Back in the 17th century, German astronomer Johannes Kepler figured out the laws of motion that made it possible to accurately predict where our solar system’s planets would appear in the sky as they orbit the sun. But it wasn’t until decades later, when Isaac Newton formulated the universal laws of gravitation, that the underlying principles were understood. Although they were inspired by Kepler’s laws, they went much further, and made it possible to apply the same formulas to everything from the trajectory of a cannon ball to the way the moon’s pull controls the tides on Earth — or how to launch a satellite from Earth to the surface of the moon or planets.

Today’s sophisticated artificial intelligence systems have gotten very good at making the kind of specific predictions that resemble Kepler’s orbit predictions. But do they know why these predictions work, with the kind of deep understanding that comes from basic principles like Newton’s laws? As the world grows ever-more dependent on these kinds of AI systems, researchers are struggling to try to measure just how they do what they do, and how deep their understanding of the real world actually is.

Now, researchers in MIT’s Laboratory for Information and Decision Systems (LIDS) and at Harvard University have devised a new approach to assessing how deeply these predictive systems understand their subject matter, and whether they can apply knowledge from one domain to a slightly different one. And by and large the answer at this point, in the examples they studied, is — not so much.

The findings were presented at the International Conference on Machine Learning, in Vancouver, British Columbia, last month by Harvard postdoc Keyon Vafa, MIT graduate student in electrical engineering and computer science and LIDS affiliate Peter G. Chang, MIT assistant professor and LIDS principal investigator Ashesh Rambachan, and MIT professor, LIDS principal investigator, and senior author Sendhil Mullainathan.

“Humans all the time have been able to make this transition from good predictions to world models,” says Vafa, the study’s lead author. So the question their team was addressing was, “have foundation models — has AI — been able to make that leap from predictions to world models? And we’re not asking are they capable, or can they, or will they. It’s just, have they done it so far?” he says.

“We know how to test whether an algorithm predicts well. But what we need is a way to test for whether it has understood well,” says Mullainathan, the Peter de Florez Professor with dual appointments in the MIT departments of Economics and Electrical Engineering and Computer Science and the senior author on the study. “Even defining what understanding means was a challenge.” 

In the Kepler versus Newton analogy, Vafa says, “they both had models that worked really well on one task, and that worked essentially the same way on that task. What Newton offered was ideas that were able to generalize to new tasks.” That capability, when applied to the predictions made by various AI systems, would entail having it develop a world model so it can “transcend the task that you’re working on and be able to generalize to new kinds of problems and paradigms.”

Another analogy that helps to illustrate the point is the difference between centuries of accumulated knowledge of how to selectively breed crops and animals, versus Gregor Mendel’s insight into the underlying laws of genetic inheritance.

“There is a lot of excitement in the field about using foundation models to not just perform tasks, but to learn something about the world,” for example in the natural sciences, he says. “It would need to adapt, have a world model to adapt to any possible task.”

Are AI systems anywhere near the ability to reach such generalizations? To test the question, the team looked at different examples of predictive AI systems, at different levels of complexity. On the very simplest of examples, the systems succeeded in creating a realistic model of the simulated system, but as the examples got more complex that ability faded fast.

The team developed a new metric, a way of measuring quantitatively how well a system approximates real-world conditions. They call the measurement inductive bias — that is, a tendency or bias toward responses that reflect reality, based on inferences developed from looking at vast amounts of data on specific cases.

The simplest level of examples they looked at was known as a lattice model. In a one-dimensional lattice, something can move only along a line. Vafa compares it to a frog jumping between lily pads in a row. As the frog jumps or sits, it calls out what it’s doing — right, left, or stay. If it reaches the last lily pad in the row, it can only stay or go back. If someone, or an AI system, can just hear the calls, without knowing anything about the number of lily pads, can it figure out the configuration? The answer is yes: Predictive models do well at reconstructing the “world” in such a simple case. But even with lattices, as you increase the number of dimensions, the systems no longer can make that leap.

