New program bolsters innovation in next-generation artificial intelligence hardware
MIT AI Hardware Program launches with five inaugural companies to advance AI technologies for the next decade.
MIT AI Hardware Program launches with five inaugural companies to advance AI technologies for the next decade.
“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.
Researchers design a user-friendly interface that helps nonexperts make forecasts using data collected over time.
CSAIL scientists came up with a learning pipeline for the four-legged robot that learns to run entirely by trial and error in simulation.
The AI-Guided Ultrasound Intervention Device is a lifesaving technology that helps a range of users deliver complex medical interventions at the point of injury.
MLK Visiting Professor S. Craig Watkins looks beyond algorithm bias to an AI future where models more effectively deal with systemic inequality.
Veteran and PhD student Andrea Henshall has used MIT Open Learning to soar from the Air Force to multiple aeronautics degrees.
A machine-learning model for image classification that’s trained using synthetic data can rival one trained on the real thing, a study shows.
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
A new MIT-wide effort launched by the Institute for Data, Systems, and Society uses social science and computation to address systemic racism.
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
Researchers find similarities between how some computer-vision systems process images and how humans see out of the corners of our eyes.
Researchers surveyed 100 high-performing companies to determine which of them are leading adopters of machine intelligence and data analytics, and how they succeed.
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.