Wardah Inam SM '12, PhD '16 founded Overjet, an AI platform that helps dentists “diagnose diseases from scans and other data,” reports Saritha Rai for Bloomberg. “Dentistry was more art than science, and I wanted to bring technology and AI to help dentists make objective decisions,” says Inam. “We began building and then improving our AI systems with tens of millions of pieces of data, including X-rays, historical information, dentist notes, and periodontal charts.”
Prof. Daniela Rus, director of CSAIL, speaks with Boston Globe reporter Evan Sellinger about her new book, “The Heart and the Chip: Our Bright Future With Robots,” in which she makes the case that in the future robots and humans will be able to team up to create a better world. “I want to highlight that machines don’t have to compete with humans, because we each have different strengths. Humans have wisdom. Machines have speed, can process large numbers, and can do many dull, dirty, and dangerous tasks,” Rus explains. “I see robots as helpers for our jobs. They’ll take on the routine, repetitive tasks, ensuring human workers focus on more complex and meaningful work.”
Writing for The Hill, Prof. Christopher Knittel and graduate student Kailin Graham emphasize the importance of ensuring the transition away from fossil fuels is an equitable process that provides support for vulnerable workers. “If we’re serious about achieving a truly just transition, far more federal policy action is needed,” they write.
MIT researchers have developed a new technique “that could allow most large language models (LLMs) like ChatGPT to retain memory and boost performance,” reports Tony Ho Tran for the Daily Beast. “The process is called StreamingLLM and it allows for chatbots to perform optimally even after a conversation goes on for more than 4 million words,” explains Tran.
MIT has been named to the number two spot in Times Higher Education’s world reputation rankings, reports Times Higher Education. MIT is “dedicated to the teaching of science and technology. The sheer number of Nobel laureates affiliated with the institution – an impressive 101 – reveals the caliber of MIT graduates,” Times Higher Education notes. “Scientific discoveries and technological advances to come out of the college include the first chemical synthesis of penicillin, the development of radar, the discovery of quarks and the invention of magnetic core memory, which aided the development of digital computers.”
A study by MIT researchers has uncovered an, “intricate relationship between jobs and the nation’s energy transition,” reports Kaleigh Harrison for Environment + Energy Leader. The study, “presents an unprecedented county-level examination of the U.S., identifying regions most intertwined with fossil fuels – ranging from intensive drilling and mining operations to heavy manufacturing sectors,” writes Harrison. “The findings underscore not only the expected impact on traditional energy bastions but also highlight the broader, often overlooked, implications for areas heavily invested in manufacturing.”
Fast Company reporter Kristin Toussaint spotlights how MIT researchers have developed a new map detailing how the shift to clean energy could impact jobs around the country. The researchers found that workers could be most impacted in areas that drill for oil and gas, as well as “regions with a high concentration of manufacturing, agriculture, and construction—all industries that rely heavily on coal, oil, and gas.”
BostInno reporter Isabel Tehan spotlights how MIT researchers have developed a model to predict how different shoes will impact different individual runners. “The model takes into account runner height, weight and other body dimensions, and the properties of the shoes — including stiffness or springiness — and can predict how that individual would run in a particular pair of shoes,” writes Tehan. “Ideally, we could make a shoe that's right for you and the way you run,” explains postdoc Sarah Fay.
Researchers from MIT and elsewhere have developed an AI model that is capable of identifying 3 ½ times more people who are at high-risk for developing pancreatic cancer than current standards, reports Felice J. Freyer for The Boston Globe. “This work has the potential to enlarge the group of pancreatic cancer patients who can benefit from screening from 10 percent to 35 percent,” explains Freyer. “The group hopes its model will eventually help detect risk of other hard-to-find cancers, like ovarian.”
Javier Ramos '12, SM '14, co-founder of InkBit, and his colleagues have developed a, “3D inkjet printer that uses contact-free computer vision feedback to print hybrid objects with a broad range of new functional chemistries,” reports Ed Brown for Tech Briefs. “Our vision for Inkbit is to reshape how the world thinks about production, from design to execution and make our technology readily available,” says Ramos. “The big opportunity with 3D printing is how to disrupt the world of manufacturing — that’s what we're focused on.”
Prof. Jessika Trancik writes for Newsweek about the importance of government policy in supporting the transition to electric vehicles. “Policy is needed to make EVs widely accessible to people while the technology and markets continue to mature,” writes Trancik, “and to ensure the process moves quickly enough to help slow the build-up of greenhouse gases in the atmosphere.”
Prof. Jessika Trancik speaks with Associated Press reporter Alexa St. John to discuss electric vehicle emissions and ownership costs. Trancik notes, “buyers should consider total cost of ownership, which for an EV is generally less than that of a gas-powered counterpart due to savings on maintenance and fuel.”
MIT researchers have used machine learning to uncover the different kinds of sentences that most likely to activate the brain’s key language processing centers, reports Kyle Wiggers and Devin Coldewey for TechCrunch. The model, “was able to predict for novel sentences whether they would be taxing on human cognition or not,” they explain.
Boston Globe reporters Aaron Pressman and Jon Chesto spotlight Liquid AI, a new startup founded by MIT researchers that is developing an AI system that relies on neural-network models that are “much simpler and require significantly less computer power to train and operate” than generative AI systems. “You need a fraction of the cost of developing generative AI, and the carbon footprint is much lower,” explains Liquid AI CEO Ramin Hasani, a research affiliate at CSAIL. “You get the same capabilities with a much smaller representation.”
Prof. Daniela Rus, director of CSAIL, and research affiliates Ramin Hasani, Mathias Lechner, and Alexander Amini have co-founded Liquid AI, a startup building a general-purpose AI system powered by a liquid neural network, reports Kyle Wiggers for TechCrunch. “Accountability and safety of large AI models is of paramount importance,” says Hasani. “Liquid AI offers more capital efficient, reliable, explainable and capable machine learning models for both domain-specific and generative AI applications."