One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

A team of researchers has recently developed a nondestructive imaging and machine learning system that accurately predicts ...

Despite the AI hype, ML tools really are proving valuable for leading-edge chip manufacturing. More aggressive feature ...

Ansys SimAI is a physics-agnostic and cloud-enabled computer-aided engineering tool that predicts performance of complex ...

At the Mount Sinai Health System we have successfully translated many algorithms from concept to testing and clinical care, ...

This paper presents a novel dynamic decoupling control method designed to manage the decoupling operations of virtually coupled train sets (VCTS) within the throat area of a railway line. The primary ...

A recent change to WeTransfer’s terms and conditions said it reserved the right to train AI using files shared on the service ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

New foundational AI models are accelerating advancements in biomedical research, according to a speaker at Cleveland Clinic’s ...

Dr. Fatma Kocer, VP Engineering Data Science at Altair, says GDL and other techniques will unleash foundational models akin ...

Henry Ford’s introduction of the conveyor belt assembly line revolutionized efficiency so thoroughly that an automated ...