Deploying AI video at scale often introduces severe infrastructure bottlenecks and cost challenges, driven primarily by heavy reliance on GPUs alone, leaving CPU cycles underutilized, even as AI is rapidly expanding across all tiers of infrastructure.
By leveraging latest-generation Intel® Xeon® processors with Intel® Advanced Matrix Extensions (Intel® AMX), organizations can rebalance their AI workloads by executing compute-intensive workloads such as Video Super-Resolution, inverse tone mapping, and bitrate optimization directly on the CPU alongside encoding pipelines.
Building on this efficient compute foundation, the Intel® Media AI Framework transforms raw media into trusted, searchable AI-ready intelligence, while simplifying deployment of media workloads. Through agentic orchestration, intelligent model routing, reusable MCP tools, and video RAG, the framework powers configurable workflows like semantic search, summarization, metadata enrichment, contextual ad placement, and other MCP-based agent flows.
This session demonstrates the larger value of bringing Xeon-based acceleration through the Intel® Media AI Framework to improve user experience, convert media into actionable intelligence, and empower customers to build and scale cost effective media AI pipelines optimized for Intel® Xeon®.
Presenters: Arnaud Perrier and Richard Chuang from Intel
