Browsing: models

LEARNING models using routinely available clinical, cognitive, and neuropsychiatric information could support the classification of Alzheimer’s disease (AD) and cognitive impairment, according to new research involving 761 participants

Artificial intelligence is becoming a practical component of embedded systems, from predictive maintenance and motor control to machine vision, industrial automation, and smart building infrastructure. But as developers integrate AI into these products, they face a security question that extends beyond the accuracy of the model: Who controls the model, what data can it access,…

Companies getting real results from AI aren’t only using foundation models (FMs) off the shelf. They’re customizing open-weight models using post-training techniques such as reinforcement learning. A model trained on your business context, product catalog, or clinical vocabulary will be more accurate for your task and cost less to run. When you build agents, your…

China is the only country other than the United States that controls substantial portions of nearly all the technologies required for artificial intelligence – the so-called AI stack. China has cheap electricity and critical minerals upstream, semiconductors and their software ecosystems in the middle, and models at the end. It is also working on governance,…

When implementing an EEG machine-learning pipeline, there are many samples obtained from a small number of subjects. One recording can be divided into multiple windows, which then can be randomly split into train and test splits. This produces a sample size that might seem very big. Yet, if the same subject’s windows are present in…