“Most updated digital maps are from places that big companies care the most about. If you’re in places they don’t care about much, you’re at a disadvantage with respect to the quality of map,” says co-author Sam Madden, a professor in the Department of Electrical Engineering and Computer Science (EECS) and a researcher in the Computer Science and Artificial Intelligence Laboratory (CSAIL). “Our goal is to automate the process of generating high-quality digital maps, so they can be available in any country.”
With billions of books, news stories, and documents online, there’s never been a better time to be reading — if you have time to sift through all the options. “There’s a ton of text on the internet,” says Justin Solomon, an assistant professor at MIT. “Anything to help cut through all that material is extremely useful.”
Each semester, Associate Professor Virginia Vassilevska Williams tries to impart one fundamental lesson to her computer-science undergraduates: Math is the foundation of everything.
Jointly part of the School of Engineering and Schwarzman College of Computing, EECS is now composed of three overlapping sub-units in electrical engineering (EE), computer science (CS), and artificial intelligence and decision-making (AI+D), which brings together computer science-heritage AI and machine learning with electrical engineering-heritage information and decision systems to exploit their significant synergies. The department will remain responsible for Course 6.
The road to commencement is a long one, especially for graduate students whose degree programs may take upwards of six years. There are many moments when focus may be lost and excitement may dwindle. Faculty mentors can play a key role in helping students persevere.
MIT researchers have devised a method that accelerates the process for creating and customizing templates used in medical-image analysis, to guide disease diagnosis.
One use of medical image analysis is to crunch datasets of patients’ medical images and capture structural relationships that may indicate the progression of diseases. In many cases, analysis requires use of a common image template, called an “atlas,” that’s an average representation of a given patient population. Atlases serve as a reference for comparison, for example to identify clinically significant changes in brain structures over time.
MIT researchers have designed a model that demonstrates an understanding of some basic “intuitive physics” about how objects should behave. The model could be used to help build smarter artificial intelligence and, in turn, provide information to help scientists understand infant cognition.
Cameras and computers together can conquer some seriously stunning feats. Giving computers vision has helped us fight wildfires in California, understand complex and treacherous roads — and even see around corners.
Computer vision models have learned to identify objects in photos so accurately that some can outperform humans on some datasets. But when those same object detectors are turned loose in the real world, their performance noticeably drops, creating reliability concerns for self-driving cars and other safety-critical systems that use machine vision.
