Chat-based assistants powered by Retrieval Augmented Generation (RAG) are transforming customer support, internal help desks, and enterprise search, by delivering fast, accurate answers grounded in your own data. With RAG, you can use a ready-to-deploy foundation model (FM) and enrich it with your own data, making responses relevant and context-awareContinue Reading
This post is co-written with Andrew Liu, Chelsea Isaac, Zoey Zhang, and Charlie Huang from NVIDIA. DGX Cloud on Amazon Web Services (AWS) represents a significant leap forward in democratizing access to high-performance AI infrastructure. By combining NVIDIA GPU expertise with AWS scalable cloud services, organizations can accelerate their time-to-train,Continue Reading
This post is co-written with Kshitiz Gupta, Wenhan Tan, Arun Raman, Jiahong Liu, and Eiluth Triana Isaza from NVIDIA. As large language models (LLMs) and generative AI applications become increasingly prevalent, the demand for efficient, scalable, and low-latency inference solutions has grown. Traditional inference systems often struggle to meet theseContinue Reading
Imagine a system that can explore multiple approaches to complex problems, drawing on its understanding of vast amounts of data, from scientific datasets to source code to business documents, and reasoning through the possibilities in real time. This lightning-fast reasoning isn’t waiting on the horizon. It’s happening today in ourContinue Reading
This post is co-written with Eliuth Triana Isaza, Abhishek Sawarkar, and Abdullahi Olaoye from NVIDIA. Today, we are excited to announce that the Llama 3.3 Nemotron Super 49B V1 and Llama 3.1 Nemotron Nano 8B V1 are available in Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, you can nowContinue Reading
As we gather for NVIDIA GTC, organizations of all sizes are at a pivotal moment in their AI journey. The question is no longer whether to adopt generative AI, but how to move from promising pilots to production-ready systems that deliver real business value. The organizations that figure this outContinue Reading
Today, we are excited to announce that the NeMo Retriever Llama3.2 Text Embedding and Reranking NVIDIA NIM microservices are available in Amazon SageMaker JumpStart. With this launch, you can now deploy NVIDIA’s optimized reranking and embedding models to build, experiment, and responsibly scale your generative AI ideas on AWS. InContinue Reading
This post is cowritten with Abdullahi Olaoye, Akshit Arora and Eliuth Triana Isaza at NVIDIA. As enterprises continue to push the boundaries of generative AI, scalable and efficient model training frameworks are essential. The NVIDIA NeMo Framework provides a robust, end-to-end solution for developing, customizing, and deploying large-scale AI models,Continue Reading
This post is co-written with Abhishek Sawarkar, Eliuth Triana, Jiahong Liu and Kshitiz Gupta from NVIDIA. At AWS re:Invent 2024, we are excited to introduce Amazon Bedrock Marketplace. This a revolutionary new capability within Amazon Bedrock that serves as a centralized hub for discovering, testing, and implementing foundation models (FMs).Continue Reading
This post is co-written with Eliuth Triana, Abhishek Sawarkar, Jiahong Liu, Kshitiz Gupta, JR Morgan and Deepika Padmanabhan from NVIDIA. At the 2024 NVIDIA GTC conference, we announced support for NVIDIA NIM Inference Microservices in Amazon SageMaker Inference. This integration allows you to deploy industry-leading large language models (LLMs) on SageMakerContinue Reading
