed support.

“I believe liberal democratic institutions, together with the norms that support them, are one of the greatest human achievements,” Acemoglu said. “It would be unthinkable for people who lived 300 years ago that we could live in societies consisting of hundreds of millions of people with diverse interests, different views, doing different things, and people still participate in politics and reach compromises, and we have state institutions that, by and large, actually provide services and do things for the people, and that we build opportunities for prosperity from which most people benefit while social freedoms are largely upheld.”

Cambridge Mayor Sumbul Siddiqui also spoke at the event. Siddiqui began her talk by telling the story of Cambridge residents working with biotech labs in the 1970s to create a groundbreaking policy on recombinant DNA research, which helped turn Kendall Square into the life science hub it is today.

“All these years later I think that story captures what makes Kendall Square so special: It’s our willingness to work together even when we face big challenges,” Siddiqui said. “It isn’t just the universities or labs, it’s also the culture of collaboration among nonprofits, governments, and residents.”

Broad Institute Chief Communications Officer Lee McGuire started his talk by reviewing a 2009 report on what made Kendall Square such a powerful driver of innovation, noting that factors like talent density, education, and a collective voice remain strong in the area today.

“This report was brilliant in that it captures so many of the special things that matter for a place like Kendall,” McGuire said. “It is the job of the Kendall Square Association and all of us to help protect those things, make sure we name them, understand them, and see them as essential elements of making sure this community stays what it is no matter what happens. As long as there’s a good idea, this is the place that’s going to get that idea moving and scale it up to change the world.”

This is a problem:

Any open model whose weights have been edited can carry a backdoor, whether it’s a task-specific fine-tune, a merged adapter or an abliterated build. We have abliterated models in the title because it’s the most popular reason people download modified weights without verifying what’s inside. Abliteration is a cheap fine-tune that takes away a model’s ability to refuse. You find the direction in the weights that carries “no” and subtract it. The model then answers things a safety-tuned version would turn down. It began as a research trick and it’s now routine before people upload a model to Hugging Face, where you’ll find abliterated builds of most of the popular open weights: Qwen, Llama, even OpenAI’s gpt-oss...

Nature Climate Change, Published online: 16 October 2026; doi:10.1038/s41558-026-02792-w

In a year containing summits from the three United Nations environmental frameworks, we consider how cooperation across the Conferences of the Parties (COPs) can facilitate implementation and impact. Co-timed with the start of the biodiversity COP, we highlight the reciprocal relationship between climate change and biodiversity.

Nature Climate Change, Published online: 16 October 2026; doi:10.1038/s41558-026-02778-8

This year, all three major Rio Conventions — on biodiversity, climate and desertification — convene their respective Conference of the Parties (COP). In advance of the biodiversity COP17, Astrid Schomaker, the executive secretary of the Convention on Biological Diversity, discusses the irrefutable need to integrate biodiversity conservation into broader environmental action to ensure local and global security and prosperity in a rapidly changing world.

Nature Climate Change, Published online: 16 October 2026; doi:10.1038/s41558-026-02775-x

Climate change will further increase the frequency and intensity of extreme weather events. Subjective experience and attribution of extreme weather events to climate change, rather than objective exposure alone, are associated with greater climate-relevant attention and choices. Political affiliation influences attention and behaviour irrespective of subjective attribution and objective exposure.

Nature Climate Change, Published online: 16 October 2026; doi:10.1038/s41558-026-02765-z

Mechanisms behind climate decision-making remain unclear. This study shows that political affiliation and subjective attribution shape attention allocation and climate-related choices, with subjective attribution moderating the effects of political affiliation and objective weather exposure.

Barry Steinhardt, a lifelong privacy champion and an early leader in the battle for digital civil liberties who served as EFF’s president in 1998-99, died last week at age 73. 

A Connecticut native, Steinhardt led the Vermont and Pennsylvania affiliates of the American Civil Liberties Union before becoming associate director of the national ACLU. There, he helped spearhead the fight to overturn much of the Communications Decency Act, resulting in the U.S. Supreme Court’s landmark Reno v. ACLU ruling in 1997. 

When the internet was still young, Steinhardt became one of the first attorneys to specialize in the intersection of technology and privacy. In early 1998 he took a leave of absence from the ACLU to become EFF’s president, and then returned to the ACLU in 1999. 

In 2002 he founded the ACLU’s Program on Technology and Liberty. After retiring from the ACLU, he continued on as a senior advisor to London-based Privacy International. 

