Meta To Use AWS Compute For Its AI
Amazon Web Services, Inc. (AWS) announced that Meta has deepened its relationship with AWS as a strategic cloud provider. Currently, Meta uses AWS’ infrastructure and capabilities to complement its existing on-premises infrastructure, and will broaden its use of AWS compute, storage, databases, and security services to provide privacy, reliability, and scale in the cloud. Meta will run third-party collaborations in AWS and use the cloud to support acquisitions of companies that are already powered by AWS. It will also use AWS’ compute services to accelerate AI research and development for its Meta AI group. In addition, Meta and AWS will work together to improve the performance for customers running PyTorch on AWS and accelerate how developers build, train, deploy, and operate artificial intelligence/machine learning models. “Meta and AWS have been expanding our collaboration over the last five years,” said Kathrin Renz, Vice President of Business Development and Industries at Amazon Web Services, Inc. “With this agreement, AWS will continue to help Meta support research and development, drive innovation, and collaborate with third parties and the open-source community at scale. Customers can rely on Meta and AWS to collaborate on PyTorch, making it easier for them to build, train, and deploy deep learning models on AWS.” AWS and Meta will help machine learning researchers and developers by further optimizing PyTorch performance and its integration with core managed services such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon SageMaker for building, training, and deploying artificial intelligence models at scale. Jason Kalich, Vice President of Production Engineering at Meta, said, “The global reach and reliability of AWS will help us continue to deliver innovative experiences for the billions of people around the world that use Meta products and services and for customers running PyTorch on AWS.”
Meta and AWS will help enterprises use PyTorch on AWS to bring deep learning models faster and easier into production
Meta and AWS will help enterprises use PyTorch on AWS to bring deep learning models faster and easier into production
["AI Research", "AWS", "Cloud Computing", "Meta", "Pytorch"]
["Pytorch", "Meta", "artificial intelligence", "machine learning", "AWS", "AI", "Meta AI", "Amazon SageMaker", "PyTorch", "AI Research", "RAG", "Cloud Computing", "deep learning", "R"]
["AI", "artificial intelligence", "machine learning", "deep learning", "Meta AI", "Amazon SageMaker", "PyTorch", "RAG", "AWS", "R"]
Meeta’s interest lies in finding out real practical applications of technology. At AIM, she writes stories that question the new inventions and the need to develop them. She believes that technology has and will continue to change the world very fast and that it is no more ‘cool’ to be ‘old-school’. If people don’t update themselves with the technology, they will surely be left behind.