Open Source, AMD GPUs, and the Future of Edge Inference: Vultr’s Big AI Bet

In this episode of the Data Center Frontier Show, we sit down with Kevin Cochrane, Chief Marketing Officer of Vultr, to explore how the company is positioning itself at the forefront of AI-native cloud infrastructure, and why they’re all-in on AMD’s GPUs, open-source software, and a globally distributed strategy for the future of inference.

Cochrane begins by outlining the evolution of the GPU market, moving from a scarcity-driven, centralized training era to a new chapter focused on global inference workloads. With enterprises now seeking to embed AI across every application and workflow, Vultr is preparing for what Cochrane calls a “10-year rebuild cycle” of enterprise infrastructure—one that will layer GPUs alongside CPUs across every corner of the cloud.

Vultr’s recent partnership with AMD plays a critical role in that strategy. The company is deploying both the MI300X and MI325X GPUs across its 32 data center regions, offering customers optimized options for inference workloads. Cochrane explains the advantages of AMD’s chips, such as higher VRAM and power efficiency, which allow large models to run with fewer GPUs—boosting both performance and cost-effectiveness. These deployments are backed by Vultr’s close integration with Supermicro, which delivers the rack-scale servers needed to bring new GPU capacity online quickly and reliably.

Another key focus of the episode is ROCm (Radeon Open Compute), AMD’s open-source software ecosystem for AI and HPC workloads. Cochrane emphasizes that Vultr is not just deploying AMD hardware; it’s fully aligned with the open-source movement underpinning it. He highlights Vultr’s ongoing global ROCm hackathons and points to zero-day ROCm support on platforms like Hugging Face as proof of how open standards can catalyze rapid innovation and developer adoption.

“Open source and open standards always win in the long run,” Cochrane says. “The future of AI infrastructure depends on a global, community-driven ecosystem, just like the early days of cloud.”

The conversation wraps with a look at Vultr’s growth strategy following its $3.5 billion valuation and recent funding round. Cochrane envisions a world where inference workloads become ubiquitous and deeply embedded into everyday life—from transportation to customer service to enterprise operations. That, he says, will require a global fabric of low-latency, GPU-powered infrastructure.

“The world is going to become one giant inference engine,” Cochrane concludes. “And we’re building the foundation for that today.”

Tune in to hear how Vultr’s bold moves in open-source AI infrastructure and its partnership with AMD may shape the next decade of cloud computing, one GPU cluster at a time.