Steinhardt chaired the 2003 Computer Freedom and Privacy Conference and served on a wide variety of significant panels and boards, including the Department of Transportation’s Negotiated Rule Making on national driver’s license standards, the Advisory Committee to the US Census, and the Blue Ribbon Panel on Genetics of the National Conference of State Legislatures. He also was selected to be a member of the US delegation to the G-8 Government and Private Sector Tokyo conference on Cyber Crime and served as an advisor to the Czech Helsinki Committee.  

“Barry led many critical technology and civil liberties fights and was an important mentor to me and others in the field,” said EFF Executive Director Nicole Ozer. “Barry’s influential work across strategy to defend and advance privacy rights and safeguard people against surveillance has made its mark on the law and policy of our digital world and protected the rights and safety of people across the United States and around the world.”   

Suzy M. Nelson, MIT vice chancellor for student life since 2016, will retire from the Institute this month. Nelson leaves MIT with a strong, coordinated Division of Student Life (DSL) built from years of close partnership with student leaders. One of her most noteworthy contributions is the elevation of student well-being, now integral to the Institute’s educational mission. 

Under Nelson’s leadership, MIT created a culture of well-being, building out a strong support network, enhancing health promotion efforts, and expanding spaces dedicated to student wellness. These efforts emphasized the importance of students finding a sense of purpose, developing positive relations, and flourishing in mind and body. 

Working with colleagues from across campus, DSL advanced new ways to coordinate student support services for undergraduate and graduate students experiencing significant challenges. MIT students now increasingly turn to programs such as Student Support Services (S3), which serves 82 percent of all undergraduates by the time they graduate, and 60 percent every year. A new CARE team coordinates resources that undergraduates, graduate students, and the MIT community rely on in a crisis, and has quickly become the thread that weaves together offices caring for students. 

Nelson prioritized student residences as the cornerstone of the MIT campus experience. She led an effort to develop architectural principles for housing to guide construction and renewal planning; partnered with alumni from fraternities, sororities, and independent living groups to undertake a comprehensive review of chapters’ deferred maintenance and facility needs; expanded services to the residential communities; and developed close working relationships with the faculty heads of house. 

“Suzy has been a wonderful leader and humane presence on our campus,” says David Mindell, head of house for Edgerton House. “She has partnered with the heads of house through trying times, as well as triumphs, and for that we are grateful. The students and their welfare have always been her first priority.”

Additionally, Nelson oversaw the construction of three new campus residences: Graduate Tower at Site 4 in 2020; New Vassar in 2021; and Graduate Junction in 2024, an innovative third-party partnership. The additional on-campus graduate housing increased capacity to accommodate nearly half of MIT’s graduate students and exceeded MIT’s commitment to the City of Cambridge. The division also worked on the renewal of four residences — New House (completed 2018), Burton Connor (completed 2022), East Campus (completed 2025), and now McCormick Hall (targeted for completion in 2028).

Beyond housing, Nelson advanced a major transformation of the core of the Stratton Student Center, leading to the opening of the Wellbeing Lab, new dance studios, improved lounge spaces, and refreshed offices for student organizations.

The Department of Athletics, Physical Education, and Recreation has played a critical role in MIT’s well-being efforts, incorporating wellness modules into physical education and wellness classes and offering recreation, intramural, and club sports opportunities to both undergraduates and graduate students. Additionally, the Institute’s athletics programs thrived during Nelson’s tenure, with MIT Engineer teams earning four national championships in 2024-25 and the number of All-Americans increasing significantly over the last five years. MIT remains the all-time leader in Academic All-Americans across all NCAA divisions. Nelson also encouraged expansion and renewal of athletic facilities, providing all students the opportunity to train using state-of-the-art equipment. 

Nelson’s leadership shaped the Institute’s approach to community standards. She helped refine student conduct processes and streamline the Committee on Discipline process. She also championed new policies supporting free expression and launched a new Dialogue Collaborative focused on coordinating efforts that promote dialogue across the campus. 

“Suzy is a remarkable leader and she has been a potent positive force within the MIT community. Her fusing of strategic vision, collaborative skill, and deep commitment to the students, DSL staff, and broader MIT community have been the hallmark of her extraordinary leadership,” says Erich Caulfield, chair of the Student Life Visiting Committee. “She has been a joy to work with, and her incomparable wisdom has been invaluable during this unprecedented period in student life at MIT and in higher education nationally."

