Scikit-learn, PyTorch, and TensorFlow remain core tools for structured data and deep learning tasks.New libraries like JAX, ...

Key Takeaways The transition requires upskilling in Python, statistics, and machine learning.Practical experience with ...

The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

In joint research with the University of Tokyo (UTokyo), the National Institute of Advanced Industrial Science and Technology ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

Some studies containing instructions in white text or small font — visible only to machines — will be withdrawn from preprint ...

Assessing the progress of new AI language models can be as challenging as training them. Stanford researchers offer a new approach.

CRISPR construct to genetically ablate the GABA transporter GAT3 in the mouse visual cortex, with effects on population-level neuronal activity. This work is important, as it sheds light on how GAT3 ...

In the fast-paced field of High Performance Computing (HPC), the convergence of Artificial Intelligence (AI) and Big Data Analysis signals a groundbreaking ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...