Norway is the world’s largest producer of farmed Atlantic salmon and a top exporter of seafood, while the United States remains the largest importer of these products, according to the Food and Agriculture Organization. Two MIT students recently traveled to Trondheim, Norway to explore the cutting-edge technologies being developed and deployed in offshore aquaculture. 

Beckett Devoe, a senior in artificial intelligence and decision-making, and Tony Tang, a junior in mechanical engineering, first worked with MIT Sea Grant through the Undergraduate Research Opportunities Program (UROP). They contributed to projects focusing on wave generator design and machine learning applications for analyzing oyster larvae health in hatcheries. While near-shore aquaculture is a well-established industry across Massachusetts and the United States, open-ocean farming is still a nascent field here, facing unique and complex challenges. 

To help better understand this emerging industry, MIT Sea Grant created a collaborative initiative, AquaCulture Shock, with funding from an Aquaculture Technologies and Education Travel Grant through the National Sea Grant College Program. Collaborating with the MIT-Scandinavia MISTI (MIT International Science and Technology Initiatives) program, MIT Sea Grant matched Devoe and Tang with aquaculture-related summer internships at SINTEF Ocean, one of the largest research institutes in Europe. 

“The opportunity to work on this hands-on aquaculture project, under a world-renowned research institution, in an area of the world known for its innovation in marine technology — this is what MISTI is all about,” says Madeline Smith, managing director for MIT-Scandinavia. “Not only are students gaining valuable experience in their fields of study, but they’re developing cultural understanding and skills that equip them to be future global leaders.” Both students worked within SINTEF Ocean’s Aquaculture Robotics and Autonomous Systems Laboratory (ACE-Robotic Lab), a facility designed to develop and test new aquaculture technologies. 

“Norway has this unique geography where it has all of these fjords,” says Sveinung Ohrem, research manager for the Aquaculture Robotics and Automation Group at SINTEF Ocean. “So you have a lot of sheltered waters, which makes it ideal to do sea-based aquaculture.” He estimates that there are about a thousand fish farms along Norway’s coast, and walks through some of the tools being used in the industry: decision-making systems to gather and visualize data for the farmers and operators; robots for inspection and cleaning; environmental sensors to measure oxygen, temperature, and currents; echosounders that send out acoustic signals to track where the fish are; and cameras to help estimate biomass and fine-tune feeding. “Feeding is a huge challenge,” he notes. “Feed is the largest cost, by far, so optimizing feeding leads to a very significant decrease in your cost.”

During the internship, Devoe focused on a project that uses AI for fish feeding optimization. “I try to look at the different features of the farm — so maybe how big the fish are, or how cold the water is ... and use that to try to give the farmers an optimal feeding amount for the best outcomes, while also saving money on feed,” he explains. “It was good to learn some more machine learning techniques and just get better at that on a real-world project.” 

In the same lab, Tang worked on the simulation of an underwater vehicle-manipulator system to navigate farms and repair damage on cage nets with a robotic arm. Ohrem says there are thousands of aquaculture robots operating in Norway today. “The scale is huge,” he says. “You can’t have 8,000 people controlling 8,000 robots — that’s not economically or practically feasible. So the level of autonomy in all of these robots needs to be increased.”

The collaboration between MIT and SINTEF Ocean began in 2023 when MIT Sea Grant hosted Eleni Kelasidi, a visiting research scientist from the ACE-Robotic Lab. Kelasidi collaborated with MIT Sea Grant director Michael Triantafyllou and professor of mechanical engineering Themistoklis Sapsis developing controllers, models, and underwater vehicles for aquaculture, while also investigating fish-machine interactions. 

“We have had a long and fruitful collaboration with the Norwegian University of Science and Technology (NTNU) and SINTEF, which continues with important efforts such as the aquaculture project with Dr. Kelasidi,” Triantafyllou says. “Norway is at the forefront of offshore aquaculture and MIT Sea Grant is investing in this field, so we anticipate great results from the collaboration.”

Kelasidi, who is now a professor at NTNU, also leads the Field Robotics Lab, focusing on developing resilient robotic systems to operate in very complex and harsh environments. “Aquaculture is one of the most challenging field domains we can demonstrate any autonomous solutions, because everything is moving,” she says. Kelasidi describes aquaculture as a deeply interdisciplinary field, requiring more students with backgrounds both in biology and technology. “We cannot develop technologies that are applied for industries where we don’t have biological components,” she explains, “and then apply them somewhere where we have a live fish or other live organisms.” 

Ohrem affirms that maintaining fish welfare is the primary driver for researchers and companies operating in aquaculture, especially as the industry continues to grow. “So the big question is,” he says, “how can you ensure that?” SINTEF Ocean has four research licenses for farming fish, which they operate through a collaboration with SalMar, the second-largest salmon farmer in the world. The students had the opportunity to visit one of the industrial-scale farms, Singsholmen, on the island of Hitra. The farm has 10 large, round net pens about 50 meters across that extend deep below the surface, each holding up to 200,000 salmon. “I got to physically touch the nets and see how the [robotic] arm might be able to fix the net,” says Tang. 

Kelasidi emphasizes that the information gained in the field cannot be learned from the office or lab. “That opens up and makes you realize, what is the scale of the challenges, or the scale of the facilities,” she says. She also highlights the importance of international and institutional collaboration to advance this field of research and develop more resilient robotic systems. “We need to try to target that problem, and let’s solve it together.”

MIT Sea Grant and the MIT-Scandinavia MISTI program are currently recruiting a new cohort of four MIT students to intern in Norway this summer with institutes advancing offshore farming technologies, including NTNU’s Field Robotics Lab in Trondheim. Students interested in autonomy, deep learning, simulation modeling, underwater robotic systems, and other aquaculture-related areas are encouraged to reach out to Lily Keyes at MIT Sea Grant.