Highly responsive to the changing needs of students, Nelson partnered closely with the Committee on Student Life and student leaders from the Undergraduate Association, Graduate Student Council, Dormcon, and the Graduate Housing Advisory Committee, as well as student representatives for individual projects. For example, Nelson created a working group to improve how student organizations gain recognition, manage membership, and apply for resources. She has worked closely with students on expanding access to nutritious food and supporting food security, and, this past year, she engaged students to help assess MIT’s dining services.

“Suzy brought her visionary leadership and humanity to DSL over this past decade to create profound, positive, and lasting change. All of us at the Institute, and especially our students, have benefited — and will continue to benefit — from the Nelson Era,” says Chancellor Melissa Nobles.  

Throughout her career at MIT, colleagues and students came to know Nelson for her collaborative style. As she navigated crises over the past decade, most notably the Covid-19 pandemic, she always convened students, faculty, and staff. And she found new ways of elevating staff, creating the Staff Engagement Advisory Board, a group of 45-plus volunteers who support the division’s positive work environment and promote professional development opportunities. Her team in DSL is grateful for the many ways she strengthened and professionalized the division, and they will continue to abide by her unwavering belief that students should help shape the communities where they live and learn. 

Nelson says of her retirement, “I am grateful to have served with so many exceptional faculty, staff, and students over these past 10 years. Because of their focused dedication to being here for students, I have every confidence that the transition to new leadership will be seamless.”

MIT will soon welcome Akirah Bradley-Armstrong as the next vice chancellor for student life. She most recently served as the vice chancellor for student affairs and success at the University of California at Santa Cruz, and has more than two decades of experience working in student affairs. She will start in the position on Oct. 19.

When corporate leaders discuss climate strategy, the message that still dominates is that, despite competing priorities and external pressures, sustainability matters. 

According to the 2026 State of Supply Chain Sustainability Report from the MIT Sustainable Supply Chain Lab, which surveyed 1,810 supply chain professionals across 91 countries, 83 percent rate sustainability as important or very important to long-term business success, the highest level in the report's seven-year history.

But commitment, the report reveals, is not the same as capacity. While 59 percent of respondents report becoming more committed to sustainability following recent U.S. policy shifts that deprioritize environmental concerns, the same organizations are being forced to compromise those commitments. Sixty-eight percent report that tariff uncertainty has compelled them to delay, scale back, or abandon sustainability strategies. Nearly one-third have seen tariff-related disruptions actually increase their operational emissions.

"Commitment is strong, measurement is expanding, and AI is accelerating," says Sreedevi Rajagopalan, director of the MIT Sustainable Supply Chain Lab and lead author of the report. "What comes next is harder: converting commitment into accountability, operational integration into strategic decision-making, and incremental decarbonization into genuine transition."

The result is a supply chain sustainability agenda stuck between conviction and constraint. 

Beyond tariffs, more than eight in 10 respondents across North America, Europe, and Asia agree that ongoing geopolitical conflict is reducing the effectiveness of their organization’s climate action. Organizations built decarbonization plans on assumptions of stable trade and relative peace, yet neither assumption is holding.

The external disruption reveals an internal vulnerability. Among companies with publicly stated sustainability goals, only 51 percent have established a formal cross-functional sustainability team, which is the governance structure most strongly associated with embedding sustainability into daily decisions. In addition, only 33 percent place sustainability oversight at the board level. Public ambition, in other words, is vastly outrunning internal accountability infrastructure. Companies with formal cross-functional teams report sustainability is "frequently or always" built into decisions 57 percent of the time. Where responsibility sits in a single function, that drops to 13 percent — a 44-point gap illustrating the return on governance investment.

Sustainability is embedding most deeply where companies make daily operational choices: transportation and logistics (39 percent), procurement (35 percent), warehousing (34 percent), and product design (33 percent). However, it thins out dramatically in decisions that lock in long-term emissions: capital investment, network design, and supply chain risk planning. This reveals that companies are becoming better at operating more sustainably, but not at designing sustainable supply chains in the long term.

The artificial intelligence story compounds this tension. Seventy-eight percent of North American organizations report current use of AI in sustainability initiatives, and 87 percent of adopters report positive impact on sustainability goals. Eighty-six percent have reduced material waste, 81 percent have reduced energy use, and 63 percent use AI to estimate missing supplier emissions data. However, among mature agentic AI users, only 53 percent report a reduction in total greenhouse gas emissions. Twenty-nine percent report an increase, suggesting that operational efficiency does not automatically translate into lower net emissions.

