New MIT class uses anthropology to improve chatbots
MIT computer science students design AI chatbots to help young users become more social, and socially confident.
MIT computer science students design AI chatbots to help young users become more social, and socially confident.
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
The approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.
By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
To help generative AI models create durable, real-world accessories and decor, the PhysiOpt system runs physics simulations and makes subtle tweaks to its 3D blueprints.
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
Strahinja Janjusevic brings an international perspective and US Naval Academy education to his graduate research in the MIT Technology and Policy Program.
By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.
The context of long-term conversations can cause an LLM to begin mirroring the user’s viewpoints, possibly reducing accuracy or creating a virtual echo-chamber.