AI, Get Up! Businesses can unleash the potential of their business data with production-ready NVIDIA NIM inference microservices for retrieval-augmented generation
Applications of generative AI are worthless, or even harmful, without accuracy, and data is the foundation of accuracy
NeMo Retriever NIM microservices, when coupled with the today-announced NVIDIA NIM inference microservices for the Llama 3.1 model collection
NeMo Retriever, for instance, can increase model throughput and accuracy for developers building AI agents and chatbots for customer support
The NeMo Retriever NIM microservices enable developers to leverage all of this while leveraging their data to an even greater extent
Compared to conventional large language models, or LLMs, embedding models are quicker and less expensive computationally
These models are slower and more computationally complex than embedding models, but they provide notable improvements in accuracy