Photonic chips use light to process data instead of electricity, enabling faster communication speeds and greater bandwidth. Most of that light typically stays on the chip, trapped in optical wires, and is difficult to transmit to the outside world in an efficient manner.

If a lot of light could be rapidly and precisely beamed off the chip, free from the confines of the wiring, it could open the door to higher-resolution displays, smaller Lidar systems, more precise 3D printers, or larger-scale quantum computers.

Now, researchers from MIT and elsewhere have developed a new class of photonic devices that enable the precise broadcasting of light from the chip into free space in a scalable way.

Their chip uses an array of microscopic structures that curl upward, resembling tiny, glowing ski jumps. The researchers can carefully control how light is emitted from thousands of these tiny structures at once.

They used this new platform to project detailed, full-color images that are roughly half the size of a grain of table salt. Used in this way, the technology could aid in the development of lightweight augmented reality glasses or compact displays.

They also demonstrated how photonic “ski jumps” could be used to precisely control quantum bits, or qubits, in a quantum computing system.

“On a chip, light travels in wires, but in our normal, free-space world, light travels wherever it wants. Interfacing between these two worlds has long been a challenge. But now, with this new platform, we can create thousands of individually controllable laser beams that can interact with the world outside the chip in a single shot,” says Henry Wen, a visiting research scientist in the Research Laboratory of Electronics (RLE) at MIT, research scientist at MITRE, and co-lead author of a paper on the new platform.

He is joined on the paper by co-lead authors Matt Saha, of MITRE; Andrew S. Greenspon, a visiting scientist in RLE and MITRE; Matthew Zimmermann, of MITRE; Matt Eichenfeld, a professor at the University of Arizona; senior author Dirk Englund, a professor in the MIT Department of Electrical Engineering and Computer Science and principal investigator in the Quantum Photonics and Artificial Intelligence Group and the RLE; as well as others at MIT, MITRE, Sandia National Laboratories, and the University of Arizona. The research appears today in Nature.

A scalable platform

This work grew out of the Quantum Moonshot Program, a collaboration between MIT, the University of Colorado at Boulder, the MITRE Corporation, and Sandia National Laboratories to develop a novel quantum computing platform using the diamond-based qubits being developed in the Englund lab.

These diamond-based qubits are controlled using laser beams, and the researchers needed a way to interact with millions of qubits at once.

“We can’t control a million laser beams, but we may need to control a million qubits. So, we needed something that can shoot laser beams into free space and scan them over a large area, kind of like firing a T-shirt gun into the crowd at a sports stadium,” Wen says.

Existing methods used to broadcast and steer light off a photonic chip typically work with only a few beams at once and can’t scale up enough to interact with millions of qubits.

To create a scalable platform, the researchers developed a new fabrication technique. Their method produces photonic chips with tiny structures that curve upward off the chip’s surface to shine laser beams into free space.

They built these tiny “ski jumps” for light by creating two-layer structures from two different materials. Each material expands differently when it cools down from the high fabrication temperatures.

The researchers designed the structures with special patterns in each layer so that, when the temperature changes, the difference in strain between the materials causes the entire structure to curve upward as it cools.

This is the same effect as in an old-fashioned thermostat, which utilizes a coil of two metallic materials that curl and uncurl based on the temperature in the room, triggering the HVAC system. “Both of these materials, silicon nitride and aluminum nitride, were separate technologies. Finding a way to put them together was really the fabrication innovation that enables the ski jumps. This wouldn’t have been possible without the pioneering contributions of Matt Eichenfield and Andrew Leenheer at Sandia National Labs,” Wen says.

On the chip, connected waveguides funnel light to the ski jump structures. The researchers use a series of modulators to rapidly and precisely control how that light is turned on and off, enabling them to project light off the chip and move it around in free space.

Painting with light

They can broadcast light in different colors and, by tweaking the frequencies of light, adjust the density of the pattern that is emitted. In this way, they can essentially paint pictures in free space using light.

“This system is so stable we don’t even need to correct for errors. The pattern stays perfectly still on its own. We just calculate what color lasers need to be on at a given time and then turn it on,” he says.

