Watch WWT Co-Founder and CEO Jim Kavanaugh and NVIDIA Founder and CEO Jensen Huang talk about the evolution and future of AI. During the discussion, Jim and Jensen will also provide practical tips for implementing AI at scale within the enterprise.

NVIDIA's newly announced Blueprints are poised to play a foundational role in developing and scaling AI applications across a variety of industries. Whether it's digital humans, virtual drug screenings or multimodal PDF data extraction workflows for RAG, these blueprints will enable developers to build customized enterprise AI solutions in a production-line manner. In this executive-led webinar, learn more about the blueprints from WWT's Vice President of Technical Delivery & Engineering Center of Excellence Nate McKie and NVIDIA Vice President of Enterprise AI Justin Boitano, and how you can modify and optimize those blueprints in WWT's one-of-a-kind AI Proving Ground to more quickly create applications tailored to your specific use cases.

As part of the NVIDIA AI Computing by HPE portfolio, HPE Private Cloud AI is the industry's first full-stack, turnkey private cloud for AI. It delivers a unique, cloud-based experience to accelerate innovation, return on investment and manage enterprise risk from AI.

Welcome to part 2 about our RAG lab infrastructure built in collaboration with NetApp, NVIDIA, and WWT. NVIDIA NIM microservices is a suite of user-friendly microservices that facilitate the deployment of generative AI models, such as large language models (LLMs), embeddings, re-rankings, and others, across various platforms. NVIDIA NIM microservices simplify the process for IT and DevOps teams to manage LLMs in their environments, providing standard APIs for developers to create AI-driven applications like copilots, chatbots, and assistants. It leverages NVIDIA's GPU technology for fast, scalable deployment, ensuring efficient inference and high performance.

Welcome to part 1 of the videos series about the RAG Lab Infrastructure built in collaboration with NetApp, NVIDIA, and World Wide Technology. This video series will take you behind the scenes of this state-of-the-art lab environment inside the AI Proving Ground from WWT, powered by the Advanced Technology Center.

WWT's Matt Halcomb unboxes a brand new NVIDIA DGX H100, offering a behind-the-scenes look at how this gold standard of AI infrastructure fits into our new AI Proving Ground lab environment within the ATC.

The world has been changed by AI and every business is trying to figure out how to leverage it. HPE Private Cloud solutions bring together optimized infrastructure and software in a unique cloud experience delivered through HPE GreenLake.

WWT's Matt Halcomb unboxes the highly anticipated Dell PowerEdge XE9680 system, also known as the Dell HGX. See how this system, part of the Dell Validated Designs for GenAI with NVIDIA, fits into WWT's AI Proving Ground lab environment.

WWT's Matt Halcomb walks us through the installation of the Cisco FlashStack AI environment in the AI Proving Ground. After the infrastructure is installed, Matt shows us the software component integration. We're excited to continue to build new environments with our partners.

WWT's Derek Elbert gives a behind the scenes look at the NetApp AI Pod in the AI Proving Ground. This environment is one of the few environments that is attached to a single NVIDIA DGX. Get an inside look into how we are using this environment to add value to our clients.

Take a behind-the-scenes look at a state-of-the-art AI lab, showcasing how Run:ai optimizes AI workloads, Red Hat OpenShift manages and scales AI applications, and Dell's validated design provides the powerful hardware foundation for AI innovation.

In this technology demonstration, we will showcase the deployment of an AI workload using Cisco Intersight automation on a single UCS X-Series blade, leveraging a neighboring X440p (X-Fabric) with an NVIDIA A40 GPU. This demo will highlight the powerful capabilities of both Cisco Intersight and the Cisco AI Toolkit, which includes tools for AI model deployment, system monitoring, and resource management. By utilizing Miniconda for environment management, CUDA for GPU acceleration, and various large language models like Vicuna and Meta OPT, we will feed data into a retrieval-augmented generation (RAG) model.