This tension is particularly visible in warehousing. Among advanced and fully automated warehouses using AI, 78 percent report higher energy use since implementing AI, and 76 percent report higher waste, yet only 24 percent use AI-driven real-time monitoring to track environmental consequences. Many organizations may not realize their energy footprint is climbing until well after implementation.

Another key area of the report is freight transportation. Nearly every freight company is reducing emissions through route optimization, load consolidation, and driver-behavior programs. However, 43 percent of fleets still operate mostly or entirely on conventional diesel and only 8 percent have completed a full transition to low-emission energy. The divergence between regions reveals why: In Europe, 84 percent of freight companies report that recent policy changes have positively affected decarbonization strategy. In North America, only 44 percent do. When policy signals are unclear, capital-intensive technology transitions stall. For example, battery-electric vehicles are at scale in 60 percent of European companies, but only 36 percent in North America.

The report reveals that one bright spot has emerged in Scope 3, or indirect, emissions collaboration. Participation in joint supplier engagement and decarbonization programs surged from 31 to 58 percent in a single year. In addition, partnerships to manage shared suppliers' emissions more than doubled, from 23 to 55 percent. The share working entirely alone collapsed from 18 to 6 percent. The report, supported by the C.H. Robinson Foundation, Breakthrough, and CO2 AI and Dassault Systèmes, reveals that companies are recognizing that Scope 3 cannot be solved in isolation. 

Across all these areas, the consistent pattern the report reveals is that corporate commitment is not the prevailing constraint to ongoing sustainability efforts. Rather, governance, accountability structures, technology infrastructure, and measurement capabilities are the current obstacles. Organizations that close the external gap by building resilience against disruption and the internal gap by hard-wiring accountability into structure will be the ones whose commitments survive. Those that do not will find that ambition without accountability moves the needle very little.

As an embryo develops from a small cluster of stem cells, those once “blank slate” cells begin to take on more specialized roles like brain, liver, or muscle cells, and organize themselves into three-dimensional structures such as tissues and organs.

The fate of each cell — what type of specialized cell it will become — depends on which genes are turned on or off in the cell. These patterns of gene activity shape the cell’s structure and function, enabling it to take on a specific role in the body.

But this decision isn’t up to individual cells. They constantly send and receive chemical signals to and from neighboring cells, which help them understand where they are, what stage of development they are in, and what they should become. These messages spread through multi-step sequences called signaling pathways, which translate external signals into specific changes in gene activity in the cell.

For researchers, being able to retrace the sequence of instructions a cell has received would offer a powerful way to understand how tissues develop and how these processes go awry in disease. 

But this has been difficult to achieve because scientists have long assumed that the effects of signaling pathways vary widely across cell types, meaning they would need to map each pathway separately in each cell type — an arduous and painstaking process.

Now, in a new study led by MIT assistant professor of biology and Whitehead Institute for Biomedical Research member Pulin Li and graduate student Nicholas Hutchins, researchers have discovered that each signaling pathway leaves behind a unique “fingerprint” — a distinctive pattern of gene activity that reflects the particular signals the cell has encountered.

Importantly, these fingerprints are consistent across different cell types for the same signaling pathway, which means that instead of mapping each cell type separately, scientists can reconstruct signaling histories across many cell types using these pathway-specific fingerprints.

This discovery was made possible through a machine learning model called IRIS. This model can detect fingerprints of different signaling pathways and pinpoint which signals a cell received at different stages of development inside an embryo, even for cell types it hasn’t encountered before. 

This artificial intelligence-driven approach marks a major advance over traditional methods, which require researchers to experimentally test every pathway in every possible cell type, and opens up the possibility to comprehensively map the signaling histories of every cell inside a mouse or human embryo at an unprecedented scale.

“Think of voice recognition systems like Siri, which are trained mainly in English, but then use that training to help them recognize other languages,” says Li. “This is called transfer learning, and this is why IRIS can work across many different cell types.”

The researchers’ detailed open-access findings, published in the journal Nature Methods on Sept. 8, could accelerate stem cell engineering for regenerative medicine and improve the creation of organoids — miniature, 3D models that mimic real organs — for studying disease mechanisms and testing new drugs. This is because once researchers learn the pattern of signals that drives a stem cell to become a specific cell type, they can recreate those signals to control the fate of stem cells in a lab or medical setting.

