AI Infrastructure Leaders Debated Standards in San Jose
The Open Compute Project Global Summit convened industry players to discuss bridging centralized and distributed computing.
Updated on Oct. 14, 2026 in Artificial Intelligence
At the Open Compute Project Global Summit in San Jose, leaders from BluSky AI, CoreWeave, Real Time Labs, and VDURA met to discuss infrastructure interoperability. The sold-out summit focused on aligning reference architectures for varied AI computing environments.
Why it matters
As AI workloads increasingly span both centralized data centers and distributed edge deployments, establishing unified infrastructure standards is essential for seamless compute integration. This collaborative framework aims to reduce complexity in scaling large-scale AI operations.
The session targeted a scale of 9,000 participants to address standardization across disparate compute environments. The current focus remains on defining frameworks that connect centralized and distributed hardware layers.
The players
BluSky AI
A Salt Lake City-based artificial intelligence firm focused on scaling AI infrastructure.
Andi Huels
The Chief AI Officer at BluSky AI who led discussions on computing interoperability.
Open Compute Project
An industry organization dedicated to developing open-source hardware and data center infrastructure standards.
The details
The panel focused on infrastructure standards and interoperability, exploring how to create reference architectures that allow hardware and software to function across hybrid compute models. By establishing these frameworks, firms aim to simplify the deployment of AI stacks, which currently require bespoke integration across centralized clusters and distributed edge nodes.
Timeline
October 12-15, 2026: The Open Compute Project Global Summit occurred in San Jose.
October 14, 2026: BluSky AI Chief AI Officer Andi Huels participated as a session speaker.
The Tech Race
This session contributes to the ongoing evolution of the Open Compute Project reference architecture program. It signifies a shift toward creating industry-wide interoperability standards to compete with vertically integrated, proprietary computing stacks.
For industry engineers and developers, these standards promise a future with simplified hardware integration and more consistent performance across hybrid AI setups. While currently in the discussion phase, successful adoption would eventually lower the technical barrier for deploying scalable AI models.
The takeaway
The industry is prioritizing interoperability to manage the complexity of modern, distributed AI workloads. Watch for published reference architectures from this summit to see which hardware standards gain broad vendor adoption in the coming year.
Further reading
Learn more about the latest developments in large-scale system design within our Artificial Intelligence section.
