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Scientific American

Current AI models require enormous resources and often provide unpredictable results. But graduate student Ziming Liu and colleagues have developed an approach that surpasses current neural networks in many respects, reports Manion Bischoff for Scientific American. “So-called Kolmogorov-Arnold networks (KANs) can master a wide range of tasks much more efficiently and solve scientific problems better than previous approaches,” Bischoff explains.

Financial Times

Financial Times reporter Robin Wigglesworth spotlights Prof. Daron Acemoglu’s new research that predicts relatively modest productivity growth from AI advances. On generative AI specifically, Acemoglu believes that gains will remain elusive unless industry reorients “in order to focus on reliable information that can increase the marginal productivity of different kinds of workers, rather than prioritizing the development of general human-like conversational tools,” he says.

Financial Times

Writing for the Financial Times, Jon Hilsenrath revisits lessons from the occupational shifts of the early 2000s when probing AI’s potential impact on the workplace. He references Prof. David Autor’s research, calling him “an optimist who sees a future for middle-income workers not in spite of AI, but because of it…creating work and pay gains for large numbers of less-skilled workers who missed out during the past few decades.”

NPR

On NPR’s Short Wave, climate correspondent Lauren Sommer reports on MIT researchers using artificial intelligence to decode the secret language of sperm whales. Prof. Daniela Rus says, “it really turned out that sperm whale communication was indeed not random or simplistic but rather structured in a very complex, combinatorial manner.”

WBUR

Prof. David Autor is a guest of Meghna Chakrabarti on WBUR’s On Point, discussing his research on the potential impact of AI on the workforce. Autor says “AI is a tool that can enable more people with the right foundational training and judgment to do more valuable work.”

TechCrunch

Researchers at MIT and elsewhere have developed a new machine-learning model capable of “predicting a physical system’s phase or state,” report Kyle Wiggers and Devin Coldewey for TechCrunch

Nature

Nature reporter Andrew Robinson reviews “The Heart and the Chip,” a new book by Prof. Daniela Rus and science writer Gregory Mone. The book “focuses on combining human and robotic strengths to pair ‘the heart and the chip’ in three interlinked fields: robotics, artificial intelligence and machine learning,” explains Robinson. 

The Hill

The Hill reporter Tobias Burns spotlights the efforts of a number of MIT researchers to better understand the impact of generative AI on productivity in the workforce. One research study “looked as cases where AI helped improved productivity and worker experience specifically in outsourced settings, such as call centers,” explains Burns. Another research study explored the impact of AI programs, such as ChatGPT, among employees. 

Forbes

Forbes selects innovators for the list’s Healthcare & Science category, written by senior contributor Yue Wang. On the list is MIT PhD candidate Yuzhe Yang, who studies AI and machine learning technologies capability to monitor and diagnose illnesses such as Parkinson's disease.

The New York Times

Researchers from MIT and elsewhere have used quantitative and computational methods to analyze animal communication, reports Emily Anthes for The New York Times.

The Guardian

An analysis by MIT researchers has identified “wide-ranging instances of AI systems double-crossing opponents, bluffing and pretending to be human,” reports Hannah Devlin for The Guardian. “As the deceptive capabilities of AI systems become more advanced, the dangers they pose to society will become increasingly serious,” says postdoctoral associate Peter Park. 

Quanta Magazine

MIT researchers have developed a new procedure that uses game theory to improve the accuracy and consistency of large language models (LLMs), reports Steve Nadis for Quanta Magazine. “The new work, which uses games to improve AI, stands in contrast to past approaches, which measured an AI program’s success via its mastery of games,” explains Nadis. 

Smithsonian Magazine

MIT researchers have used advancements in machine learning and computing to help decode whale vocalizations, reports Sarah Kuta of Smithsonian Magazine. “If researchers knew what sperm whales were saying, they might be able to come up with more targeted approaches to protecting them,” Kuta explains. “In addition, drawing parallels between whales and humans via language might help engage the broader public in conservation efforts.”

Reuters

A new analysis of years of vocalizations by sperm whales in the eastern Caribbean has provided a fuller understanding of how whales communicate using codas, reports Will Dunham of Reuters. Graduate student Pratyusha Sharma explained that: "The research shows that the expressivity of sperm whale calls is much larger than previously thought."

New Scientist

New Scientist reporter Clare Wilson writes that a new analysis by MIT researchers of thousands of exchanges made by east Caribbean sperm whales demonstrates a communication system more advanced than previously thought. “It’s really extraordinary to see the possibility of another species on this planet having the capacity for communication,” says Prof. Daniela Rus.