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

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

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

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

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

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

Overcoming the limits

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

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

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

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

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

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

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

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

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

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

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

Leveraging magnetism

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

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

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

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

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

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

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

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

Chinese companies control nearly two-thirds of Argentina’s own squid fleet.

We know that ICE wants to deploy eyeglasses with facial recognition that can identify people in real time.

Turns out Meta is prototyping the feature with a Pentagon supplier. (Alternate news story.)

This Pride month, we’re calling on the dating app Grindr to prioritize LGBTQ+ user safety by making privacy the default across its platform. That means no more sharing personal data with advertisers or training AI on private information without users’ opt-in consent.

Grindr is a dating app for the LGBTQ+ community; and for queer people, privacy violations can have life-altering consequences. Information that reveals someone’s sexual orientation, gender identity, or HIV status can be used by employers, governments, family members, scammers, or bad actors to inflict harassment, discrimination, arrest, or violence. For example, data from Grindr and other gay dating apps was sold by data brokers and used to 'out' (the act of disclosing someone's sexual orientation without permission) a gay priest in 2021. 

Despite being the world's most popular gay dating app, Grindr has repeatedly mishandled users' sensitive data. Grindr has been caught sharing users' HIV status and precise location with advertisers without obtaining valid consent, resulting in reprimands and fines in several countries. Its former Chief Privacy Officer even sued, alleging the company fired him for raising concerns about Grindr prioritizing “profit over privacy."

Grindr ended several of its most egregious data sharing practices after they were exposed. But more changes are needed if Grindr wants to earn back trust and prove its commitment to users’ privacy and safety. This Pride month, we’re calling on Grindr to make privacy the default and ensure the immediate implementation of two changes to better protect its users:

Opt Users Out of Behavioral Advertising by Default

Grindr currently allows users to opt out of behavioral advertising, but that protection is not enabled automatically (except in some unspecified regions). As we’ve long warned, behavioral advertising relies on the collection and sharing of personal data across a vast network of advertisers, intermediaries, and data brokers. Once information enters this ecosystem, users have little control over where it goes or how it is used: people’s most private and intimate information can be aggregated, sold, and combined with information from other sources to create detailed personal profiles.

By default, Grindr appears to share data with numerous advertising and tracking companies. Using TrackerControl, an app developed by privacy researcher Konrad Kollnig, we recorded Grindr contacting 20 third-party tracking domains during 15 minutes of app activity (see Grindr_TrackerControl_06-23-2026.csv for exported results). TrackerControl observed Grindr contacting Big Tech companies and ad-tech intermediaries, many of which have faced significant legal scrutiny for privacy violations. Several of these companies auction off ad space through a process called “real-time bidding,” which can expose user data to hundreds of additional companies and be exploited by data brokers. 

The dangers of Grindr’s default settings exposing users’ personal data to this ecosystem are not hypothetical. Between approximately 2017 to 2020, a location data broker collected the precise movements of millions of Grindr users from digital advertising networks and made them available for sale. The commercially available data was allegedly so detailed that, in some cases, it could be used to infer romantic encounters between specific Grindr users. 

Although Grindr has stated that it no longer shares precise location data or profile information with advertisers, it acknowledges sharing other personal data, including mobile advertising identifiers (MAIDs)—unique, persistent device IDs that allow advertising companies and data brokers to connect data about the same individual across different sources. MAIDs are not anonymous, and an entire industry exists to link them to more directly identifying information, like emails and phone numbers. According to Grindr’s privacy policy, companies receiving users’ MAIDs “are aware that such data is being transmitted from Grindr,” which could expose a users’ sexuality to the advertising and data broker ecosystem.

Opt Users Out of AI Training on Personal Data by Default

Grindr should stop training its AI models on users’ personal data without opt-in consent. 

Grindr has been investing heavily in AI features as its CEO strives to make Grindr an “AI-first business.” New AI features include a wingman chatbot, profile recommendations based on users’ inferred “type”, summaries of previous interactions with other users, and AI-generated insights about other profiles (like responsiveness, typical online hours, and engagement patterns). By default, Grindr uses its users’ personal data to train the AI models behind these features.

Grindr claims to never use sensitive health information for AI training and requires users to opt-in to AI training on “special-category” data, which includes chat content and precise location. But Grindr automatically enrolls users in AI training on other private information, including profile photos, age, taps, and display names. Users must navigate several levels of Grindr settings to prevent these personal details from being used to train Grindr’s AI.

AI systems trained on personal data create new privacy risks, including the possibility that personal information may be retained, reproduced, or exposed in unexpected ways. For example, researchers have been able to extract training data from AI systems like ChatGPT.

Beyond AI training, Grindr enables AI-powered features by default and allows both “special-category” data and other personal information to be processed by those features. Even users without access to premium-subscription AI features could have their data automatically used to power those features for other users. “Behavior-based profile insights” (pictured below) could expose information that users would never choose to share publicly, like the types of people they interact with on Grindr, their typical online hours, and how often they initiate conversation with other users.

Image of the “Profile Insights” feature from a Grindr blogpost promoting its premium, AI-first subscription

Regardless of whether new AI features leak private information, users deserve meaningful control over how their personal data is used and by whom. Grindr notifies users that their personal information may be used to train AI and that they can opt out on a separate settings page, but this notice does not specify the type of data used (i.e. profile photos, taps) and it is unlikely that people carefully read or understand it. Closing the notice or clicking its only button (which is “Proceed”) maintains Grindr’s default of using personal information for AI training. To respect users’ autonomy, Grindr should require opt-in consent before training AI models on personal data.

Notice displayed in the Grindr app about the use of personal data for new AI features

Celebrate Pride by Demanding Better Privacy

Grindr must immediately stop prioritizing profits over users’ safety. The ability to opt-out is not an acceptable substitute for opt-in consent, especially given the added risks of data sharing for LGBTQ+ users. Defaults matter—studies show that most people cannot or do not change the default settings of technologies they use.

