Welcome to day 1! My goal for today is to understand different aws services and tools related to Gen AI, and get my hands dirty! Here's a summary of what I learned today:
Bedrock is the core AWS's managed service for experimenting with and deploying pre-trained foundation models. You get access to multiple models (e.g. Claude, Titan) through a single API, without managing infrastructure.
Some other AWS services and tools related to Gen AI:
- Bedrock data manipulation: Turn unstructured data into structured form.
- Bedrock Knowledge Base: vector store for your embeddings that integrates with S3, SharePoint, and Confluence.
- Vector storage: You can choose a storage whenever you create a knowledge base. Use OpenSearch(recommended by AWS) or PostgreSQL (e.g. pgvector) for vector search and retrieval.
- Generative AI application builder: Low-code way to build Gen AI apps on top of Bedrock.
- Bedrock prompt management: Version and manage prompts in one place.
- Bedrock Flow: Multi-step, multi-agent style workflows.
- Amazon SageMaker pipelines: For automated ML workflows, including testing and validation of models.
Using Bedrock for a POC
Bedrock provides all the tools you need to build a Gen AI POC:
- Models: Multiple FMs behind one API.
- Knowledge Base: For RAG without building pipelines from scratch.
- Agents: For tool use and multi-step reasoning.
- Model evaluation: Evaluate outputs against your own criteria.
- Guardrails: Built-in safety features to prevent harmful outputs.
To be continued...