Because the individual points of light, or pixels, are so tiny, the researchers can use this platform to generate extremely high-resolution displays. For instance, with their technique, 30,000 pixels can be fit into the same area that can hold only two pixels used in smartphone displays, Wen says.

“Our platform is the ideal optical engine because our pixels are at the physical limit of how small a pixel can be,” he adds.

Beyond high-resolution displays and larger quantum computers with diamond-based qubits, the method could be used to produce Lidars that are small enough to fit on tiny robots.

It could also be utilized in 3D printing processes that fabricate objects using lasers to cure layers of resin. Because their chip generates controllable beams of light so rapidly, it could greatly increase the speed of these printing processes, allowing users to create more complex objects.

In the future, the researchers want to scale their system up and conduct additional experiments on the yield and uniformity of the light, design a larger system to capture light from an array of photonic chips with “ski jumps,” and conduct robustness tests to see how long the devices last.

“We envision this opening the door to a new class of lab-on-chip capabilities and lithographically defined micro-opto-robotic agents,” Wen says.

This research was funded, in part, by the MITRE Quantum Moonshot Program, the U.S. Department of Energy, and the Center for Integrated Nanotechnologies.

Have you ever seen a really creepy targeted ad online? One that revealed just how much these companies know about your life? It's unsettling enough to see how much companies know about you—but now we have confirmation that the government is also tapping the advertising surveillance machine to get your data. We're explaining the dangers of targeted advertising and location tracking, and the latest in the fight for privacy and free speech online, with our EFFector newsletter.

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For over 35 years, EFFector has been your guide to understanding the intersection of technology, civil liberties, and the law. This issue covers a victory for protesters seeking to hold police accountable, a troubling conflict over the Department of Defense's use of AI, and how advertising surveillance enables government surveillance.

Prefer to listen in? Big news: EFFector is now available on all major podcast platforms! In this episode we chat with EFF Staff Attorney Lena Cohen about how targeted advertising can reveal your location to federal law enforcement. You can find the episode and subscribe in your podcast player of choice: 

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Canada has a choice to make about its artificial intelligence future. The Carney administration is investing $2-billion over five years in its Sovereign AI Compute Strategy. Will any value generated by “sovereign AI” be captured in Canada, making a difference in the lives of Canadians, or is this just a passthrough to investment in American Big Tech?

Forcing the question is OpenAI, the company behind ChatGPT, which has been pushing an “OpenAI for Countries” initiative. It is not the only one eyeing its share of the $2-billion, but it appears to be the most aggressive. OpenAI’s top lobbyist in the region has met with Ottawa officials, including Artificial Intelligence Minister Evan Solomon...

Surging oil and gas prices could increase inflation — a bad omen for a renewables industry that recently canceled projects because of higher costs.

A federal judge says the agency needs to comply with a December court order to restart a program that helps states prepare for natural disasters.

The leader of Climate United is taking a position with a wealth management firm.

Getting data centers to generate their own electricity may ease one obstacle to public acceptance of data centers. But it creates new hurdles.

Five senators told the Department of Homeland Security inspector general that the Federal Emergency Management Agency has ignored lawmaker queries.

Gov. Jeff Landry said the state is close to a settlement with the oil major that would help restore the Bayou State’s disappearing coast.

The Florida Legislature passed the measure that at one point was strongly opposed by the state’s insurance commissioner, who then dropped his opposition after the bill was tweaked on the Senate floor.

The higher average temperature was driven primarily by the area west of the Mississippi River, which largely missed out on winter this year, said a NOAA scientist.

As temperatures rise aboveground, the number of subway riders reporting uncomfortable conditions increases, says a new study.

Credits and offsets in Alberta’s carbon market, known as the TIER system, have fallen to $22.53, according to a price tracker.

The strategy aims to help mobilize $767 billion a year in investment in clean energy before 2030.

MIT researchers have developed a generative artificial intelligence-driven approach for planning long-term visual tasks, like robot navigation, that is about twice as effective as some existing techniques.

