Production is at record levels but that might change.

The units can provide heating and cooling for apartments of about 500 square feet.

Organizers aim to reach “the heart, the mind and the hands” by completing the journey without burning fossil fuels.

The country experiences 10-13 tropical cyclones a year, but the frequency of intense, back-to-back typhoons is increasing.

It’s unclear whether the food giant's exit will shake the resolve of the Dairy Methane Action Alliance's other members.

Understanding how interactions between the central nervous system and the immune system contribute to problems of aging, including Alzheimer’s disease, Parkinson’s disease, arthritis, and more, can generate new leads for therapeutic development, speakers said at MIT’s symposium “The Neuro-Immune Axis and the Aging Brain” on Sept 18.

“The past decade has brought rapid progress in our understanding of how adaptive and innate immune systems impact the pathogenesis of neurodegenerative disorders,” said Picower Professor Li-Huei Tsai, director of The Picower Institute for Learning and Memory and MIT’s Aging Brain Initiative (ABI), in her introduction to the event, which more than 450 people registered to attend. “Together, today’s speakers will trace how the neuro-immune axis shapes brain health and disease … Their work converges on the promise of immunology-informed therapies to slow or prevent neurodegeneration and age-related cognitive decline.”

For instance, keynote speaker Michal Schwartz of the Weizmann Institute in Israel described her decades of pioneering work to understand the neuro-immune “ecosystem.” Immune cells, she said, help the brain heal, and support many of its functions, including its “plasticity,” the ability it has to adapt to and incorporate new information. But Schwartz’s lab also found that an immune signaling cascade can arise with aging that undermines cognitive function. She has leveraged that insight to investigate and develop corrective immunotherapies that improve the brain’s immune response to Alzheimer’s both by rejuvenating the brain’s microglia immune cells and bringing in the help of peripheral immune cells called macrophages. Schwartz has brought the potential therapy to market as the chief science officer of ImmunoBrain, a company testing it in a clinical trial.

In her presentation, Tsai noted recent work from her lab and that of computer science professor and fellow ABI member Manolis Kellis showing that many of the genes associated with Alzheimer’s disease are most strongly expressed in microglia, giving it an expression profile more similar to autoimmune disorders than to many psychiatric ones (where expression of disease-associated genes typically is highest in neurons). The study showed that microglia become “exhausted” over the course of disease progression, losing their cellular identity and becoming harmfully inflammatory.

“Genetic risk, epigenomic instability, and microglia exhaustion really play a central role in Alzheimer’s disease,” Tsai said, adding that her lab is now also looking into how immune T cells, recruited by microglia, may also contribute to Alzheimer’s disease progression.

The body and the brain

The neuro-immune “axis” connects not only the nervous and immune systems, but also extends between the whole body and the brain, with numerous implications for aging. Several speakers focused on the key conduit: the vagus nerve, which runs from the brain to the body’s major organs.

For instance, Sara Prescott, an investigator in the Picower Institute and an MIT assistant professor of biology, presented evidence her lab is amassing that the brain’s communication via vagus nerve terminals in the body’s airways is crucial for managing the body’s defense of respiratory tissues. Given that we inhale about 20,000 times a day, our airways are exposed to many environmental challenges, Prescott noted, and her lab and others are finding that the nervous system interacts directly with immune pathways to mount physiological responses. But vagal reflexes decline in aging, she noted, increasing susceptibility to infection, and so her lab is now working in mouse models to study airway-to-brain neurons throughout the lifespan to better understand how they change with aging.

In his talk, Caltech Professor Sarkis Mazmanian focused on work in his lab linking the gut microbiome to Parkinson’s disease (PD), for instance by promoting alpha-synuclein protein pathology and motor problems in mouse models. His lab hypothesizes that the microbiome can nucleate alpha-synuclein in the gut via a bacterial amyloid protein that may subsequently promote pathology in the brain, potentially via the vagus nerve. Based on its studies, the lab has developed two interventions. One is giving alpha-synuclein overexpressing mice a high-fiber diet to increase short-chain fatty acids in their gut, which actually modulates the activity of microglia in the brain. The high-fiber diet helps relieve motor dysfunction, corrects microglia activity, and reduces protein pathology, he showed. Another is a drug to disrupt the bacterial amyloid in the gut. It prevents alpha synuclein formation in the mouse brain and ameliorates PD-like symptoms. These results are pending publication.

