Electrical engineering and computer science (EECS)

MIT researchers have developed a new ultrathin material that can turn any rigid surface into a speaker, reports Haje Jan Kamps for TechCrunch. “The loudspeaker could be used in active noise cancellation, for example — combine the speaker tech with some electronics and microphones, and it could cancel out sound,” writes Kamps. “The inventors also envision immersive sound experiences, and other low-energy use cases such as smart devices, etc.”

Daily Beast reporter Tony Ho Tran writes that MIT researchers have created a new loudspeaker that is as thin as paper and produces high-quality sound. The paper-thin device “weighs roughly the same as a dime, and can be used to cover surfaces like walls and ceilings,” writes Tran. “The loudspeaker also uses a fraction of the energy a typical speaker requires, while producing comparable sound quality.”

MIT researchers have developed a new technique that uses deep learning to improve the process of drug discovery, reports Jonathan Vanian for Fortune. “The technique addresses a common problem that researchers face when using A.I. to develop novel molecular structures: life sciences experts can often face challenges synthesizing A.I.-created molecular structures,” writes Vanian. 

MIT researchers have developed an ultrathin speaker that can be applied to surfaces like wallpaper, reports Andrew Liszewski for Gizmodo. “The applications for the thin-film speaker material are endless,” writes Liszewski. “In addition to being applied to interiors like office walls or even the inside of an airplane to cancel out unwanted noises, an entire car could be wrapped in a speaker, making it easier to alert pedestrians that an otherwise silent electric vehicle was approaching.”

TechCrunch reporter Kyle Wiggers spotlights how MIT researchers have developed a new computer vision algorithm that can identify images down to the individual pixel. The new algorithm is a “vast improvement over the conventional method of ‘teaching’ an algorithm to spot and classify objects in pictures and videos,” writes Wiggers.

Nature Physics senior editor Silvia Milana spotlights “Carbon Queen: The Remarkable Life of Nanoscience Pioneer Mildred Dresselhaus” a new book written by MIT News Deputy Editorial Director Maia Weinstock. “Carbon Queen does not only capture the journey into the personal and professional life of an outstanding figure in carbon science, it is a careful account of the evolution of societal attitudes towards women from the 1950s to today” writes Milana.

TechCrunch reporter Brian Heater spotlights new MIT robotics research, including a team of CSAIL researchers “working on a system that utilizes a robotic arm to help people get dressed.” Heater notes that the “issue is one of robotic vision — specifically finding a method to give the system a better view of the human arm it’s working to dress.”

The Boston Globe highlights Robert Buderi’s new book, “Where Futures Converge: Kendall Square and the Making of a Global Innovation Hub.” Buderi features the Future Founders Initiative, an effort by Prof. Sangeeta Bhatia, President Emerita Susan Hockfield and Prof. Emerita Nancy Hopkins aimed at increasing female entrepreneurship. 

TechCrunch reporter Kyle Wiggers spotlights MIT startup Amplemarket, a sales enablement company, co-founded by João Batalha ’13, Luis Batalha and Micael Oliveira. “We’ve leveraged our combination of technical backgrounds and applied it to one of the oldest trades: sales,” says J. Batalha.

MIT startup ReadySet, co-founded by Alana Marzoev PhD ’18 and Jon Gjengset PhD ’20, provides database infrastructure to help developers build real-time applications, reports Kyle Wiggers for TechCrunch. “Rather than rebuilding these same broken systems, developers need solutions that slot into their existing infrastructure and achieve limitless read scaling,” says Marzoev. “With ReadySet, we aim to make the process of globally caching… query results as streamlined and automated as caching images in a content delivery system.”

MIT researchers and two high school seniors have developed DualFair, a new technique for removing bias from a mortgage lending dataset, reports Hiawatha Bray for The Boston Globe. “When a mortgage-lending AI was trained using DualFair and tested on real-world mortgage data from seven US states,” writes Bray, “the system was less likely to reject applications of otherwise qualified borrowers because of their race, sex, or ethnicity.”

The MIT AI Hardware Program seeks to bring together researchers from academia and industry to “examine each step of designing and manufacturing the hardware behind AI-powered technologies,” reports Emily Bamforth for EdScoop. “This program is about accelerating the development of new hardware to implement AI algorithms so we can do justice to the capabilities that computer scientists are developing,” explains Prof. Jesús del Alamo.

New research by Professor Erik Demaine, lecturer Zachary Abel, robotics engineer Martin Demaine and their colleagues explores whether it is possible to “take any polyhedral (or flat-sided) shape that’s finite (like a cube, rather than a sphere or the endless plane) and fold it flat using creases," writes Rachel Crowell for Quanta Magazine. “By moving finite to infinite ‘conceptual’ slices, they created a procedure that, taken to its mathematical extreme, produced the flattened object they were looking for,” Crowell explains.

MIT researchers have developed reconfigurable, self-assembling robotic cubes embedded with electromagnets that allow the robots to easily change shape, reports John Koetsier for Forbes. “If each of those cubes can pivot with respect to their neighbors you can actually reconfigure your first 3D structure into any other arbitrary 3D structure,” explains graduate student Martin Nisser.

CSAIL researchers have developed a new technique that could enable robots to handle squishy objects like pizza dough, reports Brian Heater for TechCrunch.  “The system is separated into a two-step process, in which the robot must first determine the task and then execute it using a tool like a rolling pin,” writes Heater. “The system, DiffSkill, involves teaching robots complex tasks in simulations.”