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SEATTLE — Meta is deepening its relationship with AWS as a “key” and “long-term” strategic cloud provider.
Meta uses AWS’s infrastructure and capabilities to complement its existing on-premises infrastructure. Meta will now broaden its use of AWS compute, storage, databases, and security services to provide privacy, reliability, and scale in the cloud, according to the companies this month.
Meta will run third-party collaborations in AWS and use the cloud to support acquisitions of companies that are already powered by AWS.
Meta will also use AWS’s compute services to accelerate artificial intelligence (AI) research and development for its Meta AI group.
See more: The Artificial Intelligence Market
Together, Meta and AWS will work to improve the performance for customers running PyTorch on AWS and accelerate how developers build, train, deploy, and operate AI/machine learning (ML) models.
AWS and Meta will help ML 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 — a service that helps developers and data scientists build, train, and deploy ML models quickly in the cloud and at the edge — for building, training, and deploying AI models at scale.
See more: The Machine Learning Market
To make it easier for developers to build large-scale deep learning (DL) models for natural language processing (NLP) and computer vision, the companies are enabling PyTorch on AWS to orchestrate large-scale training jobs across a distributed system of AI accelerators. The companies will work together to offer native tools to improve the performance, explainability, and cost of inference on PyTorch. To simplify the deployment of models in production, the companies will continue to enhance TorchServe, the serving engine native to PyTorch to deploy trained PyTorch models at scale.
“We are excited to extend our strategic relationship with AWS to help us innovate faster and expand the scale and scope of our research and development work,” said Jason Kalich, VP of production engineering, Meta.
“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.”
Kathrin Renz, VP business development and industries, AWS, said Meta and AWS have been expanding their collaboration over the last five years.
“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.”
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