Meanwhile, Kevin Tracey, professor at Hofstra University and Northwell Health, took listeners on a journey up and down the vagus nerve to the spleen, describing how impulses in the nerve regulate immune system emissions of signaling molecules, or “cytokines.” Too great a surge can become harmful, for instance causing the autoimmune disorder rheumatoid arthritis. Tracey described how a newly U.S. Food and Drug Administration-approved pill-sized neck implant to stimulate the vagus nerve helps patients with severe forms of the disease without suppressing their immune system.

The brain’s border

Other speakers discussed opportunities for understanding neuro-immune interactions in aging and disease at the “borders” where the brain’s and body’s immune system meet. These areas include the meninges that surround the brain, the choroid plexus (proximate to the ventricles, or open spaces, within the brain), and the interface between brain cells and the circulatory system.

For instance, taking a cue from studies showing that circadian disruptions are a risk factor for Alzheimer’s disease, Harvard Medical School Professor Beth Stevens of Boston Children’s Hospital described new research in her lab that examined how brain immune cells may function differently around the day-night cycle. The project, led by newly minted PhD Helena Barr, found that “border-associated macrophages” — long-lived immune cells residing in the brain’s borders — exhibited circadian rhythms in gene expression and function. Stevens described how these cells are tuned by the circadian clock to “eat” more during the rest phase, a process that may help remove material draining from the brain, including Alzheimer’s disease-associated peptides such as amyloid-beta. So, Stevens hypothesizes, circadian disruptions, for example due to aging or night-shift work, may contribute to disease onset by disrupting the delicate balance in immune-mediated “clean-up” of the brain and its borders.

Following Stevens at the podium, Washington University Professor Marco Colonna traced how various kinds of macrophages, including border macrophages and microglia, develop from the embryonic stage. He described the different gene-expression programs that guide their differentiation into one type or another. One gene he highlighted, for instance, is necessary for border macrophages along the brain’s vasculature to help regulate the waste-clearing cerebrospinal fluid (CSF) flow that Stevens also discussed. Knocking out the gene also impairs blood flow. Importantly, his lab has found that versions of the gene may be somewhat protective against Alzheimer’s, and that regulating expression of the gene could be a therapeutic strategy.

Colonna’s WashU colleague Jonathan Kipnis (a former student of Schwartz) also discussed macrophages that are associated with the particular border between brain tissue and the plumbing alongside the vasculature that carries CSF. The macrophages, his lab showed in 2022, actively govern the flow of CSF. He showed that removing the macrophages let Alzheimer’s proteins accumulate in mice. His lab is continuing to investigate ways in which these specific border macrophages may play roles in disease. He’s also looking in separate studies of how the skull’s brain marrow contributes to the population of immune cells in the brain and may play a role in neurodegeneration.

For all the talk of distant organs and the brain’s borders, neurons themselves were never far from the discussion. Harvard Medical School Professor Isaac Chiu gave them their direct due in a talk focusing on how they participate in their own immune defense, for instance by directly sensing pathogens and giving off inflammation signals upon cell death. He discussed a key molecule in that latter process, which is expressed among neurons all over the brain.

Whether they were looking within the brain, at its border, or throughout the body, speakers showed that age-related nervous system diseases are not only better understood but also possibly better treated by accounting not only for the nerve cells, but their immune system partners. 

In a joint letter to the ranking members of the House and Senate intelligence committees, EFF has joined with 20 other organizations, including the ACLU, Brennan Center, CDT, Asian Americans Advancing Justice, and Demand Progress, to express opposition to a rule change that would seriously weaken accountability in the intelligence community. Specifically, under the proposed Senate Intelligence Authorization Act, S. 2342, the general counsels of the Central Intelligence Agency (CIA) and the Office of the Director of National Intelligence (ODNI) would no longer be subject to Senate confirmation.

You can read the entire letter here. 

In theory, having the most important legal thinkers at these secretive agencies—the ones who presumably tell an agency if something is legal or not—approved or rejected by the Senate allows elected officials the chance to vet candidates and their beliefs. If, for instance, a confirmation hearing had uncovered that a proposed general counsel for the CIA thinks it's not only legal, but morally justifiable for the agency to spy on US persons on US soil because of their political or religious beliefs–then the Senate would have the chance to reject that person. 