“For example, in a two-state or three-state lattice, we showed that the model does have a pretty good inductive bias toward the actual state,” says Chang. “But as we increase the number of states, then it starts to have a divergence from real-world models.”

A more complex problem is a system that can play the board game Othello, which involves players alternately placing black or white disks on a grid. The AI models can accurately predict what moves are allowable at a given point, but it turns out they do badly at inferring what the overall arrangement of pieces on the board is, including ones that are currently blocked from play.

The team then looked at five different categories of predictive models actually in use, and again, the more complex the systems involved, the more poorly the predictive modes performed at matching the true underlying world model.

With this new metric of inductive bias, “our hope is to provide a kind of test bed where you can evaluate different models, different training approaches, on problems where we know what the true world model is,” Vafa says. If it performs well on these cases where we already know the underlying reality, then we can have greater faith that its predictions may be useful even in cases “where we don’t really know what the truth is,” he says.

People are already trying to use these kinds of predictive AI systems to aid in scientific discovery, including such things as properties of chemical compounds that have never actually been created, or of potential pharmaceutical compounds, or for predicting the folding behavior and properties of unknown protein molecules. “For the more realistic problems,” Vafa says, “even for something like basic mechanics, we found that there seems to be a long way to go.”

Chang says, “There’s been a lot of hype around foundation models, where people are trying to build domain-specific foundation models — biology-based foundation models, physics-based foundation models, robotics foundation models, foundation models for other types of domains where people have been collecting a ton of data” and training these models to make predictions, “and then hoping that it acquires some knowledge of the domain itself, to be used for other downstream tasks.”

This work shows there’s a long way to go, but it also helps to show a path forward. “Our paper suggests that we can apply our metrics to evaluate how much the representation is learning, so that we can come up with better ways of training foundation models, or at least evaluate the models that we’re training currently,” Chang says. “As an engineering field, once we have a metric for something, people are really, really good at optimizing that metric.”

In welcoming the undergraduate Class of 2029 to campus in Cambridge, Massachusetts, MIT President Sally Kornbluth began the Institute’s convocation on Sunday with a greeting that underscored MIT’s confidence in its new students.

“We believe in all of you, in the learning, making, discovering, and inventing that you all have come here to do,” Kornbluth said. “And in your boundless potential as future leaders who will help solve real problems that people face in their daily lives.”

She added: “If you’re out there feeling really lucky to be joining this incredible community, I want you to know that we feel even more lucky. We’re delighted and grateful that you chose to bring your talent, your energy, your curiosity, creativity, and drive here to MIT. And we’re thrilled to be starting this new year with all of you.”

The event, officially called the President’s Convocation for First-years and Families, was held at the Johnson Ice Rink on campus.

While recognizing that academic life can be “intense” at MIT, Kornbluth highlighted the many opportunities available to students outside the classroom, too. A biologist and cancer researcher herself, Kornbluth observed that students can participate in the Undergraduate Research Opportunities Program (UROP), which Kornbluth called “an unmissable opportunity to work side by side with MIT faculty at the front lines of research.” She also noted that MIT offers abundant opportunities for entrepreneurship, as well as 450 official student organizations.

“It’s okay to be a beginner,” Kornbluth said. “Join a group you wouldn’t have had time for in high school. Explore a new skill. Volunteer in the neighborhoods around campus.”

And if the transition to college feels daunting at any point, she added, MIT provides considerable resources to students for well-being and academic help.

“Sometimes the only way to succeed in facing a big challenge or solving a tough problem is to admit there’s no way you can do it all yourself,” Kornbluth observed. “You’re surrounded by a community of caring people. So please don’t be shy about asking for guidance and help.”

The large audience heard additional remarks from two faculty members who themselves have MIT degrees, reflecting on student life at the Institute.

As a student, “The most important things I had were a willingness to take risks and put hard work into the things I cared about,” said Ankur Moitra SM ’09, PhD ’11, the Norbert Wiener Professor of Mathematics.

