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.”
Researchers from the Media Lab developed MemPal, a wearable camera that creates a real-time automated text diary of actions and conversations to help older adults locate objects and provide reminders, writes WBUR’s Mike Kalin. “A small study conducted last year by researchers at the MIT Media Lab confirmed improved performance of object finding among users and an overall positive perception of the system. Tools like MemPal could be essential as cases of dementia continue to proliferate,” writes Kalin.
Prof. Paul Osterman speaks to Forbes’ Courtney Connley-Hampton about his new book “Disposable Workers: The Transformation of Employment,” and how AI may exacerbate the disposable worker trend. “Your only source of power in the labor market is your human capital, your skill,” says Osterman. “Get as much skill as you can. You may end up having to change jobs and move around, but if you have valuable skills, that protects you.”
Associate Prof. Taha Choukhmane speaks to Associated Press reporter Adriana Morga about explores the growing trend of consumers using AI for financial guidance, and his recommendation that AI be used as a tool in combination with other trusted sources. “I would encourage people to use AI to explain and define,” says Choukhmane. “If you’re interested in knowing what the stock market is, what the difference between a mutual fund and an index fund is, using AI to explain these concepts can be very useful because it can empower people to get the most out of these methods.”
In a Los Angeles Times opinion piece, Prof. Carlo Ratti and contributor Mario Carpo make the case that AI is built to imitate human creativity and is less capable of original design. “In a profession that defines itself through invention, GenAI increasingly is seen less as a creative genius and more as a ‘stochastic parrot’ — a term introduced in 2021 by leading AI researchers to describe a technology that learns to repeat the most likely sequences found in whatever data it’s been shown,” write Ratti and Carpo.
Upworthy’s Tod Perry outlines five key takeaways from “How to Speak,” a popular lecture on the art of public speaking given annually for MIT students for 40 years by the late Prof. Patrick Winston, which is now available to watch on MIT OpenCourseware. “I always finish [ a speech] with a joke, and that way, people think they’ve had fun the whole time,” quipped Winston in his lecture.
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.”
Principal Research Scientist John Liu speaks to Manufacturing Dive’s Nathan Owens about MIT’s Technologist Advanced Manufacturing Program (TechAMP), a 12-month-long certificate program designed to "bring experienced technicians into leadership roles with a focus on advanced manufacturing needs.” Says Liu: "We’re looking at developing this elite workforce who bridges the gap. What we’re trying to do is upskill the technician.”
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.
In a new study by MIT FutureTech, 272 researchers ranked the top 24 AI risks, write Axios reporters Jim VandeHei and Mike Allen. The researchers “assessed a 12% chance that AI's dangerous capabilities produce a catastrophic outcome by 2030, and another 12% chance of AI-enabled weapons and mass-harm capabilities [with mitigation efforts to reduce risk],” VandeHei and Allen explain.
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.
Prof. Daniela Rus, director of CSAIL, joins Hakeem Oluseyi, host of GBH’s “Particles of Thought,” to discuss the lab’s work utilizing AI to enhance robots’ ability to move, reason, and act like humans. “The objective is to bring AI’s ability to understand text, images, and other online information to make physical machines intelligent, and if we achieve this then AI will not just reside in our computers—it will drive, it will walk it will fly, it will interact with us in the physical world.”
Prof. Tom Leighton, CEO of Akamai, speaks to Fast Company reporter Victor Dey about his vision for a faster and cheaper AI grid that could serve as an alternative to large data centers, and more effectively route inference workloads. “Many inference tasks do not need the largest model or the largest cluster or the most expensive compute,” says Leighton. “What they need is the ability to marry the right model, in the right place, data and moment, at the most effective cost.”
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.”