Their method uses a specialized vision-language model to perceive the scenario in an image and simulate actions needed to reach a goal. Then a second model translates those simulations into a standard programming language for planning problems, and refines the solution.

In the end, the system automatically generates a set of files that can be fed into classical planning software, which computes a plan to achieve the goal. This two-step system generated plans with an average success rate of about 70 percent, outperforming the best baseline methods that could only reach about 30 percent.

Importantly, the system can solve new problems it hasn’t encountered before, making it well-suited for real environments where conditions can change at a moment’s notice.

“Our framework combines the advantages of vision-language models, like their ability to understand images, with the strong planning capabilities of a formal solver,” says Yilun Hao, an aeronautics and astronautics (AeroAstro) graduate student at MIT and lead author of an open-access paper on this technique. “It can take a single image and move it through simulation and then to a reliable, long-horizon plan that could be useful in many real-life applications.”

She is joined on the paper by Yongchao Chen, a graduate student in the MIT Laboratory for Information and Decision Systems (LIDS); Chuchu Fan, an associate professor in AeroAstro and a principal investigator in LIDS; and Yang Zhang, a research scientist at the MIT-IBM Watson AI Lab. The paper will be presented at the International Conference on Learning Representations.

Tackling visual tasks

For the past few years, Fan and her colleagues have studied the use of generative AI models to perform complex reasoning and planning, often employing large language models (LLMs) to process text inputs.

Many real-world planning problems, like robotic assembly and autonomous driving, have visual inputs that an LLM can’t handle well on its own. The researchers sought to expand into the visual domain by utilizing vision-language models (VLMs), powerful AI systems that can process images and text.

But VLMs struggle to understand spatial relationships between objects in a scene and often fail to reason correctly over many steps. This makes it difficult to use VLMs for long-range planning.

On the other hand, scientists have developed robust, formal planners that can generate effective long-horizon plans for complex situations. However, these software systems can’t process visual inputs and require expert knowledge to encode a problem into language the solver can understand.

Fan and her team built an automatic planning system that takes the best of both methods. The system, called VLM-guided formal planning (VLMFP), utilizes two specialized VLMs that work together to turn visual planning problems into ready-to-use files for formal planning software.

The researchers first carefully trained a small model they call SimVLM to specialize in describing the scenario in an image using natural language and simulating a sequence of actions in that scenario. Then a much larger model, which they call GenVLM, uses the description from SimVLM to generate a set of initial files in a formal planning language known as the Planning Domain Definition Language (PDDL).

The files are ready to be fed into a classical PDDL solver, which computes a step-by-step plan to solve the task. GenVLM compares the results of the solver with those of the simulator and iteratively refines the PDDL files.

“The generator and simulator work together to be able to reach the exact same result, which is an action simulation that achieves the goal,” Hao says.

Because GenVLM is a large generative AI model, it has seen many examples of PDDL during training and learned how this formal language can solve a wide range of problems. This existing knowledge enables the model to generate accurate PDDL files.

A flexible approach

VLMFP generates two separate PDDL files. The first is a domain file that defines the environment, valid actions, and domain rules. It also produces a problem file that defines the initial states and the goal of a particular problem at hand.

“One advantage of PDDL is the domain file is the same for all instances in that environment. This makes our framework good at generalizing to unseen instances under the same domain,” Hao explains.

To enable the system to generalize effectively, the researchers needed to carefully design just enough training data for SimVLM so the model learned to understand the problem and goal without memorizing patterns in the scenario. When tested, SimVLM successfully described the scenario, simulated actions, and detected if the goal was reached in about 85 percent of experiments.

Overall, the VLMFP framework achieved a success rate of about 60 percent on six 2D planning tasks and greater than 80 percent on two 3D tasks, including multirobot collaboration and robotic assembly. It also generated valid plans for more than 50 percent of scenarios it hadn’t seen before, far outpacing the baseline methods.

“Our framework can generalize when the rules change in different situations. This gives our system the flexibility to solve many types of visual-based planning problems,” Fan adds.

In the future, the researchers want to enable VLMFP to handle more complex scenarios and explore methods to identify and mitigate hallucinations by the VLMs.

