LangChain

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