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Prof. Marzyeh Ghassemi speaks with Boston Globe reporter Hiawatha Bray about her work uncovering issues with bias and trustworthiness in medical AI systems. “I love developing AI systems,” says Ghassemi. “I’m a professor at MIT for a reason. But it’s clear to me that naive deployments of these systems, that do not recognize the baggage that human data comes with, will lead to harm.”
Prof. Daniela Rus, director of CSAIL and “one of the world’s foremost thinkers on the intersection of machines and artificial intelligence,” shares her views on the promise of embodied intelligence, which would allow machines to adapt in real-time; the development of AI agents; and how the US can lead on the development of AI technologies with Aaron Mak of Politico. “The U.S. government has invested in energy grids, railroads and the internet. In the AI age, it must treat high-performance compute, data stewardship and model evaluation pipelines as public infrastructure as well,” Rus explains.
Researchers at MIT have “developed an antenna that can adjust its frequency range by physically changing in its shape” reports Mrigakshi Dixit for Interesting Engineering. “Instead of standard, rigid metal, this antenna is made from metamaterials — special engineered materials whose properties are based on their geometric structure,” explains Dixit. “It could be suitable for applications like transferring energy to wearable devices, tracking motion for augmented reality, and enabling wireless communication.”
Prof. Daniela Rus, director of CSAIL, speaks with CBS News reporter Tony Dokoupil about her work developing AI-powered robots. “AI and robots are tools,” says Rus. “They are tools created by the people, for the people. And like any other tools they’re not inherently good or bad; they are what we choose to do with them. And I believe we can choose to do extraordinary things.”
Researchers at MIT have developed a new tool, called Meschers, that allows users to create detailed computer representations of mathematically impossible objects, reports Gayoung Lee for Gizmodo. “In addition to creating aesthetically quirky objects,” Lee explains, “Meschers could eventually assist in research across geometry, thermodynamics, and even art and architecture."
Prof. Andrew Lo speaks with NBC Boston reporter Daniela Gonzalez about how AI tools could be used as a starting point to help people manage their monthly expenses and improve their savings strategies. Lo notes that AI tools “can tell you, given the kind of things you're looking to purchase, where the various deals might be.” He added that “once you get the feedback, you have to make sure that what you're getting is legit, versus what they call hallucinations that large language models are likely to do on occasion.”
Prof. Andrew Lo speaks with Bloomberg reporter Lu Wang about how AI tools could be applied to the financial services industry, working alongside humans to help manage money, balance risk, tailor strategies and possibly even act in a client’s best interest. “I believe that within the next five years we’re going to see a revolution in how humans interact with AI,” says Lo. He adds that “the financial services industry has extra layers of protection that needs to be built before these tools can be useful.”
Researchers at MIT have uncovered a variety of obstacles of AI in software development, reports Rob Wile for NBC News. They have found “the main obstacles come when AI programs are asked to develop code at scale, or with more complex logic,” writes Wile.
A new research paper by Prof. David Autor and Principal Research Scientist Neil Thompson explores the forthcoming impact of AI on jobs, reports Tim Harford for Financial Times. “[W]hile there are few certainties, Autor and Thompson’s framework does suggest a clarifying question: does AI look like it is going to do the most highly skilled part of your job or the low-skill rump that you’ve not been able to get rid of?,” writes Harford. “The answer to that question may help to predict whether your job is about to get more fun or more annoying — and whether your salary is likely to rise, or fall as your expert work is devalued like the expert work of the Luddites.”
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.”