Lightning AI, the creator of PyTorch Lightning and Lightning Studios, announced it has signed a Strategic Collaboration Agreement (SCA) with Amazon Web Services, Inc. (AWS). The SCA allows Lightning AI to leverage AWS compute services to power generative artificial intelligence (AI) services and to provide first-class support for Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances, powered by AWS Trainium accelerators, directly within the platform. By collaborating with AWS, Lightning AI is able to offer a powerful, enterprise-grade, cloud-based platform for building and deploying AI products.
Last month, the company announced Lightning Studios, which are cloud-based virtual environments where AI researchers and developers can code on the browser or from their laptops to develop and ship AI together. Developers today, string together 20 platforms to monitor, train, serve, prep data, host apps, etc. Lightning Studios unites all those tools into a single, cohesive experience that lets them stay focused on your work without context switching. Lightning AI Studio has apps that do specialized work, such as code on the cloud, multi-node training, distributed data preparation, or hosting and sharing AI web apps.
Also Read: Weaviate partners with Snowflake to bring secure GenAI to Snowpark Container Services
“Collaborating with AWS allows Lightning AI to offer our customers highly customized cloud computing and storage options,” said William Falcon, creator of PyTorch Lightning and the CEO and founder of Lightning AI. “With affordable, enterprise-grade speed and performance — at scale — we believe we have one of the world’s best end-to-end platforms for building and deploying AI products.”
Lightning AI is the company behind PyTorch Lightning, the deep learning framework of choice for developers and companies seeking to build and deploy AI products. Focusing on simplicity, modularity, and extensibility, Lightning AI Studio, its flagship product, streamlines AI development and boosts developer productivity. Its aim is to enable individual developers and enterprise users to build deployment-ready AI products.
SOURCE: BusinessWire