Drones navigate unseen environments with liquid neural networks
MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios.
MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios.
Experts convene to peek under the hood of AI-generated code, language, and images as well as its capabilities, limitations, and future impact.
“DribbleBot” can maneuver a soccer ball on landscapes such as sand, gravel, mud, and snow, using reinforcement learning to adapt to varying ball dynamics.
MIT researchers built DiffDock, a model that may one day be able to find new drugs faster than traditional methods and reduce the potential for adverse side effects.
New LiGO technique accelerates training of large machine-learning models, reducing the monetary and environmental cost of developing AI applications.
Researchers used machine learning to build faster and more efficient hash functions, which are a key component of databases.
Aided by machine learning, scientists are working to develop a vaccine that would be effective against all SARS-CoV-2 strains.
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
MIT spinout Verta offers tools to help companies introduce, monitor, and manage machine-learning models safely and at scale.