Cloud computing for scalability, cost optimization, and security
Cloud computing has been instrumental in bringing LLMs to a wider audience. LLMs use large-scale GPU processing to learn and generate human-like text, image, audio, and video, engaging in increasingly interactive and intelligent ways.
This section highlights several advantages of leveraging LLMs in a cloud environment:
- Scalability: Cloud computing enables users to access high-performance computing such as GPUs as necessary to run LLMs. This makes it easy to scale applications as required based on consumption needs.
Since LLM models such as GPT are heavy API-driven workloads, there is a need for API management services, such as Azure APIM, that help achieve scalability, security, and high availability across regions. They can also capture telemetry that can help determine token usage and error logging across organizations. We discuss scaling strategies on Azure in Chapter 7.
- Affordability: There is no need...
