artificial intelligence tagged posts

A new method developed by MIT researchers can accelerate a privacy-preserving artificial intelligence training method by about 81%. This advance could enable a wider array of resource-constrained edge devices, like sensors and smartwatches, to deploy more accurate AI models while keeping user data secure.

The MIT researchers boosted the efficiency of a technique known as federated learning, which involves a network of connected devices that work together to train a shared AI model.

In federated learning, the model is broad...

A research team led by Lee Hyun Jun and Noh Hee Yeon from the Division of Nanotechnology at DGIST has succeeded in implementing the world’s first two-terminal-based artificial intelligence (AI) semiconductor that precisely controls hydrogen with electrical signals to enable self-learning and memory. The team’s work appears in Advanced Science.

Whereas modern AI requires the rapid processing of vast amounts of data, the separation of computation and memory in conventional computers results in speed degradation and high power consumption...

For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it stumbles. A new study from the USC Viterbi School of Engineering was accepted at the IEEE SoutheastCon 2026, taking place March 12–15. It suggests something far more surprising: with the right method in place, an AI model can dramatically improve its performance in territory it was barely trained on, pushing well past what its training data alone would ever allow.

The method was developed by Minda Li, a USC Viterbi undergraduate who has been pursuing research since her freshman year, working alongside her advisor Bhaskar Krishnamachari, a Faculty Fellow and S...

AI might know where you’re going before you do. Researchers at Northeastern University used large language models, the kind of advanced artificial intelligence normally designed to process and generate language, to predict human movement.

How RHYTHM predicts human movement
RHYTHM, their innovative tool, “can revolutionize the forecasting of human movements,” forecasting “where you’re going to be in the next 30 minutes or the next 25 hours,” said Ryan Wang, an associate professor and vice chair of research in civil and environmental engineering at Northeastern.

The hope is that RHYTHM will improve domains like transportation and traffic planning to make our lives easier, but in extreme cases, RHYTHM could even be deployed to respond to natural dis...