Enterprise AI Is Not a Model Problem. It’s a Data and Orchestration Problem

Описание: Enterprise leaders are realizing that AI success is not constrained by models. The real challenge lies in data access, orchestration, security, and cost-effective infrastructure at scale. This session explores what it truly takes to operationalize AI across hybrid environments and deliver measurable business outcomes today.

In this talk, Ted Marena of AMD and Luke Norris of Kamiwaza unpack how open, enterprise-ready AI stacks are unlocking agentic workloads across industries. They explain why data ontology, inference orchestration, and security-first design matter more than incremental model improvements and how enterprises can move from experimentation to production without vendor lock-in.

Key insights include:
Why most enterprise AI bottlenecks are rooted in data orchestration, not model capability
How AMD’s open enterprise AI stack enables hybrid and multi-cloud deployment
The role of ontologies and inference meshes in agentic AI systems
What it takes to secure AI workflows at scale, including managing inference risk
How cost-efficient GPU architectures are expanding AI access beyond hyperscalers

📍 Recorded live at CXO Enterprise AI Day, Hotel Valencia, Santana Row, San Jose, CA

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