LLM features have the potential to significantly improve the user experience, however, they are expensive and can impact the performance of the product. Hence, it is critical to measure the user value they add to justify any added costs. While a product-level utilit...
These phases have quite different performance profiles. The Prefill Phase requires just one invocation of the LM, requiring the fetch of all the parameters of the model once from the DRAM, and reuses it m times to process all the m tokens in the prompt. With sufficiently ...
LLM features have the potential to significantly improve the user experience, however, they are expensive and can impact the performance of the product. Hence, it is critical to measure the user value they add to justify any added costs. While a product-level utility metric [2] f...
We use the answer_similarity and answer_correctness metrics to measure the overall performance of the RAG chain. The evaluation shows that the RAG chain produces an answer similarity of 0.8873 and an answer correctness of 0.5922 on our dataset. The correctness seems a bit low so let’s ...
I would like to understand the different query plans and how to measure the execution speed and also the "math" reason why one query is faster then the other. Also what am i doing wrong? I am not sure what tool do you use to look at the query plan, but the table you showed is ...
In addition to ROUGE, there is another metric defined to measure the quality of translations generated by LLMs by comparing them with reference translation:BLEU(BiLingual Evaluation Understudy). BLEU computes a similarity score between 0 and 1 by evaluating theoverlap of n-grams between the generate...
As we’ve seen, AI Content Detectors are not a measure of AI Content quality; they are cheap shot tools today. You may trick your client who uses such a trivial, outdated tool, but you may not trick Google. We can assume that Google already has more robust methods and models than some...
NDCG is a common metric to measure the performance of retrieval systems. A higher NDCG indicates an embedding model that is better at ranking relevant items higher in the list of retrieved results. Model Size: Size of the embedding model (in GB). It gives an idea of the computational ...
survey. Depending on your current pain points, you may want to focus your survey around a specific topic (i.e., wellbeing,DEI, etc.). However, we generally recommend beginning with anemployee engagement survey, as this survey type focuses on the measure you most want to improve: engagement...
LLM testing basics involve evaluating large language models (LLMs) to ensure their accuracy, reliability, and effectiveness. This includes assessing their performance using both intrinsic metrics, which measure the model’s output quality in isolation, and extrinsic metrics, which evaluate how well the...