The CytoDiffusion classifier analyses the shape and structure of blood cells to detect abnormalities that may indicate blood ...

Adaptive test is starting to gain traction for high-performance computing and AI chips as test programs that rely on static limits and fixed test sequences reach their practical limits.

Lewis Wallis and Dr Samuel Dicken review 2025 developments in ultra-processed foods (UPF) and high fat, sugar and salt (HFSS) ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

SLMs are not replacements for large models, but they can be the foundation for a more intelligent architecture.

A research team led by Dr. Jinung An of the Division of Intelligent Robotics at DGIST has developed a new AI foundation model ...

A practical guide to building AI prompt guardrails, with DLP, data labeling, online tokenization, and governance for secure ...

As someone who owns more than fifteen volumes from the MIT Press Essential Knowledge series, I approach each new release with both interest and caution: the series often delivers thoughtful, ...

Developed the world's first multimodal brain signal-based model capable of learning without simultaneous EEG and fNIRS measurements. - Self-learning from data of hundreds of individuals... Introducing ...

This valuable study provides solid evidence for deficits in aversive taste learning and taste coding in a mouse model of autism spectrum disorders. Specifically, the authors found that Shank3 knockout ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...