“In the long term, generative AI models could act as agents and make use of the right tools to solve much more complicated problems. But what does it mean to have the right tools, and how do we incorporate those tools? There is still a long way to go, but by bringing visual-based planning into the picture, this work is an important piece of the puzzle,” Fan says.

This work was funded, in part, by the MIT-IBM Watson AI Lab.

Nature Climate Change, Published online: 11 March 2026; doi:10.1038/s41558-026-02578-0

The adoption and effectiveness of carbon pricing are highly reshaped by interactions with other climate mitigation policies. A global comparative assessment of policy synergies and conflicts can guide policymakers in designing policy portfolios that can achieve higher mitigation cost-effectiveness.

Nature Climate Change, Published online: 11 March 2026; doi:10.1038/s41558-026-02574-4

Interactions between climate policy instruments can have synergistic and conflicting effects, but these interactions are not systematically understood. This research provides global evidence on how policy characteristics and interactions in different contexts could lead to different outcomes.

Nature Climate Change, Published online: 11 March 2026; doi:10.1038/s41558-026-02562-8

The feasibility of climate policies hinges on public support. A survey of 13 EU countries shows that ‘middle groups’—citizens whose support across mitigation measures varies, rather than being uniformly supportive or opposed—play a pivotal role in shaping overall public policy support and electoral outcomes.

The government should not help a religious institution to punish or deter members from inquiring about their faith. Yet, once again, the Watch Tower Bible and Tract Society is trying to use flimsy copyright claims to exploit the special legal tools available to copyright owners in order to unmask anonymous online speakers. And, once again, EFF has stepped in to urge the courts not to give Watch Tower’s attempts the force of law, with the help of local counsel Jonathan Phillips of Phillips & Bathke, P.C.

EFF’s client, J. Doe, is a member of the Jehovah’s Witnesses who became interested in the history of the organization’s public statements, and how they’ve changed over time. They created research tools to analyze those documents and ultimately created a website, JWS Library, allowing others to use those tools and verify their findings through an archive that included documents suppressed by the church. Doe and others discovered prophecies that failed to come true, erasure of a leader’s disgrace, increased calls for obedience and donations, and other insights about the Jehovah’s Witnesses’ practices. Doe also used machine translation on a foreign-language document to help the community understand what the church was saying to different audiences and also to help understand potential changes in the organization’s attitudes towards dissent.

Within the church, dissent or even asking questions has often been punished by labeling members as apostates and ostracizing—or “disfellowshipping”— them. As a result, Doe and others choose to speak anonymously to avoid retaliation that could cost them family, friend, and professional relationships.

There is no law against questioning the Jehovah’s Witnesses. Instead, Watch Tower argues that Doe’s activities constitute copyright infringement and seeks to use the special process provided in the Digital Millennium Copyright Act (DMCA) to unmask them. It sent DMCA subpoenas to Google and Cloudflare, seeking information that would help them uncover Doe’s identity.

The problem for Watch Tower is that Doe’s research and commentary are clear fair uses allowed under copyright law. The First Amendment does not permit the unmasking of anonymous speakers based on such weak claims. Indeed, the First Amendment protects anonymous speakers precisely because some would be deterred from speaking if they faced retribution for doing so.

EFF stands with those who question the claims of those in power and who share the tools and knowledge needed to do so. We urge the judges in the Southern District of New York to quash these improper subpoenas and not allow copyright to be used to suppress important, legitimate speech.

With time dwindling in the Olympic women’s ice hockey gold medal game on Feb. 19, players for Team USA and Team Canada lined up for a key faceoff in Canada’s end. Canada had a 1-0 lead. USA had 2:23 left, and an ace up their sleeve: analytics.

USA Coach John Wroblewski pulled the goalkeeper, to get a player advantage, and had forward Alex Carpenter take the faceoff. Statistics show that Carpenter is not only very good at winning faceoffs; she also wins a lot of them cleanly. That allows her team to quickly regain possession, without too many teammates nearby. Knowing that, Wroblewski directed the USA players to spread out, largely away from the faceoff circle, in position to circulate the puck as soon as they got it back.

