August 12, 2019
Writing for Science, Derek Lowe spotlights how MIT researchers are developing a platform that could be used to automate the production of molecules for use in medicine, solar energy and more. “The eventual hope is to unite the software and the hardware in this area,” reports Lowe, “and come up with a system that can produce new compounds with a minimum of human intervention.”
Writing for The Wall Street Journal, Prof. Stuart Madnick examines the ethical challenges posed by new AI technologies. “Ethical decisions are indeed hard, and AI will increasingly raise these dilemmas,” writes Madnick. “The dialogue on these matters must be started now, by creators of the science, by business leaders responsible for its uses, and by society which will have to live with the consequences.”
Fast Company reporter Lara Sorokanich spotlights how Prof. of the Practice Zeynep Ton’s work is focused on working with employers to improve the quality of jobs. Sorokanich writes that Ton “cites increasing minimum-wage laws and improved pay at Walmart, Target, and Amazon as signs of the sea change to come—but they’re just the first steps in what she considers a crucial overhaul of low-wage-workers’ conditions.”
TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a new way to speed up the planning process involved in a robot grasping an object. The new technique reduces the “total time from as much as 10 or more minutes to less than a second,” Etherington explains. “That’s many orders of magnitude better.”
Gizmodo visits Prof. Joseph Paradiso to learn more about the giant modular synthesizer he created. “One of the beautiful things about modular synths, I think, is they don’t do anything when you turn them on,” says Paradiso. “It forces you to be creative, to really try to think of something new because you are starting with nothing.”
MIT researchers have developed a new algorithm that can accurately identify actions in video while consuming a small fraction of the processing power previously required, reports Will Knight for Wired. “The work is a step towards having AI recognize what’s happening in video, perhaps helping to tame the vast amounts now being generated,” Knight explains.
Engadget reporter Christine Fisher writes that MIT researchers have developed a new technique that improves the speed and performance of video recognition models. Fisher writes that the new method “reduces the size of video-recognition models, speeds up training and could improve performance on mobile devices.”