Helping AI models to meet the real world
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
Read More“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.
Read MoreResearchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
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 MoreResearchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power.
Read MoreAssistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.
Read MoreFounded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.
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