Running your own language model, the list of prerequisites gets long fast: compute provisioning, GPU allocation, model downloads, service wiring, storage configuration, and authentication, with no guarantee it stays running once you get there. Many teams look at that list and reach for a commercial AI service instead. The teams that don't spend months on infrastructure work before a single model reaches production.
Fuzzball removes that overhead by capturing AI model deployment as a reusable, templated workflow. In this webinar, we'll demonstrate two ways Fuzzball supports AI deployment:
- CIQ's own tutorial video generation workflow, running live in Fuzzball on Nvidia DGX hardware.
- A self-scaling LLM that grows from a single team's use to full production serving, without changing the underlying workflow.
Join us July 16 at 3:00 PM ET / 12:00 PM PT for both demos and a live Q&A.
