AWS Machine Learning Blog

Category: HAQM Nova

AWS Field Experience reduced cost and delivered low latency and high performance with HAQM Nova Lite foundation model

The AFX team’s product migration to the Nova Lite model has delivered tangible enterprise value by enhancing sales workflows. By migrating to the HAQM Nova Lite model, the team has not only achieved significant cost savings and reduced latency, but has also empowered sellers with a leading intelligent and reliable solution.

How Infosys improved accessibility for Event Knowledge using HAQM Nova Pro, HAQM Bedrock and HAQM Elemental Media Services

In this post, we explore how Infosys developed Infosys Event AI to unlock the insights generated from events and conferences. Through its suite of features—including real-time transcription, intelligent summaries, and an interactive chat assistant—Infosys Event AI makes event knowledge accessible and provides an immersive engagement solution for the attendees, during and after the event.

Build an automated generative AI solution evaluation pipeline with HAQM Nova

In this post, we explore the importance of evaluating LLMs in the context of generative AI applications, highlighting the challenges posed by issues like hallucinations and biases. We introduced a comprehensive solution using AWS services to automate the evaluation process, allowing for continuous monitoring and assessment of LLM performance. By using tools like the FMeval Library, Ragas, LLMeter, and Step Functions, the solution provides flexibility and scalability, meeting the evolving needs of LLM consumers.

Build a FinOps agent using HAQM Bedrock with multi-agent capability and HAQM Nova as the foundation model

Build a FinOps agent using HAQM Bedrock with multi-agent capability and HAQM Nova as the foundation model

In this post, we use the multi-agent feature of HAQM Bedrock to demonstrate a powerful and innovative approach to AWS cost management. By using the advanced capabilities of HAQM Nova FMs, we’ve developed a solution that showcases how AI-driven agents can revolutionize the way organizations analyze, optimize, and manage their AWS costs.

Model customization, RAG, or both: A case study with HAQM Nova

The introduction of HAQM Nova models represent a significant advancement in the field of AI, offering new opportunities for large language model (LLM) optimization. In this post, we demonstrate how to effectively perform model customization and RAG with HAQM Nova models as a baseline. We conducted a comprehensive comparison study between model customization and RAG using the latest HAQM Nova models, and share these valuable insights.