Akamai Technologies and VAST Data have announced a new agreement aimed at accelerating and streamlining data-intensive AI inference at the edge. This collaboration seeks to address critical challenges like latency, cost, and scalability that currently hinder the widespread adoption of AI-powered applications.
The partnership combines Akamai’s extensive distributed platform with VAST Data’s AI data platform, designed to provide faster local response times and improved localization for distributed inference. Unlike AI training, which typically occurs in centralized environments, inference requires continuous, on-demand operation with minimal latency, especially when deployed at a planetary scale.
“Latency, cost, and scalability are hurdles to deploying AI-powered applications at scale,” the press release states. This collaboration aims to overcome these obstacles by integrating VAST Data’s platform into the Akamai Cloud, thereby lowering costs and enhancing the customer experience.
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One of the key advantages of this partnership is the ability to provide consistent and secure access to an organization’s data from the edge to the cloud through a single global namespace. This addresses a significant limitation of traditional cloud service providers, which often struggle to deliver inference at the scale and distribution required for global services. Akamai, with its highly distributed cloud, is uniquely positioned to offer AI inference at the edge, meeting the demands for local response times and localization.
Jeff Denworth, Co-Founder of VAST Data, emphasized the potential of this collaboration, stating, “With this agreement, Akamai and VAST Data will deliver next-generation AI infrastructure that combines hyperscale performance, security, and efficiency to meet the growing demands of enterprise AI workloads, closer to the digital touchpoint.”
Featured image credit: Akamai