Vapor IO, VAST Data to integrate inferencing capabilities at the edge for AI deployments
Vapor IO and VAST Data have announced a collaboration aimed at simplifying, accelerating, and optimizing AI deployments for enterprises. The collaboration merges Vapor IO’s Zero Gap AI with the VAST Data platform, creating an integrated edge-to-core AI fabric designed to address various business needs.
According to the company, the combined solution offers enterprises flexibility in tailoring systems to specific use cases, optimizing critical factors such as cost, latency, accuracy, and resiliency. By integrating data capture, training, and inferencing capabilities at the edge, the platform provides an optimal architecture for enterprise AI operations.
The hardware foundation for this offering is provided by Supermicro, supporting NVIDIA and VAST technologies as part of the Zero Gap AI services.
Cole Crawford, founder and CEO of Vapor IO, highlights the transformative impact of the collaboration, emphasizing the enhanced capabilities for deploying AI pipelines dynamically and efficiently.
“With VAST Data, we’re supercharging our Zero Gap AI platform, simplifying the deployment of AI pipelines and integrating the capabilities for these pipelines to asynchronously train, tune, inference, and retrain. This enhancement drives unprecedented value for our customers, making AI operations more dynamic and efficient than ever before,” adds Crawford.
The partnership enables customers to deploy AI from edge to core to cloud, allowing for centralized model training and real-time inferencing at the edge. This approach facilitates continuous improvement of models with new data while offering flexibility in data and AI deployment, both companies note.
John Mao, vice president of technical alliances at VAST Data, emphasizes the agility required to span various environments, including on-premises, near-premises, and multi-cloud setups.
“Vapor IO and VAST Data share a unified vision to deliver AI-as-a-Service capabilities that aren’t tied to specific deployment models or physical locations, making it easier to turn data into actionable intelligence,” adds Mao.
“The proliferation of data requires an agile system that can span on-premises, near-premises, cloud and multi-cloud environments. The combination of these two products makes an ideal solution for enterprises looking to rapidly and cost-effectively scale their use of AI.”
The collaboration aims to deliver AI-as-a-Service capabilities independent of deployment models or physical locations. As the technology rolls out across the U.S., plans for global expansion are also on the horizon, the companies note.
Read more:
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Vapor IO eyes $180 billion market with new ‘Monetize the AI Edge’ initiative
Article Topics
AI | Vapor IO | VAST Data | Zero Gap AI
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