If Grindr wants to back up its claim that it “takes user privacy very seriously,” it should make privacy the default across its platform, rather than something users need to go through complicated processes to opt in to. 

Poke your head into just about any online social network—or any general conversations about internet culture—and you’ll likely find a boogieman: the algorithm. Since at least the moment Facebook introduced (and apologized for) its News Feed, “the algorithm” has been shorthand for the ways the tech giants control what we see and when we see it. In the age of enshittification, there is a push to reclaim our feeds and networks. Good news: there’s a tool that’s been around for decades that can help wrangle many of your feeds into something manageable: Really Simple Syndication, more commonly known as RSS.

What’s RSS and How Do I Use It?

RSS has been around since 1999, but its real publicity glow-up came from Google Reader, a newsreader service that Google offered between 2005 and 2013. Despite the alarm bells people rang at the time, the death of Google Reader wasn’t the death of RSS, and many replacements have come and gone over the years.

RSS may seem complicated, but it boils down to one general concept: when websites publish new content, like news articles, blog entries, webcomics, videos, or podcasts, that content gets added to an RSS feed, where your RSS reader (aka newsreader, feed reader, or aggregator) will show you that content in chronological order. If you’ve ever used a podcast player like Apple Podcasts or Spotify to follow different podcasts, you’ve used RSS. You can think of it like an internet-wide “follow” button, where you can track the contents of websites, users, and more.

People talk about RSS like it’s a power user’s secret trick to making the internet more usable, but the real secret is that it’s not that hard to set up and use. Here’s what you need to do:

• Find an RSS reader: RSS readers come in many forms. Feedly, NewsBlur, or The Old Reader, are web-based, but have their own apps (though they also support third-party apps). Others, like NetNewsWire, are app-based, and support either using a web-based RSS reader like Feedly, or a local file. Some live in browsers or web extensions. There’s an abundance of choice in RSS readers, and part of the fun is finding one that best accomplishes what you want to do. But don’t worry about finding the right RSS reader right away. One of the many magic tricks of RSS is that it is platform agnostic, and nearly every RSS reader—whether it's a website or an app, supports importing and exporting a list of the sites you subscribe to. This means you can change RSS readers in a couple minutes. If you need some help finding an RSS reader, Wired, The Verge, and Privacy Guides all have useful roundups. 
• Collect your feeds: As for adding websites to your feeds, the process is straightforward. Most RSS readers are designed to help find the feed for a site for you, so you don’t need to go hunting down a special link. Just drop the URL of what you want to follow in your reader, and if an RSS feed exists, it should be able to find it. If not, some sites, including ours (and our current podcast, EFFector as well as our last series, How to Fix the Internet), provide direct links to our RSS feeds.
• Sort, filter, and build your feed: Adding a bunch of new feeds can be overwhelming, particularly for news sites. RSS readers typically include folders, which let you group similar feeds together and can be great for lifting up low-traffic updates you don’t want to miss. Your reader may also have different filters, like the option to block any article that contains “sponsored post.” 

RSS Is the Best Way to Follow the News

It can be very difficult to follow the news, whether that means politics, tech policy, or your hobbies. Solutions like Google News or Apple News have tried to make this simpler, but many find that their algorithmic feeds are as often a source of frustration and annoyance as they are genuinely useful. And no matter how often you tap on news stories that matter to you from publications you respect, there may always be stories that refuse to bubble up.

RSS can make reading the news much easier, reliable, and more private. The vast majority of news sites have RSS feeds you can subscribe to, and many, including CNN, The New York Times, BBC, Wired, Politico, and many others, offer RSS for specific sections or special feeds that include the full text of articles for subscribers, so you aren’t just pummeled with a firehose of news all day long (we’ll get to a tip below in the next section that tackles this problem if they don’t have separate feeds, though). In many cases, you can read articles right in your RSS reader, never being forced to engage with wonky comments sections or poor design choices on websites.

Of course, the news isn’t just general news sites, it also includes hobbyist or more niche sites, local news offerings, and blogs. Most of these sorts of websites also offer RSS feeds, as do newsletter platforms like Substack or Ghost. 

RSS Offers One Way to Fix Some Social Feeds

Decentralized social media like Mastodon, Bluesky, and Threads, use RSS for user feeds, so you can follow your friend’s posts on Bluesky or Mastodon without actually having an account on either. This can be especially helpful for news sources, too—where you likely wouldn’t want to subscribe to a feed of everything a national news organization publishes because that would include dozens if not hundreds of stories a day, you can instead subscribe to their social media posts, which often get you the most breaking or important news.

The internet is more than just Facebook.

Some legacy social media works with RSS, too, including YouTube, Reddit (though that is currently at risk), and Tumblr. But others, like Facebook, LinkedIn, and Instagram, wall off posts behind account requirements that seem to pop up if you simply look at an account page for too long, let alone come in from an RSS feed. These walled gardens prevent information from getting out there, which ranges from annoying, like when your favorite local brewery only posts their food truck schedule on Instagram, to dangerous, like when local public services only post to a Facebook page.

The internet is more than just Facebook. It’s more than Mastodon or Bluesky, too. It’s a decentralized smorgasbord of websites, tools, feeds, newsletters, social profiles, and more, and treating it as such will help us wrangle the information we want and trust. 

Other Surprising Places You’ll Find RSS Feeds

When in doubt, try copying and pasting the URL for a site into your RSS reader of choice, you might be surprised to find a feed that proves useful to you. Many places on the internet may offer RSS feeds without you even realizing it. For example, if you want to keep an eye on an artist’s prints that you like, but they don’t have Instagram where they usually post, you might be able to subscribe to their webstore, as some shopping platforms, like Big Cartel, create an RSS feed automatically. And for something even more tweakable, even Google Alerts can be turned into RSS feeds.

RSS is one of the best examples we have of the open web, where we can design and customize how we experience the internet, not the other way around.

