MIT Schwarzman College of Computing

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.” 

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.  

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.” 

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.”  

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.  

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.  

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.” 

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.” 

Chronicle of Philanthropy reporter Maria Di Mento spotlights how the creation of the MIT Schwarzman College of Computing allowed MIT to develop new “interdisciplinary programs to prepare students for an AI-saturated world and help them understand the social and ethical implications of digital technologies.” Prof. Daniel Huttenlocher, dean of the Schwarzman College of Computing, explains that: “MIT realized that effective education in the age of AI has to look different than it has in the past. Traditional siloing of expertise won’t work when AI is expected to touch nearly every part of people’s lives and is changing the way people in disciplines outside of computing are advancing their work.”

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.”

Writing for Forbes, contributor Ron Schmelzer highlights Describe Anything, Anywhere, at Any Moment (DAAAM), a new system developed by MIT researchers that could enable robots to capture details of objects they see while exploring an environment. In the future, the system could allow factory workers to send robotic assistants to find items. DAAAM “lets a robot build a detailed map of a space, attach descriptions to objects in that map, and answer plain English questions later,” Schmelzer explains. 

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.”