Advancements in battery innovation are transforming both mobility and energy systems alike, according to Kurt Kelty, vice president of battery, propulsion, and sustainability at General Motors (GM). At the MIT Energy Initiative (MITEI) Fall Colloquium, Kelty explored how GM is bringing next-generation battery technologies from lab to commercialization, driving American battery innovation forward. The colloquium is part of the ongoing MITEI Presents: Advancing the Energy Transition speaker series.

At GM, Kelty’s team is primarily focused on three things: first, improving affordability to get more electric vehicles (EVs) on the road. “How do you drive down the cost?” Kelty asked the audience. “It's the batteries. The batteries make up about 30 percent of the cost of the vehicle.” Second, his team strives to improve battery performance, including charging speed and energy density. Third, they are working on localizing the supply chain. “We've got to build up our resilience and our independence here in North America, so we're not relying on materials coming from China,” Kelty explained.

To aid their efforts, resources are being poured into the virtualization space, significantly cutting down on time dedicated to research and development. Now, Kelty’s team can do modeling up front using artificial intelligence, reducing what previously would have taken months to a couple of days.

“If you want to modify … the nickel content ever so slightly, we can very quickly model: ‘OK, how’s that going to affect the energy density? The safety? How’s that going to affect the charge capability?’” said Kelty. “We can look at that at the cell level, then the pack level, then the vehicle level.”

Kelty revealed that they have found a solution that addresses affordability, accessibility, and commercialization: lithium manganese-rich (LMR) batteries. Previously, the industry looked to reduce costs by lowering the amount of cobalt in batteries by adding greater amounts of nickel. These high-nickel batteries are in most cars on the road in the United States due to their high range. LMR batteries, though, take things a step further by reducing the amount of nickel and adding more manganese, which drives the cost of batteries down even further while maintaining range.

Lithium-iron-phosphate (LFP) batteries are the chemistry of choice in China, known for low cost, high cycle life, and high safety. With LMR batteries, the cost is comparable to LFP with a range that is closer to high-nickel. “That’s what’s really a breakthrough,” said Kelty.

LMR batteries are not new, but there have been challenges to adopting them, according to Kelty. “People knew about it, but they didn’t know how to commercialize it. They didn’t know how to make it work in an EV,” he explained. Now that GM has figured out commercialization, they will be the first to market these batteries in their EVs in 2028.

Kelty also expressed excitement over the use of vehicle-to-grid technologies in the future. Using a bidirectional charger with a two-way flow of energy, EVs could charge, but also send power from their batteries back to the electrical grid. This would allow customers to charge “their vehicles at night when the electricity prices are really low, and they can discharge it during the day when electricity rates are really high,” he said.

In addition to working in the transportation sector, GM is exploring ways to extend their battery expertise into applications in grid-scale energy storage. “It’s a big market right now, but it’s growing very quickly because of the data center growth,” said Kelty.

When looking to the future of battery manufacturing and EVs in the United States, Kelty remains optimistic: “we’ve got the technology here to make it happen. We’ve always had the innovation here. Now, we’re getting more and more of the manufacturing. We’re getting that all together. We’ve got just tremendous opportunity here that I’m hopeful we’re going to be able to take advantage of and really build a massive battery industry here.”

This speaker series highlights energy experts and leaders at the forefront of the scientific, technological, and policy solutions needed to transform our energy systems. Visit MITEI’s Events page for more information on this and additional events.

“MIT hasn’t just prepared me for the future of work — it’s pushed me to study it. As AI systems become more capable, more of our online activity will be carried out by artificial agents. That raises big questions: How should we design these systems to understand our preferences? What happens when AI begins making many of our decisions?”

These are some of the questions MIT Sloan School of Management PhD candidate Benjamin Manning is researching. Part of his work investigates how to design and evaluate artificial intelligence agents that act on behalf of people, and how their behavior shapes markets and institutions. 

Previously, he received a master’s degree in public policy from the Harvard Kennedy School and a bachelor’s in mathematics from Washington University in St. Louis. After working as a research assistant, Manning knew he wanted to pursue an academic career.

“There’s no better place in the world to study economics and computer science than MIT,” he says. “Nobel and Turing award winners are everywhere, and the IT group lets me explore both fields freely. It was my top choice — when I was accepted, the decision was clear.” 

After receiving his PhD, Manning hopes to secure a faculty position at a business school and do the same type of work that MIT Sloan professors — his mentors — do every day.

“Even in my fourth year, it still feels surreal to be an MIT student. I don’t think that feeling will ever fade. My mom definitely won’t ever get over telling people about it.”

Of his MIT Sloan experience, Manning says he didn’t know it was possible to learn so much so quickly. “It’s no exaggeration to say I learned more in my first year as a PhD candidate than in all four years of undergrad. While the pace can be intense, wrestling with so many new ideas has been incredibly rewarding. It’s given me the tools to do novel research in economics and AI — something I never imagined I’d be capable of.”

As an economist studying AI simulations of humans, for Manning, the future of work not only means understanding how AI acts on our behalf, but also radically improving and accelerating social scientific discovery.

“Another part of my research agenda explores how well AI systems can simulate human responses. I envision a future where researchers test millions of behavioral simulations in minutes, rapidly prototyping experimental designs, and identifying promising research directions before investing in costly human studies. This isn’t about replacing human insight, but amplifying it: Scientists can focus on asking better questions, developing theory, and interpreting results while AI handles the computational heavy lifting.”

He’s excited by the prospect: “We are possibly moving toward a world where the pace of understanding may get much closer to the speed of economic change.”

Our muscles are nature’s actuators. The sinewy tissue is what generates the forces that make our bodies move. In recent years, engineers have used real muscle tissue to actuate “biohybrid robots” made from both living tissue and synthetic parts. By pairing lab-grown muscles with synthetic skeletons, researchers are engineering a menagerie of muscle-powered crawlers, walkers, swimmers, and grippers.