If you prefer to track policy over products, then you’ll be happy to know that government sites often support RSS, including most U.S. government sites, many of which break them into different sections like the U.S. Department of State’s various feeds. Many local governments or other public services, like fire departments may offer the same. Some universities (and university newspapers) also sometimes offer some RSS feeds. 

And even if a website doesn’t have an RSS feed, there are workarounds from tools like RSSHub, RSS-Bridge, and RSS.app that require varying levels of technical expertise or a willingness to pay subscription fees.

RSS is one of the best examples we have of the open web, where we can design and customize how we experience the internet, not the other way around. RSS has come in and out of fashion, been declared dead, and has come back, every time. Open systems are the best way forward to a free, equitable internet, and the resilience and continued reinvention of RSS has shown just how creative the web community can be with open protocols.

David Autor, the Daniel (1972) and Gail Rubinfeld Professor in the MIT Department of Economics, has been named head of the Department of Economics, effective July 1.

“David is a world-class labor economist,” says Agustín Rayo, the Kenan Sahin Dean of the School of Humanities, Arts, and Social Sciences. “He is also an individual of wisdom and insight. I look forward to welcoming him to the school’s leadership team.”

Autor’s scholarship explores the labor-market impacts of technological change and globalization on job polarization, skill demands, earnings levels and inequality, and electoral outcomes. He serves as faculty co-director of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work. 

“I’ve been at MIT since 1999, and I owe my career to the Institute, the department, and colleagues who are as kind as they are accomplished,” Autor says. “Stepping into this role is a chance to contribute to a place that has shaped me at every stage.”

Autor succeeds Jon Gruber, the Ford Professor of Economics, who has served as department head since July 2023.

Autor says he “aims to build on the stellar standard set by its faculty and students while navigating budget tightening and a shifting political landscape.” 

“Just as important, I want to lead the department toward the opportunities that advancing AI is opening in how we teach and what we research,” he adds.

Autor serves as co-director of the National Bureau of Economic Research (NBER) Labor Studies Program. He earned a BA in psychology from Tufts University in 1989 and a PhD in public policy from Harvard University’s Kennedy School of Government in 1999. 

Autor has received numerous awards for both his scholarship — the National Science Foundation CAREER Award, an Alfred P. Sloan Foundation Fellowship, the Sherwin Rosen Prize for outstanding contributions to the field of Labor Economics, the Andrew Carnegie Fellowship in 2019, the Society for Progress Medal in 2021 — and for his teaching, including the MIT MacVicar Faculty Fellowship, the James A. and Ruth Levitan Award for excellence in teaching, the Undergraduate Economic Association Teaching Award, and the Faculty Appreciation Award from the MIT Technology and Policy Program.

In 2020, Autor received the Heinz 25th Special Recognition Award from the Heinz Family Foundation for his work “transforming our understanding of how globalization and technological change are impacting jobs and earning prospects for American workers.” 

In 2023, Autor was one of two researchers across all scientific fields who was named a NOMIS Distinguished Scientist. 

In 2024, Autor was one of five senior scholars selected by the Schmidt Sciences Foundation as an AI2050 Senior Fellow.

This is not science fiction. It’s not premature. If towns, cities, states, or the federal government want to act to reign in the emergence of armed police drones and robots, we have precious little time. In the absence of substantial regulation around when and how domestic law enforcement in the United States can deploy force using drones, the companies that markets technology to law enforcement have been moving. It’s past time concerned people take notice. Cities should not procure weaponized drones or robots, and multi-purpose drones and robots should be restricted from causing harm. 

Since 2021, EFF has been advocating against the use of armed robots or drones by law enforcement. This call has become more urgent as companies are moving in to take advantage of the lax regulatory landscape.

This month, two disturbing developments raised concerns that we might be on the verge of a larger trend of drone militarization. The first is that the CEO of Skydio, one of the most prolific vendors of police drones in the United States, signaled that the company has a more permissive attitude toward arming their drones in some contexts than many people expected. When asked on a podcast about the public perception that the company had restrictions around letting the military arm their drones, CEO Adam Bry said, “This is an area where I’ve gotten some things wrong. We said some things previously that led folks externally and internally to believe that, for example, we would prevent the military from putting weapons on our drones […] It’s very easy to sit back in a Silicon Valley office and think that we’re very smart, that we know the technology, and the idea of using it for X, Y, or Z thing seems evil or bad, so we’re going to write a policy or ban people from doing it. I think that’s ultimately misguided.”

Simply put: he is signaling that Skydio will not implement restrictions on their customers’ use of their devices. 

Bry was specifically asked about the military arming drones but the question reveals a disturbing truth: whether police arm drones domestically is currently based more on the internal ethical commitments of companies than it is any laws created by elected officials. Combining Skydio’s huge amount of police contracts, including supplying entire fleets for Drone as First Responders (DFR) programs, and the tendency of military technologies like surveillance aerostats to get redeployed on U.S. soil, creates a real recipe for the emergence of armed police drones. 

The other piece on the chess board to keep our eye on is the introduction of weaponized drones as a tool of school safety. A company called Campus Guardian Angel will run pilot programs in schools in Georgia and Florida in Fall 2026 to introduce drones that are designed to swarm, distract, crash into, and even shoot irritants at potential school shooters. This comes just years after a large national backlash that got the large police tech company Axon to pause its development of drones armed with tasers as a solution to school shootings. 

Although it may be obvious to some people, it’s worth saying again: antagonizing an active shooter with a small drone is a dangerous idea. In chaotic situations, deploying physical harm via drone is likely to get bystanders or good samaritans hurt by accident. It is also unproven that this technology will work to distract or deter an actual school shooter–especially when the demonstrations we see online revolve around crashing drones into stationary mannequins in pristine, controlled conditions. Another important question: What would happen if a potential shooter shoots at the small moving drone and endangers the people fleeing behind it? After all, in the demonstrations we’ve seen it is unclear if these drones have the ability to see what is behind them.  This is an unproven and potentially dangerous method of combating the very serious problem of gun violence in schools, and it’s one that helps to normalize armed drones as a solution to other policing problems as well. 