He emphasized to students the importance of staying grounded and being true to themselves, especially in the face of, say, social media pressures.

“These are the things that make it harder to find your own way and what you really care about,” Moitra said. “Because the rest of the world’s opinion is right there staring you in the face, and it’s impossible to avoid it. And how will you discover what’s important to you, what’s worth pouring yourself into?”

Moitra also advised students to be wary of the tech tools “that want to do the thinking for you, but take away your agency” in the process. He added: “I worry about this because it’s going to become too easy to rely on these tools, and there are going to be many times you’re going to be tempted, especially late at night, with looming p-set deadlines. As educators, we don’t always have fixes for these kinds of things, and all we can do is open the door and hope you walk through it.”

Beyond that, he suggested,“Periodically remind yourself about what’s been important to you all along, what brought you here. For your next four years, you’re going to be surrounded by creative, clever, passionate people every day, who are going to challenge you. Rise to that challenge.” 

Christopher Palmer PhD ’14, an associate professor of finance in the MIT Sloan School of Management, began his remarks by revealing that his MIT undergraduate application was not accepted — although he later received his doctorate at the Institute and is now a tenured professor at MIT.

“I played the long game,” he quipped, drawing laughs.

Indeed, Palmer’s remarks focused on cultivating the resilience, focus, and concentration needed to flourish in the long run.

While being at MIT is “thrilling,” Palmer advised students to “build enough slack into your system to handle both the stress and take advantage of the opportunities” on campus. Much like a bank conducts a “stress test” to see if it can withstand changes, Palmer suggested, we can try the same with our workloads: “If you build a schedule that passes the stress test, that means time for curiosity and meaningful creativity.”

Students should also avoid the “false equivalency that your worth is determined by your achievements,” he added. “You have inherent, immutable, instrinsic, eternal value. Be discerning with your commitments. Future you will be so grateful that you have built in the capacity to sleep, to catch up, to say ‘Yes’ to cool invitations, and to attend to your mental health.”

Additionally, Palmer recommended that students pursue “deep work,” involving “the hard thinking where progress actually happens” — a concept, he noted, that has been elevated by computer scientist Cal Newport SM ’06, PhD ’09. As research shows, Palmer explained, “We can’t actually multitask. What we’re really doing is switching tasks at high frequency and incurring a small cost every single time we switch our focus.”

It might help students, he added, to try some structural changes: Put the phone away, turn off alerts, pause notifications, and cultivate sleep. A healthy blend of academic work, activities, and community fun can emerge.

Concluding her own remarks, Kornbluth also emphasized that attending MIT means being part of a community that is respectful of varying viewpoints and all people, and sustains an ethos of fair-minded understanding.

“I know you have extremely high expectations for yourselves,” Kornbluth said, adding: “We have high expectations for you, too, in all kinds of ways. But I want to emphasize one that’s more important than all the others — and that’s an expectation for how we treat each other. At MIT, the work we do is so important, and so hard, that it’s essential we treat each other with empathy, understanding and compassion. That we take care to express our own ideas with clarity and respect, and make room for sharply different points of view. And above all, that we keep engaging in conversation, even when it’s difficult, frustrating or painful.”

Look at this: McDonald’s chose the password “123456” for a major corporate system.

Nature Climate Change, Published online: 25 August 2025; doi:10.1038/s41558-025-02395-x

Many of us have experienced heatwaves and survived unscathed — or so we thought. Research now shows that exposure to heatwaves affects the rate at which we age.

Nature Climate Change, Published online: 25 August 2025; doi:10.1038/s41558-025-02407-w

Ageing is linked to environmental factors. This study shows that although participants gradually adapted to heat over time, cumulative exposure to heatwaves had stable and adverse impacts on ageing, especially among manual workers, rural residents and those with limited air conditioning.

Revolution Wind off Rhode Island is about 80 percent completed.

Nice short article on the bobtail squid.

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.

This academic year, I am taking a sabbatical from the Kennedy School and Harvard University. (It’s not a real sabbatical—I’m just an adjunct—but it’s the same idea.) I will be spending the Fall 2025 and Spring 2026 semesters at the Munk School at the University of Toronto.