As the letter says, “The general counsels of the CIA and ODNI wield extraordinary influence, and they do so entirely in secret, shaping policies on surveillance, detention, interrogation, and other highly consequential national security matters. Moreover, they are the ones primarily responsible for determining the boundaries of what these agencies may lawfully do. The scope of this power and the fact that it occurs outside of public view is why Senate confirmation is so important.” 

It is for this reason that EFF and our ally organizations urge Congress to remove this provision from the Senate Intelligence Authorization Act.

The MIT Schwarzman College of Computing and the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) recently celebrated the launch of the MIT–MBZUAI Collaborative Research Program, a new effort to strengthen the building blocks of artificial intelligence and accelerate its use in pressing scientific and societal challenges.

Under the five-year agreement, faculty, students, and research staff from both institutions will collaborate on fundamental research projects to advance the technological foundations of AI and its applications in three core areas: scientific discovery, human thriving, and the health of the planet.

“Artificial intelligence is transforming nearly every aspect of human endeavor. MIT’s leadership in AI is greatly enriched through collaborations with leading academic institutions in the U.S. and around the world,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “Our collaboration with MBZUAI reflects a shared commitment to advancing AI in ways that are responsible, inclusive, and globally impactful. Together, we can explore new horizons in AI and bring broad benefits to society.”

“This agreement will unite the efforts of researchers at two world-class institutions to advance frontier AI research across scientific discovery, human thriving, and the health of the planet. By combining MBZUAI’s focus on foundational models and real-world deployment with MIT’s depth in computing and interdisciplinary innovation, we are creating a transcontinental bridge for discovery. Together, we will not only expand the boundaries of AI science, but also ensure that these breakthroughs are pursued responsibly and applied where they matter most — improving human health, enabling intelligent robotics, and driving sustainable AI at scale,” says Eric Xing, president and university professor at MBZUAI.

Each institution has appointed an academic director to oversee the program on its campus. At MIT, Philip Isola, the Class of 1948 Career Development Professor in the Department of Electrical Engineering and Computer Science, will serve as program lead. At MBZUAI, Le Song, professor of machine learning, will take on the role.

Supported by MBZUAI — the first university dedicated entirely to advancing science through AI, and based in Abu Dhabi, U.A.E. — the collaboration will fund a number of joint research projects per year. The findings will be openly publishable, and each project will be led by a principal investigator from MIT and one from MBZUAI, with project selections made by a steering committee composed of representatives from both institutions.

MIT associate professor of physics Riccardo Comin has been selected as 2025 Experimental Physics Investigator by the Gordon and Betty Moore Foundation. Two MIT physics alumni — Gyu-Boong Jo PhD ’10 of Rice University, and Ben Jones PhD ’15 of the University of Texas at Arlington — were also among this year’s cohort of 22 honorees.

The prestigious Experimental Physics Investigators (EPI) Initiative recognizes mid-career scientists advancing the frontiers of experimental physics. Each award provides $1.3 million over five years to accelerate breakthroughs and strengthen the experimental physics community.

At MIT, Comin investigates magnetoelectric multiferroics by engineering interfaces between two-dimensional materials and three-dimensional oxide thin films. His research aims to overcome long-standing limitations in spin-charge coupling by moving beyond epitaxial constraints, enabling new interfacial phases and coupling mechanisms. In these systems, Comin’s team explores the coexistence and proximity of magnetic and ferroelectric order, with a focus on achieving strong magnetoelectric coupling. This approach opens new pathways for designing tunable multiferroic systems unconstrained by traditional synthesis methods.

Comin’s research expands the frontier of multiferroics by demonstrating stacking-controlled magnetoelectric coupling at 2D–3D interfaces. This approach enables exploration of fundamental physics in a versatile materials platform and opens new possibilities for spintronics, sensing, and data storage. By removing constraints of epitaxial growth, Comin’s work lays the foundation for microelectronic and spintronic devices with novel functionalities driven by interfacial control of spin and polarization.

Comin’s project, Interfacial MAGnetoElectrics (I-MAGinE), aims to study a new class of artificial magnetoelectric multiferroics at the interfaces between ferroic materials from 2D van der Waals systems and 3D oxide thin films. The team aims to identify and understand novel magnetoelectric effects to demonstrate the viability of stacking-controlled interfacial magnetoelectric coupling. This research could lead to significant contributions in multiferroics, and could pave the way for innovative, energy-efficient storage devices.

