Teaching machines to reason about what they see
Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency.
Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency.
MIT Professor David Pesetsky describes the science of language and how it sheds light on deep properties of the human mind.
System could provide fine-scale meshes for growing highly uniform cultures of cells with desired properties.
Technique could improve machine-learning tasks in protein design, drug testing, and other applications.
Algorithm designs optimized machine-learning models up to 200 times faster than traditional methods.
Maike Sonnewald adapts a method that identifies areas of the global ocean with similar physics, revealing global dynamical regimes.
Master’s student and Marshall Scholar Kyle Swanson uses computer science to help make drug development more efficient.
Faculty representing all five MIT schools offer views on the ethical and societal implications of new technologies.
A popular student-coordinated class draws a capacity crowd from across the MIT campus and beyond.
Professor of biology Ernest Fraenkel and visiting scientist Judah Cohen win the Sub-Seasonal Climate Forecast Rodeo competition.
Research projects show creative ways MIT students are connecting computing to other fields.
Fireside chat brings together six Turing Award winners to reflect on their field and the MIT Stephen A. Schwarzman College of Computing.
Anyone can submit tech-based solution applications until July 1.
Final day of the MIT Schwarzman College of Computing celebration explores enthusiasm, caution about AI’s rising prominence in society.
Stephen A. Schwarzman and MIT President L. Rafael Reif discuss the Institute’s historic new endeavor.