I will be organizing a reading group on AI security in the fall. I will be teaching my cybersecurity policy class in the Spring. I will be working with Citizen Lab, the Law School, and the Schwartz Reisman Institute. And I will be enjoying all the multicultural offerings of Toronto...

EFF legal intern Noam Shemtov was the principal author of this post.

When police have a warrant to search a phone, should they be able to see everything on the phone—from family photos to communications with your doctor to everywhere you’ve been since you first started using the phone—in other words, data that is in no way connected to the crime they’re investigating? The Michigan Supreme Court just ruled no. 

In People v. Carson, the court held that to satisfy the Fourth Amendment, warrants authorizing searches of cell phones and other digital devices must contain express limitations on the data police can review, restricting searches to data that they can establish is clearly connected to the crime.

The realities of modern cell phones call for a strict application of rules governing the scope of warrants.

EFF, along with ACLU National and the ACLU of Michigan, filed an amicus brief in Carson, expressly calling on the court to limit the scope of cell phone search warrants. We explained that the realities of modern cell phones call for a strict application of rules governing the scope of warrants. Without clear limits, warrants would  become de facto licenses to look at everything on the device, a great universe of information that amounts to “the sum of an individual’s private life.” 

The Carson case shows just how broad many cell phone search warrants can be. Defendant Michael Carson was suspected of stealing money from a neighbor’s safe. The warrant to search his phone allowed the police to access:

Any and all data including, text messages, text/picture messages, pictures and videos, address book, any data on the SIM card if applicable, and all records or documents which were created, modified, or stored in electronic or magnetic form and, any data, image, or information.

There were no temporal or subject matter limitations. Consequently, investigators obtained over 1,000 pages of information from Mr. Carson’s phone, the vast majority of which did not have anything to do with the crime under investigation.

The Michigan Supreme Court held that this extremely broad search warrant was “constitutionally intolerable” and violated the particularity requirement of the Fourth Amendment. 

The Fourth Amendment requires that warrants “particularly describ[e] the place to be searched, and the persons or things to be seized.” This is intended to limit authorization to search to the specific areas and things for which there is probable cause to search and to prevent police from conducting “wide-ranging exploratory searches.” 

Cell phones hold vast and varied information, including our most intimate data.

Across two opinions, a four-Justice majority joined a growing national consensus of courts recognizing that, given the immense and ever-growing storage capacity of cell phones, warrants must spell out up-front limitations on the information the government may review, including the dates and data categories that constrain investigators’ authority to search. And magistrates reviewing warrants must ensure the information provided by police in the warrant affidavit properly supports a tailored search.

This ruling is good news for digital privacy. Cell phones hold vast and varied information, including our most intimate data—“privacies of life” like our personal messages, location histories, and medical and financial information. The U.S. Supreme Court has recognized as much, saying that application of Fourth Amendment principles to searches of cell phones must respond to cell phones’ unique characteristics, including the weighty privacy interests in our digital data. 

We applaud the Michigan Supreme Court’s recognition that unfettered cell phone searches pose serious risks to privacy. We hope that courts around the country will follow its lead in concluding that the particularity rule applies with special force to such searches and requires clear limitations on the data the government may access.

The MIT Sailing Pavilion hosted an altogether different marine vessel recently: a prototype of a solar electric boat developed by James Worden ’89, the founder of the MIT Solar Electric Vehicle Team (SEVT). Worden visited the pavilion on a sizzling, sunny day in late July to offer students from the SEVT, the MIT Edgerton Center, MIT Sea Grant, and the broader community an inside look at the Anita, named for his late wife.

