When it comes to predicting people’s preferences, it pays to consider “the power of three”
MIT researchers provide a major upgrade to the nearly century-old idea of random utility models.
NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery
IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.
Teaching AI agents to ask better questions by playing “Battleship”
MIT researchers use the classic game as a test bed for AI agents, finding a small AI model can outperform the biggest ones at 1 percent of the cost.
New research enables a robot to chart a better course
By rapidly generating a smooth path plan that cuts travel time and avoids obstacles, the open-source “MIGHTY” system could streamline disaster recovery and parcel delivery.
Researchers “reprogram” materials by quickly rearranging their atoms
A new method for precisely moving columns of individual atoms within a material could give rise to exotic quantum properties.
Method for stress-testing cloud computing algorithms helps avoid network failures
The “MetaEase” technique provides a heads-up to potential scenarios that could cause long wait-times or outages.
Games people — and machines — play: Untangling strategic reasoning to advance AI
Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.
The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
A faster way to estimate AI power consumption
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
Teaching AI models to say “I’m not sure”
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
Human-machine teaming dives underwater
Researchers are developing hardware and algorithms to improve collaboration between divers and autonomous underwater vehicles engaged in maritime missions.
New technique makes AI models leaner and faster while they’re still learning
Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.
Helping data centers deliver higher performance with less hardware
Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.
Evaluating the ethics of autonomous systems
MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.