How do neural networks work? It’s a question that can confuse novices and experts alike. A team from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) says that understanding these representations, as well as how they inform the ways that neural networks learn from data, is crucial for improving the interpretability, efficiency, and generalizability of deep learning models.

As a college student in Serbia with a passion for math and physics, Ana Trišović found herself drawn to computer science and its practical, problem-solving approaches. It was then that she discovered MIT OpenCourseWare, part of MIT Open Learning, and decided to study a course on Data Analytics with Python in 2012 — something her school didn’t offer.

Six current MIT affiliates and 27 additional MIT alumni have been elected as fellows of the American Association for the Advancement of Science (AAAS). 

“We’re not just witnessing the future unfold—we're helping to invent it.” – CSAIL Director Professor Daniela Rus 

Agentic AI systems are “designed to pursue complex goals with autonomy and predictability” (MIT Technology Review). Agentic AI models enable productivity by taking goal-directed actions, making contextual decisions, and adjusting plans based on changing conditions with minimal human oversight.

20 years ago in a pre-ChatGPT world, a fake-paper generator created by 3 MIT kids fooled a major conference so badly that they had to completely reconfigure their reviewing practices.

A hospital that wants to use a cloud computing service to perform artificial intelligence data analysis on sensitive patient records needs a guarantee those data will remain private during computation. Homomorphic encryption is a special type of security scheme that can provide this assurance.

CSAIL Alliances Affiliate Member Sony Interactive Entertainment (SIE) hosted a January 2025 IAP course, “The Nexus of Games and AI.” Designed to “introduce students to game creation, current game-related research, and an exploration of the technology, the art, and the fun of video games,” this course allowed SIE to engage with a broad range of students, meet CSAIL faculty, and deepen their connection to MIT CSAIL.

It’s difficult to build devices that replicate the fluid, precise motion of humans, but that might change if we could pull a few (literal) strings.

This week CSAIL announced a gift from JPMorgan Chase that will enable important new breakthroughs in artificial intelligence research at MIT’s largest interdepartmental lab.