Artificial intelligence for augmentation and productivity
The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.
The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.