Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

An AI-driven computational toolkit, Gcoupler, integrates ligand design, statistical modeling, and graph neural networks to predict endogenous metabolites that allosterically modulate the GPCR–Gα ...

Discover Taiwo Feyijimi's work at the crossroads of AI, engineering, and learning. Explore his innovative frameworks shaping ...

Here are 11 free NPTEL data science and analytics courses from leading IITs cover graph theory, Bayesian modelling, Python, R ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

This article will examine the practical pitfalls and limitations observed when engineers use modern coding agents for real ...

Local LLMs thrive on Apple's hardware, and a huge part of it is thanks to MLX.

For Gabriel Petersson, the path to becoming a research scientist at OpenAI didn’t start in a lecture hall but began with a ...

The disaster that struck John Quackenbush and his lab at the Harvard T.H. Chan School of Public Health began when the Trump ...

UC Berkeley Computer Science Professor Sarah Chasins joins WIRED to answer the internet's burning questions about coding. How ...

Interview: Java’s next era is shaped by cloud costs, AI-driven load and the need for deterministic performance. Gil Tene ...

John Quackenbush built a lab that is at the forefront of human genetics research and bioinformatics. Trump administration ...