Does Agentic AI Break the Case for GPU-Only Inference?

Why attend:

• Watch a live demo of an inference workload on OCI + WEKA and see the KV cache bottleneck and the fix in action, not described in a slide
• Hear Semi-Analysis push WEKA and Oracle on where the CPU/GPU line actually sits — this isn’t your typical scripted vendor session
• Get straight answers on where your inference budget is actually going

What you’ll leave with:
A framework for evaluating your own inference stack and where CPU should be doing the work, where GPU still wins, and how to tell the difference in your own environment. Not a takeaway deck; a way of thinking about the next architecture decision in front of you.

Agent sessions aren’t one continuous GPU pass, they’re dozens of model steps interrupted by CPU-side tool calls, retrieval, and code execution. Every one of those gaps risks evicting the GPU’s KV cache, forcing an expensive recompute. Recent industry benchmarking, including NVIDIA’s own analysis of agentic workloads, points to this exact failure point. This session covers what it means for your architecture on OCI, live.

Agenda:
9:30 AM Arrival
9:45 AM Welcome & Opening Remarks
10:00 AM Fireside Discussion, moderated by Semi-Analysis
11:00 AM Live Demonstration
11:15 AM Open Discussion and Q&A
11:30 AM – 12:30 PM Lunch & Executive Networking

Moderated by Semi-Analysis, the independent analyst firm known for the most technically rigorous, least forgiving benchmarking in AI infrastructure.

Who should attend:
Infrastructure and platform leaders working on AI inference at scale, teams evaluating RAG, agentic AI, model serving, OKE, CPU inference, GPU alternatives, or AI cost control. Messaging is platform-agnostic throughout.

Meet Our Speakers

Val Bercovici

Chief AI Officer at WEKA

Manu Mishra

Principal Solutions Architect, Oracle