LangChain

In: Artificial Intelligence

In healthcare, the ability to quickly analyze and interpret medical reports is crucial for both healthcare providers and patients. While medical reports contain valuable information, they often remain underutilized due to their complex nature and the time-intensive process of analysis. This complexity manifests in several ways: the interpretation of multipleContinue Reading

In: Artificial Intelligence

Developing generative AI agents that can tackle real-world tasks is complex, and building production-grade agentic applications requires integrating agents with additional tools such as user interfaces, evaluation frameworks, and continuous improvement mechanisms. Developers often find themselves grappling with unpredictable behaviors, intricate workflows, and a web of complex interactions. The experimentationContinue Reading

In: Artificial Intelligence

Amazon Bedrock Knowledge Bases offers a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) to internal data sources. It’s a cost-effective approach to improving LLM output so it remains relevant, accurate, and useful in various contexts. It also provides developers with greater control over theContinue Reading

In: Artificial Intelligence

This post is co-written with Harrison Chase, Erick Friis and Linda Ye from LangChain. Generative AI is set to revolutionize user experiences over the next few years. A crucial step in that journey involves bringing in AI assistants that intelligently use tools to help customers navigate the digital landscape. InContinue Reading

In: Artificial Intelligence

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. From deriving insights to powering generative artificial intelligence (AI)-driven applications, the ability to efficiently process and analyze large datasets is a vital capability. However, managing the complex infrastructure required for big dataContinue Reading