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The Boston Globe

Boston Globe reporter James McCown highlights the architectural design of the new MIT Schwarzman College of Computing, noting that it is, “the most exciting work of academic architecture in Greater Boston in a generation.”Dean Daniel Huttenlocher adds: “The building was designed to be the physical embodiment of the college’s mission of fortifying studies in computer science and artificial intelligence. The building’s transparent and open design is already drawing a mix of people from throughout the campus and beyond.”

Business Insider

Prof. Daron Acemoglu’s new study projects just mild economic upside in the U.S. stemming from AI advancement, writes Business Insider’s Filip De Mott. According to Acemoglu, AI-led U.S. GDP growth in the next 10 years will rise just 0.93% to 1.16%, due to uncertainty on how much AI can really advance total factor productivity.

The Economist

Prof. Regina Barzilay joins The Economist’s “Babbage” podcast to discuss how artificial intelligence could enable health care providers to understand and treat diseases in new ways. Host Alok Jha notes that Barzilay is determined to “overcome those challenges that are standing in the way of getting AI models to become useful in health care.” Barzilay explains: “I think we really need to change our mindset and think how we can solve the many problems for which human experts were unable to find a way forward.”  

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.”

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

Popular Mechanics

Researchers at CSAIL have created three “libraries of abstraction” – a collection of abstractions within natural language that highlight the importance of everyday words in providing context and better reasoning for large language models, reports Darren Orf for Popular Mechanics. “The researchers focused on household tasks and command-based video games, and developed a language model that proposes abstractions from a dataset,” explains Orf. “When implemented with existing LLM platforms, such as GPT-4, AI actions like ‘placing chilled wine in a cabinet' or ‘craft a bed’ (in the Minecraft sense) saw a big increase in task accuracy at 59 to 89 percent, respectively.”

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. 

Scientific American

Scientific American’s Nick Hilden reports on the influence that popular narratives have on our collective perceptions. Graduate student Pat Pataranutaporn notes: “why do we always imagine science fiction to be a dystopia? Why can’t we imagine science fiction that gives us hope?”

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.

Fast Company

In an article for Fast Company, Lecturer Guadalupe Hayes-Mota offers five takeaways concerning the potential impact of AI on healthcare. Understanding AI’s healthcare potential “is crucial for business leaders and policymakers to foster an environment where AI and other analytics tools enhance rather than complicate societal outcomes,” Hayes-Mota writes.

New York Times

Break Through Tech A.I., a new program hosted and supported by MIT and a number of other universities, is providing free artificial intelligence courses to “reduce obstacles to tech careers for underrepresented college students, including lower-income, Latina and Black young women,” reports Natasha Singer for The New York Times. The program “aims to help lower-income students, many of whom have part-time jobs on top of their schoolwork, learn A.I. skills, develop industry connections and participate in research projects they can discuss with job recruiters,” writes Singer.