Pattie Maes receives ACM SIGCHI Lifetime Research Award
Professor of media technology honored for research in human-computer interaction that is considered both fundamental and influential.
A new way to make graphs more accessible to blind and low-vision readers
The Tactile Vega-Lite system, developed at MIT CSAIL, streamlines the tactile chart design process; could help educators efficiently create these graphics and aid designers in making precise changes.
3D printing approach strings together dynamic objects for you
“Xstrings” method enables users to produce cable-driven objects, automatically assembling bionic robots, sculptures, and dynamic fashion designs.
New platform lets anyone rapidly prototype large, sturdy interactive structures
The system uses reconfigurable electromechanical building blocks to create structural electronics.
Robotic helper making mistakes? Just nudge it in the right direction
New research could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human.
Introducing the MIT Generative AI Impact Consortium
The consortium will bring researchers and industry together to focus on impact.
MIT students' works redefine human-AI collaboration
Projects from MIT course 4.043/4.044 (Interaction Intelligence) were presented at NeurIPS, showing how AI transforms creativity, education, and interaction in unexpected ways.
Explained: Generative AI’s environmental impact
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.
Teaching AI to communicate sounds like humans do
Inspired by the human vocal tract, a new AI model can produce and understand vocal imitations of everyday sounds. The method could help build new sonic interfaces for entertainment and education.
MIT Schwarzman College of Computing welcomes Frida Polli as visiting innovation scholar
The neuroscientist turned entrepreneur will focus on advancing the intersection of behavioral science and AI across MIT.
Study reveals AI chatbots can detect race, but racial bias reduces response empathy
Researchers at MIT, NYU, and UCLA develop an approach to help evaluate whether large language models like GPT-4 are equitable enough to be clinically viable for mental health support.
Researchers reduce bias in AI models while preserving or improving accuracy
A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.
Enabling AI to explain its predictions in plain language
Using LLMs to convert machine-learning explanations into readable narratives could help users make better decisions about when to trust a model.
Daniela Rus wins John Scott Award
MIT CSAIL director and EECS professor named a co-recipient of the honor for her robotics research, which has expanded our understanding of what a robot can be.
Citation tool offers a new approach to trustworthy AI-generated content
Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.