Worden’s fascination with solar power began at age 10, when he picked up a solar chip at a “hippy-like” conference in his hometown of Arlington, Massachusetts. “My eyes just lit up,” he says. He built his first solar electric vehicle in high school, fashioned out of cardboard and wood (taking first place at the 1984 Massachusetts Science Fair), and continued his journey at MIT, founding SEVT in 1986. It was through SEVT that he met his wife and lifelong business partner, Anita Rajan Worden ’90. Together, they founded two companies in the solar electric and hybrid vehicles space, and in 2022 launched a solar electric boat company.

On the Charles River, Worden took visitors for short rides on Anita, including a group of current SEVT students who peppered him with questions. The 20-foot pontoon boat, just 12 feet wide and 7 feet tall, is made of carbon fiber composites, single crystalline solar photovoltaic cells, and lithium iron phosphate battery cells. Ultimately, Worden envisions the prototype could have applications as mini-ferry boats and water taxis.

With warmth and humor, he drew parallels between the boat’s components and mechanics and those of the solar cars the students are building. “It’s fun! If you think about all the stuff you guys are doing, it’s all the same stuff,” he told them, “optimizing all the different systems and making them work.” He also explained the design considerations unique to boating applications, like refining the hull shape for efficiency and maneuverability in variable water and wind conditions, and the critical importance of protecting wiring and controls from open water and condensate.

“Seeing Anita in all its glory was super cool,” says Nicole Lin, vice captain of SEVT. “When I first saw it, I could immediately map the different parts of the solar car to its marine counterparts, which was astonishing to see how far I’ve come as an engineer with SEVT. James also explained the boat using solar car terms, as he drew on his experience with solar cars for his solar boats. It blew my mind to see the engineering we learned with SEVT in action.”

Over the years, the Wordens have been avid supporters of SEVT and the Edgerton Center, so the visit was, in part, a way to pay it forward to MIT. “There’s a lot of connections,” he says. He’s still awed by the fact that Harold “Doc” Edgerton, upon learning about his interest in building solar cars, carved out a lab space for him to use in Building 20 — as a first-year student. And a few years ago, as Worden became interested in marine vessels, he tapped Sea Grant Education Administrator Drew Bennett for a 90-minute whiteboard lecture, “MIT fire-hose style,” on hydrodynamics. “It was awesome!” he says.

For both research and medical purposes, researchers have spent decades pushing the limits of microscopy to produce ever deeper and sharper images of brain activity, not only in the cortex but also in regions underneath, such as the hippocampus. In a new study, a team of MIT scientists and engineers demonstrates a new microscope system capable of peering exceptionally deep into brain tissues to detect the molecular activity of individual cells by using sound.

“The major advance here is to enable us to image deeper at single-cell resolution,” says neuroscientist Mriganka Sur, a corresponding author along with mechanical engineering professor Peter So and principal research scientist Brian Anthony. Sur is the Paul and Lilah Newton Professor in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences at MIT.

In the journal Light: Science and Applications, the team demonstrates that they could detect NAD(P)H, a molecule tightly associated with cell metabolism in general and electrical activity in neurons in particular, all the way through samples such as a 1.1-millimeter “cerebral organoid,” a 3D-mini brain-like tissue generated from human stem cells, and a 0.7-milimeter-thick slice of mouse brain tissue.

In fact, says co-lead author and mechanical engineering postdoc W. David Lee, who conceived the microscope’s innovative design, the system could have peered far deeper, but the test samples weren’t big enough to demonstrate that.

“That’s when we hit the glass on the other side,” he says. “I think we’re pretty confident about going deeper.”

Still, a depth of 1.1 milimeters is more than five times deeper than other microscope technologies can resolve NAD(P)H within dense brain tissue. The new system achieved the depth and sharpness by combining several advanced technologies to precisely and efficiently excite the molecule and then to detect the resulting energy, all without having to add any external labels, either via added chemicals or genetically engineered fluorescence.

