Improving the reliability of circuits for quantum computers
A new technique helps scientists measure a phenomenon that can cause quantum circuits to perform differently than expected, increasing the error in computations.
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.
It took 40 years for technology to catch up to this zipper design
An old patent from MIT Professor Bill Freeman inspired the new “Y-zipper,” a three-sided fastener that snaps gear, robots, and art into shape at the push of a button.
Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models
A new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.
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.
Enabling privacy-preserving AI training on everyday devices
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
Mapping molecular markers of physical fitness
A new study reveals cellular pathways that appear to underlie some differences in physical fitness.
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.
New chip can protect wireless biomedical devices from quantum attacks
Ultra-efficient chip design enables extremely strong cryptography algorithms to run on energy-constrained edge devices.
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.
Professor Emeritus Jack Dennis, pioneering developer of dataflow models of computation, dies at 94
The influential first leader of the Computation Structures Group at MIT played a key role in the development of asynchronous computing.
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.