Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
The AI Policy Forum (AIPF) is an initiative of the MIT Schwarzman College of Computing to move the global conversation about the impact of artificial intelligence from principles to practical…
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Researchers use machine learning to automatically solve, explain, and generate university-level math problems at a human level.
Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.
New hardware offers faster computation for artificial intelligence, with much less energy
Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.
Costis Daskalakis appointed inaugural Avanessians Professor in the MIT Schwarzman College of Computing
The MIT Stephen A. Schwarzman College of Computing has named Costis Daskalakis as the inaugural holder of the Avanessians Professorship. His chair began on July 1. Daskalakis is…