In October, a modified Dallara-15 Indy Lights race car programmed by MIT Driverless will hit the famed Indianapolis Motor Speedway at speeds of up to 120 miles per hour. The Indy Autonomous Challenge (IAC) is the world’s first head-to-head, high-speed autonomous race. It offers MIT Driverless a chance to grab a piece of the $1.5 […]Read More
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Numerous studies have shown that trained dogs can detect many kinds of disease — including lung, breast, ovarian, bladder, and prostate cancers, and possibly Covid-19 — simply through smell. In some cases, involving prostate cancer for example, the dogs had a 99 percent success rate in detecting the disease by sniffing patients’ urine samples. But […]Read More
Human language can be inefficient. Some words are vital. Others, expendable. Reread the first sentence of this story. Just two words, “language” and “inefficient,” convey almost the entire meaning of the sentence. The importance of key words underlies a popular new tool for natural language processing (NLP) by computers: the attention mechanism. When coded into […]Read More
There’s a mesmerizing video animation on YouTube of simulated, self-driving traffic streaming through a six-lane, four-way intersection. Dozens of cars flow through the streets, pausing, turning, slowing, and speeding up to avoid colliding with their neighbors. And not a single car stopping. But what if even one of those vehicles was not autonomous? What if […]Read More
Cryo-electron microscopy (cryo-EM) allows scientists to produce high-resolution, three-dimensional images of tiny molecules such as proteins. This technique works best for imaging proteins that exist in only one conformation, but MIT researchers have now developed a machine-learning algorithm that helps them identify multiple possible structures that a protein can take. Unlike AI techniques that aim […]Read More
To catch cancer earlier, we need to predict who is going to get it in the future. The complex nature of forecasting risk has been bolstered by artificial intelligence (AI) tools, but the adoption of AI in medicine has been limited by poor performance on new patient populations and neglect to racial minorities. Two years […]Read More
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 […]Read More
Contemporary robots can move quickly. “The motors are fast, and they’re powerful,” says Sabrina Neuman. Yet in complex situations, like interactions with people, robots often don’t move quickly. “The hang up is what’s going on in the robot’s head,” she adds. Perceiving stimuli and calculating a response takes a “boatload of computation,” which limits reaction […]Read More
The field of artificial intelligence is moving at a staggering clip, with breakthroughs emerging in labs across MIT. Through the Undergraduate Research Opportunities Program (UROP), undergraduates get to join in. In two years, the MIT Quest for Intelligence has placed 329 students in research projects aimed at pushing the frontiers of computing and artificial intelligence, […]Read More
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). AAAI Fellows are selected in […]Read More