These developments also mean It’s not enough to follow San Francisco’s lead, which became the first city to change its policy regarding how robots could be used in order to ban police from using deadly force via robots in 2022. A robust and effective policy must include both drones and robots (not one or the other), and it has to explicitly prevent drones and robots from deploying any body harm — including deadly force and less-lethal measures like kinetic strikes, pepper spray, rubber bullets, or tasers. In addition, cities and states should not procure weaponized drones and robots. 

Since 2021, EFF has been advocating against the use of armed robots or drones by law enforcement. This call has become more urgent as companies are moving in to take advantage of the lax regulatory landscape. We cannot continue to rely solely on the good will of companies that make their money selling technology to police departments to protect us from dangerous police technology. Lawmakers need to act now. 

Ignoring EFF’s warnings about the dangers and impossibility of implementing a new mandate for 3D print surveillance software, the California State Assembly has signed off on legislation to do just that. In the process, legislators amended the bill to make it even more confusing, while failing to address the risks to privacy, speech, and consumer rights. We must renew our call on legislators to drop this bill as it heads to the state senate, and protect the tools of creators in the state.

Take action

Tell CA Senators to stand with creators

What’s changed about the bill?

Since we first wrote about AB  2047, a bill targeting 3D printers for the rare, impractical, and already outlawed practice of manufacturing firearms without a license, it has picked up several amendments. Some are welcome changes, but most have only highlighted the technocratic absurdity of the proposed scheme. Our core concerns—that this mandate censors lawful speech, builds out corporate surveillance, and criminalizes open source experimentation—have not been remedied. 

Removes criminalization of resale

Starting with one silver lining, the current bill includes a carveout for the private resale of devices. The original bill would have made it a criminal offense for an individual to resell 3D printers purchased before this mandated censorship and surveillance software. This is a clear win for the 3D-printing community, but it is unfortunately not enough.

Ineffective carveouts for open source

One of the most dangerous aspects of the bill is that it criminalizes individual users for common practices, like creating and using alternative open source programs with their 3D printer. New amendments provide a carveout for the use of an open source tool, but only if it includes compliant censorship software. The bill burdens open source developers with ambiguous and unrealistic standards for print blocking, and continues to create a chilling effect for open source users.

Removes any actual requirement to work

To reiterate—there is no world where the mandated technology actually works as intended. It will both block lawful use of 3D printers, and allow firearms to be printed by anyone determined to do so. There is no amendment that can change this reality.

Instead, the current bill simply drops the pretense that this mandate is expected to work. The performance standard of algorithms changed from “effectively prevent[ing] a technically skilled user from evading [the algorithm]” to “substantially reduce the likelihood of foreseeable circumvention attempts…” The bill will still require all prints to be surveilled, but instead of testing efficacy against a skilled user, it just plays whack-a-mole with the (literally) infinite number of circumventions that any user can employ. 

Further, the bill now leaves us with an unclear process that relies on non-governmental third parties to define standards, and now relies on manufacturers and resellers to self-police.

Hollywood gets a cut

The bill includes yet another carve out for commercial users. This time for the entertainment industry, which makes extensive use of 3D printers for props and costumes. 

That’s fine for big studios, but it leaves out indie filmmakers, cosplayers, and many other small creators. 

This is simply a defensive edit to limit corporate opposition. There isn’t a clear division in 3D-printing between consumer and commercial tools. These are general purpose tools which might be picked up by a prop department of a big studio, or an artist getting ready for Comic Con. Indeed consumer level products are not only used by amateur artists and engineers developing their skills. Commercial 3D printers, like their traditional 2D equivalents, are frequently used in workplaces, as well as by professionals honing their skills or just trying to get some work done at home. 

Commercial carveouts hands printer manufacturers the ability to sell a more expensive tier of printers, locking-in and up-charging their commercial customers. Some of those customers will choose to buy general retail versions, but that carries its own price: increased risk of IP theft as all printed files are surveilled the same way they are for hobbyists. That means a real risk of businesses leaking any prototypes or new designs to not only the printer manufacturer, but potentially snooping governments and/or the general public through data breaches.

Demand  your senator oppose AB 2047

This updated version of AB 2047 downgrades performance standards and removes oversight while still threatening privacy and choice for users of 3D printers. A printer surveillance system won’t work for its intended purpose, and will only harm law abiding users. 

Act now to demand your senators to vote no on this ineffective and invasive bill.

Take action

Tell CA Senators to stand with creators

The number of U.S. data centers is growing, largely to power artificial intelligence programs. That has led to concern about the environmental consequences of data centers — and their impact on the energy grid itself. What will happen if scores of new data centers come online? 

A new study by MIT researchers indicates that the impact of data centers could vary significantly, depending on how their energy use is structured.

Specifically, if data centers move a significant portion of their energy consumption to non-peak hours, it might actually help lower average energy costs. The environmental impact, in terms of type of energy consumed, would differ by location, with some places likely seeing a greater buildout of renewables and others experiencing a relative increase in fossil fuel use. 

“The key with data centers is: How can we add them to the network without adding a lot to our peak usage?” says Christopher Knittel, an economist in the MIT Sloan School of Management and co-author of a new paper detailing the study. “One way for data centers to do that — to add to average usage but not the peak usage — is if they provide some grid flexibility during those high-cost periods. And that’s what we’ve been interested in understanding.”

Specifically, the paper finds that a flexible arrangement for data-center energy consumption, compared to an inflexible one, would produce cost savings of up to 5 percent in Texas, 4 percent in the Mid-Atlantic region, and 2 percent in the western U.S. states. To achieve that, data centers would have to move more than 20 percent of their consumption — sometimes more like 50 percent — to non-peak hours. 