But for the most part, these designs are limited in the amount of motion and power they can produce. Now, MIT engineers are aiming to give bio-bots a power lift with artificial tendons.

In a study appearing today in the journal Advanced Science, the researchers developed artificial tendons made from tough and flexible hydrogel. They attached the rubber band-like tendons to either end of a small piece of lab-grown muscle, forming a “muscle-tendon unit.” Then they connected the ends of each artificial tendon to the fingers of a robotic gripper.

When they stimulated the central muscle to contract, the tendons pulled the gripper’s fingers together. The robot pinched its fingers together three times faster, and with 30 times greater force, compared with the same design without the connecting tendons.

The researchers envision the new muscle-tendon unit can be fit to a wide range of biohybrid robot designs, much like a universal engineering element.

“We are introducing artificial tendons as interchangeable connectors between muscle actuators and robotic skeletons,” says lead author Ritu Raman, an assistant professor of mechanical engineering (MechE) at MIT. “Such modularity could make it easier to design a wide range of robotic applications, from microscale surgical tools to adaptive, autonomous exploratory machines.”

The study’s MIT co-authors include graduate students Nicolas Castro, Maheera Bawa, Bastien Aymon, Sonika Kohli, and Angel Bu; undergraduate Annika Marschner; postdoc Ronald Heisser; alumni Sarah J. Wu ’19, SM ’21, PhD ’24 and Laura Rosado ’22, SM ’25; and MechE professors Martin Culpepper and Xuanhe Zhao.

Muscle’s gains

Raman and her colleagues at MIT are at the forefront of biohybrid robotics, a relatively new field that has emerged in the last decade. They focus on combining synthetic, structural robotic parts with living muscle tissue as natural actuators.

“Most actuators that engineers typically work with are really hard to make small,” Raman says. “Past a certain size, the basic physics doesn’t work. The nice thing about muscle is, each cell is an independent actuator that generates force and produces motion. So you could, in principle, make robots that are really small.”

Muscle actuators also come with other advantages, which Raman’s team has already demonstrated: The tissue can grow stronger as it works out, and can naturally heal when injured. For these reasons, Raman and others envision that muscly droids could one day be sent out to explore environments that are too remote or dangerous for humans. Such muscle-bound bots could build up their strength for unforeseen traverses or heal themselves when help is unavailable. Biohybrid bots could also serve as small, surgical assistants that perform delicate, microscale procedures inside the body.

All these future scenarios are motivating Raman and others to find ways to pair living muscles with synthetic skeletons. Designs to date have involved growing a band of muscle and attaching either end to a synthetic skeleton, similar to looping a rubber band around two posts. When the muscle is stimulated to contract, it can pull the parts of a skeleton together to generate a desired motion.

But Raman says this method produces a lot of wasted muscle that is used to attach the tissue to the skeleton rather than to make it move. And that connection isn’t always secure. Muscle is quite soft compared with skeletal structures, and the difference can cause muscle to tear or detach. What’s more, it is often only the contractions in the central part of the muscle that end up doing any work — an amount that’s relatively small and generates little force.

“We thought, how do we stop wasting muscle material, make it more modular so it can attach to anything, and make it work more efficiently?” Raman says. “The solution the body has come up with is to have tendons that are halfway in stiffness between muscle and bone, that allow you to bridge this mechanical mismatch between soft muscle and rigid skeleton. They’re like thin cables that wrap around joints efficiently.”

“Smartly connected”

In their new work, Raman and her colleagues designed artificial tendons to connect natural muscle tissue with a synthetic gripper skeleton. Their material of choice was hydrogel — a squishy yet sturdy polymer-based gel. Raman obtained hydrogel samples from her colleague and co-author Xuanhe Zhao, who has pioneered the development of hydrogels at MIT. Zhao’s group has derived recipes for hydrogels of varying toughness and stretch that can stick to many surfaces, including synthetic and biological materials.

To figure out how tough and stretchy artificial tendons should be in order to work in their gripper design, Raman’s team first modeled the design as a simple system of three types of springs, each representing the central muscle, the two connecting tendons, and the gripper skeleton. They assigned a certain stiffness to the muscle and skeleton, which were previously known, and used this to calculate the stiffness of the connecting tendons that would be required in order to move the gripper by a desired amount.

From this modeling, the team derived a recipe for hydrogel of a certain stiffness. Once the gel was made, the researchers carefully etched the gel into thin cables to form artificial tendons. They attached two tendons to either end of a small sample of muscle tissue, which they grew using lab-standard techniques. They then wrapped each tendon around a small post at the end of each finger of the robotic gripper — a skeleton design that was developed by MechE professor Martin Culpepper, an expert in designing and building precision machines.

When the team stimulated the muscle to contract, the tendons in turn pulled on the gripper to pinch its fingers together. Over multiple experiments, the researchers found that the muscle-tendon gripper worked three times faster and produced 30 times more force compared to when the gripper is actuated just with a band of muscle tissue (and without any artificial tendons). The new tendon-based design also was able to keep up this performance over 7,000 cycles, or muscle contractions.

Overall, Raman saw that the addition of artificial tendons increased the robot’s power-to-weight ratio by 11 times, meaning that the system required far less muscle to do just as much work.

“You just need a small piece of actuator that’s smartly connected to the skeleton,” Raman says. “Normally, if a muscle is really soft and attached to something with high resistance, it will just tear itself before moving anything. But if you attach it to something like a tendon that can resist tearing, it can really transmit its force through the tendon, and it can move a skeleton that it wouldn’t have been able to move otherwise.”

The team’s new muscle-tendon design successfully merges biology with robotics, says biomedical engineer Simone Schürle-Finke, associate professor of health sciences and technology at ETH Zürich.

