Fast Company reporter Ruth Reader writes that researchers from MIT and other institutions have developed a new miniaturized detector that could be used to detect diseases by smell. “This paper was about integrating all the techniques that we know can work independently and finding out what of all this can go and become [part of] an integrated smartphone-based diagnostic,” says research scientist Andreas Mershin.
UPI reporter Brooks Hays writes that MIT researchers have developed a new machine learning algorithm that can anticipate and recognize a protein’s varied structures. “The new AI-system,” writes Hays, “does more than image a diversity of conformations, it can also predict the varied motions of different protein structures.”
TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a new “liquid” machine learning system that can learn on the job. Etherington notes that the system has “the potential to greatly expand the flexibility of AI technology after the training phase, when they’re engaged in the actual practical inference work done in the field.”
Wired reporter Will Knight spotlights how MIT researchers built a machine learning system that can help predict which patients are most likely to develop breast cancer. “What the AI tools are doing is they're extracting information that my eye and my brain can't,” says Constance Lehman, a professor of radiology at Harvard Medical School and division chief of breast imaging at MGH.
TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a new system that devises hardware architecture that can speed up a robot’s operations. Etherington notes that “this research could help unlock the sci-fi future of humans and robots living in integrated harmony.”
Fortune reporters Jeremy Kahn and Jonathan Vanian highlight MIT startup Macro-Eyes, which is focused on using AI to improve health care in low and middle-income countries.
Forbes contributor Louis Columbus spotlights Verta, an MIT startup that is “dedicated to solving the complex problems of managing machine learning model versions and providing a platform where they can be launched into production.”
Axios reporter Bryan Walsh spotlights a new study by researchers from MIT’s Task Force on the Work of the Future that examines the impact of AI on the future of work. Walsh notes that the report’s authors “recommend programs that can enhance computer skills from kindergarten through the university level, while urging businesses and worker organizations to build cushions for the sometimes harsh changes AI will wreak on work.”
Writing for the Financial Times, Ryosuke Harada highlights a new MIT report that emphasizes the “importance of education and investment in human resources and warns that in the absence of a strategy, jobs will be lost and divisions in society will widen.”
Forbes contributor Rob Toews spotlights the work of Professor Daniela Rus, the deputy dean of research for the Schwarzman College of Computing and director of CSAIL; graduate student Joy Buolamwini; and former MIT postdoc Rana el Kaliouby for their work shaping the future of AI. “They also serve as role models for the next generation of AI leaders, reflecting what a more inclusive AI community can and should look like," writes Toews.
Writing for Wired, Will Knight spotlights how MIT researchers developed a new technique to squeeze an AI vision algorithm onto a low-power computer chip that can run for months on a battery. The advance “could help bring more advanced AI capabilities, like image and voice recognition, to home appliances and wearable devices, along with medical gadgets and industrial sensors.”
Research scientist Brian Subirana speaks with The Economist’s Babbage podcast about his work developing a new AI system that could be used to help diagnose people asymptomatic Covid-19.
Prof. Daron Acemoglu speaks with Guardian reporter Lauren Aratani about the impact of automation on inequality. While AI has “tremendous potential for making humans more productive,” Acemoglu notes that it also “has been a major driver in the increase in inequality.”
Forbes contributor Adi Gaskell highlights a new study by CSAIL researchers that underscores the importance of foreign-born scientists when it comes to breakthroughs in AI. The researchers noted that “If we want the United States to continue to be ground zero for computer science, we need to make sure that our policies make it easy to continue to bring host international researchers to join our institutions.”
Axios reporter Bryan Walsh writes that during the virtual AI and the Work of the Future Congress, Elisabeth Reynolds, executive director of the MIT Task Force on the Work of the Future, noted that “education and training are central to helping the current and next generation thrive in the labor market.”