A team of scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Jameel Clinic (J-Clinic) demonstrated a deep learning system to predict cancer risk using just a patient’s mammogram. The model showed significant promise and even improved inclusivity: It was equally accurate for both white and Black women, which is especially important given that Black women are 43 percent more likely to die from breast cancer.
MIT researchers have developed a type of neural network that learns on the job, not just during its training phase. These flexible algorithms, dubbed “liquid” networks, change their underlying equations to continuously adapt to new data inputs. The advance could aid decision making based on data streams that change over time, including those involved in medical diagnosis and autonomous driving.
As part of the MIT Task Force on the Work of the Future’s series of research briefs, Professor Thomas Malone, Professor Daniela Rus, and Robert Laubacher collaborated on "Artificial Intelligence and the Future of Work," a brief that provides a comprehensive overview of AI today and what lies at the AI frontier.
CSAIL's Alan Edelman and Sam Madden have been elected as fellows of the Association for Computing Machinery (ACM). Both faculty members are "recognized as the top 1 percent for their outstanding accomplishments in computing and information technology and/or outstanding service to ACM and the larger computing community".
CSAIL's Sabrina Neuman has found a way to fight the mismatch between a robot’s “mind” and body. The method, called robomorphic computing, uses a robot’s physical layout and intended applications to generate a customized computer chip that minimizes the robot’s response time.
Gary Gensler, FinTech@CSAIL Faculty Co-Director, has been selected by President-elect Joe Biden to serve as the chair of the U.S. Securities and Exchange Commission (SEC).
Antonio Torralba, faculty head of Artificial Intelligence and Decision Making within the Department of Electrical Engineering and Computer Science (EECS) and the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science, has been selected as a 2021 Fellow by the Association for the Advancement of Artificial Intelligence (AAAI).
MIT neuroscientists have found that reading computer code does not activate the regions of the brain that are involved in language processing. Instead, it activates a distributed network called the multiple demand network, which is also recruited for complex cognitive tasks such as solving math problems or crossword puzzles.