“The tough-hydrogel tendons create a more physiological muscle–tendon–bone architecture, which greatly improves force transmission, durability, and modularity,” says Schürle-Finke, who was not involved with the study. “This moves the field toward biohybrid systems that can operate repeatably and eventually function outside the lab.”

With the new artificial tendons in place, Raman’s group is moving forward to develop other elements, such as skin-like protective casings, to enable muscle-powered robots in practical, real-world settings.

This research was supported, in part, by the U.S. Department of Defense Army Research Office, the MIT Research Support Committee, and the National Science Foundation.

Large language models (LLMs) sometimes learn the wrong lessons, according to an MIT study.

Rather than answering a query based on domain knowledge, an LLM could respond by leveraging grammatical patterns it learned during training. This can cause a model to fail unexpectedly when deployed on new tasks.

The researchers found that models can mistakenly link certain sentence patterns to specific topics, so an LLM might give a convincing answer by recognizing familiar phrasing instead of understanding the question.

Their experiments showed that even the most powerful LLMs can make this mistake.

This shortcoming could reduce the reliability of LLMs that perform tasks like handling customer inquiries, summarizing clinical notes, and generating financial reports.

It could also have safety risks. A nefarious actor could exploit this to trick LLMs into producing harmful content, even when the models have safeguards to prevent such responses.

After identifying this phenomenon and exploring its implications, the researchers developed a benchmarking procedure to evaluate a model’s reliance on these incorrect correlations. The procedure could help developers mitigate the problem before deploying LLMs.

“This is a byproduct of how we train models, but models are now used in practice in safety-critical domains far beyond the tasks that created these syntactic failure modes. If you’re not familiar with model training as an end-user, this is likely to be unexpected,” says Marzyeh Ghassemi, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), a member of the MIT Institute of Medical Engineering Sciences and the Laboratory for Information and Decision Systems, and the senior author of the study.

Ghassemi is joined by co-lead authors Chantal Shaib, a graduate student at Northeastern University and visiting student at MIT; and Vinith Suriyakumar, an MIT graduate student; as well as Levent Sagun, a research scientist at Meta; and Byron Wallace, the Sy and Laurie Sternberg Interdisciplinary Associate Professor and associate dean of research at Northeastern University’s Khoury College of Computer Sciences. A paper describing the work will be presented at the Conference on Neural Information Processing Systems.

Stuck on syntax

LLMs are trained on a massive amount of text from the internet. During this training process, the model learns to understand the relationships between words and phrases — knowledge it uses later when responding to queries.

In prior work, the researchers found that LLMs pick up patterns in the parts of speech that frequently appear together in training data. They call these part-of-speech patterns “syntactic templates.”

LLMs need this understanding of syntax, along with semantic knowledge, to answer questions in a particular domain.

“In the news domain, for instance, there is a particular style of writing. So, not only is the model learning the semantics, it is also learning the underlying structure of how sentences should be put together to follow a specific style for that domain,” Shaib explains.   

But in this research, they determined that LLMs learn to associate these syntactic templates with specific domains. The model may incorrectly rely solely on this learned association when answering questions, rather than on an understanding of the query and subject matter.

For instance, an LLM might learn that a question like “Where is Paris located?” is structured as adverb/verb/proper noun/verb. If there are many examples of sentence construction in the model’s training data, the LLM may associate that syntactic template with questions about countries.

So, if the model is given a new question with the same grammatical structure but nonsense words, like “Quickly sit Paris clouded?” it might answer “France” even though that answer makes no sense.

“This is an overlooked type of association that the model learns in order to answer questions correctly. We should be paying closer attention to not only the semantics but the syntax of the data we use to train our models,” Shaib says.

Missing the meaning

The researchers tested this phenomenon by designing synthetic experiments in which only one syntactic template appeared in the model’s training data for each domain. They tested the models by substituting words with synonyms, antonyms, or random words, but kept the underlying syntax the same.

In each instance, they found that LLMs often still responded with the correct answer, even when the question was complete nonsense.

When they restructured the same question using a new part-of-speech pattern, the LLMs often failed to give the correct response, even though the underlying meaning of the question remained the same.

They used this approach to test pre-trained LLMs like GPT-4 and Llama, and found that this same learned behavior significantly lowered their performance.

Curious about the broader implications of these findings, the researchers studied whether someone could exploit this phenomenon to elicit harmful responses from an LLM that has been deliberately trained to refuse such requests.

They found that, by phrasing the question using a syntactic template the model associates with a “safe” dataset (one that doesn’t contain harmful information), they could trick the model into overriding its refusal policy and generating harmful content.

“From this work, it is clear to me that we need more robust defenses to address security vulnerabilities in LLMs. In this paper, we identified a new vulnerability that arises due to the way LLMs learn. So, we need to figure out new defenses based on how LLMs learn language, rather than just ad hoc solutions to different vulnerabilities,” Suriyakumar says.

While the researchers didn’t explore mitigation strategies in this work, they developed an automatic benchmarking technique one could use to evaluate an LLM’s reliance on this incorrect syntax-domain correlation. This new test could help developers proactively address this shortcoming in their models, reducing safety risks and improving performance.

In the future, the researchers want to study potential mitigation strategies, which could involve augmenting training data to provide a wider variety of syntactic templates. They are also interested in exploring this phenomenon in reasoning models, special types of LLMs designed to tackle multi-step tasks.

“I think this is a really creative angle to study failure modes of LLMs. This work highlights the importance of linguistic knowledge and analysis in LLM safety research, an aspect that hasn’t been at the center stage but clearly should be,” says Jessy Li, an associate professor at the University of Texas at Austin, who was not involved with this work.

This work is funded, in part, by a Bridgewater AIA Labs Fellowship, the National Science Foundation, the Gordon and Betty Moore Foundation, a Google Research Award, and Schmidt Sciences.

