Category: Generative AI

In this post, we show you how DXC and AWS collaborated to build an AI assistant using large language models (LLMs), enabling users to access and analyze different data types from a variety of data sources. The AI assistant is powered by an intelligent agent that routes user questions to specialized tools that are optimized for different data types such as text, tables, and domain-specific formats. It uses the LLM’s ability to understand natural language, write code, and reason about conversational context.

MSD, a leading pharmaceutical company, collaborates with AWS to implement a powerful text-to-SQL generative AI solution using Amazon Bedrock and Anthropic’s Claude 3.5 Sonnet model. This approach streamlines data extraction from complex healthcare databases like DE-SynPUF, enabling analysts to generate SQL queries from natural language questions. The solution addresses challenges such as coded columns, non-intuitive names, and ambiguous queries, significantly reducing query time and democratizing data access.

In this post, we demonstrate how to interact with the Amazon Titan Image Generator G1 v2 model on Amazon Bedrock to generate an image. Then, we show you how to use Anthropic’s Claude 3.5 Sonnet on Amazon Bedrock to describe it, evaluate it with a score from 1–10, explain the reason behind the given score, and suggest improvements to the image.

In this post, we introduce the core dimensions of responsible AI and explore considerations and strategies on how to address these dimensions for Amazon Bedrock applications.

In this post, we explore how Principal used QnABot paired with Amazon Q Business and Amazon Bedrock to create Principal AI Generative Experience: a user-friendly, secure internal chatbot for faster access to information. Using generative AI, Principal’s employees can now focus on deeper human judgment based decisioning, instead of spending time scouring for answers from data sources manually.

In this post, we walk through a step-by-step guide to automating invoice processing using Streamlit and Amazon Bedrock, addressing the challenge of handling invoices from multiple vendors with different formats. We show how to set up the environment, process invoices stored in Amazon S3, and deploy a user-friendly Streamlit application to review and interact with the processed data.

In this post, we show you how to build a generative AI-powered trip-planning service that revolutionizes the way travelers discover and explore destinations. By using advanced AI technology and Amazon Location Service, the trip planner lets users translate inspiration into personalized travel itineraries. This innovative service goes beyond traditional trip planning methods, offering real-time interaction through a chat-based interface and maintaining scalability, reliability, and data security through AWS native services.

This post explores a solution that uses the power of AWS generative AI capabilities like Amazon Bedrock and OpenSearch vector search to perform damage appraisals for insurers, repair shops, and fleet managers.

Stability AI’s newest launch of Stable Diffusion 3.5 Large (SD3.5L) on Amazon SageMaker JumpStart enhances image generation, human anatomy rendering, and typography by producing more diverse outputs and adhering closely to user prompts, making it a significant upgrade over its predecessor. In this post, we explore advanced prompt engineering techniques that can enhance the performance of these models and facilitate the creation of compelling imagery through text-to-image transformations.

In this post, we explore the approach behind building an AWS AI-powered Chrome extension that aims to revolutionize the live streaming experience by providing real-time transcription, translation, and summarization capabilities directly within your browser.