“This research has the potential to make significant contributions to the field of multiferroics by demonstrating the viability of stacking-controlled interfacial magnetoelectric coupling,” according to Comin’s proposal. “The findings could pave the way for future applications in spintronics, data storage, and sensing. It offers a significant opportunity to explore fundamental physics questions in a novel materials platform, while laying the ground for future technological applications, including microelectronic and spintronic devices with new functionalities.”

Comin’s group has extensive experience in researching 2D and 3D ferroic materials and electronically ordered oxide thin films, as well as ultrathin van der Waals magnets, ferroelectrics, and multiferroics. Their lab is equipped with state-of-the-art tools for material synthesis, including bulk crystal growth of van der Waals materials and pulsed laser deposition targets, along with comprehensive fabrication and characterization capabilities. Their expertise in magneto-optical probes and advanced magnetic X-ray techniques promises to enable in-depth studies of electronic and magnetic structures, specifically spin-charge coupling, in order to contribute significantly to understanding spin-charge coupling in magnetochiral materials.

The coexistence of ferroelectricity and ferromagnetism in a single material, known as multiferroicity, is rare, and strong spin-charge coupling is even rarer due to fundamental chemical and electronic structure incompatibilities.

The few known bulk multiferroics with strong magnetoelectric coupling generally rely on inversion symmetry-breaking spin arrangements, which only emerge at low temperatures, limiting practical applications. While interfacial magnetoelectric multiferroics offer an alternative, achieving efficient spin-charge coupling often requires stringent conditions like epitaxial growth and lattice matching, which limit material combinations. This research proposes to overcome these limitations by using non-epitaxial interfaces of 2D van der Waals materials and 3D oxide thin films.

Unique features of this approach include leveraging the versatility of 2D ferroics for seamless transfer onto any substrate, eliminating lattice matching requirements, and exploring new classes of interfacial magnetoelectric effects unconstrained by traditional thin-film synthesis limitations.

Launched in 2018, the Moore Foundation’s EPI Initiative cultivates collaborative research environments and provides research support to promote the discovery of new ideas and emphasize community building.

“We have seen numerous new connections form and new research directions pursued by both individuals and groups based on conversations at these gatherings,” says Catherine Mader, program officer for the initiative.

The Gordon and Betty Moore Foundation was established to create positive outcomes for future generations. In pursuit of that vision, it advances scientific discovery, environmental conservation, and the special character of the San Francisco Bay Area.

Ammonia is one of the most widely produced chemicals in the world, used mostly as fertilizer, but also for the production of some plastics, textiles, and other applications. Its production, through processes that require high heat and pressure, accounts for up to 20 percent of all the greenhouse gases from the entire chemical industry, so efforts have been underway worldwide to find ways to reduce those emissions.

Now, researchers at MIT have come up with a clever way of combining two different methods of producing the compound that minimizes waste products, that, when combined with some other simple upgrades, could reduce the greenhouse emissions from production by as much as 63 percent, compared to the leading “low-emissions” approach being used today.

The new approach is described in the journal Energy & Fuels, in a paper by MIT Energy Initiative (MITEI) Director William H. Green, graduate student Sayandeep Biswas, MITEI Director of Research Randall Field, and two others.

“Ammonia has the most carbon dioxide emissions of any kind of chemical,” says Green, who is the Hoyt C. Hottel Professor in Chemical Engineering. “It’s a very important chemical,” he says, because its use as a fertilizer is crucial to being able to feed the world’s population.

Until late in the 19th century, the most widely used source of nitrogen fertilizer was mined deposits of bat or bird guano, mostly from Chile, but that source was beginning to run out, and there were predictions that the world would soon be running short of food to sustain the population. But then a new chemical process, called the Haber-Bosch process after its inventors, made it possible to make ammonia out of nitrogen from the air and hydrogen, which was mostly derived from methane. But both the burning of fossil fuels to provide the needed heat and the use of methane to make the hydrogen led to massive climate-warming emissions from the process.

To address this, two newer variations of ammonia production have been developed: so-called “blue ammonia,” where the greenhouse gases are captured right at the factory and then sequestered deep underground, and “green ammonia,” produced by a different chemical pathway, using electricity instead of fossil fuels to hydrolyze water to make hydrogen.

