Developing drugs to combat Covid-19 is a global priority, requiring communities to come together to fight the spread of infection. At MIT, researchers with backgrounds in machine learning and life sciences are collaborating, sharing datasets and tools to develop machine learning methods that can identify novel cures for Covid-19. This research is an extension of a community effort launched earlier this year. In February, before the Institute de-densified as a result of the pandemic, the first-ever AI Powered Drug Discovery and Manufacturing Conference, conceived and hosted by the Abdul Latif Jameel Clinic for Machine Learning in Health, drew attendees including pharmaceutical industry researchers, government regulators, venture capitalists, and pioneering drug researchers. More than 180 health care companies and 29 universities developing new artificial intelligence methods used in pharmaceuticals got involved, making the conference a singular event designed to lift the mask and reveal what goes on in the process of Continue reading MIT conference reveals the power of using artificial intelligence to discover new drugs→

Albert Einstein famously postulated that “the only real valuable thing is intuition,” arguably one of the most important keys to understanding intention and communication.  But intuitiveness is hard to teach — especially to a machine. Looking to improve this, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with a method that dials us closer to more seamless human-robot collaboration. The system, called “Conduct-A-Bot,” uses human muscle signals from wearable sensors to pilot a robot’s movement.  “We envision a world in which machines help people with cognitive and physical work, and to do so, they adapt to people rather than the other way around,” says Professor Daniela Rus, director of CSAIL, deputy dean of research for the MIT Stephen A. Schwarzman College of Computing, and co-author on a paper about the system.  To enable seamless teamwork between people and machines, electromyography and motion sensors are worn Continue reading Muscle signals can pilot a robot→

Six MIT faculty members are among more than 250 leaders from academia, business, public affairs, the humanities, and the arts elected to the American Academy of Arts and Sciences, the academy announced Thursday. One of the nation’s most prestigious honorary societies, the academy is also a leading center for independent policy research. Members contribute to academy publications, as well as studies of science and technology policy, energy and global security, social policy and American institutions, the humanities and culture, and education. Those elected from MIT this year are: Robert C. Armstrong, Chevron Professor in Chemical Engineering; Dave L. Donaldson, professor of economics; Catherine L. Drennan, professor of biology and chemistry; Ronitt Rubinfeld, professor of electrical engineering and computer science; Joshua B. Tenenbaum, professor of brain and cognitive sciences; and Craig Steven Wilder, Barton L. Weller Professor of History. “The members of the class of 2020 have excelled in laboratories and Continue reading Six from MIT elected to American Academy of Arts and Sciences for 2020→

As cases of Covid-19 continue to climb in parts of the United States, the number of people seeking treatment is threatening to overwhelm many hospitals, forcing some facilities to ration their care and reserve ventilators, hospital beds, and other limited medical resources for the sickest patients.  Having a handle on local hospitals’ capacity and resource availability could help balance the load of Covid-19 patients requiring hospitalization across a region, for instance allowing an EMT to send a patient to a facility where they are more likely to be treated quickly. But many states lack real-time data on their current capacity to treat Covid-19 patients.  A group of researchers in MIT’s Computer Science and Intelligence Laboratory (CSAIL), working with the MIT spinoff Mobi Systems, are aiming to help level demand across the entire health care network by providing real-time updates of hospital resources, which they hope will help patients, EMTs, and Continue reading Reporting tool aims to balance hospitals’ Covid-19 load→

Marija Ilic — a senior research scientist at the Laboratory for Information and Decision Systems, affiliate of the MIT Institute for Data, Systems, and Society, senior staff in MIT Lincoln Laboratory’s Energy Systems Group, and Carnegie Mellon University professor emerita — is a researcher on a mission: making electric energy systems future-ready. Since the earliest days of streetcars and public utilities, electric power systems have had a fairly standard structure: for a given area, a few large generation plants produce and distribute electricity to customers. It is a one-directional structure, with the energy plants being the only source of power for many end users. Today, however, electricity can be generated from many and varied sources — and move through the system in multiple directions. An electric power system may include stands of huge turbines capturing wild ocean winds, for instance. There might be solar farms of a hundred megawatts or Continue reading Shedding light on complex power systems→

Artificial intelligence has become a focus of certain ethical concerns, but it also has some major sustainability issues.  Last June, researchers at the University of Massachusetts at Amherst released a startling report estimating that the amount of power required for training and searching a certain neural network architecture involves the emissions of roughly 626,000 pounds of carbon dioxide. That’s equivalent to nearly five times the lifetime emissions of the average U.S. car, including its manufacturing. This issue gets even more severe in the model deployment phase, where deep neural networks need to be deployed on diverse hardware platforms, each with different properties and computational resources.  MIT researchers have developed a new automated AI system for training and running certain neural networks. Results indicate that, by improving the computational efficiency of the system in some key ways, the system can cut down the pounds of carbon emissions involved — in some Continue reading Reducing the carbon footprint of artificial intelligence→

Researchers have been able to restore sensation to the hand of a research participant with a severe spinal cord injury using a brain-computer interface (BCI) system. The technology harnesses neural signals that are so minuscule they can’t be perceived and enhances them via artificial sensory feedback sent back to the participant, resulting in greatly enriched motor function. More details

Housed at TED and supported by leading social impact advisor The Bridgespan Group, The Audacious Project is a collaborative funding initiative that’s catalyzing social impact on a grand scale by convening funders and social entrepreneurs, with the goal of supporting bold solutions to the world’s most urgent challenges. Among this year’s carefully selected change-makers is Jim Collins and a team at MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic), including co-principal investigator Regina Barzilay. The funding provided through The Audacious Project will support the response to the antibiotic resistance crisis through the development of new classes of antibiotics to protect patients against some of the world’s deadliest bacterial pathogens. “The work of Jim Collins and his colleagues is more relevant now than ever before,” says Anantha P. Chandrakasan, dean of the MIT School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “We Continue reading Jim Collins receives funding to harness AI for drug discovery→