AWS' new approach to RAG evaluation could help enterprises reduce AI spending

RAG, a critical approach for enterprises to reduce LLM hallucinations and drive AI business outcomes, demands substantial engineering practices.

AWS introduces an automated RAG evaluation process, leveraging item response theory for factual accuracy assessment of RAG models.

AWS aims to enable enterprises to build efficient RAG solutions without costly fine-tuning, inefficient workflows, or excessive in-context learning.

Read at InfoWorld