IRIS is a neural network-based model, which, in essence, is an AI-driven system designed to recognize patterns in complex data, similar to how our brains spot patterns. It examines a cell’s overall gene activity and estimates which signaling pathways were likely “on” at specific times during development.

Li and Hutchins trained IRIS on a large experimental dataset that measured how thousands of human embryonic stem cells responded to dozens of combinations of six major signaling pathways at multiple stages of development. This created a comprehensive map, or atlas, of how signaling combinations influence cell behavior. 

The team then tested IRIS using single cells from mouse embryos during gastrulation, a stage when cells are rapidly branching into different fates. IRIS could accurately predict when and where specific signaling pathways would activate in cells destined to become part of heart, gut, muscle, and spinal cord tissue. This variation in signaling molecules is what guides cells to form the right structures in the right places.

With this approach, scientists can not only begin to understand the fundamentals of cell-to-cell communication, but also gain a practical roadmap for guiding stem cells into specific, functional cell types in the lab.

When the researchers employed IRIS to identify signals needed to create a cell type critical for lung development, the model predicted that activating a specific signaling pathway would encourage lung-specific development. Experiments in mouse embryos confirmed the model’s prediction. By identifying the precise combinations of signals that drive lung cell development, they can more reliably generate accurate, lab-grown models of lung tissue.

“In these ways, IRIS is helping us decode the language cells use to talk to each other at a much faster rate than we could realistically achieve through experiments,” Hutchins says.

These improved models would allow researchers to study diseases like asthma, lung cancer, and pulmonary fibrosis, in which lung tissue becomes scarred, often without a known cause. They can then use these models to test potential therapies, and ultimately design regenerative treatments that can repair the damaged tissue.

No one should have to choose between speaking freely and protecting their immigration status. Yet that’s precisely the choice the Trump administration’s mass surveillance of online speech forces on noncitizens living in the U.S.   

Last fall, we sued on behalf of three major labor unions to stop this surveillance program. And just this month, we won our first major ruling: A federal district court denied the government’s motion to dismiss our lawsuit. This means the case can move forward—a win for free speech and a critical step in protecting our First Amendment rights online. We’ve already explained why this is a big deal for our clients, so let's take a closer look at the court’s reasoning.  

Our Lawsuit 

 Since taking power, the Trump administration has used AI and other automated tools to broadly surveil the social media and online speech of visa and green card holders, with the goal of identifying and punishing people who express views it opposes. The government is targeting a broad range of views, including criticism of the Trump administration; support for Palestine or criticism of Israel; “rationalizing or making light of” Charlie Kirk’s murder; and anything nebulously “hostile” to American culture, founding principles, “traditional American views,” or “our way of life.”  

It has paired that surveillance with a public intimidation campaign. High-ranking officials have explicitly threatened to punish noncitizens for their online speech, then followed through with a series of terrifying viewpoint-driven enforcement actions. This has led to a significant chilling effect on speech, not just for noncitizens, but also for their families, coworkers, and friends. 

In response, three major labor unions—the United Auto Workers (UAW), the Communications Workers of America (CWA), and the American Federation of Teachers (AFT)—sued the Departments of State and Homeland Security alleging that this viewpoint-based surveillance program violates the First Amendment and the Administrative Procedure Act (APA).  The unions are represented by EFF, Muslim Advocates (MA), and the Media Freedom & Information Access Clinic (MFIA). 

The government moved to dismiss our lawsuit, arguing first that federal immigration law prevents federal district courts from hearing the case, and second, that the unions don’t have “standing” to sue. Judge Alvin K. Hellerstein of the Southern District of New York rejected both arguments and allowed the case to proceed. At this stage in the litigation, the court accepted all of the facts in our complaint as true and analyzed the law based on those facts. We will now prove these facts as the case proceeds. 

Federal Immigration Law Doesn’t Block Our Lawsuit 

 The government first argued that the court had no power to hear our case at all. It pointed to three provisions of the Immigration and Nationality Act (INA) that restrict when federal courts can review immigration matters. The district court disagreed and rejected each provision in turn. 

The first provision, 8 U.S.C. § 1252(b)(9), is often called the “zipper clause.” It bars federal courts from hearing challenges that arise from efforts to deport someone, except through review of an individual’s final removal order. The government claimed the zipper clause applies here because our lawsuit is really an effort to stop it from initiating adverse immigration actions. 

