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Forbes contributor Tanya Fileva spotlights how MIT CSAIL researchers have developed a system called Air-Guardian, an “AI-enabled copilot that monitors a pilot’s gaze and intervenes when their attention is lacking.” Fileva notes that “in tests, the system ‘reduced the risk level of flights and increased the success rate of navigating to target points’—demonstrating how AI copilots can enhance safety by assisting with real-time decision-making.”
Prof. Ryan Williams has published a new proof that explores computational complexity and flips the script on years of assumptions about the trade-offs between computation space and time, reports Max Springer for Scientific American. Williams found that “any problem can be transformed into one you can solve by cleverly reusing space, deftly cramming the necessary information into just a square-root number of bits,” Springer explains. “This progress is unbelievable,” says Mahdi Cheraghchi of the University of Michigan. “Before this result, there were problems you could solve in a certain amount of time, but many thought you couldn’t do so with such little space.”
Prof. Daniela Rus, director of CSAIL, speaks with Newsweek reporter Marni Rose McFall about the impact of AI on entry level jobs. “We need a strong pipeline of talent that starts with entry-level roles, internships, and hands-on learning opportunities," says Rus. "These early experiences remain essential stepping stones, helping people build technical confidence, domain fluency, and problem-solving skills. And soon, the skills companies will be looking for in entry-level workers is how well they can make the most of AI tools."
Prof. Daniela Rus, director of CSAIL, and research affiliate Ramin Hasani have been named to The Boston Globe’s 2025 list of Tech Power Players working in the foundational AI sector, reports Aaron Pressman for The Boston Globe. Rus and Hasani are co-founders of Liquid AI, a startup that has developed “an AI technique with fewer software ‘neurons’ than large language models of OpenAI and others,” explains Pressman. This means “Liquid AI requires less computing power (and electricity.)”
MIT researchers have developed Boltz-2, an AI algorithm “that unites protein folding and prediction of small-molecule binding affinity in one package,” reports Laura Howes for Chemical & Engineering News. “The researchers say their new AI model approaches the level of accuracy achieved by traditional computational chemistry—such as methods involving free-energy perturbation calculations—but much more quickly and cheaply,” explains Howes.
Researchers at MIT and elsewhere have developed Boltz-2, an open-source generative AI model that can help researchers find new medicines faster, reports Alex Knapp for Forbes. The tool “can not only predict the structure of proteins, it can also predict its binding affinity–that is, how well a potential drug is able to interact with that protein,” explains Knapp. “This is crucial in the early stages of developing a new medicine.”
Wall Street Journal reporter Angelina Torre spotlights “Letterlocking: The Hidden History of the Letter,” a new book by MIT Libraries Conservator Jana Dambrogio and King’s College London Senior Lecturer Daniel Smith that explores the history and art of “folding a letter so it serves as its own envelope.” The book “calls on scholars to ‘read the folds’ of written correspondence – to peer into the historical, social or personal circumstances that might not be explicitly stated,” explains Torre.
Prof. Daniela Rus, director of CSAIL, speaks with Financial Times reporter Michael Peel about ongoing efforts to balance autonomous vehicles’ “efficient operation with the need for them to minimize damage in collisions.” Rus notes that a new framework offers a “potential path towards AVs that can navigate complex, multi-agent scenarios with an awareness of differing levels of vulnerability among road users,” says Rus.
Prof. Daniela Rus, director of CSAIL, speaks with Wall Street Journal reporter Isabelle Bousquette about her vision for the future of robots as soft, squishy, flexible and maybe even edible. Bousquette notes that Rus is a “pioneer” in the field of soft robotics and Steve Crowe, chair of the Robotics Summit and Expo, emphasizes: “there’s literally nobody in the world that knows more about this stuff than Daniela Rus.” “I really wanted to broaden our view of what a robot is,” says Rus. “If you have a mechanism that’s made out of paper and that moves, is that a robot or not? If you have an origami flower that you attach to a motor, is that a robot or not? To me, it’s a robot.”
CSAIL Research Scientist Neil Thompson speaks with Wired reporter Will Knight about how new AI systems are developing new algorithms that could be used to help advance scientific research and innovation. “If these capabilities can be used to tackle bigger, less tightly-scoped problems, it has the potential to accelerate innovation—and thus prosperity,” says Thompson.
Prof. Pulkit Agrawal speaks with Darian Woods and Geoff Brumfiel of NPR’s The Indicator from Planet Money about his work developing a simulator that can be used to train robots. “The power of simulation is that you can collect, you know, very large amounts of data,” explains Agrawal. “For example, in three hours', you know, worth of simulation, we can collect 100 days' worth of data.”
Researchers at MIT have concluded that AI does not develop “value systems” over time, reports Kyle Wiggers for TechCrunch. “For me, my biggest takeaway from doing all this research is to now have an understanding of models as not really being systems that have some sort of stable, coherent set of beliefs and preferences,” says graduate student Stephen Casper. “Instead, they are imitators deep down who do all sorts of confabulation and say all sorts of frivolous things.”
“AT MIT innovation ranges from awe-inspiring technology to down-to-earth creativity,” notes Chronicle during a visit to campus to peek behind the scenes at the innovations underway at the Institute. Classes taught by Prof. Erik Demaine are a “mix of rigorous math and creative collaboration,” host Anthony Everett explains, highlighting how Demaine’s work in computational origami has found its way into practical applications in such fields as medicine, architecture and space exploration. “I think origami provides a really powerful tool for making transformable shapes,” Demaine relates.
Prof. Pulkit Agrawal speaks with NPR Short Wave host Regina Barber and science correspondent Geoff Brumfiel about his work developing a new technique that allows robots to train in simulations of scanned home environments. “The power of simulation is that we can collect very large amounts of data,” explains Agrawal. “For example, in three hours' worth of simulation, we can collect 100 days' worth of data.”
Prof. David Sontag, Monica Agrawal PhD '23, Luke Murray SM '22, and Divya Gopinath '19, MEng '20 co-founded Layer Health - an AI healthcare startup that is applying large language models (LLMs) to help clinicians with medical chart reviews and data abstraction, reports Seth Joseph for Forbes. “The same chart review problem we’re solving with our clinical registry module is faced by clinicians at the point of care,” says Sontag. “For example, one of our next modules will focus on real-time clinical decision support to help automate clinical care pathways, leading to more reliable, high-quality care."