Explore how AI predictive analytics reshapes industries by providing insights, forecasting trends, and enhancing ...

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

A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

Artificial intelligence (AI) is infamous for its resource-heavy training, but a new study may have found a solution in a novel communications system, called ZEN, that markedly improves the way large ...

A major scientific advance in protein modeling developed by Microsoft Research AI for Science, has been published in Science.

The goals of this Perspective are threefold: (1) to inform a broad audience, including machine learning (ML) and artificial intelligence (AI) academics and professionals, about synthetic drug ...

Some studies containing instructions in white text or small font — visible only to machines — will be withdrawn from preprint ...

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

This report tries to investigate the effective use of the machine learning in the area of image analysis and processing. The field of healthcare taking a large datasets of image like X-ray, Ultrasound ...

In Part 1, we explored the challenges of implementing machine learning and real-time analytics in semiconductor ...

Two new open-source tools are set to make fluorescence lifetime imaging microscopy—or FLIM—faster, simpler and more ...

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