MIT scientists show how fast algorithms are improving across a broad range of examples, demonstrating their critical importance in advancing computing.
An electrical impedance tomography toolkit lets users design and fabricate health and motion sensing devices.
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
Model-free framework reorients over 2,000 diverse objects with a hand facing both upward and downward, in a step toward more human-like manipulation.
“Evolution Gym” is a large-scale benchmark for co-optimizing the design and control of soft robots that takes inspiration from nature and evolutionary processes.
Deep-learning methods confidently recognize images that are nonsense, a potential problem for medical and autonomous-driving decisions.
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
MIT researchers develop "FrameDiff," a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
MIT researchers characterize gene expression patterns for 22,500 brain vascular cells across 428 donors, revealing insights for Alzheimer’s onset and potential treatments.
MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.
Researchers create a new simulation tool for robots to manipulate complex fluids in a step toward helping them more effortlessly assist with daily tasks.
MIT researchers characterize gene expression patterns for 22,500 brain vascular cells across 428 donors, revealing insights for Alzheimer’s onset and potential treatments.
MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.
Researchers create a new simulation tool for robots to manipulate complex fluids in a step toward helping them more effortlessly assist with daily tasks.
Scientists demonstrate that AI-risk models, paired with AI-designed screening policies, can offer significant and equitable improvements to cancer screening.
“Privid” could help officials gather secure public health data or enable transportation departments to monitor the density and flow of pedestrians, without learning personal information about people.
MIT engineers Edward Adelson and Sandra Liu duo develop a robotic gripper with rich sensory capabilities.