Carpenter won the faceoff, and Team USA quickly started a passing move. Laila Edwards soon launched a shot that longtime star Hilary Knight deflected in for the crucial, game-tying goal with 2:04 left. Team USA then won in overtime. And data-driven decision-making had also won big; indeed, it helped change the Olympics.

“What it does for a coach, the other thing these analytics do, is … it allows you to move forward with this confidence level,” Wroblewski said on Saturday at the 20th annual MIT Sloan Sports Analytics Conference (SSAC), during a hockey analytics panel where he detailed his decision-making for that faceoff, and in the gold medal game generally.

Using the data, he added, lets coaches “limit the emotion” that might cloud their in-game decisions.

“By the time you get to that decision, you’re then allowed the freedom to step away from the decision, to allow the players to go earn their medal,” Wroblewski added.

You don’t usually find coaches divulging their tactical secrets just three weeks after a big game has been played. But then, this is the MIT Sloan conference, a trailblazing forum that has helped analytics ideas spread throughout sports. Coaches, players, and analysts know any data-driven discussion will find an interested audience.

“Analytics was massive for us going into the gold medal game,” Wroblewski said.

20 years on: From classrooms to convention halls

The 20th edition of SSAC was a strong one, with many substantive panel discussions and interviews; the annual research paper, hackathon, and case study contests; mentorship events and informal networking opportunities; and more. Over 2,500 people attended the two-day event, held at Boston’s Menino Conference and Exhibition Center (MCEC). The conference was founded in 2007 by Daryl Morey, now president of basketball operations for the NBA Philadelphia 76ers, and Jessica Gelman, now CEO of the Kraft Analytics Group.

The first three editions of the conference were held on the MIT campus. In 2010, it first moved to the MCEC (one of two regular convention-center sites it uses), and starting in 2011, the conference became a two-day event.

Today people attend for the panels, the career opportunities, and, in some cases, to make news. NBA Commissioner Adam Silver was on hand this year, engaging in an on-stage conversation with former WNBA great Sue Bird, publicly addressing some of the key issues facing his league, and drawing wide media coverage.

First, though, Silver reflected about attending the second edition of the conference on the MIT campus in 2008, when he was deputy commissioner.

“It was literally a classroom of 20 people we were talking to,” Silver recalled. “I think it was the beginning of the moment when people were taking sports as a discipline more seriously. … I give Jessica and Daryl a lot of credit [for that].”

Addressing tanking and gambling

A core part of Silver’s comments focused on two big issues in pro basketball: tanking and gambling. About eight NBA teams appear to be tanking this season, that is, losing games in order to increase their chances of getting a high draft pick.

“We are going to make substantial changes for next year,” Silver said, although he also added: “I am an incrementalist. I think we’ve got to be a little bit careful about how huge a change we make at once. I’m not ruling anything out. But I am paying attention to that.”

To be sure, tanking has long been a part of professional basketball, as Bird noted during the conversation.

“We did it in Seattle, to be honest,” Bird said. “Breanna Stewart was coming out of college. We were in a ‘rebuild.’”

Still, in this NBA season, tanking has become an epidemic, in “a little bit of a perfect storm,” as Silver put it on Friday. And almost every proposed solution seems to have drawbacks. Perhaps the simplest cure for tanking, actually, would be robust analytical studies showing that it is not a very effective team-building strategy. If that is what the numbers reveal, of course.

Meanwhile, multiple arrests of NBA players and coaches at the beginning of the season show further that sports gambling continues to present challenges to professional sports leagues.

“I personally think there should be more regulation now, not less,” Silver said on Friday, suggesting that federal rules would simplify things in the U.S., where 39 states allow sports gambling to some extent. He also said the NBA can continue to work on monitoring data to protect against gambling scandals.

“I think there are some large-platform companies are that are looking at a business opportunity to come in and in a much more sophisticated way work as a detection service with the league,” Silver said.

