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Guy Currier of The Futurum Group presented on “The Next Wave of AI,” focusing on the increasing importance of inference outside hyperscale data centers. He highlighted a maturing AI market characterized by a significant shift in investment from AI training towards AI inference. This trend, supported by Futurum Group research, indicates faster growth in inference, particularly between 2025 and 2027, with fine-tuning and smaller model training also categorized under this evolving landscape. This development aligns with the Open Compute Project’s new AI Compute Continuum initiative, which acknowledges the critical role of AI extending beyond traditional enterprise data centers to the furthest reaches of the edge.
Currier employed a historical analogy of the Roman Empire’s expansion through “colonias” or outposts to illustrate the progression of AI deployment. He described the initial phase of AI development as being concentrated in elite, core, cloud-based environments, similar to these powerful yet contained Roman settlements. The current and future wave involves extending AI capabilities, much like building Roman roads, by distributing AI services and applications to the edge. This expansion is driven by the practical need to place AI where it offers optimal performance, considering factors such as data proximity and specific physical environment requirements, ultimately providing users and architects with enhanced control and flexibility across a continuum from core to edge.
The presentation underscored the emerging concept of “hyper-hybridity,” suggesting that every edge deployment is fundamentally a hybrid one, spanning cloud, on-premise, and diverse edge locations. While the core AI market remains larger, the edge market is projected to grow substantially, nearing parallel in size by 2030. Critical enduring questions for this expansion include the necessity for robust standards, particularly given the traditional hyperscale focus of organizations like OCP. There is also a recognition of immense diversity in processing units beyond GPUs, the indispensable role of resilient networking to overcome edge discontinuities, and the intricate interplay between hardware and software in driving efficient, distributed AI solutions, including the rapid development of custom chips.
Personnel: Guy Currier
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