A method for designing neural networks optimally suited for certain tasks
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
With further development, the programmable system could be used in a range of applications including gene and cancer therapies.
New LiGO technique accelerates training of large machine-learning models, reducing the monetary and environmental cost of developing AI applications.
J-WAFS researchers are using remote sensing observations to build high-resolution systems to monitor drought.
Computational chemists design better ways of discovering and designing materials for energy 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 uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
A process that seeks feedback from human specialists proves more effective at optimization than automated systems working alone.