The paper is titled “Flexible Data Centers Reduce Power System Costs But Can Increase Emissions,” and appears today in the journal iScience. The authors are Juan Ramon L. Senga, a postdoc in MIT’s Center for Energy and Environmental Policy Research; Shen Wang, a postdoc in MIT’s Center for Energy and Environmental Policy Research; and Knittel, who is the George P. Schultz Professor at MIT Sloan and the associate dean for climate and sustainability at MIT. 

The 20 percent solution

The expansion of data centers has raised questions about additional stress for the U.S. grid, the global effects of increased fossil-fuel consumption, and the local environmental effects of data centers. The current study examines the first two of these issues. 

To conduct the research, the scholars extensively simulated scenarios in which data centers expand, using the so-called “Gen X” model of the U.S. power grid, for a year’s worth of energy use. 

The study focused on the grid systems in three areas: Texas, the Mid-Atlantic region, and the “Western Interconnect,” comprising the 11 large western states in the lower 48 states of the U.S. The researchers studied these regions because they collectively host most of the country’s data centers — about 82 percent of U.S. data centers by 2030, according to one analysis. 

A bit counterintuitively, the researchers found that adding data centers could lower energy costs in some scenarios. Typically, about 60 percent of grid expenses are fixed costs, like power lines, while about 40 percent consists of energy costs. Adding data centers to the grid could, in effect, apportion the fixed costs over a higher volume of energy use. 

“It’s really just math,” Knittel says. 

But there is a catch. Lower costs might only happen if data centers increase their average consumption faster than their peak-hours consumption, when energy is most expensive. As it happens, most data centers do have flexibility built into their energy-use patterns, since they usually run at about 80 percent capacity.

In the study’s modeling, that flexibility often consists of shifting use from early-morning and early-evening peaks, to more midday energy consumption, when the energy load is lower and solar is at full capacity. The simulations show this makes a difference.

“There are two dimensions that data centers have to make decisions about,” Knittel says. “One is how much of their load in any one time period is flexible. And two, how many hours, plus or minus, can they move that computation?”

Pretty soon, real money

Additionally, data centers have different amounts of flexibility based on the types of AI-related computation they host. Data centers being used for AI training data tend to consume energy at a steady rate, but as a result could provide more flexibility for shifting power loads compared to inference data centers, which are used more for online search queries. In the latter case, consumption is driven more by end-user Internet habits.

Overall, Knittel emphasizes, the magnitude of cost savings suggested by the study, ranging from 2 percent to 7 percent, is significant. 

“Three percent is a big number,” Knittel says. “When you’re talking about the grid, 3 percent or 6 percent doesn’t sound like a lot. But when you’re multiplying it by 100 billion dollars, it becomes real money.”

When it comes to environmental impact, the modeling finds that the projected level of data center growth by 2030 would be very significant in terms of carbon dioxide emissions. Compared to a world with no data center growth, the study finds those emissions would rise by 58 percent in Texas, 20 percent in the Mid-Atlantic region, and by 24 percent in the western U.S. That underscores the need to be strategic about data center consumption. 

But the modeling also finds that the implications of data center buildout for clean-energy use vary by region. In Texas, where 54 percent of grid power is wind energy, having more data centers with flexible patterns of energy use could reduce emissions, by increasing demand for wind energy. The study finds that in this scenario, there could be 40 percent fewer CO2 emissions. 

However, in the Mid-Atlantic region, where there is a reasonable amount of solar energy but relatively less wind power, more data centers with flexible consumption patterns could increase both renewable energy and fossil-fuel energy consumption.  Here the modeling suggests an increase in CO2 emissions system-wide of 3 percent. 

“When data centers provide some flexibility in that latter scenario, the data centers actually move hours to when sun and wind energy production is slowing, and that allows a coal plant to stay on,” Knittel observes. “So it doesn’t necessarily attract more renewable investment. It attracts more coal investment.”

“That’s why we have policy”

For any of this to happen, however, the data centers would have to implement the flexible energy-use schedules modeled in the study. And it’s not clear that companies using data centers would be motivated to do that. To Knittel, this suggests officials might have to craft regulations in this area. 

“That’s why we have policy,” Knittel says.

More specifically, he adds, there is one big policy lever officials could use to achieve this goal: offering quicker initial hookups to the grid in return for time-of-use flexibility. 

“One big concern about these data centers now is how long it takes for them to connect to the grid,” Knittel says. “One way to provide flexibility now is what’s called ‘connect and manage,’ which is, connecting you faster to the grid if you agree to provide flexibility. Tech firms would take that deal. They would rather connect a year earlier, and throttle down computation a few hours a day, than to have to wait. We do this with power plants too.”

Certainly, Knittel adds, as firms competing with each other, “Tech companies say they won’t provide flexibility alone. But if everyone in the industry has to, it’s okay.” 

The current study is the first to examine the “end-to-end” implications of the centers for costs and emissions. The results, the scholars feel, bear further evaluation — and it is a topic they are continuing to model. 

“Those are two dimensions I think we should all be considering here,” Knittel says. “The end result is really up to us, and up to policy.” 

The research received support from the Future Energy Systems Center of the MIT Energy Initiative. 

Preventing adversaries from interfering with communications is crucial to national security. Tactical satellite communications (SATCOM) focus on securing reliable communications channels against adversaries in contested environments. In support of this mission, a team from MIT Lincoln Laboratory is building a prototype antenna characterized by low size, weight, power, and cost (SWaP-C).

Threats in contested environments — specifically proliferated low Earth orbit (pLEO), where satellites must be as low-SWaP as possible because of the high volume of satellites present — are signal jamming and signals intelligence. Mitigating these threats through methods such as changing the shape of antenna beams in real time so that the ground user's signals can't be interfered with, and preparing for future advanced capabilities, are key to ensuring that satellites stay in communication with users on the ground.

"Looking toward the future challenges of tactical SATCOM, there is a clear need for novel approaches to radio-frequency (RF) aperture designs that are scalable and low SWaP-C without sacrificing functionality," says Michael Craton, a technical staff member in Lincoln Laboratory's Tactical Satellite Communications Group. "That is, we want to think about ways we can achieve exquisite performance using less-expensive hardware. We want to anticipate future threats and have an idea about how to deal with them before they become a problem."

