This is the fourth installment in a multi-part series on evaluating various RAG systems using Tonic Validate, a RAG ...

With AI observability, we can guard against hallucinations, catch irrelevant and incomplete responses, and identify security ...

RAG draws on additional, newer and domain-specific data sources. This lets an LLM parse more data than it was initially trained on and answer questions with greater accuracy and less bias — both of ...

Krutrim's AI model releases come just days after the emergence of DeepSeek-R1 sent shock waves across the tech industry.

With RAG, they can access external data ... Kiela said enterprise AI is reaching a critical turning point, with AI agents set to become available to the employees of every major company.

Retrieval-Augmented Generation (RAG) is a machine learning framework that combines the advantages of both retrieval-based and generation-based models. The RAG framework is highly regarded for its ...

to evaluate different aspects of RAG system performance. For evaluating selection mechanisms, the system analyzes the relevancy scores of the top 5 retrieved images across a test set of 1,000 ...