Category: Intermediate (200)

In this post, we explore how Amazon Q Business uses personalization to improve the relevance of responses and how you can align your use cases and end-user data to take full advantage of this capability

In this post, we demonstrate how to simplify data access to Amazon S3 from SageMaker Studio using S3 Access Grants, specifically for different user personas using IAM principals.

In this post, we show you the Employee Productivity GenAI Assistant Example, a solution built on AWS technologies like Amazon Bedrock, to automate writing tasks and enhance employee productivity.

In this post, we discuss how Amazon Bedrock Knowledge Bases provides a powerful solution for numerical analysis on documents. You can deploy this solution in an AWS account and use it to analyze different types of documents.

In this post, we show you how DoorDash built a generative AI agent using Amazon Connect, Amazon Lex, and Amazon Bedrock Knowledge Bases to provide a low-latency, self-service experience for their delivery workers.

In this post, we showcase the latest generation of Just Walk Out technology by Amazon, powered by a multi-modal foundation model (FM). We designed this multi-modal FM for physical stores using a transformer-based architecture similar to that underlying many generative artificial intelligence (AI) applications.

In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.

The clustered regularly interspaced short palindromic repeat (CRISPR) technology holds the promise to revolutionize gene editing technologies, which is transformative to the way we understand and treat diseases. This technique is based in a natural mechanism found in bacteria that allows a protein coupled to a single guide RNA (gRNA) strand to locate and make […]

In this post, we provide a step-by-step guide for creating an enterprise ready RAG application such as a question answering bot. We use the Llama3-8B FM for text generation and the BGE Large EN v1.5 text embedding model for generating embeddings from Amazon SageMaker JumpStart.

In this post, we dive into the best practices and techniques for prompting Meta Llama 3 using Amazon SageMaker JumpStart to generate high-quality, relevant outputs. We discuss how to use system prompts and few-shot examples, and how to optimize inference parameters, so you can get the most out of Meta Llama 3.