Join us for the Virtual Lab Workshop! During this exclusive session, the host will launch the "Introduction to OpenShift AI with Intel and Dell Infrastructure" lab. This lab is designed to provide an environment to gain hands-on experience with the fundamental features of OpenShift AI. The environment that supports the lab is completely virtual, removing any hardware dependencies associated with physical infrastructure. This one-hour event is limited to 60 participants who will have the opportunity to engage in Q&A during the session. Attendees are encouraged to actively participate by launching the lab themselves alongside the host for a hands-on experience.

Join us for the Virtual Lab Workshop! During this exclusive session, the host will introduce the Cisco RoCE Networking lab. This lab is designed to provide an environment to gain hands-on experience with the fundamental features of Cisco RoCE Networking Lab. This lab will demonstrate how the Cisco Nexus Dashboard Fabric Controller (NDFC) can easily set up an AI/ML fabric with a simple point-and-click GUI. This one-hour event is limited to 60 participants who will have the opportunity to engage in Q&A during the session. Attendees are encouraged to actively participate by launching the lab themselves alongside the host for a hands-on experience.

Join us for the Virtual Lab Workshop! During this exclusive session, the host will introduce the Liqid Composable Disaggregated Infrastructure (CDI) Lab. This lab has been purpose-built to allow users to validate NVIDIA GPU and Intel Optane NVMe technology composition to Dell PowerEdge servers via software. This one-hour event is limited to 60 participants who will have the opportunity to engage in Q&A during the session. Attendees are encouraged to actively participate by launching the lab themselves alongside the host for a hands-on experience.

AI development often involves diverse tools and frameworks that necessitate a flexible and portable infrastructure. Learn from Technical Solutions Architect Steve Younger about why the Kubernetes platform is inherently designed for flexibility and portability, making it highly suitable for managing AI workloads across different environments.