A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
New type of “state-space model” leverages principles of harmonic oscillators.
“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.
The National Academy of Engineering (NAE) elected EECS School of Engineering Distinguished Professor for AI and Health, CSAIL principal investigator, and Jameel Clinic faculty lead Regina Barzilay for her work on machine learning models that can read structures in text, molecules, and medical images.
Researchers make headway in solving a longstanding problem of balancing curious “exploration” versus “exploitation” of known pathways in reinforcement learning.
Last week CSAIL hosted the first “Hot Topics in Computing” speaker series, a new monthly forum where computing experts hold discussions with community members on various topics in the computer science field.
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.
This past year MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) was at the forefront of many diverse technological innovations covering a breadth of topics, from healthcare and cybersecurity to self-driving cars.
November 1, 2017 - Yann LeCun of New York University and Facebook AI Research gave a Dertouzos Distinguished Lecture titled "How Could Machines Learn as Efficiently as Animals and Humans?"