Hyperscalers and OEMs Race to Optimize Compute Efficiency and Accelerate AI Monetization
The enormous demand for generative Artificial Intelligence (AI) has led to unprecedented CAPEX by hyperscalers, foundation model builders, and those capitalizing on the exploding demand for compute. Global technology intelligence firm ABI Research's discussions across the value chain have exposed the dynamics in the rapidly evolving AI server market, powering the race to increase the efficiency and accuracy of generative AI models.
"The rapid pace of silicon innovation has left space for differentiation," explains Paul Schell, Industry Analyst at ABI Research. "The expertise needed to plan, deploy, and run today's high-performance accelerator clusters has created the opportunity for those with the in-house engineering talent to leverage their organizational capital, capture more value, and ride the generative AI wave."
The professional services offered by Tier One OEMs Supermicro, HPE, Dell, and Lenovo, and challengers like Penguin Solutions, are increasingly seen as a necessary part of their AI server go-to-market. Furthermore, the offering of 'burnt-in' solutions that cater to various end-customers and deployment sizes helps end customers deploy with fewer hurdles, accelerating the monetization of their AI product.
"Time to market matters more than usual in the current stage of the AI race, and AI server vendors able to offer their customers the agility they seek will come out on top", explains Paul Schell. "In addition, cluster management software that can squeeze more out of the pricey hardware is of enormous value – both monetary and operational – for customers without an extensive legacy in AI or HPC compute."