Research

Maxime Cohen PhD ‘15 speaks to Forbes’ Karl Moore about his latest book “Pricing in the Age of AI,” that explores how AI is transforming pricing decisions for businesses, consumers and society. “We may be entering an era of agent-to-agent commerce, in which AI systems negotiate directly with one another on behalf of consumers and businesses,” says Cohen. “This could fundamentally reshape how prices are determined and how transactions take place.” 

Washington Post reporter Ariana Eunjung Cha spotlights Prof. Pattie Maes’ research at the intersection of AI and memory, including her wearable AI devices designed to assist older adults that “capture pieces of everyday experience and make them retrievable later.” Maes’ research “takes on particular urgency for people with Alzheimer’s disease and other forms of dementia, diseases defined by memory loss that can rob a person’s ability to navigate everyday life independently,” writes Eunjung Cha.  

Using satellite data, graduate student Caroline Needell and her colleagues found that the risk of runaway collapse in tall ice cliffs “depends on two main factors: how steeply the sea floor beneath the glacial ice deepens, and how quickly the ice flows seawards,” writes Marissa Grunes for New Scientist. “This idea has been suggested by idealized mathematical models, but had never been systematically measured in real glaciers,” notes Grunes. “The key question, says Needell, is whether thinning [from runway collapse] can outcompete rapid ice loss, restabilizing the glacier. Her study suggests that it might.”  

Prof. Sherry Turkle joins The Boston Globe’s Anna Kusmer, host of the “Say More” podcast, to discuss how AI chatbots can significantly deskill school-aged children, as detailed in her latest book, “Artificial Intimacy: Who We Become When We Talk to Machines.” “People in the thick of this know it is not good for children, it’s a deskilling,” says Turkle. “If your chatbot reads for you, you don’t learn to read, you learn to listen to a podcast about a book, if your chatbot writes for you, you don’t learn to think, because thinking is writing, you learn to sort of edit your chatbots ideas: you learn to prompt.”  

MIT researchers have developed the Probabilistic Bias Correction (PBC) tool, which “uses machine learning to identify systematic bias in a model and make corrections” to improve weather forecasts, reports The Verge’s Justine Calma. “The researchers found that PBC improved the accuracy of a leading physics-based weather model by the European Centre for Medium-Range Weather Forecasts (ECMWF) for 98 percent of precipitation and 92 percent of temperature targets,” notes Calma. “The machine learning framework also doubled the accuracy of ECMWF’s new AI forecasting system in the study’s analysis.” 

Gizmodo’s Ellyn Lapointe spotlights the Probabilistic Bias Correction (PBC) tool developed by MIT researchers to “correct systemic errors in forecast models and improve the accuracy of their subseasonal outlooks.” “Extreme weather has the largest impact on our society and improved forecasts of these events can yield large societal benefits,” says Research Scientist Judah Cohen. “Interestingly, previous bias correction schemes actually made forecasts of extreme weather worse, and our model showed clear improvement of extreme weather forecasts.”  

On The New York Times’ “Ezra Klein Show,” Prof. Sherry Turkle shares her insights on humans seeking companionship with AI chatbots, detailed in her latest book, “Artificial Intimacy: Who We Become When We Talk to Machines.” In relationships with chatbots, “on the one hand, people start to see the chatbots more like people,” says Turkle. “But I think, maybe more significantly, people start to be disappointed with people when they don’t behave like chatbots. They start to think of themselves as if they were computers.”  

MIT researchers have developed an AI system “that not only minimizes forecasting errors, but learns from its inevitable mistakes through a method called postprocessing,” writes reporter Andrew Paul for Popular Science. “Their AI postprocessing integration blew the existing forecasting models out of the water,” notes Paul. “Such massive improvements could soon help the farmers and energy providers who already rely on subseasonal forecasts, but the benefits may even save lives.” 

Research led by Principal Research Scientist Neil Thompson suggests that AI is likely to be upend theoretical scientific fields within a few years, writes Wired’s Will Knight. “As with math, Thompson says, we should expect advances in other areas to have both positive and negative effects,” writes Knight. “He notes that theoretical advances sometimes drive practical advances in science and suggests that greater use of AI may mean that more progress happens this way.” 

MIT spinout Cambridge Heavy Industries is developing a desktop-sized fusion reactor that can enable 50 to 80 experiments per day, writes TechCrunch’s Tim De Chant. “Cambridge Heavy’s fusion reactor uses lasers to compress a fuel target, similar to the groundbreaking experiment that proved controlled fusion reactions could produce more power than they consume,” notes De Chant. “But unlike other inertial confinement designs, Cambridge Heavy’s minimizes the number of lasers required to spark fusion.”  

Prof. Ankur Moitra and Prof. John Urschel share their thoughts with Forbes’ Alex Knapp about OpenAI releasing more than 700 math preprint papers online. “We’re used to landmark results being accompanied by new insights and theories,” writes Moitra. “But these feel different. The claims are spectacular, the papers are incomprehensible and there’s no punchline in sight that explains why the mysteries suddenly unraveled.” Adds Urschel: “It’s obvious that how we do and evaluate mathematics is going to have to change. What I think is constant is the fundamental idea of understanding that underpins our profession. And I’m excited to learn from these breakthroughs.” 

Using a technique based on Raman microscopy, MIT researchers have found a way to detect senescent cells, “zombie cells” that accumulate as tissues age, without destroying them, writes reporter Eric Ralls for Earth.com. “If the approach eventually works in living people, researchers could gain a way to track senescent cells over time without repeatedly removing tissue,” notes Ralls. “That could help scientists understand how these cells contribute to aging and whether treatments designed to eliminate them are working.” 

Boston Globe reporter Jon Chesto spotlights the fall fair event held as part of the MIT x GE Vernova Energy & Climate Alliance, during which, GE Vernova CEO Scott Strazik shared his enthusiasm for hiring MIT graduates. “Something we talk a lot about inside Vernova is the world is changing very quickly but we need to change quicker and even faster than that so we can lead in the world,” says Strazik. “Over the last year-plus on this campus, we see a lot of opportunities for us to get better through bringing you into the organization.”  

Prof. John Urschel speaks with Wall Street Journal reporter Andrew Beaton about how he called an audible and pivoted from the NFL to a career in mathematics, delving into his time playing for the Baltimore Ravens, his graduate studies at MIT and the publication of his latest research, which proves a decades-old mathematical conjecture. “I feel like I bet on myself in a big way,” Urschel says. “I’m living my best life right now.” 

Prof. Virginia Vassilevska Williams speaks to the Scientific American’s Peter Hall and Joseph Howlett about AI assisting in faster matrix multiplications. “Matrix multiplication is needed all over the place,” says Williams. “But also, its complexity is one of the great mysteries in computer science. In a maybe diabolical sense, the advance on matrix multiplication can be seen as an attempt by the LLMs to speed themselves up.”