Nature reporter Amanda Heidt speaks with postdoctoral researcher Tigist Tamir about her experience using generative AI with attention-deficit hyperactivity disorder. “Whether I’m reading, writing or just making to-do lists, it’s very difficult for me to figure out what I want to say. One thing that helps is to just do a brain dump and use AI to create a boiled-down version,” Tamir explains. She adds, “I feel fortunate that I’m in this era where these tools exist.”
Postdoc Xuhai Xu and his colleagues have developed an AI program that can distribute pop-up reminders to help limit smartphone screen time, reports Jeremy Hsu for New Scientist. Xu explains that “a random notification to stop doomscrolling won’t always tear someone away from their phone. But machine learning can personalize that intervention so it arrives at the moment when it is most likely to work,” writes Hsu.
Graduate student Dhruv Gaur speaks with Boston.com reporter Lauren Daley about his viral message expressing support for Alex Trebek when he competed on “Jeopardy” in 2019, and his experience being invited back for the show’s first invitational tournament. “I listened to a ton of podcasts — old pop culture from the ‘70s ‘80s and ‘90s; history, Shakespeare,” says Gaur of how he prepared for the tournament. “I got really into quiz games on my phone or computer. I was shocked that nobody realized what I was doing because anytime I got a free second I’d be doing a quiz, or asking friends to go to bar trivia.”
A number of MIT faculty and alumni – including Prof. Daniela Rus, Prof. Regina Barzilay, Research Affiliate Haddad Habib, Research Scientist Lex Fridman, Marc Raibert PhD '77, former Postdoc Rana El Kaliouby and Ray Kurzweil '70 – have been named key figures “at the forefront of Boston’s AI revolution,” reports Wyndham Lewis for Boston Magazine. These researchers are “driving progress and reshaping the way we live,” writes Lewis.
MIT researchers have developed a new technique that uses a large language model to allow robots to self-correct after making a mistake, reports Brian Heater for TechCrunch. “Researchers behind the study note that while imitation learning (learning to do a task through observation) is popular in the world of home robotics, it often can’t account for the countless small environmental variations that can interfere with regular operation, thus requiring a system to restart from square one,” writes Heater. “The new research addresses this, in part, by breaking demonstrations into smaller subsets."
Prof. Pulkit Agrawal and graduate student Gabriel Margolis speak with The Economist’s Babbage podcast about the simulation research and technology used in developing intelligent machines. “Simulation is a digital twin of reality,” says Agrawal. “But simulation still doesn’t have data, it is a digital twin of the environment. So, what we do is something called reinforcement learning which is learning by trial and error which means that we can try out many different combinations.”
Using the James Webb Space Telescope, postdoc Rohan Naidu will be studying “some of the particularly large and red galaxies, [called little red dots,] that appear much brighter and more massive than theorists have expected galaxies at this epoch to be,” reports Jonathan O’Callaghan for Scientific American. Naidu’s “program will seek to settle the debat about little red dots once and for all,” writes O’Callaghan.
A new study conducted by researchers at MIT and elsewhere has found large language models (LLMs) can be used to predict the future as well as humans can, reports Chris Stokel-Walker for Fast Company. “Accurate forecasting of future events is very important to many aspects of human economic activity, especially within white collar occupations, such as those of law, business and policy,” says postdoctoral fellow Peter S. Park.
Former postdoc Leah Ellis speaks with GBH All Things Considered host Arun Rath about Sublime Systems, an MIT startup she co-founded that aims to produce carbon-free cement to combat climate change. “Sublime Systems and this technology spun out of my postdoctoral work at MIT,” says Ellis. “My co-founder and I are both electric chemists, so we have experience with battery technologies and electrochemical systems. Our idea was thinking about how we might use renewable energy—which we know has become more abundant, inexpensive and available—to eliminate the CO2 emissions from cement.”
Graduate student Lauren “Ren” Ramlan programmed Doom, an iD software video game, to run on a display made from E.coli cells, reports Andrew Paul for Popular Science. For the project to work, “Ramlan first grew cells within a 32×48 1-bit well plate, then connected the makeshift screen to a controller capable of processing and translating binary code into the ‘addition or omission of a repressor controlling the fluorescence of the cells,’” writes Paul. “Basically, Ramlan swapped a traditional screen’s tiny light diodes for glowing bacterial cells."
Arthur Musah '04, MEng '05 and Philip Abel '15 speak with GBH “Under The Radar” host Callie Crossley about Musah’s documentary, “Brief Tender Light,” which follows the life of four African-born students on their personal and academic experiences at MIT. “The takeaway for me is about how we all belong in all spaces all around the world,” says Musah. “For me, the film has always been about celebrating the lives of African students and Black people at institutions like MIT.”
Chronicle of Higher Ed reporter Karin Fischer spotlights “A Brief Tender Light,” a documentary created by Arthur Musah '04, MEng '05 that follows four African undergraduates at MIT on their journey as international students studying and working in Boston. Musah’s “dream scenario is that such screenings could facilitate dialogue between groups represented in the documentary, such as international and African students, students of color, and gay and lesbian students,” writes Fischer.
Graduate student Zhichu Ren has developed CRESt (Copilot for Real-World Experimental Scientist), a lab assistant which “suggests experiments, retrieves data, manages equipment and guides research to the next steps in an experiment,” reports Ryan Heath for Axios.
Prof. Fiona Murray, associate dean for innovation and inclusion at MIT Sloan, speaks with Bloomberg Law reporter Lauren Castle about her recent study that found female PhD students are 17% less likely to become new inventors compared with their male counterparts. “What we can show is relative to the supply into Ph.D. programs, there’s still just this huge difference in the percentage of women on patents coming out of the labs than there are in the university,” says Murray.
Writing for Inside Higher Ed, Columbia University Simons Fellow Robert W. Fernandez highlights MIT’s “publicly published outcomes for students of color.” “MIT’s data showed, for example, that the population of enrolled graduate students in biology who identified as underrepresented minorities increased from 4 percent in 2005 to 19 percent in 2023—suggesting that the institute’s recruitment efforts for that department have improved over time,” explains Fernandez.