How to evaluate a RAG application Before we begin, it is important to distinguish LLM model evaluation from LLM application evaluation. Evaluating LLM models involves measuring the performance of a given model across different tasks, whereas LLM application evaluation is about evaluating different compone...
We used the following metrics to evaluate embedding performance: Embedding latency: Time taken to create embeddings Retrieval quality: Relevance of retrieved documents to the user query Hardware used 1 NVIDIA T4 GPU, 16GB Memory Where’s the code? Evaluation notebooks for each of the above embedding...
RAG combines the power of generative models with external knowledge, allowing systems to produce more specific, context-relevant responses. Vector databases lie at the foundation of RAG systems. Selecting the correct vector database is important in optimizing our RAG system for maximum performance and...
To hear about the latest innovations and best practices for building RAG applications, check out theretrieval-augmented generation sessionsfromNVIDIA GTC 2024. Related resources GTC session:Large-Scale Production Deployment of RAG Pipelines GTC session:Generative AI Theater: Supercharge Software Delivery W...
1.Model size vs. performance Large models: LLMs are well-known for their impressive performance across a range of tasks, thanks to their massive number of parameters. For example, GPT-3 boasts 175 billion parameters, while PaLM scales up to 540 billion parameters. This enormous size allows LL...
Building Trust in AI: The Role of RAG in Data Security and Transparency This article is an excerpt from the book, "Unlocking Data with Generative AI and RAG", by Keith Bourne. Master Retrieval-Augmented Generation (RAG), the most popular generative AI tool, to unlock the full potential of...
However, researchers will need to further evaluate whether SEER-based studies use this study design appropriately. Case-series study A case series includes multiple individuals across time who were diagnosed with the same disease or received the same treatment [105]. Case-series studies are subsets ...
where AI systems might be employed to evaluate other AI systems, aiming to ensure ongoing reliability and performance at scale. He also explored the potential of using AI to oversee AI systems, addressing challenges related to transparency, accountability, and fairness in AI development and deployment...
program, or initiative. Typically used in project management, environmental assessments, and business strategies, it provides a reference to evaluate performance, identify deviations, and measure success. The report helps stakeholders track advancements, adjust strategies, and ensure alignment with objectives...
Evaluate performance. Run test queries to check if your search results are relevant and accurately ranked. You can also experiment with different embedding models to improve the performance of your vector search queries. To learn more, see How to Evaluate Your LLM Application. Troubleshooting Consider...