 The district court wholly rejected this argument. Relying on the Second Circuit’s decision in Ozturk v. Hyde, it held that the zipper clause bars only challenges to a particular individual’s removal proceedings, not a lawsuit like ours that challenges the constitutionality of the surveillance program itself. That the surveillance program might affect someone’s immigration proceeding down the line doesn’t turn our lawsuit into a removal challenge. 

 The court similarly rejected the government’s argument that § 1252(g) and § 1252(f)(1) prevent federal courts from hearing this case. Our suit, the court explained, “challenges the constitutionality of a government policy that is collateral to any active removal proceedings,” so § 1252(g) doesn’t apply. And § 1252(f)(1) only limits what kind of relief a court can give. So while the court may not be able to stop a particular person’s removal proceedings, it can still block “an unlawful surveillance program that suppresses free speech.” 

 The Unions Have Standing to Sue 

 To sue in federal court, a plaintiff must show that it has “standing” to bring its claims. This requires a plaintiff to show an “injury in fact” that is, among other things, “concrete.” That’s often a high bar in surveillance cases, where plaintiffs can’t easily see what the government is doing behind the scenes. And the Supreme Court has held that a person’s mere subjective fear of surveillance is too speculative to confer standing.  

Even so, our plaintiffs cleared the bar. The court held that the unions alleged concrete injuries, including a chill on members’ speech that is objectively reasonable, not just subjectively felt. It found that the unions had established standing in two ways: “organizational standing,” based on the unions’ own injuries, and “associational standing,” based on injuries the unions’ members have suffered. 

Organizational Standing 

The court first held that our plaintiffs had successfully alleged an injury to the unions themselves (injury was the only aspect of organizational standing the government disputed). The surveillance program has harmed the unions’ ability to carry out their core responsibilities, including “organizing their members and advocating for the unions’ goals.” The court made two key points: 

1. Unions Are Injured When Members Go Silent 

As we explained in our complaint, the surveillance program has caused members to step back from union leadership roles; stop participating in union activities online and in person; remove their names from union webpages; and avoid filling out bargaining surveys. Members who might otherwise spread the unions’ message and raise awareness of union issues are staying quiet, hampering the unions’ ability to organize. The court said this amounts to a concrete injury for purposes of standing. 

2. Surveillance Doesn’t Need to Target Pro-Union Speech  

 The court also rejected the government’s claim that members’ retreat from union activities was “essentially an overreaction,” because the surveillance doesn't target pro-union views. The court said this misunderstands the issue: “the question is whether the Government’s conduct would deter a person of ordinary firmness from engaging in protected activity, not whether the specific expression a member forgoes is itself among the viewpoints the Government disfavors.” 

Here, the surveillance program monitors noncitizens’ online activity indiscriminately, and members “cannot reliably predict which of their activities will be captured” and attributed to a disfavored viewpoint. What’s more, the court noted, the unions’ organizing often happens alongside the very advocacy the government is alleged to target, “including pro-Palestine and anti-ICE activism on college campuses.” That makes members’ retreat from union activity a foreseeable consequence of the program. 

Associational Standing  

 The court also held that the unions established associational standing to sue on behalf of their members. Of the three requirements for associational standing, the government challenged only two. It argued that members lacked sufficiently concrete injuries to sue in their own right, and that the claims aren’t “germane” to the unions’ purpose. 

The court disagreed and found associational standing for every claim but one: members’ right to receive information. That claim survives anyway, because the unions’ organizational standing covers it. Along the way, the court made several important rulings. 

 1. The Ongoing Surveillance Is a Present Injury 

 As a threshold matter, the government argued that our case is a “pre-enforcement challenge,” meaning we sued before the government actually punished anyone. That would trigger a different test, and the government argued we failed it because we hadn’t alleged a sufficiently imminent threat of prosecution. 

The court disagreed, explaining that “Plaintiffs’ allegations are of an ongoing surveillance program that is actively chilling the speech of their members and otherwise causing harm.” That chilling effect is a First Amendment injury even if there isn’t a direct prohibition on speech. And when government conduct is actively chilling speech right now, a challenge to it isn’t pre-enforcement. 

 2. Surveillance + Public Threats Reasonably Chills Speech 

 The court rejected the government’s argument that we alleged only a generalized, subjective, speculative fear of surveillance, explaining that “the chilling effect” of the program can “itself be an injury when the plaintiffs are surveilled.” Here, plaintiffs have alleged that their members are under active surveillance, which has had objective chilling effects on their speech. And the government is targeting certain disfavored viewpoints, making it “viewpoint discrimination” that is “presumptively unconstitutional.” 