Through it all, Silver said, the NBA will continue to be a data-driven operation. Have you watched a game with a long instant-replay review, and gotten a little impatient? Still, have you kept watching that game? So does almost everyone.

“For years people would tell us, ‘Don’t use instant replay, because you’ll turn fans off,’” Silver said. However, he added, “The data suggests, in terms of ratings and what servers tell us, you almost never lose a fan when you’re going to replay. Because they want to see the replay and they want to see what happened.”

The minnows got big

Sports analytics took root in baseball, with its discrete pitcher-hitter actions. Legendary MLB general manager Branch Rickey employed a statistician for the great Brooklyn Dodgers of the 1950s; the famous manager Earl Weaver thought analytically with the Baltimore Orioles in the 1970s. Baseball analyst Bill James made sports analytics a viable pursuit with his annual “Baseball Abstract” bestsellers in the 1980s, and Michael Lewis’ “Moneyball” popularized it.

But data can be applied to all sports — and sometimes is most valuable when only some teams are interested in it. Take soccer. In the English Premier League, about three clubs have been heavily oriented around analytics over the last decade: Liverpool FC, Brighton FC, and Brentford FC. That has helped Liverpool win multiple titles, while Brighton and Brentford, smaller clubs, have startled many with their success.

Saturday at SSAC, Brentford’s majority owner Matthew Benham made one of his most visible public appearances, in an onstage interview with podcaster Roger Bennett. Benham first made money wagering on soccer, then invested in Brentford, his childhood club.

“The information we used in the early days was really, really rudimentary,” Benham said. In his account, his success building an analytics-based club has only partly been about the numbers.

“A lot of the success has just been in running things efficiently.” Benham said. He prefers to have management discussions that are an “exchange of views, rather than debate,” since the latter implies an interaction with a clear winner and loser. Instead, compiling independent-minded views from his executives is more important.

Brentford also uses “a combination of old-style scouting and data” for its player acquisition decisions, Benham said. Not every decision works. Brentford could have signed current Arsenal FC star Eberechi Eze for a mere $4 million pounds in 2019, and passed; Crystal Palace FC acquired Eze, then realized a windfall when Arsenal purchased his services.

Still, pressed by Bennett to specify a little more about his analytical thinking, Benham implied that strikers are valuable not only for their finishing skills, but for consistently getting open for shots on goal. Fans tend to focus too much on a player’s misses, rather than how many chances are created by their off-ball work.

“Getting in position is way, way more informative than finishing,” Benham said.

A similar insight seems to have guided Liverpool’s thinking. As it happens, a Friday panel at SSAC featured Ian Graham, who ran Liverpool’s analytics operations from 2012 to 2023, and weighed in on a number of subjects. Among other things, Graham noted, teams are too cautious when tied late in a match; soccer grants three points for a win, one for a draw, and zero for a loss, so from a tied position, the reward for winning is twice as great as the penalty for losing.

“Teams don’t go for it enough,” Graham said. “Teams think a draw is an okay result.”

The limits of knowledge

Sports, of course, are ultimately played by imperfect, injury-prone, and sometimes exhausted athletes. One consistent lesson from the MIT Sloan conference involves the limits of data and plans.

“We think the data is giving us an answer, when actually it’s giving us some information, and we still have to make a choice,” said Ariana Andonian, vice president of player personnel for the Philadelphia 76ers, during a basketball panel on Saturday.

Asked about the promise of artificial intelligence for sports analytics, Sonia Raman, head coach of the WNBA’s Seattle Storm, noted that its insights might always be limited by circumstances.

“It’s not like you can just get an AI report in the middle of the game that says, ‘Get some shooting in,’” said Raman, who, prior to coaching in the WNBA and NBA served for 12 years as head coach of the MIT women’s basketball team.

“You can have a great plan, but if it’s poorly executed, it’s way worse than a poor plan that’s well executed,” added Steven Adams, a center for the NBA’s Houston Rockets (who is currently not playing due to injury), during the same panel.

And yet, in some games and matches, the analytics do work, the plans do come to fruition, and the numbers do make a difference. When that happens, as John Wroblewski can now attest, the results are golden.