AWS Developers | 6 Steps to Create a Similarity Search Engine with Amazon Bedrock @awsdevelopers | Uploaded 1 month ago | Updated 1 hour ago
Learn how how to build an accessible similarity search engine, using generative AI and retrieval augmented generation (RAG). You’ll create your semantic search in six easy steps, while getting hands-on with AWS AppSync, Aurora PG, GraphQL, and Amazon Bedrock.

Resources:
🛠️ GitHub repo: github.com/aws-samples/appsync-similarity-search
🌐 Community.AWS Post: https://community.aws/content/2f1mRXuakNO22izRKDVNRazzxhb/how-to-use-retrieval-augmented-generation-rag-for-go-applications
🌐 Community.AWS Post: https://community.aws/content/2fBLRJLSP54YWR4Ji3ZNksJw8Nb/the-computeless-rag-tool-orchestrating-rag-with-aws-appsync
📚 Learn more: aws.amazon.com/blogs/mobile/connect-aws-bedrock-large-language-models-to-enterprise-knowledge-databases-and-apis
📚 Learn more: aws.amazon.com/blogs/mobile/create-a-fullstack-sample-web-app-powered-by-amazon-bedrock

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Chapters:
00:00 - Introduction
01:08 - RAG with Amazon Bedrock
02:16 - Using AWS AppSync
04:32 - Demo
15:00 - Next Steps

#amazonbedrock #similaritysearch #appsync