NVIDIA’s Post

🚀 Exciting news from NVIDIA! They’ve announced a new reference architecture for cloud providers to offer generative AI services. This comprehensive blueprint is designed to build high-performance, scalable, and secure data centers capable of handling the demands of generative AI and large language models (LLMs). -Compatibility & Interoperability: Ensures seamless integration of various hardware and software components, reducing deployment time and cost. High-Performance Infrastructure: Featuring the latest GPU architectures like Hopper and Blackwell, high-performance storage, and advanced networking solutions. -Scalability: Designed for cloud-native environments, facilitating flexible and scalable AI systems to meet growing demands. -Comprehensive Support: NVIDIA’s AI Enterprise software suite and access to subject-matter experts for maintenance and support. Benefits for Cloud Providers: -Accelerated Rollout: Faster deployment of AI solutions, giving providers a competitive edge. -Optimized Performance: Benchmarked with industry standards to ensure top-notch performance. -Reduced Costs: Streamlined deployment and compatibility reduce overall costs. -Expertise & Support: Access to NVIDIA’s wealth of knowledge and best practices. -NVIDIA is pushing the boundaries of AI technology, making it accessible and efficient for organizations of all sizes and industries. This architecture is a game-changer for cloud providers looking to harness the power of generative AI and LLMs without the heavy investment in infrastructure. #AI #GenerativeAI #CloudComputing #Innovation #NVIDIA #TechNews #LLMs #ArtificialIntelligence

🗞️ICYMI: Rafay now supports GPU-based workloads in data centers and in all major public clouds, which includes turnkey MLOps and LLMOps capabilities for data scientists. Our new AI Suite with standards-based pipelines helps enterprise platform teams speed AI application  development. According to our CEO Haseeb Budhani: "Rafay has extended our enterprise PaaS offering to support GPU-based workloads in data centers and in all major public clouds. Beyond the multicluster matchmaking capabilities and other powerful PaaS features that deliver a self-service compute consumption experience for developers and data scientists, platform teams can also make users more productive with turnkey MLOps and LLMOps capabilities available on the Rafay platform.” Read more in TDWI: https://lnkd.in/gzf4vuah #PaaS #cloud #automation #K8s #Kubernetes #GPU #LLMOps #Developers #AI #AIpolicy

The era of AI is here, take 4 minutes of your day ⏲ #Novulis #DigitalTransformation #Innovation #Microsoft #Azure #Dynamics365 #DataAI #ITConsulting #PowerPlatform #Copilot #AI https://lnkd.in/eh_R2nAK

#Topics HPE discovers new vision for an AI-native architecture [ad_1] Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here. Hewlett Packard Enterprise (HPE) is expanding its artificial intelligence (AI) efforts with a series of new initiatives announced today at the HPE Discover Barcelona 2023 event. The updates include an expanded partnership with Nvidia that involves both hardware and software to optimize AI for enterprise workloads. The HPE Machine Learning Development Environment (MLDE) which was first released in 2022, is being enhanced with new features to help enterprises consume, customize and create AI models. HPE is also extending MLDE to be available as a managed service, running on AWS and Google Cloud. Additionally, HPE is boosting its own cloud efforts for AI, with new AI-optimized instances in HPE Greenlake and increased performance for file storage in support of AI workloads. The new updates are all designed to support HPE’s vision for a full-stack AI-native architecture optimized from hardware to software. Modern enterprise AI workloads are extremely computationally intensive, require data as a first-class input, and need massive scale for p...

In the rapidly evolving field of cloud computing, the emergence of generative AI agents, or more colloquially, agentic AI, heralds a potential paradigm shift in how we do AI in the cloud—even before we fully capitalize on generative AI’s true potential. Just as cloud computing transformed the tech landscape, agentic AI has the potential to revolutionize our approach to generative AI architecture by introducing autonomy, intelligence, and efficiency.

Denodo Integrates NVIDIA NIM Inference Microservices to Accelerate and Optimize AI Capabilities for Enterprises @Denodo, a leader in #datamanagement, announced that it has integrated NVIDIA NIM inference microservices into the #DenodoPlatform, as part of its focus on bolstering its rapidly expanding #artificialintelligence (#AI) capabilities. @NVIDIA AI NIM is a collection of cloud-native microservices that simplify and accelerate the deployment of #generativeAI models across a variety of environments, including the #cloud, on-premises data centers, and workstations. Read all the details in this article by @IT Digest!

#Denodo, a leader in #datamanagement, announced that it has integrated NVIDIA NIM inference microservices into the #DenodoPlatform, as part of its focus on bolstering its rapidly expanding #artificialintelligence (#AI) capabilities. NVIDIA AI NIM is a collection of cloud-native microservices that simplify and accelerate the deployment of #generativeAI models across a variety of environments, including the #cloud, on-premises data centers, and workstations. Read all the details in this article by IT Digest!

As AI Factories become the bedrock of modern economies across the world, where Data Comes In and Intelligence comes out, data sovereignty is a cultural and economic imperative. #Oracle and #NVIDIA today announced an expanded collaboration to deliver sovereign AI solutions to customers around the world. Customers can now run their entire AI-Stack and other Cloud Services and SaaS applications from within their Data Centers - including #NVIDIA's AI Enterprise Software Platform deployable across following option a. OCI Dedicated Region b. Oracle Alloy c. Oracle EU Sovereign Cloud d. Oracle Government Cloud Oracle is the only hyperscaler capable of delivering AI and full cloud services locally, anywhere.

Turn-Key Data Storage Solution for Large Scale AI Training and Inference – Hundreds of Petabytes in a Multi-tier Solution Supports the Massive Data Capacity Required and High-Performance Data Bandwidth Necessary for Scalable AI Workloads. Supermicro a Total IT Solution Manufacturer for AI, Cloud, Storage, and 5G/Edge, is launching full stack optimized storage solution for AI and ML data pipelines from data collection to high performance data delivery. This new solution maximizes AI time-to-value by keeping GPU data pipelines fully saturated. For AI training, massive amounts of raw data at petascale capacities can be collected, transformed, and loaded into an organization's AI workflow pipeline. This multi-tiered Supermicro solution has been proven to deliver multi-petabyte data for AIOps and MLOps in production environments. The entire multi-rack scale solution from Supermicro is designed to reduce implementation risks, enable organizations to train models faster, and quickly use the

And the evolution of GenAI continues! Instead of a single function LLM that might summarize a document or craft a customer support response, welcome to task-oriented “agents” that can complete multi-step functions. In the post below, you will read about a sample task that was solved. However, this is just the beginning! Over the next few months, we will begin to see many more business-functions solved by agentic workflows. This is a great example of how NVIDIA and Oracle are working together to leverage NIM inferencing microservices to easily deploy these agents. Think of a NIM as an “easy button” similar to “paint by numbers”. Just follow the steps, and you too can paint your enterprise-grade work of art.