More than 300 people across academia and industry spilled into an auditorium to attend a BoltzGen seminar on Thursday, Oct. 30, hosted by the Abdul Latif Jameel Clinic for Machine Learning in Health (MIT Jameel Clinic). Headlining the event was MIT PhD student and BoltzGen’s first author Hannes Stärk, who had announced BoltzGen just a few days prior.

Building upon Boltz-2, an open-source biomolecular structure prediction model predicting protein binding affinity that made waves over the summer, BoltzGen (officially released on Sunday, Oct. 26.) is the first model of its kind to go a step further by generating novel protein binders that are ready to enter the drug discovery pipeline.

Three key innovations make this possible: first, BoltzGen’s ability to carry out a variety of tasks, unifying protein design and structure prediction while maintaining state-of-the-art performance. Next, BoltzGen’s built-in constraints are designed with feedback from wetlab collaborators to ensure the model creates functional proteins that don’t defy the laws of physics or chemistry. Lastly, a rigorous evaluation process tests the model on “undruggable” disease targets, pushing the limits of BoltzGen’s binder generation capabilities.

Most models used in industry or academia are capable of either structure prediction or protein design. Moreover, they’re limited to generating certain types of proteins that bind successfully to easy “targets.” Much like students responding to a test question that looks like their homework, as long as the training data looks similar to the target during binder design, the models often work. But existing methods are nearly always evaluated on targets for which structures with binders already exist, and end up faltering in performance when used on more challenging targets.

“There have been models trying to tackle binder design, but the problem is that these models are modality-specific,” Stärk points out. “A general model does not only mean that we can address more tasks. Additionally, we obtain a better model for the individual task since emulating physics is learned by example, and with a more general training scheme, we provide more such examples containing generalizable physical patterns.”

The BoltzGen researchers went out of their way to test BoltzGen on 26 targets, ranging from therapeutically relevant cases to ones explicitly chosen for their dissimilarity to the training data. 

This comprehensive validation process, which took place in eight wetlabs across academia and industry, demonstrates the model’s breadth and potential for breakthrough drug development.

Parabilis Medicines, one of the industry collaborators that tested BoltzGen in a wetlab setting, praised BoltzGen’s potential: “we feel that adopting BoltzGen into our existing Helicon peptide computational platform capabilities promises to accelerate our progress to deliver transformational drugs against major human diseases.”

While the open-source releases of Boltz-1, Boltz-2, and now BoltzGen (which was previewed at the 7th Molecular Machine Learning Conference on Oct. 22) bring new opportunities and transparency in drug development, they also signal that biotech and pharmaceutical industries may need to reevaluate their offerings. 

Amid the buzz for BoltzGen on the social media platform X, Justin Grace, a principal machine learning scientist at LabGenius, raised a question. “The private-to-open performance time lag for chat AI systems is [seven] months and falling,” Grace wrote in a post. “It looks to be even shorter in the protein space. How will binder-as-a-service co’s be able to [recoup] investment when we can just wait a few months for the free version?” 

For those in academia, BoltzGen represents an expansion and acceleration of scientific possibility. “A question that my students often ask me is, ‘where can AI change the therapeutics game?’” says senior co-author and MIT Professor Regina Barzilay, AI faculty lead for the Jameel Clinic and an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL). “Unless we identify undruggable targets and propose a solution, we won’t be changing the game,” she adds. “The emphasis here is on unsolved problems, which distinguishes Hannes’ work from others in the field.” 

Senior co-author Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering and Computer Science who is affiliated with the Jameel Clinic and CSAIL, notes that "models such as BoltzGen that are released fully open-source enable broader community-wide efforts to accelerate drug design capabilities.”

Looking ahead, Stärk believes that the future of biomolecular design will be upended by AI models. “I want to build tools that help us manipulate biology to solve disease, or perform tasks with molecular machines that we have not even imagined yet,” he says. “I want to provide these tools and enable biologists to imagine things that they have not even thought of before.”

The U.S. military is mighty, formidable, and singular in influence, stationed in at least 128 overseas bases across 51 countries. Concealed beneath the United States’ biggest investment is a surprise: The military was responsible for the birth of an industry. Today, that industry is essential for its operations.

“If you think about it, logistics started as a military function,” says Chris Caplice, executive director of the MIT Center for Transportation and Logistics (CTL). “The idea of getting supplies, ammunition, food, all the material you need to the front line was the core of logistics, and really supply chain came out of that over the last decades or centuries.”

For Caplice and the leadership at MIT CTL, a collaboration with the U.S. military seemed inevitable. In 2006, MIT CTL launched the Military Fellows program, wherein three military logistics officers participate in the MIT Supply Chain Management master’s program. “The education goes two ways: One is that these people who have been in the service for more than 20 years step out of their silo and see all the research we’re doing that’s more focused on the private sector, and is cutting-edge. On the other side, you have students who may have never interacted with the military are able to learn from them,” reflects Caplice.

This year’s cohort holds 80 years of combined military service. It comprises Lukas Toth from the Army Reserve, Duston Mullen from the South Dakota Army National Guard, and Charles Greene from the Active Army. Though they work in different components of the U.S. Army, they all agree that their experience in the program so far has been humbling. 

“All of the MIT SCM students have strong academic backgrounds and are exceptionally better at math than us,” Toth laughs. “If you’re coming to this program, you’re sharp and you want to make a difference, not just in your life, but you want to make a difference in the world. Getting to sit in a room with 40 young people who want to make change happen and want to solve complex problems has been super rewarding.”

No strangers to being challenged, adversity is what called the fellows to become logistics officers in the first place. “It comes down to a quote I heard: Operations is easy, fighting the war is easy, but logistics is hard,” says Mullen. 