One way to tackle the challenge of proliferated interference and jamming is through adaptive antenna arrays. Unlike single-element antennas, arrays are made up of multiple antennas that work together to guide and shape energy to and from the array. Adaptive arrays can change beam states quickly (a technique called adaptive beamforming) and change them in real time, depending on conditions, to prevent interference in certain directions by placing nulls, or signals that interfere with others. However, adaptive arrays have high SWaP, making them difficult to operate in SWaP-constrained environments like pLEO.  

To address this problem, the team developed the Hosted Nimble Beamforming Anti-Jam Reflectarray (HoNi BAJR), a scanning reflectarray antenna prototype with a surface made up of reflective elements that can be individually controlled. When a signal hits the surface of the reflectarray, individual elements reflect energy with some phase shift to control the beam that is formed so that it blocks interference. Because the elements are very simple, the array can be scaled and controlled easily. Reflectarrays are similar to phased arrays, which consist of multiple elements that can be electronically controlled for quick beam changes, but scanning reflectarrays reflect signals toward a separate feed antenna, which eliminates much of the design complexity in conventional antenna arrays.

Unlike phased arrays that require amplifiers for each antenna element, reflectarrays do not require amplifiers because signals are collected by the feed antenna and combined in free space; this lack of amplifiers for each element in the reflectarray lowers the SWaP required and helps with scalability, as the beamforming network does not have to be redesigned each time the size of the array is changed. A reflectarray uses much less power than a typical array, dropping the power consumption by about 95 percent.  

The prototype HoNi BAJR reflectarray was designed for communications in a pLEO constellation with wide coverage across the horizon and can cater to low-power users in the presence of proliferated jamming. The array is sized to fit on a typical small satellite platform.

The HoNi BAJR team tested the array's beamforming capabilities at the laboratory's RF Systems Testing Facility, successfully demonstrating a high scan angle, which means the array can receive signals from a wide area. Their testing also showed that there is little loss in signal when synthesizing multipeak beams, or splitting the beam, indicating that reflectarrays can get signals to multiple users without information loss. 

Suppressing interference (unwanted signals from equipment like cell phone towers or electrical devices) is also very important to ensuring the antenna works correctly. The HoNi BAJR team's work in this area is based on two programs funded through an internally administered R&D portfolio: Deployable Electronically Scanning Reflectarray (DESRa) and Phase Analog Beamforming (PhAB, which uses DESRa hardware). PhAB demonstrated that it was possible to adapt to nulls and mitigate signal jamming in real time. However, in the dynamic signal environment of HoNi BAJR, there may not be time to adapt these beams fast enough for the signal environment. The team innovated a solution: creating regions of interference suppression, instead of targeting individual points of interference, by shaping the side lobes of the beam. The technique faltered slightly in testing because of difficulty in controlling the side lobes, as they're sensitive to small signal changes. However, proper calibration (measuring effects from the instruments and the system to ensure the full signal received and transmitted by the antenna is accounted for) may help.

While key to ensuring a system works correctly, calibration is one of the biggest challenges of operating reflectarrays. Not much precedent exists for calibrating a scanning reflectarray, so the team is researching approaches. All aspects of the reflectarray (e.g., forming and shaping beams) will be improved by calibration, and full usage of the array will require a comprehensive understanding of calibration. Another major area the team is exploring is where reflectarrays can best be used.

"Designing hardware is always a challenge, but figuring out how to fit the technology into a complete and functional system that meets mission needs is the hardest part," Craton says. "We believe scanning reflectarrays have a lot of untapped potential for the missions we care about, but because they have not been used in this space before, a lot of gaps in functionality remain. We need to first build up capabilities for the things that we need to do."

Early studies show that reflectarrays can be used in situations where beams are scheduled, where there is proliferated interference in less-dynamic signal environments (or dynamic signal environments, if you can achieve good calibration), and on power-constrained platforms. Future work will focus on further exploring how reflectarrays can be used, improving calibration procedures, and refining beamforming capabilities.

“Illuminating.” “Spectacular.” “Compelling.” This is how community college students described the two days they spent at MIT.nano learning about the complex tools inside the cleanroom and building and packaging their own functional photonic chips.

“Integrated photonics is an essential part of semiconductor packaging today,” says Anu Agarwal, principal research scientist in the Materials Research Laboratory at MIT. “But there is no single, standardized university curriculum for integrated electronics-photonics packaging. We need to create educational materials to teach this subject across the talent pipeline from K-12 and beyond, which is exactly what we’re doing at the Initiative for Knowledge and Innovation in Manufacturing (IKIM) and MIT.nano.”

As leader of the Lab for Education and Application Prototypes (LEAP) facility located on MIT.nano’s fifth floor, Agarwal stresses the importance of hands-on learning when studying integrated photonics, the science of guiding and manipulating light on a semiconductor chip. Through the Northeast Consortia for Advanced Integrated Silicon Technologies (NCAIST) program, she’s bringing community and four-year college students to MIT.nano for experimental boot camps that teach how to use semiconductor tools for electronic-photonic packaging and testing.

“Having a workforce skilled in resource-efficient semiconductor manufacturing, including electronic-photonic packaging, is critical to maintain the exponential growth of the chip industry and build national security,” says Agarwal. “MIT.nano, through programs like NCAIST, are helping to train more people in STEM.”

Working closely with AIM Photonics, a U.S. Manufacturing Innovation Institute, NCAIST coordinates and accelerates the transition of technician education content and teaching methodologies from key AIM-affiliated U.S. universities to community, technical, and four-year colleges in the Northeast. Through NCAIST, in Massachusetts, the Massachusetts Bay Community College (MBCC) is paired with MIT, North Shore Community College (NSCC) with Stonehill College, and Springfield Technical Community College (STCC) with Western New England University.