Blue ammonia is already beginning to be used, with a few plants operating now in Louisiana, Green says, and the ammonia mostly being shipped to Japan, “so that’s already kind of commercial.” Other parts of the world are starting to use green ammonia, especially in places that have lots of hydropower, solar, or wind to provide inexpensive electricity, including a giant plant now under construction in Saudi Arabia.

But in most places, both blue and green ammonia are still more expensive than the traditional fossil-fuel-based version, so many teams around the world have been working on ways to cut these costs as much as possible so that the difference is small enough to be made up through tax subsidies or other incentives.

The problem is growing, because as the population grows, and as wealth increases, there will be ever-increasing demands for nitrogen fertilizer. At the same time, ammonia is a promising substitute fuel to power hard-to-decarbonize transportation such as cargo ships and heavy trucks, which could lead to even greater needs for the chemical.

“It definitely works” as a transportation fuel, by powering fuel cells that have been demonstrated for use by everything from drones to barges and tugboats and trucks, Green says. “People think that the most likely market of that type would be for shipping,” he says, “because the downside of ammonia is it’s toxic and it’s smelly, and that makes it slightly dangerous to handle and to ship around.” So its best uses may be where it’s used in high volume and in relatively remote locations, like the high seas. In fact, the International Maritime Organization will soon be voting on new rules that might give a strong boost to the ammonia alternative for shipping.

The key to the new proposed system is to combine the two existing approaches in one facility, with a blue ammonia factory next to a green ammonia factory. The process of generating hydrogen for the green ammonia plant leaves a lot of leftover oxygen that just gets vented to the air. Blue ammonia, on the other hand, uses a process called autothermal reforming that requires a source of pure oxygen, so if there’s a green ammonia plant next door, it can use that excess oxygen.

“Putting them next to each other turns out to have significant economic value,” Green says. This synergy could help hybrid “blue-green ammonia” facilities serve as an important bridge toward a future where eventually green ammonia, the cleanest version, could finally dominate. But that future is likely decades away, Green says, so having the combined plants could be an important step along the way.

“It might be a really long time before [green ammonia] is actually attractive” economically, he says. “Right now, it’s nowhere close, except in very special situations.” But the combined plants “could be a really appealing concept, and maybe a good way to start the industry,” because so far only small, standalone demonstration plants of the green process are being built.

“If green or blue ammonia is going to become the new way of making ammonia, you need to find ways to make it relatively affordable in a lot of countries, with whatever resources they’ve got,” he says. This new proposed combination, he says, “looks like a really good idea that can help push things along. Ultimately, there’s got to be a lot of green ammonia plants in a lot of places,” and starting out with the combined plants, which could be more affordable now, could help to make that happen. The team has filed for a patent on the process.

Although the team did a detailed study of both the technology and the economics that show the system has great promise, Green points out that “no one has ever built one. We did the analysis, it looks good, but surely when people build the first one, they’ll find funny little things that need some attention,” such as details of how to start up or shut down the process. “I would say there’s plenty of additional work to do to make it a real industry.” But the results of this study, which shows the costs to be much more affordable than existing blue or green plants in isolation, “definitely encourages the possibility of people making the big investments that would be needed to really make this industry feasible.”

This proposed integration of the two methods “improves efficiency, reduces greenhouse gas emissions, and lowers overall cost,” says Kevin van Geem, a professor in the Center for Sustainable Chemistry at Ghent University, who was not associated with this research. “The analysis is rigorous, with validated process models, transparent assumptions, and comparisons to literature benchmarks. By combining techno-economic analysis with emissions accounting, the work provides a credible and balanced view of the trade-offs.”

He adds that, “given the scale of global ammonia production, such a reduction could have a highly impactful effect on decarbonizing one of the most emissions-intensive chemical industries.”

The research team also included MIT postdoc Angiras Menon and MITEI research lead Guiyan Zang. The work was supported by IHI Japan through the MIT Energy Initiative and the Martin Family Society of Fellows for Sustainability. 

Chatbots like ChatGPT and Claude have experienced a meteoric rise in usage over the past three years because they can help you with a wide range of tasks. Whether you’re writing Shakespearean sonnets, debugging code, or need an answer to an obscure trivia question, artificial intelligence systems seem to have you covered. The source of this versatility? Billions, or even trillions, of textual data points across the internet.