As logistics officers are responsible for everything from feeding soldiers to fixing trucks to warehousing and distribution, they must perform these functions at varying scales, and with varying threats to their operations. “Our work is: How do we enable the war fighter to be able to deliver when the nation requires? We’re looking at the supply chain and ensuring that we can deliver at the right time, right place, and in the right quantity with precision and accuracy,” says Greene. 

Although companies focus extensively on optimizing their supply chains for cost and efficiency, logistics officers in the military have an additional obstacle. “That last mile could be a contested mile, and the enemy gets a vote,” adds Toth. “At the end of the day, the civilian industry’s consumer has a product they want, and at the end of the day, our war fighters have a product that they want, but we have the added challenge of having to overcome a competitor who may go so far as to destroy us.”

Despite the fellows’ rich practical experience in the military, their academic experience still brings applicable use in terms of introduction to new technologies with which they hope to engage senior military leaders, insight into industry problem-solving to reduce overall military spending and influence decision-making, and, above all, communication. In the military, the stakes are higher than in the private sector, making communication rife with consequence. 

“This experience is helping us better communicate with industry and build an industry and logistics network so that if a challenge does come our country's way, we can better communicate with everybody to solve those challenges,” reflects Toth. 

In 1965, after completing his PhD in civil engineering at MIT, Professor Richard de Neufville joined the first class of White House Fellows, one of the nation’s most prestigious programs for leadership and public service, through which he spent an intensive year working full-time at the highest levels of government. Soon after, de Neufville joined the MIT faculty and led a steering committee that developed what would become the MIT Technology and Policy Program (TPP). TPP was approved in 1975 and launched in 1976 as an Institute-wide hub of education and research, and included a two-year, research-based master’s degree, with de Neufville serving as its founding chair.

This October, TPP held a symposium and celebration at MIT, marking TPP’s 50th year as an interdisciplinary effort focused on advancing the responsible leadership of technology through the integration of technical expertise and rigorous policy analysis in critical areas such as energy, the environment, security, innovation, and beyond.

As the 1988 “TPP Fact Book” stated: “The Technology and Policy Program educates men and women for leadership on the important technological issues confronting society. We prepare our graduates to excel in their technical fields, and to develop and implement effective strategies for dealing with the risks and opportunities associated with those technologies. This kind of education is vital to the future of our society.”

Now in its 50th year, TPP’s legacy of education, research, and impact has shaped more than 1,500 alumni who are among the most distinguished technology policy leaders across the world. TPP alumni often describe the program as life-changing and transformative — an educational experience that shaped their understanding of purpose, systems, and leadership in ways that continue to guide their careers throughout their lives. Today, over 50 TPP graduate students conduct research across the Institute on topics such as energy grid modeling, environmental protection, nuclear safety, industrial decarbonization, space system engineering and public policy, technoeconomic modeling of materials value chains, and governance of global digital systems and artificial intelligence.

Working to bring technically-informed and scientifically robust insights to technology policy is as urgent today as it was 50 years ago, says Christine Ortiz, Morris Cohen Professor of Materials Science and Engineering and the current director of TPP. “The role of technology policy is more essential than ever, helping to shape national and international priorities and underpinning societal and planetary well-being,” said Ortiz in her opening remarks. “Today’s symposium is convened with urgency amid a rapidly shifting landscape. We are situated here today at the epicenter of profound technological advancement, reaffirming our collective responsibility to ensure that innovation advances the well-being of humanity and the health of our planet.”

North stars and new routes

The TPP 50th Anniversary Symposium — North Stars and New Routes — held on Oct. 11, convened more than 630 participants from 30 countries, both in-person and virtually. The gathering brought together alumni, faculty, students, and global leaders to celebrate five decades of impact while exploring bold new directions for the future of technology and policy.

Over the course of seven thematic sessions and 45 speakers, the symposium offered a sweeping view of the current issues shaping the next era of technology policy. Discussions spanned a wide range of topics, including energy systems modeling, global environmental governance, ecologically neutral manufacturing, design of global digital systems, trust as national security infrastructure, the future of technology policy as a domain of scholarship, and the role of technology policy in the future of the research university.

The day opened with a dynamic panel examining the technical frontiers and possibilities of interactive energy systems modeling. Speakers highlighted the dual role of simulation tools as both advanced instruments for understanding decision outcomes and uncertainties, as well participatory platforms for engaging policymakers and stakeholders.

The next session, focused on global environmental governance, explored new approaches to planetary cooperation and emphasized how data-driven policy, equitable technology transfer, and accountability mechanisms can strengthen international climate action. Panelists called for adaptive and integrated governance frameworks that mirror the interconnectedness and complexity of the environmental systems they aim to protect.

In a session on ecologically neutral manufacturing, participants discussed advances in circular materials design and life-cycle modeling that reduce industrial emissions and resource intensity. Speakers underscored the importance of policies promoting reuse, recycling, and cleaner production — linking manufacturing innovation with both economic competitiveness and ecological resilience.

Turning to the design and governance of global digital systems, keynote speaker David Clark, senior research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory and a pioneering architect of the internet, examined how the architecture of digital networks both reflects and shapes societal values, power, and accountability. He noted that the internet’s original open design — built for innovation and resilience — now faces pressing challenges of trust, privacy, and control. The next generation of digital infrastructure, he argued, must embed trust and accountability into its very foundations. The subsequent panel expanded on these themes, exploring how global digital ecosystems are influenced by the competing incentives of governments, corporations, and users. Speakers called for governance models that integrate technical, economic, and ethical considerations — emphasizing that true accountability depends not only on external regulation, but on embedding human values directly into the design of technology.

The theme of trust carried into the next discussion, with the focus on trust as infrastructure for security policy, where experts emphasized that national and global security must evolve to encompass cyber-trust, space governance, and technological resilience as essential infrastructures for stability in an era defined by AI and geopolitical complexity and uncertainty.