The chill is also objectively reasonable, the court held, because the government has extensively publicized the surveillance program through public statements and social media posts, making clear that noncitizens who post disfavored views will be targeted for removal. Notably, the court agreed with us that the “threat of adverse immigration consequences, under a government whose harsh immigration crackdowns has been heavily publicized and reported on, is certainly enough to deter a person of ordinary firmness from the exercise of First Amendment rights.” This is a concrete injury sufficient for standing. 

3. Demanding Social Media Handles Also Causes Harm 

Under the surveillance program, applicants for certain immigration benefits must disclose all social media handles they have used during the preceding five years and, in some instances, maintain public social media accounts. The district court held that this too amounts to a First Amendment injury, undermining the rights to anonymity and freedom of association.  

The judge pointed to one CWA member we identified, a lawful permanent resident with a pending naturalization application who is subject to the five-year disclosure requirement. The member has deleted one social media account, set another to private, and removed past posts expressing disfavored views. These allegations, the court said, show an actual and objectively reasonable injury due to the government’s surveillance program.

4. General, Public Threats Can Still Be Coercive 

We also argued that the Trump administration is waging a campaign of coercive threats to suppress disfavored speech, which the First Amendment prohibits. The court agreed that this campaign can be an actionable injury of its own. 

Notably, the court held that it didn’t matter that the government’s statements were not specifically targeted at certain individuals, and were instead made on social media or to the public. In this case, the court explained, “the number, severity, and high-profile examples of action upon those threats are such that a reasonable person would perceive the communication as coercive.” 

That means it’s reasonable that the unions’ members “would, and did, limit their public speech on disfavored viewpoints” in response. That the threats were made to the general public “does not diminish this injury,” as the very purpose of the challenged surveillance program is to intimidate noncitizens into silence.  

5. Free Speech is Central to Union Functioning 

The court also found that the unions met the second prong of associational standing. It held that the unions’ interests in protecting their members’ rights to speak freely, organize, and advocate, are “germane” to the unions’ missions. The court put it plainly:

The freedom of Plaintiffs’ members to speak, associate, and appear publicly is not incidental to union work, but rather is the mechanism through which unions recruit, organize, communicate, and bargain. A program alleged to silence members and drive them from the unions’ rolls therefore strikes at the unions’ representational function itself.

Next Steps 

When the government surveils what people post online and threatens to punish them for their viewpoints, the result is exactly what our clients have experienced. Members have deleted their accounts, scrubbed posts, and withdrawn from union activities. 

The government must now answer our complaint and we will move forward with the discovery process, in which we anticipate getting more information from the government about its surveillance program. We look forward to continuing to prove our case. 

With rising temperatures, the buttressing ice shelves at the edges the Antarctic ice sheet are melting and calving off at record rates, leaving behind sheer cliffs of solid ice. The stability of these exposed ice cliffs could influence how Antarctica further breaks apart and contributes to sea level rise around the world. 

Scientists have assumed that an ice cliff’s stability depends on its height: Ice cliffs that are taller than 100 meters — about the height of the Statue of Liberty — should collapse under their own weight. And once a cliff sloughs off, it should expose even taller, inland cliffs that collapse in turn. At least, that’s been the idea.

But researchers at MIT and the Woods Hole Oceanographic Institution (WHOI) have found that the stability of an ice cliff depends on more than its height. And even when a cliff topples, it doesn’t necessarily set off a runaway collapse. 

In a study appearing today in Science, the team presents an analysis of over 15,000 ice cliffs in Antarctica that were monitored by satellites over a four-year period. They observed how the ice cliffs and the larger ice sheet evolved over time, and found that those ice cliffs that collapsed did so at a much faster rate than scientists had predicted. But these collapsing cliffs also quickly stabilized, instead of continuing to erode the larger ice sheet. 

“We found that when the cliffs were retreating, they were doing so faster than what has been modeled, which would mean more ice loss and higher contributions of sea level rise,” says study author Caroline Needell, a graduate student in the MIT-WHOI Joint Program. “But because we found that the retreat was short-lived, and all the glaciers eventually stabilized, that would suggest that things won’t be so bad. We don’t see this runaway effect.”

The study’s co-authors are Catherine Walker, assistant scientist at WHOI, and Jeremy Bassis, associate professor at the University of Michigan.

Ice height

In glacial science, ice cliff collapse is described by a process known as marine ice cliff instability (MICI), which assumes that if an ice cliff exceeds a critical height, it will collapse. If then a taller cliff is exposed, it too should collapse, triggering a cascade of instabilities that shrink and erode the ice sheet over time. 

