We use several different foundational models (also known as large language models, or LLMs) for different purposes. Each LLM has its own strength and is best utilized for the specific use case at hand. Given that LLMs have incredibly large compute and infrastructure footprint, we use Bedrock to click and install the required LLM, run the necessary training or inference jobs in a serverless architecture, and uninstall it at the end to save costs.