In the final session, which explored the role of technology policy in the future of the research university, panelists discussed how research institutions can strengthen their societal role by embedding technology policy and interdisciplinary scholarship into the institutional structure. Speakers emphasized the need for universities to evolve into more cohesive, outward-looking engines of policy innovation — coordinating existing centers of excellence, improving communication between research and government, and expanding educational pathways that integrate engineering, social science, and civic engagement.

Technology, policy, and power

In a keynote address, Senator Edward J. Markey, U.S. senator for Massachusetts, delivered a compelling call for moral and democratic leadership in governing the technologies shaping modern life. He warned that the rapid expansion of artificial intelligence and digital systems has outpaced the ethical and policy frameworks needed to protect society, declaring that “the privacy protections of all preceding generations have broken down.” Markey called for a renewed commitment to AI civil rights and accountability in the digital age, urging that technology must be harnessed as “a tool for connection, not addiction,” and developed to advance human dignity, fairness, and shared prosperity.

Framing technology as both a source of immense potential and a concentration of power, Markey argued that the defining question of our era is who controls that power, and to what end. He urged policymakers, researchers, and citizens alike to ensure that innovation strengthens democracy rather than undermines it. Closing on a note of determination and hope, Markey reminded the audience that technology policy is inseparable from human and planetary well-being: “Technology is power … the question is, who wields it and for what purpose. We must ensure it serves democracy, equality, and the future of our planet.”

New Institute-wide policy initiative announced

The symposium concluded with the announcement of an exciting new Institute-wide initiative, Policy@MIT, introduced by Maria Zuber, E.A. Griswold Professor of Geophysics and Presidential Advisor for Science and Technology Policy. Zuber described the effort as a bold and unifying step to synergize and amplify policy initiatives across MIT, strengthening the Institute’s capacity to inform evidence-based policymaking. 

Building upon the foundational work of TPP — within which the program will serve as a core pillar — Policy@MIT aims to connect MIT’s deep technical expertise with real-world policy challenges, foster collaboration across schools and disciplines, and train the next generation of leaders to ensure that science and technology continue to serve humanity and the planet.

Extending MIT TPP’s legacy of technology and policy leadership 

As MIT charts the next half-century of leadership at the intersection of technology, policy, and society, TPP continues to serve as a cornerstone of this mission. Operating within the MIT Institute for Data, Systems, and Society (IDSS), the MIT School of Engineering, and the MIT Schwarzman College of Computing, TPP distinctively engages and integrates state-of-the-art modeling, simulation, and analytical methods in information and decision systems, statistics and data science, and the computational social sciences, with a diverse range of foundational, emerging, and cross-disciplinary policy analysis methods. Sitting at the confluence of engineering, computer science, and the social sciences, TPP equips students and researchers to study some of the most important and complex emerging issues related to technology through systems thinking, technical rigor, and policy analysis.

Founding IDSS director Munther Dahleh, the William A. Coolidge Professor in Electrical Engineering and Computer Science, described this integration as cultivating the “trilingual student” — someone fluent in data and information, social reasoning, and a technical domain. “What we’re trying to produce in the TPP program,” he explained, “is the person who can navigate all three dimensions of a problem.”

Reflecting on TPP’s enduring mission, Ortiz concluded the symposium, “As we look ahead to the next 50 years, this is a pivotal moment for the Technology and Policy Program — both at MIT and globally. TPP holds tremendous potential for growth, translation, and impact as a leader in technology policy for the nation and the world.”

On a sunny, warm Sunday MIT students, staff, and faculty spread out across the fields of Hannan Healthy Foods in Lincoln, Massachusetts. Some of these volunteers pluck tomatoes from their vines in a patch a few hundred feet from the cars whizzing by on Route 117. Others squat in the shade cast by the greenhouse to snip chives. Still others slice heads of Napa cabbage from their roots in a bed nearer the woods. Everything being harvested today will wind up in Harvest Boxes, which will be sold at a pop-up farm stand the next day in the lobby of the Stata Center back on the MIT campus.

This initiative — a pilot collaboration between MIT’s Office of Sustainability (MITOS), MIT Anthropology, Hannan Healthy Foods, and the nascent MIT Farm student organization — sold six-pound boxes of fresh, organic produce to the MIT community for $10 per box — half off the typical wholesale price. The weekly farm stands ran from Sept. 15 through Oct. 27.

“There is a documented need for accessible, affordable, fresh food on college campuses,” says Heather Paxson, William R. Kenan, Jr. Professor of Anthropology and one of the organizers of the program. “The problems for a small farmer in finding a sufficient market … are connected to the challenges of food insecurity in even wealthy areas. And so, it really is about connecting those dots.”

Through the six weeks of the project, farm stand shoppers purchased more than 2,000 pounds of fresh produce that they wouldn’t otherwise have had access to. Hannan, Paxson, and the team hope that this year’s pilot was successful enough to continue into future growing seasons, either in this farm stand form or as something else that can equally serve the campus community.

“This year we decided to pour our heart, soul, and resources into this vision and prove what’s possible,” says Susy Jones, senior sustainability project manager at MITOS. “How can we do it in a way that is robust and goes through the official MIT channels, and yet pushes the boundaries of what’s possible at MIT?”

A growing idea

Mohammed Hannan, founder of Hannan Healthy Foods, first met Paxson and Jones in 2022. Jones was looking for someone local who grew vegetables common in Asian cuisine in response to a student request. Paxson wanted a small farm to host a field trip for her subject 21A.155 (Food, Culture and Politics). In July, Paxson and Jones learned about an article in the Boston Globe featuring Hannan as an example of a small farmer hit hard by federal budget cuts.

