Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

Abstract: Surface electromyography (sEMG) signals are electrical signals released by muscles during movement, which can directly reflect the muscle conditions during various actions. When a series of ...

Abstract: This paper presents a study on Dynamic Sequential Distribution Network Reconfiguration (DSDNR), which considers the sequential control of individual switches in real-time distribution ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...

Forbes contributors publish independent expert analyses and insights. Originally developed by Anyscale, Ray is an open source distributed computing framework for AI workloads, including data ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

The PyTorch team at Meta, stewards of the PyTorch open source machine learning framework, has unveiled Monarch, a distributed programming framework intended to bring the simplicity of PyTorch to ...

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...