From MIT to IBM, expediting AI and quantum deployment
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems.
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems.
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
Read MoreWith millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.
Read MoreA new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
Read More“GeoPT” helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately.
Read MoreDirector of CSAIL and MIT professor honored for her contributions to robotics, artificial intelligence, and autonomous systems.
Read MoreMIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.
Read MoreA new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.
Read MoreDuring the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy.
Read MoreBuilding on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
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