Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

Qualcomm confirmed a $3.92 billion all-stock deal to buy AI software startup Modular, paired with a Meta Platforms CPU ...

Generative AI and Recurrent Networks run on Q.ANT's Second-Generation Photonic Processor Complexity Model Graph Climbing the complexity ladder of AI Models Second Generation NPU Q.ANT Native ...

Abstract: Deep learning has witnessed rapid progress through frameworks such as PyTorch, which has become the dominant choice for researchers and practitioners due to its dynamic computation, ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

What is this book about? Graph neural networks are a highly effective tool for analyzing data that can be represented as a graph, such as social networks, chemical compounds, or transportation ...

python 3.8 numpy 1.20.3 pytorch 1.8.0 pytorch-sparse 0.6.11 All datasets are downloaded from package torch_geometric and saved as series of .pt file without any ...

Brief: Researchers from the Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) have developed a distributed implementation of graph convolutional neural ...