Category: AWS Big Data

In this post, we aim to provide business leaders with a non-technical overview of purpose-built accelerators (PBAs) and their role within the financial services industry (FSI).

In this post, we explore how to build a scalable and efficient Retrieval Augmented Generation (RAG) system using the new EMR Serverless integration, Spark’s distributed processing, and an HAQM OpenSearch Service vector database powered by the LangChain orchestration framework. This solution enables you to process massive volumes of textual data, generate relevant embeddings, and store them in a powerful vector database for seamless retrieval and generation.

In this post, we explore using the Anthropic Claude 3 on HAQM Bedrock large language model (LLM). HAQM Bedrock provides access to several LLMs, such as Anthropic Claude 3, which can be used to generate semi-structured data relevant to the healthcare industry. This can be particularly useful for creating various healthcare-related forms, such as patient intake forms, insurance claim forms, or medical history questionnaires.

Organizations are using machine learning (ML) and AI services to enhance customer experience, reduce operational cost, and unlock new possibilities to improve business outcomes. Data underpins ML and AI use cases and is a strategic asset to an organization. As data is growing at an exponential rate, organizations are looking to set up an integrated, […]