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One CPU doesn't fit every AI workload. Hear why agentic AI is creating new roles for CPUs across the data center.

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🎤 Overheard at #CES2026: AI compute is entering the yottascale era. William Myrhang shows how the AMD Helios AI Platform enables AI to scale by the rack and by the data center, not one server at a time. Designed for agentic and large-scale AI workloads, Helios makes yottascale compute practical, deployable, and sustainable. Zettaflops defined the early AI boom. Yottaflops will define what comes next. AMD is helping build the open foundation needed to support this unprecedented scale.

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Agentic AI is here, and AMD is helping Luma AI deliver the infrastructure needed to support these advanced models. This collaboration, spotlighted at CES, highlights how AMD and Luma AI are working together to enable what’s next. ▶️ Hear more from CEO of Luma AI, Amit Jain (amit).

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$AMD CEO Lisa Su says the server CPU market could exceed $120B by 2030 growing over 35% annually as agentic AI drives more compute demand. If every user has multiple AI agents constantly calling tools and generating tokens then CPUs become critical again.

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AI in the network is shifting the conversation beyond GPUs. At MWC 2026, Intel's Kevork Kechichian, EVP & GM of the Data Center Group, explains why inference workloads are bringing CPUs back into focus, especially in telco environments where power, space, and efficiency matter. With platforms like Intel Xeon and Clearwater Forest, operators are seeing up to 30% performance gains and 60% better power efficiency, helping scale AI workloads without overhauling infrastructure. As networks evolve toward AI-driven operations and 6G, one principle is becoming clear: The future of AI infrastructure is about using the right compute for the right workload.

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