Accelerate your generative AI development with NVIDIA on AWS
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LLMs can help increase efficiency across enterprise tasks but these models often struggle to understand real-time events and specific knowledge domains, which can lead to inaccuracies. Fine-tuning LLMs can help improve accuracy, but it can be costly, labor-intensive, and require ample technical expertise. NeMo Retriever, part of NVIDIA AI Enterprise, on AWS helps enterprises enhance their generative AI applications with retrieval-augmented generation (RAG) capabilities.
Watch this Spotlight Series event to see a demo on how NeMo Retriever can optimize the embedding and retrieval process of RAG to deliver higher accuracy and more efficient responses for AI applications.
You will learn how to:
- Connect LLMs to multiple data sources and knowledge bases so that users can easily interact with data and receive accurate, up-to-date answers.
- Quickly train, customize, and deploy LLMs at scale leveraging existing code and pretrained models.
- Accelerate time to solution and reduce total cost of ownership (TCO) for deploying AI into production with NVIDIA AI Enterprise on AWS.