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 about 81%. This advance could enable a wider array of resource-constrained edge ...
Tech Xplore

Brain-inspired approach can teach AI to doubt itself just enough to avoid overconfidence

Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning. Machine learning is a computational approach that allows models to uncover ...

Egg-scanning AI may let hatcheries sort life, death and sex before chicks emerge

Eggs and poultry provide important sources of protein globally, driving a major industry with large economic impacts.
IEEE

A Topical Review of Quantum and Classical Machine Learning Approaches to Disaster Escape Routing Problems

Abstract: The pathfinding problem in a graph has been solved using several classical algorithms, notably Dijkstra’s and A* algorithms. However, most classical algorithms are most effective on static ...
IEEE

Quantum Machine Learning: Recent Advances, Challenges, and Perspectives

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...
Forbes

Machine Learning Trends For 2026

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...
Frontiers

Clinical problem selection for machine learning-based clinical decision support in the intensive care unit: complexity, actionability, and the way forward

Machine learning (ML)-based clinical decision support (CDS) in the intensive care unit (ICU) has the potential to improve medical decision-making and patient outcomes. The chasm between model ...
Automation World

AI-Driven Motion Control: How Machine Learning Optimizes Motors, Reduces Downtime and Cuts Energy Costs

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
marktechpost

Nested Learning: A New Machine Learning Approach for Continual Learning that Views Models as Nested Optimization Problems to Enhance Long Context Processing

How can we build AI systems that keep learning new information over time without forgetting what they learned before or retraining from scratch? Google Researchers has introduced Nested Learning, a ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...