A 3D design environment from CSAIL lets users iterate an object’s shape and electronic function in one cohesive space, to add existing sensors to early-stage prototypes.

A group led by researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) has developed a machine learning model that can look at an X-ray to quantify how severe the edema is, on a four-level scale ranging from 0 (healthy) to 3 (very, very bad). The system determined the right level more than half of the time, and correctly diagnosed level 3 cases 90 percent of the time.

Most new roboticists want to program their robots to solve interesting, complex tasks — but it turns out that just moving them through space without colliding with objects is more difficult than it sounds.

The national dialogue on race has progressed powerfully and painfully in the past year, and issues of racial bias in the news have become ubiquitous. However, for over a decade, researchers from MIT’s Imagination, Computation, and Expression Laboratory (ICE Lab) have been developing systems to model, simulate, and analyze such issues of identity. 

In a new study at the European Conference on Computer Vision last month, researchers unveiled a hybrid language-vision model that can compare and contrast a set of dynamic events captured on video to tease out the high-level concepts connecting them. 

When a natural disaster occurs, on-the-ground emergency response teams act quickly to make life-saving decisions. Reducing the response time in such situations is critical to reduce damage impact and save lives. Helpful efforts are being taken to reduce the burden, such as a damage assessment tool by UNDP, though few automated methods exist. In recent work, MIT is creating tools that can automatically analyze images.

OpenAI unveiled the largest language model in the world, a text-generating tool called GPT-3 that can write creative fiction, translate legalese into plain English, and answer obscure trivia questions. It’s the latest feat of intelligence achieved by deep learning, a machine learning method patterned after the way neurons in the brain process and store information.

Researchers have published a series of papers that address shortcomings of existing meshing tools by seeking out mathematical structure in the problem. In collaboration with scientists at the University of Bern and the University of Texas at Austin, their work shows how areas of math like algebraic geometry, topology, and differential geometry could improve physical simulations used in computer-aided design (CAD), architecture, gaming, and other sectors.