Training machines to learn more like humans do
Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.
Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.
Martin Luther King Jr. Scholar Brian Nord trains machines to explore the cosmos and fights for equity in research.
With further development, the programmable system could be used in a range of applications including gene and cancer therapies.
Computational chemists design better ways of discovering and designing materials for energy applications.
MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
A new tool brings the benefits of AI programming to a much broader class of problems.