A study by researchers at MIT examines how the use of large language models impacts the human brain, reports Elizabeth Hlavinka for Salon. Research scientist Nataliya Kos'myna says the results “suggest large language models could affect our memory, attention and creativity.”
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.”
Postdoc Isabella Loaiza speaks with ABC News reporter Max Zahn about her study examining how jobs and tasks across the U.S. economy shifted between 2016-2024. Loaiza and her colleagues found that “rather than dispense with qualities like critical thinking and empathy, workplace technology heightened the need for workers who exhibit those attributes,” Zahn explains. “It is true we’re seeing AI having an impact on white-collar work instead of more blue-collar work,” says Loaiza. “We found that jobs that are very human-intensive are probably more robust.”
Writing for The Boston Globe, Prof. David Mindell spotlights how “a new wave of industrial companies, many in New England, are leveraging new technologies to create jobs, empower workers, and address climate change.” Mindell notes that “young Americans — new industrialists — are devoting themselves to making things for the common good.” He adds: "The country needs this generation of builders who are excited about working with their hands, about the satisfactions of building the world, and who see that work as building our communities.”
Forbes reporter Michael Nietzel spotlights MIT’s Initiative for New Manufacturing (INM), “an institution-wide effort intended to promote and advance the future of U.S. manufacturing.” Nietzel notes that the INM is part of an effort to “rethink how MIT could help shape the future of manufacturing through workforce training, advanced technologies, and industry collaborations. It will focus on enhancing the future manufacturing capacity and sophistication of several major industries.”
Wall Street Journal reporter Dominique Mosbergen spotlights how Prof. James Collins and his lab have built their “own algorithms to trawl chemical databases, such as those of existing pharmaceutical drugs, for potential antibacterial compounds.” Collins’ His lab is “also experimenting with using generative AI to design completely new molecules that could kill bacteria,” writes Mosbergen.
Lecturer Michael Schrage speaks with Forbes reporter Josipa Majic Predin about the shift towards generative AI in business. "AI should not be seen overwhelmingly as just an ethical or a technical or a digital innovation and platform," says Schrage. "It's actually a philosophical capability and resource."
Writing for The Boston Globe, graduate students Manuj Dhariwal SM '17 and Shruti Dhariwal SM '18 highlight new efforts to reframe the language used to describe the ways humans are interacting with AI technologies. “It is a subtle reframing, but one that we urgently need as AI systems become interwoven with our creative, social, and emotional worlds,” they write. “The point is not necessarily to choose one over the other — but to clearly distinguish one from the other.”
Principal Research Scientist Kalyan Veeramachaneni speaks with WBUR On Point host Meghna Chakrabarti about the benefits and risks of training AI on synthetic data. “I think the AI that we have as of today and we are using is largely very small; I don't mean that as in size, but in the tasks that it can do,” says Veeramachaneni. “And as days go by, we are asking more and more of it… that requires us to provide more data, train more models that are much more efficient in reasoning, and can solve problems that we haven't thought of solving.”
Prof. Pattie Maes speaks with Financial Times reporter Cristina Criddle about recent developments aimed at increasing AI memory retention. “The more a system knows about you, the more it can be used for negative purposes to either make you buy stuff or convince you of particular beliefs,” says Maes. “So you have to start thinking about the underlying incentives of the companies that offer these services.”
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.”
Jia Haojun PhD '24, graduate student Gao Wenhao and postdoctoral associate James Utama Surjadi have been named to the Forbes 30 and Under 30 Asia: Healthcare & Science list, writes Yue Wang for Forbes. The list honors those “who are using cutting-edge technology to innovative and improve their industry.”
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 conducted a survey to understand how people interact with AI companions, reports David Adam for Nature. The researchers found that 12% [of users] were drawn to the apps to help them cope with loneliness and 14% used them to discuss personal issues and mental health,” writes Adam. “Forty-two per cent of users said they logged on a few times a week, with just 15% doing so every day. More than 90% reported that their sessions lasted less than one hour.”