Akamai and VAST Data collaborate on edge AI inference
Akamai Technologies and VAST Data have entered into an agreement to enhance the speed and efficiency of data-intensive AI inferencing.
The collaboration will combine Akamai’s massive distributed platform with the VAST Data Platform’s innovative approach to data-intensive computing to integrate data for large, distributed customers that need better local response time and localisation for distributed AI inference.
Latency, cost, and scalability present challenges to the large-scale deployment of AI-powered applications. Unlike training, which is resource-intensive and occurs in controlled environments, inference must operate continuously, on demand, and often with ultra-low latency. Adding VAST Data to the Akamai Cloud aims to reduce costs and enhance customer experience to help democratise edge AI computing.
While many cloud service providers support large-scale centralised AI training, they do not operate inference at the scale and distribution for planetary-scale service. As the world’s most distributed cloud, Akamai is uniquely positioned to deliver AI inference at the edge, helping enterprises meet local response time and localisation requirements. With VAST, Akamai Cloud users can benefit from consistency and fast, secure access to all of their organisation’s data, from edge to cloud, via a single global namespace.
“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,” said Jeff Denworth, Co-Founder of VAST Data. “Together, we are providing organisations with an AI-ready data platform that ensures seamless scalability, intelligent automation, and enterprise-grade security for the most demanding AI and inference applications.”
Built from the ground up for end-to-end AI pipelines, the VAST Data Platform is a breakthrough approach to data-intensive computing that serves as the comprehensive software infrastructure required to capture, catalogue, refine, enrich, and preserve data through real-time deep data analysis and deep learning. This system is designed to provide seamless and universal data access and computing from edge to cloud. The platform features an innovative parallel architecture to solve the challenges of scale, simplicity, resilience and efficiency.
The platform adopts a new approach to integrating unstructured data with structured data with declarative functions and can store, process, and distribute data as a global data-defined computing platform. It also embraces a first-principles perspective to simplify the data experience by introducing several new architectural conventions that challenge long-standing trade-offs in data-intensive computing.
www.akamai.com
www.vastdata.com
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