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

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.

From GPT to Claude to Gemini, model names change fast, but use cases matter more. Here's how I choose the best model for the ...

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

A peer-reviewed paper about Chinese startup DeepSeek's models explains their training approach but not how they work through ...

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 ...

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...

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 ...