Rather than focusing the required NAD(P)H excitation energy on a neuron with near ultraviolet light at its normal peak absorption, the scope accomplishes the excitation by focusing an intense, extremely short burst of light (a quadrillionth of a second long) at three times the normal absorption wavelength. Such “three-photon” excitation penetrates deep into tissue with less scattering by brain tissue because of the longer wavelength of the light (“like fog lamps,” Sur says). Meanwhile, although the excitation produces a weak fluorescent signal of light from NAD(P)H, most of the absorbed energy produces a localized (about 10 microns) thermal expansion within the cell, which produces sound waves that travel relatively easily through tissue compared to the fluorescence emission. A sensitive ultrasound microphone in the microscope detects those waves and, with enough sound data, software turns them into high-resolution images (much like a sonogram does). Imaging created in this way is “three-photon photoacoustic imaging.”

“We merged all these techniques — three-photon, label-free, photoacoustic detection,” says co-lead author Tatsuya Osaki, a research scientist in the Picower Institute in Sur’s lab. “We integrated all these cutting-edge techniques into one process to establish this ‘Multiphoton-In and Acoustic-Out’ platform.”

Lee and Osaki combined with research scientist Xiang Zhang and postdoc Rebecca Zubajlo to lead the study, in which the team demonstrated reliable detection of the sound signal through the samples. So far, the team has produced visual images from the sound at various depths as they refine their signal processing.

In the study, the team also shows simultaneous “third-harmonic generation” imaging, which comes from the three-photon stimulation and finely renders cellular structures, alongside their photoacoustic imaging, which detects NAD(P)H. They also note that their photoacoustic method could detect other molecules such as the genetically encoded calcium indicator GCaMP, that neuroscientists use to signal neural electrical activity.

With the concept of label-free, multiphoton, photoacoustic microscopy (LF-MP-PAM) established in the paper, the team is now looking ahead to neuroscience and clinical applications.

For instance, through the company Precision Healing, Inc., which he founded and sold, Lee has already established that NAD(P)H imaging can inform wound care. In the brain, levels of the molecule are known to vary in conditions such as Alzheimer’s disease, Rett syndrome, and seizures, making it a potentially valuable biomarker. Because the new system is label-free (i.e., no added chemicals or altered genes), it could be used in humans, for instance, during brain surgeries.

The next step for the team is to demonstrate it in a living animal, rather than just in in vitro and ex-vivo tissues. The technical challenge there is that the microphone can no longer be on the opposite side of the sample from the light source (as it was in the current study). It has to be on top, just like the light source.

Lee says he expects that full imaging at depths of 2 milimeters in live brains is entirely feasible, given the results in the new study.

“In principle, it should work,” he says.

Mercedes Balcells and Elazer Edelman are also authors of the paper. Funding for the research came from sources including the National Institutes of Health, the Simon Center for the Social Brain, the lab of Peter So, The Picower Institute for Learning and Memory, and the Freedom Together Foundation.

Think of the Web as a digital territory with its own social contract. In 2014, Tim Berners-Lee called for a “Magna Carta for the Web” to restore the balance of power between individuals and institutions. This mirrors the original charter’s purpose: ensuring that those who occupy a territory have a meaningful stake in its governance.

Web 3.0—the distributed, decentralized Web of tomorrow—is finally poised to change the Internet’s dynamic by returning ownership to data creators. This will change many things about what’s often described as the “CIA triad” of ...

The Ballard Health CEO vowed to rebuild after Hurricane Helene. But President Trump’s One Big Beautiful Bill could stop that.

A team of researchers hopes to provide the long-elusive answer, thanks to the growing field of attribution science.

The research is drawing skepticism. "There's a bazillion other reasons" people don't buy flood insurance, one expert said.

The state's response to July 4 flooding has focused on training requirements for local officials and tighter regulations for summer camps.

The Commerce Department said it will examine demand for turbines and what equipment domestic manufacturers can provide.

Connie Hedegaard says Europe can’t afford to go soft on climate while China races ahead and companies like BP backtrack.

“The central bank should develop climate-informed interest-rate policies that proactively address expected and unexpected climate shocks,” says a study published by the South African Reserve Bank.

The ECB’s plan to apply climate-risk penalties to corporate bonds used as collateral in transactions "lacks ambition," argues one nonprofit.