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

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

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

mlip is a Python library for training and deploying Machine Learning Interatomic Potentials (MLIP) written in JAX. It provides the following functionality: See the Installation section for details on ...

This is a machine learning-based A-shares stock selection system designed to help users make investment decisions by predicting future stock price trends. The system utilizes the LightGBM model ...

Exploring the relationship between audio–visual perception in Fuzhou universities and college students' attention restoration quality using machine learning ...

I Drove Tesla's 2026 Model Y Juniper For 1,000 Miles, The Real-World Range Numbers Finally Match Tesla's Claims, But That Back Window Is Dangerously Small ...

Learn about data quality, model evaluation, model explainability, and model reliability aspects to consider when working with AI and machine learning models.

Yusuf Roohani, PhD, machine learning group lead at the Arc Institute, is among a team of researchers training artificial intelligence (AI) models with transcriptome data to predict how cell gene ...

A federal judge sided with Meta in a lawsuit that alleged the company had illegally trained its AI models on copyrighted works.