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NVIDIA DGX Cloud Lepton

Unifies GPU compute across cloud providers for AI development, training, and deployment with a single, consistent platform.

Introduction

NVIDIA DGX Cloud Lepton connects developers to a global network of GPU compute, across multiple cloud providers, through a single platform. Designed for AI natives and model builders, it streamlines AI development, training, and deployment by unifying compute environments. Key features include:

  • Unified AI Platform: Provides a consistent experience for development, training, and inference.
  • Multi-Cloud Deployment: Enables seamless deployment across various cloud providers and regions.
  • Integrated Tools: Streamlines the path from prototype to production, reducing infrastructure management complexity.
  • Global GPU Access: Connects developers to a global network of NVIDIA Cloud Partners (NCPs) and GPU marketplaces.

Use cases include:

  • AI model development and training.
  • Scalable AI application deployment.
  • Data sovereignty compliance with regional compute selection.
  • Low-latency AI workload execution.

Alternatives

  • AWS SageMaker

    Offers a comprehensive suite of services for building, training, and deploying machine learning models at scale within the AWS ecosystem.

  • Google Cloud Vertex AI

    Provides a unified platform for the entire machine learning workflow, from data ingestion to model deployment, leveraging Google's infrastructure.

  • Azure Machine Learning

    A cloud-based environment that helps you build, train, and deploy machine learning models quickly and efficiently using Microsoft's Azure services.

  • Databricks

    A unified data and AI platform that enables collaborative data science, engineering, and machine learning across multiple cloud environments.

  • Run:AI

    Specializes in orchestrating and optimizing GPU resources for AI workloads, allowing efficient utilization across hybrid and multi-cloud infrastructures.

  • Weights & Biases

    An MLOps platform that helps track, visualize, and manage machine learning experiments and models, often integrating with various compute environments including GPUs.

  • CoreWeave

    A specialized cloud provider offering highly performant, GPU-accelerated infrastructure tailored for AI and machine learning workloads.

  • Lambda Labs

    Provides dedicated GPU cloud services and on-prem solutions, focusing on high-performance computing for deep learning and AI research.

  • Paperspace Gradient

    Offers a managed cloud platform for developing, training, and deploying machine learning models with access to powerful GPU instances.

  • Domino Data Lab

    An enterprise MLOps platform that provides a central hub for data science teams to collaborate, manage, and deploy models across various compute environments.

FAQ

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