Those data aren’t enough to teach a robot to be a helpful household or factory assistant, though. To understand how to handle, stack, and place various arrangements of objects across diverse environments, robots need demonstrations. You can think of robot training data as a collection of how-to videos that walk the systems through each motion of a task. Collecting these demonstrations on real robots is time-consuming and not perfectly repeatable, so engineers have created training data by generating simulations with AI (which don’t often reflect real-world physics), or tediously handcrafting each digital environment from scratch.

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Toyota Research Institute may have found a way to create the diverse, realistic training grounds robots need. Their “steerable scene generation” approach creates digital scenes of things like kitchens, living rooms, and restaurants that engineers can use to simulate lots of real-world interactions and scenarios. Trained on over 44 million 3D rooms filled with models of objects such as tables and plates, the tool places existing assets in new scenes, then refines each one into a physically accurate, lifelike environment.

Steerable scene generation creates these 3D worlds by “steering” a diffusion model — an AI system that generates a visual from random noise — toward a scene you’d find in everyday life. The researchers used this generative system to “in-paint” an environment, filling in particular elements throughout the scene. You can imagine a blank canvas suddenly turning into a kitchen scattered with 3D objects, which are gradually rearranged into a scene that imitates real-world physics. For example, the system ensures that a fork doesn’t pass through a bowl on a table — a common glitch in 3D graphics known as “clipping,” where models overlap or intersect.

How exactly steerable scene generation guides its creation toward realism, however, depends on the strategy you choose. Its main strategy is “Monte Carlo tree search” (MCTS), where the model creates a series of alternative scenes, filling them out in different ways toward a particular objective (like making a scene more physically realistic, or including as many edible items as possible). It’s used by the AI program AlphaGo to beat human opponents in Go (a game similar to chess), as the system considers potential sequences of moves before choosing the most advantageous one.

“We are the first to apply MCTS to scene generation by framing the scene generation task as a sequential decision-making process,” says MIT Department of Electrical Engineering and Computer Science (EECS) PhD student Nicholas Pfaff, who is a CSAIL researcher and a lead author on a paper presenting the work. “We keep building on top of partial scenes to produce better or more desired scenes over time. As a result, MCTS creates scenes that are more complex than what the diffusion model was trained on.”

In one particularly telling experiment, MCTS added the maximum number of objects to a simple restaurant scene. It featured as many as 34 items on a table, including massive stacks of dim sum dishes, after training on scenes with only 17 objects on average.

Steerable scene generation also allows you to generate diverse training scenarios via reinforcement learning — essentially, teaching a diffusion model to fulfill an objective by trial-and-error. After you train on the initial data, your system undergoes a second training stage, where you outline a reward (basically, a desired outcome with a score indicating how close you are to that goal). The model automatically learns to create scenes with higher scores, often producing scenarios that are quite different from those it was trained on.

Users can also prompt the system directly by typing in specific visual descriptions (like “a kitchen with four apples and a bowl on the table”). Then, steerable scene generation can bring your requests to life with precision. For example, the tool accurately followed users’ prompts at rates of 98 percent when building scenes of pantry shelves, and 86 percent for messy breakfast tables. Both marks are at least a 10 percent improvement over comparable methods like “MiDiffusion” and “DiffuScene.”

The system can also complete specific scenes via prompting or light directions (like “come up with a different scene arrangement using the same objects”). You could ask it to place apples on several plates on a kitchen table, for instance, or put board games and books on a shelf. It’s essentially “filling in the blank” by slotting items in empty spaces, but preserving the rest of a scene.

According to the researchers, the strength of their project lies in its ability to create many scenes that roboticists can actually use. “A key insight from our findings is that it’s OK for the scenes we pre-trained on to not exactly resemble the scenes that we actually want,” says Pfaff. “Using our steering methods, we can move beyond that broad distribution and sample from a ‘better’ one. In other words, generating the diverse, realistic, and task-aligned scenes that we actually want to train our robots in.”

Such vast scenes became the testing grounds where they could record a virtual robot interacting with different items. The machine carefully placed forks and knives into a cutlery holder, for instance, and rearranged bread onto plates in various 3D settings. Each simulation appeared fluid and realistic, resembling the real-world, adaptable robots steerable scene generation could help train, one day.