They knew right away they wanted to help. They pulled in Zachary Rapaport and Aleks Banas, architecture master’s students and the co-founders of MIT Farm, an organization dedicated to getting the MIT community off campus and onto local farms. This MIT contingent connected with Hannan to come up with a plan.

“These projects — when they flow, they flow,” says Jones. “There was so much common ground and excitement that we were all willing to jump on calls at 7 p.m. many nights to figure it out.”

After a series of rapid-fire brainstorming sessions, the group decided to host weekly volunteer sessions at Hannan’s farm during the autumn growing season and sell the harvest at a farm stand on campus.

“It fits in seamlessly with the MIT motto, ‘mind and hand,’ ‘mens et manus,’ learning by doing, as well as the heart, which has been added unofficially — mind, hand, heart,” says Paxson.

Jones tapped into the MITOS network for financial, operational, student, and city partners. Rapaport and Banas put out calls for volunteers. Paxson incorporated a volunteer trip into her syllabus and allocated discretionary project funding to subsidize the cost of the produce, allowing the food to be sold at 50 percent of the wholesale price that Hannan was paid for it.

“The fact that MIT students, faculty, and staff could come out to the farm, and that our harvest would circulate back to campus and into the broader community — there’s an energy around it that’s very different from academics. It feels essential to be part of something so tangible,” says Rapaport.

The volunteer sessions proved to be popular. Throughout the pilot, about 75 students and half a dozen faculty and staff trekked out to Lincoln from MIT’s Cambridge, Massachusetts, campus at least once to clear fields and harvest vegetables. Hannan hopes the experience will change the way they think about their food.

“Harvesting the produce, knowing the operation, knowing how hard it is, it’ll stick in their brain,” he says.

On that September Sunday, second-year electrical engineering and computer science major Abrianna Zhang had come out with a friend after seeing a notification on the dormspam email lists. Zhang grew up in a California suburb big on supporting local farmers, but volunteering showed her a different side of the job.

“There’s a lot of work that goes into raising all these crops and then getting all this manual labor,” says Zhang. “It makes me think about the economy of things. How is this even possible … for us to gain access to organic fruits or produce at a reasonable price?”

Setting up shop

Since mid-September, Monday has been Farm Stand day at MIT. Tables covered in green gingham tablecloths strike through the Stata Center lobby, holding stacks of cardboard boxes filled with produce. Customers wait in line to claim their piece of the fresh harvest — carrots, potatoes, onions, tomatoes, herbs, and various greens.

Many of these students typically head to off-campus grocery stores to get their fresh produce. Katie Stabb, a sophomore civil and environmental engineering major and self-proclaimed “crazy plant lady,” grows her own food in the summer, but travels far from campus to shop for her vegetables during the school year. Having this stand right at MIT gives her time back, and she’s been spreading the news to her East Campus dorm mates — even picking boxes up for them when they can’t make it themselves and helping them figure out what to do with their excess ingredients.

“I have encountered having way too many chives before, but that’s new for some folks,” she says. “Last week we pooled all of our chives and I made chive pancakes, kind of like scallion pancakes.”

Stabb is not alone. In a multi-question customer survey conducted at the close of the Farm Stand season, 62 percent of respondents said the Harvest Box gave them the chance to try new foods and 49 percent experimented with new recipes. Seventy percent said this project helped them increase their vegetable intake.

Nearly 60 percent of the survey respondents were graduate students living off campus. Banas, one of the MIT Farm co-leads, is one of those grad students enjoying the benefits.

“I was cooking and making food that I bought from the farm stand and thought, ‘Oh, this is very literally influencing my life in a positive way.’ And I’m hoping that this has a similar impact for other people,” she says.

The impact goes beyond the ability of students to nourish themselves with fresh vegetables. New communities have grown from this collaboration. Jones, for example, expanded her network at MITOS by tapping into expertise and resources from MIT Dining, the Vice President for Finance Merchant Services, and the MIT Federal Credit Union.

“There were just these pockets of people in every corner of MIT who know how to do these very specific things that might seem not very glamorous, but make something like this possible,” says Jones. “It’s such a positive, affirming moment when you’re starting from scratch and someone’s like, ‘This is such a cool idea, how can I help?’”

Strengthening community

Inviting people from MIT to connect across campus and explore beyond Cambridge has helped students and employees alike feel like they’re part of something bigger.

“The community that’s grown around this work is what keeps me so engaged,” says Rapaport. “MIT can have a bit of a siloing effect. It’s easy to become so focused on your classes and academics that your world revolves around them. Farm club grew out of wanting to build connections across the student body and to see ourselves and MIT as part of a larger network of people, communities, and relationships.”

This particular connection will continue to grow, as Rapaport and Banas will use their architectural expertise to lead a design-build team in developing a climate-adaptive and bio-based root cellar at Hannan Healthy Foods, to improve the farm’s winter vegetable storage conditions. 

Community engagement is an ethos Hannan has embraced since the start of his farming journey in 2018, motivated by a desire to provision first his family and then others with healthy food.

“One thing I have done over the years, I was not trying to do farming by myself,” he says. “I always reached out to as many people as I could. The idea is, if community is not involved, they just see it as an individual business.”

It’s why he gifts his volunteers huge bags of tomatoes at the end of a shift, or donates some of his harvest to food banks, or engages an advisory committee of local residents to ensure he’s filling the right needs.

“There’s a reciprocal dimension to gifting that needs to continue,” says Paxson. “That is what builds and maintains community — it’s classic anthropology."

And much of what’s exchanged in this type of reciprocity can’t be charted or graded or marked on a spreadsheet. It’s cooking pancakes with dorm mates. It’s meeting and appreciating new colleagues. It’s grabbing a friend to harvest cabbage on a beautiful autumn Sunday.

“Seeing a student who volunteered over the weekend harvesting chives come to the market on Monday and then want to take a selfie with those chives,” says Jones. “To me, that’s a cool moment.”