Tech Xplore

How everyday devices could train AI faster while keeping personal data on-device

A new method developed by MIT researchers can accelerate a privacy-preserving artificial intelligence training method by ...
HealthTech Magazine

Federated Machine Learning Gives Healthcare Organizations a Competitive AI Advantage

By bringing the training of ML models to users, health systems can advance their AI ambitions while maintaining data security ...

New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines

EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...

The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path

In 2016, an AI program he developed at Google DeepMind, AlphaGo, taught itself to play the famously difficult game of Go with ...
Frontiers

Brain-inspired learning and adaptation in large models

Recent advances in large-scale AI models, including large language and vision-language-action models, have significantly expanded the capabilities of ...
IEEE

Communication Efficient Federated Learning with Quantization-Aware Training Design

Model quantization is an effective method that can improve communication efficiency in federated learning (FL). The existing FL quantization protocols almost stay at the level of post-training ...
IEEE

An Investigation and Performance Evaluation of Aggregation Algorithms in Federated Learning Architecture

Abstract: Centralized data collection, the basis of traditional machine learning (ML), raises significant privacy and security concerns. Federated Learning (FL) addresses these issues by enabling ...