While the system could be an encouraging path forward in generating lots of diverse training data for robots, the researchers say their work is more of a proof of concept. In the future, they’d like to use generative AI to create entirely new objects and scenes, instead of using a fixed library of assets. They also plan to incorporate articulated objects that the robot could open or twist (like cabinets or jars filled with food) to make the scenes even more interactive.

To make their virtual environments even more realistic, Pfaff and his colleagues may incorporate real-world objects by using a library of objects and scenes pulled from images on the internet and using their previous work on “Scalable Real2Sim.” By expanding how diverse and lifelike AI-constructed robot testing grounds can be, the team hopes to build a community of users that’ll create lots of data, which could then be used as a massive dataset to teach dexterous robots different skills.

“Today, creating realistic scenes for simulation can be quite a challenging endeavor; procedural generation can readily produce a large number of scenes, but they likely won’t be representative of the environments the robot would encounter in the real world. Manually creating bespoke scenes is both time-consuming and expensive,” says Jeremy Binagia, an applied scientist at Amazon Robotics who wasn’t involved in the paper. “Steerable scene generation offers a better approach: train a generative model on a large collection of pre-existing scenes and adapt it (using a strategy such as reinforcement learning) to specific downstream applications. Compared to previous works that leverage an off-the-shelf vision-language model or focus just on arranging objects in a 2D grid, this approach guarantees physical feasibility and considers full 3D translation and rotation, enabling the generation of much more interesting scenes.”

“Steerable scene generation with post training and inference-time search provides a novel and efficient framework for automating scene generation at scale,” says Toyota Research Institute roboticist Rick Cory SM ’08, PhD ’10, who also wasn’t involved in the paper. “Moreover, it can generate ‘never-before-seen’ scenes that are deemed important for downstream tasks. In the future, combining this framework with vast internet data could unlock an important milestone towards efficient training of robots for deployment in the real world.”

Pfaff wrote the paper with senior author Russ Tedrake, the Toyota Professor of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering at MIT; a senior vice president of large behavior models at the Toyota Research Institute; and CSAIL principal investigator. Other authors were Toyota Research Institute robotics researcher Hongkai Dai SM ’12, PhD ’16; team lead and Senior Research Scientist Sergey Zakharov; and Carnegie Mellon University PhD student Shun Iwase. Their work was supported, in part, by Amazon and the Toyota Research Institute. The researchers presented their work at the Conference on Robot Learning (CoRL) in September.

The company Flok is surveilling us as we drive:

A retired veteran named Lee Schmidt wanted to know how often Norfolk, Virginia’s 176 Flock Safety automated license-plate-reader cameras were tracking him. The answer, according to a U.S. District Court lawsuit filed in September, was more than four times a day, or 526 times from mid-February to early July. No, there’s no warrant out for Schmidt’s arrest, nor is there a warrant for Schmidt’s co-plaintiff, Crystal Arrington, whom the system tagged 849 times in roughly the same period.

You might think this sounds like it violates the Fourth Amendment, which protects American citizens from unreasonable searches and seizures without probable cause. Well, so does the American Civil Liberties Union. Norfolk, Virginia Judge Jamilah LeCruise also agrees, and in 2024 she ruled that plate-reader data obtained without a search warrant couldn’t be used against a defendant in a robbery case...

Every time you check the time on your phone, make an online transaction, or use a navigation app, you are depending on the precision of atomic clocks.

An atomic clock keeps time by relying on the “ticks” of atoms as they naturally oscillate at rock-steady frequencies. Today’s atomic clocks operate by tracking cesium atoms, which tick over 10 billion times per second. Each of those ticks is precisely tracked using lasers that oscillate in sync, at microwave frequencies.

Scientists are developing next-generation atomic clocks that rely on even faster-ticking atoms such as ytterbium, which can be tracked with lasers at higher, optical frequencies. If they can be kept stable, optical atomic clocks could track even finer intervals of time, up to 100 trillion times per second.

Now, MIT physicists have found a way to improve the stability of optical atomic clocks, by reducing “quantum noise” — a fundamental measurement limitation due to the effects of quantum mechanics, which obscures the atoms’ pure oscillations. In addition, the team discovered that an effect of a clock’s laser on the atoms, previously considered irrelevant, can be used to further stabilize the laser.

The researchers developed a method to harness a laser-induced “global phase” in ytterbium atoms, and have boosted this effect with a quantum-amplification technique. The new approach doubles the precision of an optical atomic clock, enabling it to discern twice as many ticks per second compared to the same setup without the new method. What’s more, they anticipate that the precision of the method should increase steadily with the number of atoms in an atomic clock.

