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

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

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 ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

Northwestern Engineering faculty and students participated in the annual forum for advances in theory, empirics, and ...

Flood modeling in arid environments like Saudi Arabia is constrained by the absence of reliable hydrological datasets and ...

I was a moderator for the TikTok platform for over a year. I won't give away any secrets or inside information, but I will ...

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data. This includes text from books and websites, images from public databases, ...

This project examines a tree-based machine learning approach to predict customer behavior outcomes in ecommerce, using a large dataset. The project compares different classification methods to solve ...

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.