By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

The partners in Lantern, a machine learning software firm focused on product distribution, pitched the technology to HVACR ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

One example involved a system built by a summer intern for his own project work. The tool geolocates devices within a drawing set and links them to a digital twin of the facility. Instead of searching ...

A survey of over 1,000 enterprises conducted by S&P Global Market Intelligence in 2025 revealed that 42% of companies ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Some school district IT teams have been experimenting with using generative AI tools for cybersecurity, for example to ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with projects that support AI development. For several decades now, the most innovative ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...

A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.