Download RSS feed: News Articles / In the Media / Audio
The Register’s Thomas Claburn highlights a new study by MIT researchers that found large AI models can still reproduce an artist’s style, even when the artist’s work is removed from its training data, making attribution more difficult. “[G]iven the contemporary adoption of these models for creative and commercial purposes, attributability also carries ethical, policy, financial, and legal implications,” the researchers note.
MIT researchers found the more data an AI model is trained on could complicate AI copyright, auditing, and governance, writes Computer World’s Taryn Plumb. “[S]ingle artworks by specific artists, or photographs of certain people, could be entirely removed from datasets, and the model could still reproduce that image or style,” writes Plumb. “Essentially, tangible connections are lost, and linking to specific data points responsible for generated samples is ‘practically impossible,’ or can even vanish, the researchers explained.”
Boston.com’s Elizabeth Mehler spotlights an AI-powered flood predictor and disaster response tool built by Arush Shangari, an MIT Beaver Works Research Scholar. “Through MIT Beaver Works and MIT CSAIL, I taught myself artificial intelligence and time-series forecasting,” says Shangari. “There was a lot of that error analysis and just learning in general.”
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.”
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.
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. Daniela Rus, director of CSAIL, joins Hakeem Oluseyi, host of GBH’s “Particles of Thought,” to discuss her group’s work developing liquid neural networks, AI that runs locally on a given device rather than a data center to increase privacy and improve energy efficiency. By using liquid AI, "you avoid privacy concerns and you avoid the security concerns associated with accessing the cloud,” says Rus. “Furthermore, the cost of running your models on a device is much, much lower than running a huge model in the cloud.”
Writing for Forbes about efforts to improve air travel safety, Tanya Eves highlights the Air-Guardian system, an eye-tracking monitor for pilots developed by CSAIL researchers that assists when attention wavers. “In tests, it reduced flight risk and improved navigation success rates,” writes Eves. “It's a model for how the virtual co-pilot relationship should work: not replacement, but a seamless, intelligent partnership that understands when to act and when to stay silent.”
Scientific American reporter Deni Ellis Béchard spotlights graduate student Alex Zhang for the publication’s special section featuring 28 rising young scientists. “The types of research that I want to work on are things that I think should be shared for the benefit of people in general,” Zhang says of his work aimed at improving AI user experience with recursive language models.
Writing for IEEE Spectrum, reporter Matthew S. Smith highlights Fractal, a new operating system hand-coded by CSAIL researchers to provide a clear view of security vulnerabilities. “We paved the way with techniques such as custom kernel patches and kernel extensions,” says graduate student Joseph Ravichandran. “The dream was always to have a completely custom operating system which would make these hacks unnecessary.”
Nature reporter Jyoti Madhusoodanan features Prof. Regina Barzilay and Prof. James Collin’s work developing AI tools aimed at accelerating the process of drug discovery and tackling the growing problem of antibiotic resistance. Barzilay notes that the goal of AI-based drug design is not to have the perfect method, but to find working solutions to the antibiotic-resistance crisis. “To me, the art is really in taking the tools we currently have, which are already doing quite a bit, and translating them into something which is useful in clinic,” she explains.
Prof. Regina Barzilay speaks with WBUR’s Priyanka Dayal McCluskey about her work developing an AI risk detection tool that can analyze mammogram images and help predict risk of breast cancer before it happens or spreads. Barzilay, who describes the tool as a hi-tech weather forecast for breast health, notes that: “We really need to have tools that can help, rather than just staring at an image and trying to guess.”
Sybil, a new AI tool developed by researchers from MIT and Mass General Brigham Cancer Institute, “analyzes a single CT scan and generates a risk score predicting the likelihood of developing lung cancer over a period of up to six years,” reports Ivan Rodriguez for WCVB-TV. “In 2023, researchers reported that Sybil achieved an accuracy rate of 86% to 94% in distinguishing high-risk patients from low-risk patients within a year.”
Fortune reporter Nick Lichtenberg highlights research by MIT economists that finds “automation doesn’t affect all parts of a job equally. The critical variable is whether the tasks being automated are the expert parts of a role or the administrative scaffolding around them.”