“The NCAIST program offers a transformative opportunity for our community college students to experience hands-on training at MIT.nano’s LEAP facility,” says Marina Bograd, professor and chair of the engineering department at MassBay Community College. “For many of them, this is their first time stepping into a cleanroom or seeing semiconductor manufacturing up close. The experience helps open doors that might otherwise feel out of reach, builds confidence, and inspires our students to see themselves pursuing careers in emerging technologies.”

The most recent MIT.nano boot camp, held on May 20-21, expanded participation to include not only those from MBCC, but also students from NSCC, Stonehill College, and SUNY Polytechnic Institute, where NCAIST is headquartered. Twelve students spent two full days at MIT.nano operating a die saw, die bonder, wire bonder, and flip chip tool to build and test a packaged chip.

“I found the combination of hands-on activities, lectures, and informal discussion with the MIT.nano team and fellow students fostered an awesome learning environment,” says Cari Caudill, a student at NSCC. “As a mechanical engineering student, I was most interested in packaging and the machines themselves, so I loved getting direct experience with the tools and discussing with our instructors how procedural and technological development has impacted precision, efficiency, and scalability in the semiconductor industry.”

"The NCAIST boot camp was an exciting and illuminating experience!” adds MassBay Community College student Wyatt Maurer. “I really appreciated getting the chance to work with semiconductor manufacturing tools and to learn about the future of photonics from leaders in the field.”

Students attended lectures on cleanroom safety by Kristofor Payer, assistant director of operations at MIT.nano; electronic-photonic packaging by Agarwal; and photonic integrated circuit sensing by Department of Materials Science and Engineering graduate student Lizzie Gower. They were also offered virtual reality (VR) simulation exercises by Sajan Saini, the director of education at IKIM, to help build intuition about photonic devices and semiconductor packaging tools. These VR simulations serve as a foundational tool to help students visualize photonic devices and complex tool mechanics, as well as run digital process steps and deepen their technical understanding. By bridging physical fabrication with advanced simulation resources, the LEAP students are mastering highly specialized manufacturing, assembly, and testing pipelines required to build the future of electronic-photonic integration.

“The experience at this boot camp not only strengthens our student technical skills, it helps them see themselves as future contributors to a rapidly evolving field,” says Mary Beth Steigerwald, professor and engineering department chair at North Shore Community College. “It also enriches their professional portfolios and gives them a stronger, more compelling story to share during internship and transfer interviews.”

The students will use this training to secure summer internships at hard technology companies. Several have also been accepted to four-year degree programs to continue their education in the fall.

Every summer for the past 13 years, students in MIT’s club dynaMIT have taught STEM principles to Boston-area middle school students at no cost, all in an effort to inspire the next generation of innovators.

In August, dynaMIT will welcome two cohorts of budding scientists and engineers to campus. First, 40 middle schoolers in grades 6–7 will dive into hands-on STEM learning through creative activities like solar s'mores and paper rockets. The following week, another 40 students in grades 8–9 will join in, exploring innovative experiments that spark curiosity and creative problem-solving. Each day, a new topic is covered, exposing attendees to chemistry, machine learning, physics, math, biology, and earth and space science.

Several of the program's attendees have gone on to apply and be accepted to MIT, including the club’s co-director, Dominique Dang. When the Quincy, Massachusetts, native saw the club’s table at the Midway Fair, she knew she wanted to join to give back.

“I didn’t receive a lot of STEM exposure in middle school, but then I saw online about the STEM program offered by dynaMIT, and I was really interested. I had so much fun, and it introduced me to creating things, and not just reading about them in a textbook. I knew I wanted to be a scientist, but I didn’t know what type of science I wanted to study, so having dynaMIT expose me to a different STEM topic each day was a transformative experience,” says Dang, who is now studying computer science and molecular biology.

Megan Zhu, the club’s other co-director, was immediately drawn to the organization’s educational mission. A biology major with plans to pursue an MD/PhD program, Zhu is passionate about advancing science education and aspires to teach at the university level upon completing her degree.

“I happened to stop by the dynaMIT table at the club fair, and it seemed really cool. I spoke to a couple of the club leaders, and they talked about how they help support education in the Boston area. Education has always been something that I was passionate about in my hometown in Rapid City, South Dakota, and I wanted to emphasize giving back to the community,” says Zhu.

Lukeman Nouri, who grew up in Saugus, Massachusetts, attended dynaMIT as a sixth grader. “I barely knew what MIT was, or even what STEM meant, so I wasn't particularly excited to go. However, that changed after the very first day of the program! I remember extracting DNA from a strawberry, making elephant toothpaste, and gathering fingerprints from various surfaces. However, my biggest highlight was learning Scratch and creating my very first game,” says Nouri, who is majoring in computer science and engineering. “After dynaMIT, MIT became my dream college, and I spent the next six years learning more about STEM and MIT.”

Erick Liang, who grew up in Boston’s Chinatown and Roslindale neighborhoods and is now majoring in nuclear science and engineering and physics, had a similar experience after attending dynaMIT. “As a first-generation, low-income student, having a meaningful and engaging program like dynaMIT to participate in over the summer was really important for me. DynaMIT exposed me to different fields of science I had not encountered yet in elementary or middle school and helped spark my interest in STEM,” says Liang.

Zhu says this year they are adding a new activity related to climate change and clean water that they hope will create an interest in these two important areas. “This summer, one of our activities is called Sponge City. It’s about runoff water and clean, reusable water. We’ll have the students build a city that can withstand a storm. They will be given a budget and have to decide how to spend the resources after we pour water all over the tray containing their city — all in an effort to show them how important climate change and clean drinking water are.”

The club is also partnering with the Koch Institute for Integrative Cancer Research at MIT and will tour lab space and work on a fun experiment about cell heterogeneity and cancer tumor formation. Attendees will then be able to talk to scientists and ask them questions.

“I’m looking forward to giving this cohort the same great experience that I had six summers ago. DynaMIT was so much fun, and I learned so much from it that I feel a responsibility to help make it just as impactful for future students,” says Nouri.

