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Gizmodo

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.” 

Fast Company

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.  

Digital Trends

MIT researchers have discovered that when individual images are removed from large AI diffusion models, the models are still able to produce like images, writes Digital Trends’ Varun Mirchandani. “The more interesting takeaway is that this connection becomes increasingly difficult to trace as datasets grow,” writes Mirchandani. “An AI-generated image may draw on patterns learned from an enormous pool of material without having a clear, identifiable source image behind it.” 

 

The Register

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.  

 

Computer World

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.” 

New Scientist

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.” 

Fast Company

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.” 

Fox News

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.  

GBH

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.” 

Tech Briefs

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.” 

Chronicle of Philanthropy

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.”

Forbes

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.”

Forbes

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. 

IEEE Spectrum

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.”

CNN

In an effort to defend medical devices against quantum attacks, MIT researchers have engineered an ultra-efficient microchip that can protect wireless biomedical devices, such as insulin pumps and pacemakers, reports Katie Hunt for CNN. The microchip, which is around the size of an extremely fine needle tip, “includes built-in protection needed for post-quantum cybersecurity. The device achieved between 20 and 60 times higher energy efficiency than other post-quantum security techniques.”