MIT Schwarzman College of Computing

Prof. Justin Solomon joins GBH’s “The Curiosity Desk" to explain the Navier-Stokes problem and the significance of this longstanding challenge being solved by an AI platform. “There are concerns and there’s excitement,” says Solomon. “Obviously, working on the Navier-Stokes equations and other open problems shows that these AI tools are capable of assisting with proofs, or at least counter examples in this particular case, of really hard questions that have been open for centuries.” 

For The Wall Street Journal, reporter Jennifer Hiller spotlights Xcimer Energy, a fusion startup that is developing technology to defend against drones and other threats, founded by alumni Conner Galloway M.S. ‘09 and Alexander Valys ‘08. “We realized that no one was actually pursuing the approach to fusion that we thought was going to work, and so ultimately that’s what led to Xcimer,” says Valys.  

Writing for The Boston Globe, President Emeritus L. Rafael Reif describes the need to develop a universal “moral floor,” like the Ten Commandments, which provide clear guidelines for the use of AI. “Today, people are creating and developing intelligence that is much more capable, in narrow ways, than our own,” Reif explains. “We owe humanity the same discipline to civilize AI before it is too late: Write down what lines must never be crossed, make the list short enough to remember, and hold every actor building it, and using it, accountable for its actions.”

Prof. Regina Barzilay, graduate student Aziz Ayed and alumna Sydney Pham ‘24 are featured in an article about AI models and the workforce, written by Nature’s Ben Deighton. “Sometimes models can make sense of unexpected observations, which can guide further iterations of studies,” Pham says. “It’s helpful to understand how the models generate their results.” 

Prof. Daniela Rus, Director of MIT CSAIL, and Prof. David Autor, department head of Economics, are featured on Time’s “TIME100 AI 2026” list of 100 innovators, leaders, and thinkers reshaping the world through their advances in AI. “Over three decades, [Rus] has conducted pioneering work in robotics, extending the understanding of what form robots can take,” writes Tharin Pillay, while Steven Freiss describes Autor as “one of the nation’s most vocal and prominent economists aiming to ascertain AI’s potential impacts on labor.” 

Prof. Emeritus Rodney Brooks speaks to Scientific American’s Mary Randolph about humanoid robots interacting with the real world. “When you see a performance of an [artificial intelligence] system or a robot on one thing,” says Brooks, “that fools us into thinking that it has the same general competence as a human. And that’s a mistake people make.” 

A new study by MIT researchers found that it is impossible to draw a direct link between AI diffusion model outputs and an artist’s body of work, writes Gizmodo’s Webb Wright. “If a [diffusion] model generates something, you want to be able to say, ‘Oh, this part of the training data was responsible,'” says Zheng Dai, PhD ’24, lead author on the study. “It’s important for us to understand how these models work to properly study them or regulate them.” 

Prof. David Gifford and Zheng Dai PhD ’24 discovered that AI diffusion models can replicate the style of an artist even when their work was omitted from datasets, leading to ‘attribution decay,’ writes Fast Company’s Jesus Diaz. “This trend, what the researchers call ‘attribution decay,’ means that artificial intelligence can produce an image that resembles a particular artist’s work, while having no provable causal link to that artist’s actual contribution to the training data,” explains Diaz.  

MIT researchers found the more data an AI model is trained on could complicate AI copyright, auditing, and governance, writes Computer World’s Taryn Plumb. “[S]ingle artworks by specific artists, or photographs of certain people, could be entirely removed from datasets, and the model could still reproduce that image or style,” writes Plumb. “Essentially, tangible connections are lost, and linking to specific data points responsible for generated samples is ‘practically impossible,’ or can even vanish, the researchers explained.” 

Forbes’ “50 Over 50” list spotlights four MIT faculty leading innovation in science and technology: Prof. Paula Hammond, dean of the MIT School of Engineering; Prof. Dina Katabi; Prof. Nergis Mavalvala, dean of the MIT School of Science; and Aude Oliva, director of MIT-IBM Computing Research Lab. The 50 “science and technology standouts on this list are advancing how we use AI, fight osteoporosis and deploy clean energy.”  

Bloomberg’s Gautam Mukunda highlights Prof. Scott Stern’s finding that 0.07% of business registrations in the 2010s reached meaningful acquisition within six years, and Prof. Danielle Li and Prof. Lindsey Raymond’s finding that AI technologies increased customer support agent productivity by 15%, to predict AI’s role in the influx of business applications filed in June.  

Researchers from MIT and Toyota Research Institute developed SceneSmith, a system that allows robots to practice everyday tasks and action plans in over 1,300 AI generated environments before entering a real home or workplace, writes Fox News’ Kurt Knutsson. “SceneSmith's ability to combine realistic design with usable physics gives the project its strongest advantage,” notes Knutsson.  

Graduate student Peter Zhi Xuan Li speaks to Tech Briefs’ Andrew Corselli about his team’s work developing a new chip that allows small, autonomous robots and other battery-limited devices to construct detailed 3D maps of their environments using a fraction of the power required by other systems. “Today, a robot uses separate, incompatible internal representations for different jobs: one for mapping, another for tracking its own motion, another for rendering what it sees, and every conversion adds memory footprint and energy,” says Li. “Our goal is a single shared representation.”