In previous studies, scientists have characterized MICI mainly by modeling the physical properties of ice, scaling these relationships up to the size of an ice cliff and combining these predictions with a few observations of actual ice cliffs in Antarctica. Through these efforts, scientists had determined that ice cliffs become unstable and collapse when they are taller about 100 meters.  

“Predictive ice-sheet models that have been used so far to represent ice cliff instability just take into account cliff height,” Needell notes. “That’s the only variable that matters. And once the cliff height reaches the critical threshold, usually 100 meters, it should initiate this runaway effect of ice sheet retreat.”

But she and her colleagues wondered: How tall do ice cliffs really get? And when they collapse, do they really set off a runaway retreat? 

To answer these questions, they looked to data collected by NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) — a satellite that passes over the Earth’s polar regions and uses a laser altimeter to measure the height of ice sheets, glaciers, sea ice, and the level of the ocean in and around Antarctica. 

The team collected the satellite’s data from 2019 to 2023, which included measurements every three months of over 15,000 ice cliffs. From this dataset, they observed that the average ice cliff was about 30 meters tall — much shorter than the proposed critical height. But they did see a few rare ice cliffs that exceeded 100 meters. 

They also looked for other features that might influence a cliff’s stability. Interestingly, they found that ice cliffs that more or less stayed in place over time also had thicker mélange — a term for the slushy mix of broken icebergs and sea ice that gathers at the front of an ice cliff. 

“We measured mélange height and found taller cliffs have thicker mélange, which could be a built-in stabilizing effect,” Needell explains.

The satellite data also showed that the height of the surrounding water can stabilize a cliff: The deeper the water, the more it can buoy and push back against the cliff, keeping it from collapsing. 

Glacial speed bump

“After we did that global analysis, we thought, ok, let’s zoom in on the tallest cliffs and see how they’re behaving,” Needell says.

The team focused in on four regions around the Antarctic ice sheet where the satellite captured the tallest ice cliffs, each about 100 meters tall, with one that was 127 meters tall. They compiled measurements of these four cliffs and how they evolved every three months, over four years. 

From these measurements, they saw that indeed, the tallest cliffs collapsed, and the ice sheet in those regions retreated, at a surprisingly faster rate than MICI models had predicted. 

“But that retreat was short-lived,” Needell notes. 

After that, the ice spread back out toward the ocean.

“It’s this rapid retreat, punctuated by periods of stabilization,” Needell says. “That was puzzling to us. Then, we thought: We need to look at all the things that affect cliff height.”

The first thing they considered was the topography of the land underneath the ice. If that topography is relatively flat, then the slope of the overlying ice sheet reflects that actual height of the ice itself. But if there’s a bump or rise in the land, the ice sitting directly over that bump is in fact shorter than it appears. The topography then could act as a literal speed bump, thinning the overlying ice, and making it less likely to collapse. 

When the researchers checked topographic measurements of Antarctic, they found that indeed, ice cliffs stabilized around regions where the land happened to rise up. 

They also found that the taller a cliff is, the faster they “thin out” — as they collapse, once tall cliffs settle into shorter, more stable cliffs that prevents further collapse. 

“Now we know what to look for,” Needell says. “We really need to know the bed topography, and we need to know the ice thinning rate, in order to get ice cliff instability right, because this value really matters in the context of projecting sea level rise.” 

This research was supported, in part, by NASA, the U.S. National Science Foundation, and the DOMINOS project, a component of the International Thwaites Glacier Collaboration.

Matthew Green has a new site that tries to estimate the number of cryptanalyst-hours that have been spent analyzing different public-key algorithms:

Abstract: We estimate how much public cryptanalysis each public-key assumption has received, using the literature itself as the instrument. From roughly sixteen thousand candidate papers we classify cryptanalytic work on ECDLP, structured and plain lattices, syndrome decoding and their comparators, then convert papers into estimated research-allocation years through a person-level author map. These publication-based estimates may substantially overstate actual time spent. Lattices have overtaken elliptic curves in this cumulative measure only recently; we express that history as inference budgets under stated productivity assumptions. The study was conducted by AI models: Claude Fable 5.1 and Claude Opus 5.5 built the pipeline, ran the analysis and wrote this page, with contributions from GPT-6 Astra. Matthew Green set the questions, made the key methodological decisions and oversaw the work...