Cloud Computing

Cloud computing is the on-demand delivery of computing power, database storage, applications, and other IT resources via the internet with pay-as-you-go pricing.

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Definition

Cloud computing is the delivery of different services through the Internet. These resources include tools and applications like data storage, servers, databases, networking, and software.

Cloud Computing in AI

The AI revolution is built on the backbone of cloud computing. Modern Large Language Models require thousands of interconnected chips to train, a scale only possible through massive cloud data centers.

Key Providers

  • Amazon Web Services (AWS): The market leader, offering services like Amazon Bedrock and SageMaker for AI.
  • Google Cloud Platform (GCP): Known for its custom TPUs and Vertex AI platform.
  • Microsoft Azure: Strategic partner of OpenAI, providing the infrastructure for ChatGPT and Azure AI Studio.

Deployment Models

  1. Public Cloud: Owned and operated by third-party cloud service providers.
  2. Private Cloud: Dedicated to a single organization.
  3. Hybrid Cloud: Combines on-premises infrastructure with public clouds.

Benefits for AI Development

  • Scalability: Easily add more computing power as model size grows.
  • Accessibility: Developers can access state-of-the-art hardware without upfront capital investment.
  • Global Reach: Deploy AI models close to users across the world for low latency.

Frequently Asked Questions

Cloud computing provides the massive computational power ([GPUs](/glossary/gpu-computing) and [TPUs](/glossary/tensor-processing-unit)) required to train and serve large-scale AI models that would be too expensive for most companies to run locally.
Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

Related Terms

AI Infrastructure

AI infrastructure refers to the integrated hardware and software components required to develop, train, and deploy AI models at scale, including high-performance GPUs, storage, and networking.

GPU Computing

Computing paradigm that leverages GPUs to accelerate parallel computations in AI, machine learning, and data processing through massive parallelization.

Scalable AI

Artificial intelligence systems designed to efficiently handle increasing workloads, data volumes, and complexity while maintaining performance and reliability

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