7 News Boston spotlights MIT being named the No. 1 national university by U.S. News and World Report for its 2027 “Best College Rankings.” The ranking highlighted MIT’s “high enrollment of just over 4,500 students in 2025, its student faculty ratio of 8-1 and its 4-1 academic calendar.”
The Boston Globe’s Chloe Craft highlights MIT being ranked No. 1 in the U.S. News & World Report’s 2027 “Best Colleges Rankings.” “Take a look at the rankings of U.S. News & World Report’s 2027 lists of the nation’s best universities and liberal arts colleges, released Tuesday, and you’ll find lots of schools from New England near the top of the charts,” writes Craft. “MIT, ranked No. 1 for the first time ever.”
MIT has been named the No. 1 national university in U.S. News & World Report’s 2027 “Best Colleges Rankings,” writes Chloe Craft for The Boston Globe. MIT is proud to be “part of a strong network of excellent colleges and universities across the nation, dedicated to educating students and pursuing curiosity-driven research. America’s economic strength, scientific leadership, and national security depend on world-class education and research institutions.”
Jeffrey Riley, executive director of MIT RAISE’s “Day of AI” K-12 program, speaks to WBUR’s Suevon Lee about the importance of teaching school-aged children AI literacy skills. “Kids need to know about voice clones and deepfakes and plagiarism,” says Riley. “We need to teach kids so that they're healthy skeptics of this technology, that they mistrust and verify the information they're getting from it.”
MIT alumni Tom Brown ‘10, co-founder of Anthropic, and Edwin Chen ‘08, founder of Surge AI, are highlighted among the 10 youngest billionaires on the 2026 “Forbes 400 List,” by reporter Alicia Park. Brown “was lead author of the 2020 paper introducing GPT-3, the language model that demonstrated such systems could write fluently and triggered the current investment boom in artificial intelligence,” writes Park. Chen’s Surge AI, “employs people to label data, as well as rate and correct AI-generated answers to train models.”
MIT researchers are leading a new project documenting what major AI systems say about elections in an effort to understand how the technology influences the democratic process, writes Tiffany Hsu for The New York Times. “AI is becoming part of the way people encounter and make sense of political information, and yet we know relatively little about what that information environment actually looks like, how it differs for different user demographics, political identities and geographies,” says Prof. Chara Podimata, a leader of the project.
Akamai will honor their late cofounder Danny Lewin SM ’98, a victim of the American Airlines Flight 11 on 9/11, by illuminating their headquarters in blue the evening of Sept. 11, write Jon Chesto and Shirley Leung for The Boston Globe. “Lewin remains revered at Akamai; its highest employee award is given out each year in his honor,” Chesto and Leung write.
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 have discovered that when individual images are removed from large AI diffusion models, the models are still able to produce like images, writes Digital Trends’ Varun Mirchandani. “The more interesting takeaway is that this connection becomes increasingly difficult to trace as datasets grow,” writes Mirchandani. “An AI-generated image may draw on patterns learned from an enormous pool of material without having a clear, identifiable source image behind it.”
The Register’s Thomas Claburn highlights a new study by MIT researchers that found large AI models can still reproduce an artist’s style, even when the artist’s work is removed from its training data, making attribution more difficult. “[G]iven the contemporary adoption of these models for creative and commercial purposes, attributability also carries ethical, policy, financial, and legal implications,” the researchers note.
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.”
Prof. Joshua Tenenbaum discusses whether AI systems will perform better if they have increased awareness of the world around them with New Scientist’s Daniel Cossins. “One of the big misconceptions is that intelligence is a single thing, that there is a single world model in the brain,” says Tenenbaum. “What we actually have is the ability to run many different models depending on the context, task and goal.”
Prof. Jackson Lu speaks to Fast Company’s Sarah Bregel about metacognitive techniques, tuning into one’s thinking and learning process, to use AI more creatively. “Even the most powerful AI won’t boost creativity if employees don’t know how to use it effectively,” says Lu. “Organizations should pair AI deployment with metacognition training to maximize the creative benefits.”
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.