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Newsweek

MIT researchers have developed an AI-powered robotic therapy system that combines wearable force sensors and camera recordings of physical therapists’ movements to provide personalized therapy to patients, writes Newsweek’s Claudia Tanner. “Robotic assistance will allow patients to practice exercises more often while still receiving support tailored to their abilities,” says Johannes Lachner, who completed this work as a postdoctoral fellow at MIT. “Our goal is to take a step toward more accessible and personalized physical rehabilitation, giving more patients the opportunity to regain movement and independence.” 

New Scientist

According to new research by MIT physicists, a laser able to capture neutrinos, abundant yet intangible particles in the universe, is likely impossible to build, writes New Scientist’s Karmela Padavic-Callaghan. “The key to the neutrino laser proposal was a memory effect: when an atom in the BEC (Bose-Einstein condensate) emitted a neutrino, it would be more likely to continue emitting more neutrinos in the same direction, thus pushing them into a beam, because the quantum state that all the ultracold atoms share would retain a trace of that first emission,” Padavic-Callaghan explains. “[Prof. Wolfgang] Ketterle and his colleagues showed that this memory, although present, would be about 10,000 billion times too brief to affect the neutrinos as intended.” 

Fortune

Prof. Paul Osterman speaks to Fortune’s Nick Lichtenberg about how his new book “Disposable Workers: The Transformation of Employment” explores how a perceived lack of ambition among Gen Z reflects the decreased amount of job security and opportunity available to young workers. “No one has job security anymore, but these folks [disposable workers] are hired with that expectation and are not going to be around for long,” says Osterman.

Forbes

MIT Media Lab researchers found that using large language models for writing assistance was associated with weaker recall and lower ownership of the work produced, writes Forbes’ Glenn Llopis. “Notice the pattern: when AI does too much, the person may retain too little,” writes Llopis.  

Forbes

A study by researchers from the MIT Media Lab found up to 55% lower neural connectivity in participants who used AI for writing assistance, and flagged children as especially vulnerable, writes Forbes’ Dana Williams. “83% of participants who used a chatbot could not quote a single sentence from an essay they had finished minutes earlier, versus roughly 11% of those who wrote unaided,” Williams notes. “The words were produced, but they never entered a mind.”  

Thomson Reuters

A 2025 report by MIT researchers found that 62% of accounting professionals worry about errors in AI generated outputs, writes Thomson Reuters. “AI is doing real, meaningful work in tax workflows right now with even greater capabilities coming. But it’s also generating real anxiety,” Thomson Reuters notes.  

Health Day

MIT researchers found that unless an individual is affected by stroke or dementia, their ability to process language does not decline with age, writes Health Day’s Dennis Thompson. “Scans show that activity in the brain’s language processing network is nearly identical among seniors to that found in younger adults,” writes Thompson. “These results indicate that parts of the brain dedicated to unique functions like language might be less prone to age-related decline than general-purpose networks that contribute to many different skills.”  

Financial Times

The Financial Times’ Anjana Ahuja spotlights research led by Prof. Dennis Whyte on the economics of fusion energy. “Economic Q, the metric devised by Whyte and others and which must exceed one to represent net economic gain, compares the capital gained over a fusion energy plant’s lifetime to that expended,” writes Ahuja. “Factors reflect the extreme engineering involved and include construction costs, component durability and the efficiency of converting fusion power into a commodity.” 

Gizmodo

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.” 

The Boston Globe

In conversation with The Boston Globe’s Hilary Burns, MIT President Emeritus L. Rafael Reif discusses his views on the value of US research universities and why saying so publicly matters. It's “tough times for universities, and that means a non-ending decline for the US,” warns Reif. “There is something unique about a university that companies do not have and national labs do not have, which is students. If we believe that science is important, we have to have a place where we create the scientists of the future.” 

Forbes

Forbes’ Satya Krishnaswamy highlights a study co-authored by Lawrence Schmidt, a research affiliate at Sloan, that found AI can contribute to growth in certain roles where workers focus on higher-value tasks. “Schmidt’s research found that increased AI use was linked to both employment and sales growth,” writes Krishnaswamy.  

Forbes

Writing for Forbes, Arvid Ernst Gollwitzer, a research scholar at the Broad Institute of MIT and Harvard, spotlights FINGERS-7B, an AI foundation model for Alzheimer’s prevention his research team developed at MIT. “By analyzing signals spanning everything from genetic risk factors to long-term environmental exposures, the model detects patterns that no single-domain approach could find,” writes Gollwitzer. “These patterns, which we call multi-omic precision signatures, represent a new kind of biomarker for gauging early disease risk.” 

Forbes

MIT researchers have found that AI search features are unevenly distributed worldwide, and can sometimes share misleading information about images, writes Forbes’ Hastimal Jangid. “These incidents are important reminders that systems are only as good as the data they're trained on and that the long tail of data documenting the physical world is still being filled in,” writes Jangid.

Hotel Mars

Postdoctoral Associate Rohan Naidu joins John Batchelor and David Livingston, hosts of the “Hotel Mars” podcast, to discuss his research discovering black hole stars from little red dots using NASA’s James Webb Space Telescope. “When we first discovered the little red dots, we assumed that red means dust, and so the idea was that the little red dots are the kind of black holes that we see in our backyard,” says Naidu. “But now we have this paradigm shift where we are realizing that red does not mean dust. Red could mean that you have this black hole star kind of object where all the blue light is being soaked up in this dense star-like cocoon.” 

Fast Company

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.