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.
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.
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.
Preview tool helps makers visualize 3D-printed objects
By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.
AI system learns to keep warehouse robot traffic running smoothly
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.
A better method for identifying overconfident large language models
This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.
Generative AI improves a wireless vision system that sees through obstructions
With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.
A better method for planning complex visual tasks
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
Improving AI models’ ability to explain their predictions
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.