Liang adds, “I am excited to return and help set up the plasma demo kits for the program’s physics day!”

“It’s a great full-circle moment,” says Dang. “That’s just one of the reasons why I joined the club.”

“Watching the students work on the activities is always the most rewarding part of the two weeks, and that makes the entire year of planning worth it,” says Zhu, adding, “the club is also an excellent community at MIT.”

Students interested in joining dynaMIT or volunteering for this summer’s program can find more information on the club’s website.

Imagine working at a warehouse or office sometime in the near future, and you’re asked to help a new trainee learn the basics of their job. The catch: It’s a robot. To teach them, you might want to play a game of “show and tell” — that is, physically showing how to do something a few different ways, while also explaining what you’re doing.

Let’s say you asked the robot to place some coffee on your desk without disturbing you during a Zoom call. You’ll prefer that the robot doesn’t get too close to you and the laptop so that it doesn’t interrupt your meeting. To enable this behavior, the robot should be trained with data that clearly demonstrates the full task. Computer scientists have attempted to explain manipulation tasks to robots by recording lots of physical demonstrations or writing extensive directions. But if you don’t have both, the machine is likely to misunderstand what it needs to do.

It’s laborious for humans to do all that showing and telling, so researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have automated the process of teaching a robot, while clarifying instructions automatically and using nearly five times less demonstration data. Their “Masked Inverse Reinforcement Learning” (Masked IRL) approach uses a large language model (LLM) to elaborate on ambiguous prompts based on the data collected from a user’s demo. Another LLM then narrows down which details an algorithm should incorporate into a motion plan, so that a robot can safely complete chores in homes, offices, and factories.

“Our approach could come in handy when a human interacts with a robot but doesn’t want to spell out all the details of a task,” says MIT PhD student and CSAIL researcher Minyoung Hwang, who is a lead author on a paper presenting the project. “We’re minimizing human effort by enabling machines to get to the bottom of what users really want.”

According to Hwang, Masked IRL can help robots safely maneuver in settings where there are elements a human might not describe in a prompt, but that are crucial nonetheless. For example, a machine grabbing you a snack from the kitchen may not know to avoid bumping into your laptop. Likewise, a factory robot placing items into different boxes must carefully navigate around shelves.

To learn new tasks in these situations, Masked IRL uses the robot’s sensors to capture information about its surroundings. These components also log each movement of a kinesthetic demonstration — a training approach where a human physically moves a robot to do a specific action. It’s sort of like being the machine’s physical therapist, bending joints in a particular direction to show a robot how to grab, move, and place objects.

MIT’s system then calls on an LLM to compare this sequence of motions (called a trajectory) to the shortest possible path. The model also elaborates on what might be unclear in a prompt, turning a request like “stay close” into “stay close to the surface of the table.” Using the trajectory comparison and clarified directions, the LLM begins to understand why the motions it was trained on are important to the task. 

A second LLM then evaluates details of the environment, such as the position of obstacles and the shape of the robot’s target object. During this process, it “masks” (in other words, ignores) the elements it deems irrelevant to the task at hand, scoring each one as either a “1” (important) or “0” (not so much). For example, whether or not a user was leaning on a table during a demonstration would be a “0,” making it irrelevant. Any detail considered a “1” is incorporated into the final action plan by an algorithm.

These masks gave Masked IRL a key advantage over comparable baselines in both 3D and real-world demos because it taught a robot which information to prioritize. Thanks to the researchers’ system, virtual and real robots alike were able to skillfully maneuver objects around obstacles, such as moving a coffee mug around a laptop to different spots on a table. In these tasks, Masked IRL correctly identified users’ preferences, which they didn’t explicitly state in their prompts, up to 15 percent more often than comparable baselines.

During simulation experiments, CSAIL researchers also found that Masked IRL was a fast learner. It required fewer demos to understand how to move the mug than its baselines. They also found that the robots performed better when an LLM cleared up instructions, instead of having the machine try to follow a vague request.

This more focused approach also translated well to a real robotic arm, executing prompts the system hadn’t seen during its training phase. After being trained on 50 kinesthetic demonstrations, the robot carefully moved a cup toward a human while avoiding colliding with a user’s computer — an obstacle it learned to avoid by elaborating on a more general request to “stay away.” It also wiped a table down while “staying close” to it, and handed a user a bag of chips while “staying away” from both a human and a table.

Masked IRL senses and explains what users leave unsaid, but soon, it might “see” it too. CSAIL researchers plan to make their approach more dynamic by equipping it with cameras, allowing a robot to take images of its surroundings. Then it could highlight and focus on specific elements nearby. For example, if you asked the machine to pick up a toy, it might see some bananas nearby and ignore them before handling its target object.

Hwang wrote the paper with three CSAIL colleagues: PhD student Alexandra Forsey-Smerek ’20, SM ’22; postdoc Nathaniel Dennler; and MIT Assistant Professor Andreea Bobu, who is a member of the Department of Aeronautics and Astronautics and CSAIL. Their work was supported, in part, by the Tata Group via the MIT Generative AI Impact Consortium Award, and the Department of Defense. They’ll present the project at the 2026 IEEE International Conference on Robotics and Automation in June.

A database of almost a million passports from around the world was leaked online.

Note what happened. A high-value credential—a passport—was used in an ancillary low-value authentication system: ID verification for cannabis dispensaries. And it’s the low-value system that got hacked, putting the high-value credential at risk.

But how they do so varies from state to state.

Republican legislation would grant the oil and gas industry immunity from litigation that seeks compensation for the costs of climate change.

Deb Haaland, the Interior secretary under former President Joe Biden, is set to face Republican nominee Gregg Hull in November.

The Department of Energy would have to distribute funding for state energy and weatherization programs on a set timeline.

The decision fell short of requests from climate organizations who brought the lawsuit to force the company to reduce its oil and gas production.

Almost half of the 27 EU member states now support delaying the rules.