ExecuTorch 1.0 allows developers to deploy PyTorch models directly to edge devices, including iOS and Android devices, PCs, and embedded systems, with CPU, GPU, and NPU hardware acceleration.
AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The open source PyTorch machine learning (ML) framework is widely used ...
Facebook Inc. today updated its popular artificial intelligence software framework PyTorch with support for new features that enable a more seamless AI model deployment to mobile devices. PyTorch is ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...
7dOpinion
Is Meta Killing FAIR?
Meta shifts focus to advanced AI with its Super Intelligence Lab, raising questions about the future of FAIR and open AI ...
Just when you thought the pace of change of AI models couldn’t get any faster, it accelerates yet again. In the popular news media, the introduction of DeepSeek in January 2025 created a moment that ...
Facebook Inc. today revealed that it’s going all-in on PyTorch as its default artificial intelligence framework. The company said that by migrating all of its AI systems to PyTorch, it will be able to ...
eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback