The article focuses on navigating the deployment of Large Language Models (LLMs) for users outside major AI companies. It outlines when self-hosting is appropriate, emphasizing that while it offers control, it requires significant infrastructure management. In contrast, using an API provider simplifies deployment as the provider handles the backend. The article aims to provide practical best practices and tips for deploying LLMs in corporate environments, highlighting the different deployment strategies employed by businesses versus dedicated AI Labs.
The right choice between self-hosting LLMs or using an API provider depends on specific needs, as self-hosting can be complex and resource-intensive.
Building applications with LLMs requires a different deployment strategy than those deployed by AI Labs, emphasizing bespoke infrastructure tailored for corporate use.
Collection
[
|
...
]