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Computer Science and Artificial Intelligence Laboratory (CSAIL)

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The Boston Globe

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.”

TechCrunch

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." 

Scientific American

Researchers from MIT and elsewhere have developed a new AI technique for teaching robots to pack items into a limited space while adhering to a range of constraints, reports Nick Hilden for Scientific American. “We want to have a learning-based method to solve constraints quickly because learning-based [AI] will solve faster, compared to traditional methods,” says graduate student Zhutian “Skye” Yang.

Politico

Writing for Politico, MIT Prof. Armando Solar-Lezama and University of Texas at Austin Prof. Swarat Chaudhuri examine the recent executive order on AI. “Especially as new ways to train models with limited resources emerge, and as the price of computing goes down,” they write, “such regulations could start hurting the outsiders — the researchers, small companies, and other independent organizations whose work will be necessary to keep a fast-moving technology in check.”

The Boston Globe

Prof. Daniela Rus, director of CSAIL, speaks with The Boston Globe’s Hiawatha Bray the future of AI. “Everyone is recognizing that AI can have an impact on their business, and they’re just wondering exactly how,” says Rus. She adds that she foresees, “a future where generative AI is not just a technological marvel, but a force for hope and a force for good.”

Curiosity Stream

Four faculty members from across MIT - Professors Song Han, Simon Johnson, Yoon Kim and Rosalind Picard - speak with Curiosity Stream about the opportunities and risks posed by the rapid advancements in the field of AI. “We do want to think about which human capabilities we treasure,” says Picard. She adds that during the Covid-19 pandemic, “we saw a lot of loss of people's ability to communicate with one another face-to-face when their world moved online. I think we need to be thoughtful and intentional about what we're building with the technology and whether it's diminishing who we are or enhancing it.”

The Messenger

Writing for The Messenger, graduate student Kartik Chandra highlights the MIT Art Lending Program, which allows students to select one piece from the List Visual Arts Center’s collection to keep in their dorm rooms for the duration of the academic year. “Three years into my time at MIT, I’m convinced the program works well,” writes Chandra. “Our relationship with art changes from the moment we walk into the gallery. As students wander, pondering what to take home, conventional measures of fame, monetary worth, and even beauty fall away, and the only question that matters becomes: Does this piece speak to you, personally? And something always does — as if it were put there just for you.”

The Daily Beast

Researchers from MIT and elsewhere have developed a new 3D printing process that “allows users to create more elastic materials along with rigid ones using slow-curing polymers,” reports Tony Ho Tran for the Daily Beast. The researchers used the system to create a, “3D printed hand complete with bones, ligaments, and tendons. The new process also utilizes a laser sensor array developed by researchers at MIT that allows the printer to actually ‘see’ what it’s creating as it creates it.”

The Economist

The Economist reporter Rachel Lloyd predicts a “distinct change” in topics for bestselling books in 2024. Lloyd predicts artificial intelligence will take a lead, spotlighting “The Heart and Chip: Our Bright Future with Robots,” by Prof. Daniela Rus, director of CSAIL, as a leading example of the shift.

Nature

Researchers at MIT and elsewhere have identified key cell types that may protect the brain against Alzheimer’s symptoms, reports Sara Reardon for Nature. “Most Alzheimer’s research has focused on excitatory neurons, which relay electrical signals to activate other neurons,” explains Reardon. “But the authors found that the cells with reelin or somatostatin were inhibitory neurons, which halt neuronal communication. These inhibitory cells might therefore have a previously unknown role in the types of cognitive function that are lost during Alzheimer’s.”

GBH

Prof. Eric Klopfer, co-director of the RAISE initiative (Responsible AI for Social Empowerment in Education), speaks with GBH reporter Diane Adame about the importance of providing students guidance on navigating artificial intelligence systems. “I think it's really important for kids to be aware that these things exist now, because whether it's in school or out of school, they are part of systems where AI is present,” says Klopfer. “Many humans are biased. And so the [AI] systems express those same biases that they've seen online and the data that they've collected from humans.”

The Economist

Prof. Regina Barzilay speaks with The Economist about how AI can help advance medicine in areas such as uncovering new drugs. With AI, “the type of questions that we will be asking will be very different from what we’re asking today,” says Barzilay.

Scientific American

A new study by MIT researchers demonstrates how “machine-learning systems designed to spot someone breaking a policy rule—a dress code, for example—will be harsher or more lenient depending on minuscule-seeming differences in how humans annotated data that were used to train the system,” reports Ananya for Scientific American. “This is an important warning for a field where datasets are often used without close examination of labeling practices, and [it] underscores the need for caution in automated decision systems—particularly in contexts where compliance with societal rules is essential,” says Prof. Marzyeh Ghassemi.

Forbes

Forbes reporter Rob Toews spotlights Prof. Daniela Rus, director of CSAIL, and research affiliate Ramin Hasani and their work with liquid neural networks. “The ‘liquid’ in the name refers to the fact that the model’s weights are probabilistic rather than constant, allowing them to vary fluidly depending on the inputs the model is exposed to,” writes Toews.

Forbes

Venti Technologies, which was co-founded by MIT researchers and alumni, is working to build autonomous vehicles for industrial and global supply chain hubs, reports Bruce Rogers for Forbes. “Working with the world's leading port operator provides Venti the opportunity to bring the economics of autonomous vehicles to over 60 ports globally,” writes Rogers. “These ports operate 24/7 requiring 2-3 shifts of human drivers.”