The researchers detail the method, which they call global phase spectroscopy, in a study appearing today in the journal Nature. They envision that the clock-stabilizing technique could one day enable portable optical atomic clocks that can be transported to various locations to measure all manner of phenomena.

“With these clocks, people are trying to detect dark matter and dark energy, and test whether there really are just four fundamental forces, and even to see if these clocks can predict earthquakes,” says study author Vladan Vuletić, the Lester Wolfe Professor of Physics at MIT. “We think our method can help make these clocks transportable and deployable to where they’re needed.”

The paper’s co-authors are Leon Zaporski, Qi Liu, Gustavo Velez, Matthew Radzihovsky, Zeyang Li, Simone Colombo, and Edwin Pedrozo-Peñafiel, who are members of the MIT-Harvard Center for Ultracold Atoms and the MIT Research Laboratory of Electronics.

Ticking time

In 2020, Vuletić and his colleagues demonstrated that an atomic clock could be made more precise by quantumly entangling the clock’s atoms. Quantum entanglement is a phenomenon by which particles can be made to behave in a collective, highly correlated manner. When atoms are quantumly entangled, they redistribute any noise, or uncertainty in measuring the atoms’ oscillations, in a way that reveals a clearer, more measurable “tick.”

In their previous work, the team induced quantum entanglement among several hundred ytterbium atoms that they first cooled and trapped in a cavity formed by two curved mirrors. They sent a laser into the cavity, which bounced thousands of times between the mirrors, interacting with the atoms and causing the ensemble to entangle. They were able to show that quantum entanglement could improve the precision of existing atomic clocks by essentially reducing the noise, or uncertainty between the laser’s and atoms’ tick rates.

At the time, however, they were limited by the ticking instability of the clock’s laser. In 2022, the same team derived a way to further amplify the difference in laser versus atom tick rates with “time reversal” — a trick that relies on entangling and de-entangling the atoms to boost the signal acquired in between.

However, in that work the team was still using traditional microwaves, which oscillate at much lower frequencies than the optical frequency standards ytterbium atoms can provide. It was as if they had painstakingly lifted a film of dust off a painting, only to then photograph it with a low-resolution camera.

“When you have atoms that tick 100 trillion times per second, that’s 10,000 times faster than the frequency of microwaves,” Vuletić says. “We didn’t know at the time how to apply these methods to higher-frequency optical clocks that are much harder to keep stable.”

About phase

In their new study, the team has found a way to apply their previously developed approach of time reversal to optical atomic clocks. They then sent in a laser that oscillates near the optical frequency of the entangled atoms.

“The laser ultimately inherits the ticking of the atoms,” says first author Zaporski. “But in order for this inheritance to hold for a long time, the laser has to be quite stable.”

The researchers found they were able to improve the stability of an optical atomic clock by taking advantage of a phenomenon that scientists had assumed was inconsequential to the operation. They realized that when light is sent through entangled atoms, the interaction can cause the atoms to jump up in energy, then settle back down into their original energy state and still carry the memory about their round trip.

“One might think we’ve done nothing,” Vuletić says. “You get this global phase of the atoms, which is usually considered irrelevant. But this global phase contains information about the laser frequency.”

In other words, they realized that the laser was inducing a measurable change in the atoms, despite bringing them back to the original energy state, and that the magnitude of this change depends on the laser’s frequency.

“Ultimately, we are looking for the difference of laser frequency and the atomic transition frequency,” explains co-author Liu. “When that difference is small, it gets drowned by quantum noise. Our method amplifies this difference above this quantum noise.”

In their experiments, the team applied this new approach and found that through entanglement they were able to double the precision of their optical atomic clock.

“We saw that we can now resolve nearly twice as small a difference in the optical frequency or, the clock ticking frequency, without running into the quantum noise limit,” Zaporski says. “Although it’s a hard problem in general to run atomic clocks, the technical benefits of our method it will make it easier, and we think this can enable stable, transportable atomic clocks.”

This research was supported, in part, by the U.S. Office of Naval Research, the National Science Foundation, the U.S. Defense Advanced Research Projects Agency, the U.S. Department of Energy, the U.S. Office of Science, the National Quantum Information Science Research Centers, and the Quantum Systems Accelerator.

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