This lab is intended to give you an overview of HPE Private Cloud AI, HPE's turnkey solution for on-prem AI workloads. HPE has paired with NVIDIA's AI Enterprise software giving customers a scalable on-prem solution that can handle multiple different AI workloads from Inference, RAG, model fine-tuning, and model training.

NVIDIA Blueprints: PDF Ingestion, also known as NVIDIA-Ingest, or NV-Ingest, this blueprint is a scalable, performance-oriented document content and metadata extraction microservice. Including support for parsing PDFs, Word and PowerPoint documents, it uses specialized NVIDIA NIM microservices to find, contextualize, and extract text, tables, charts and images for use in downstream generative applications.

Explore the hidden dangers of prompt injection in Large Language Models (LLMs). This lab reveals how attackers manipulate LLMs to disclose private information and behave in ways that they were not intended to. Discover the intricacies of direct and indirect prompt injection and learn to implement effective guardrails.

In the current AI market, the demand for scalable and secure deployments is increasing. Public cloud providers (AWS, Google, and Microsoft) are competing to provide GenAI infrastructure, driving the need for multi-cloud and hybrid cloud deployments. However, distributed deployments come with challenges, including: Complexity in managing multi-cloud environments. Lack of unified visibility across clouds. Inconsistent security and policy enforcement. F5 Distributed Cloud provides a solution by offering a seamless, secure, and portable environment for GenAI workloads across clouds. This lab will guide you through setting up and securing GenAI applications with F5 Distributed Cloud on AWS EKS and GCP GKE.

Training data poisoning poses significant risks to Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. This lab explores these dangers through a case study of an online forum, demonstrating how corrupted data can compromise AI effectiveness and security, and examines methods to mitigate such threats.

HPE Private Cloud AI, a pioneering turnkey solution, integrates NVIDIA and HPE technologies to simplify and accelerate AI development. It offers scalable configurations and enables experimentation and innovation in a secure on-premises environment. Explore its capabilities through hands-on lab experiences and easily streamline your AI journey.

This lab will go into the basics of Retrieval Augmented Generation (RAG) through hands on access to a dedicated environment.

NVIDIA DGX H100 integration and validation environment for enterprise AI workflows.

The Dell Reference Architecture environment is a full-stack solution that includes Dedicated Dell PowerSwitch High-Speed Networking, Dell PowerEdge Accelerator Optimized Compute nodes (XE9680 and R760xa servers), and Dell PowerScale Storage (F600 Array) as the hardware components and includes multiple MLOps and Kubernetes Platform solutions.

Red Hat OpenShift AI, formerly known as Red Hat OpenShift Data Science, is a platform designed to streamline the process of building and deploying machine learning (ML) models. It caters to both data scientists and developers by providing a collaborative environment for the entire lifecycle of AI/ML projects, from experimentation to production. In this lab, you will explore the features of OpenShift AI by building and deploying a fraud detection model. This environment is built ontop of Dell R660's and Intel Xeon's 5th generation processors.

Lab that walks through Cisco Flash Stack for AI

The NVIDIA Blueprints for generative virtual screening demonstrate how generative AI and accelerated NVIDIA NIM microservices can be leveraged to design optimized small molecules more intelligently and efficiently.