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Infinidat Cures RAG Inferencing Response Time Troubles

Generative AI (GenAI) and Large Language Models (LLMs) offer equal opportunities as they do challenges. These AI systems can perform various language tasks but may "hallucinate," providing inaccurate information. Mitigating this is crucial.

This paper explores the boons of Retrieval-Augmented Generation (RAG) inferencing and how to mitigate all-too-common RAG storage latency bottlenecks.

Download your copy to address these RAG inferencing issues and see how Infinidat’s Neural Cache technology address RAG latency and enhances LLM performance.

These are also closely related to: "Create ultra-low latency feature store with ElastiCache for Redis"

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