Want to learn how to train an artificial intelligence model? Ask a friend.
MIT Machine Intelligence Community introduces students to nuts and bolts of machine learning.
MIT Machine Intelligence Community introduces students to nuts and bolts of machine learning.
Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.
A new tool for predicting a person’s movement trajectory may help humans and robots work together in close proximity.
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Researchers submit deep learning models to a set of psychology tests to see which ones grasp key linguistic rules.
MIT Quest for Intelligence-sponsored undergraduate research projects demystify AI.
Insights on the formation of particle networks hold potential for engineering new and improved materials.
Researchers unveil a tool for making compressed deep learning models less vulnerable to attack.
Model improves a robot’s ability to mold materials into shapes and interact with liquids and solid objects.
Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency.
After a personal loss led to a new perspective, Nancy Hua ’07 left a career in finance to start the company.
Digitally mapping informal transportation networks in developing cities can help them reach the United Nations' Sustainable Development Goals.
Undergraduate research projects show how students are advancing research in human and artificial intelligence, and applying intelligence tools to other disciplines.
Researchers have devised a faster, more efficient way to design custom peptides and perturb protein-protein interactions.
Climate-driven changes in phytoplankton communities will intensify the blue and green regions of the world’s oceans.