Democratizing Access to Advanced AI: The Future of GPU provisioning

Join us for a live stream podcast featuring Dario Tranchitella from @clastixlabs as we explore the concept of Kubernetes virtual nodes and their impact on AI inference!

In this episode, we'll dive into:

- Virtual nodes in Kubernetes and how they're changing the rules for resource management
- K8s.gpu as an cluster-to-cluster implementation of the virtual node paradigm, leveraging the power of managed controlplane and @seeweb GPU offering
- A live demo showcasing the integration of a virtual node as an inference runner for [Helix.ai](http://tryhelix.ai)
- Sneaky peak to what Helix framework can do for GenAI App development

Why should you care?

1. We'll explore how virtual nodes in Kubernetes are opening new possibilities for resource allocation and management, particularly in the realm of on-demand resources for AI and machine learning. Learn how this concept allows for seamless integration of external resources, making GPU-intensive tasks more accessible and efficient.

2. Discover Helix AI, a cutting-edge generative AI stack designed for versatility and control. We'll demonstrate how Helix can be deployed on your own infrastructure - whether locally, on your private cloud, or on-premise.

3. The combination of virtual nodes and platforms like Helix are democratizing access to advanced AI capabilities, allowing organizations to harness generative AI while maintaining control over their infrastructure and data.

🔔 Set a reminder and join us live for an in-depth look at the future of AI infrastructure and a Q&A session with our expert guest!