Victoria Gayton
Latest from Victoria Gayton
Three insights you may have missed from theCUBE’s coverage of the ‘Scaling the Agentic Era’ event
As artificial intelligence agents move from proof-of-concept tools to production systems, the cost of every generated token is becoming a direct business concern. The shift is pushing infrastructure providers to focus not just on raw performance, but on efficiency, throughput and the economics of running agentic workloads continuously at scale. That pressure is reshaping how ...
What to expect at the AMD Advancing AI event: Join theCUBE July 22-23
Enterprise artificial intelligence infrastructure has become as critical to AI success as the models themselves. As organizations move AI into production, attention is increasingly shifting toward the infrastructure, software and ecosystems required to support deployment at scale. Those themes are reflected across Advanced Micro Devices Inc.’s recent announcements and executive discussions ahead of its Advancing ...
Three insights you may have missed from theCUBE’s coverage of Pure Accelerate
As enterprises advance their artificial intelligence initiatives, they’re discovering that the real constraint isn’t model sophistication — It’s data. AI outcomes now depend on whether organizations can access, mobilize and operationalize data as an active system rather than a passive repository. This shift was a defining theme at Pure Accelerate 2026. The challenge is not simply ...
Three insights you may have missed from theCUBE’s coverage of FinOps X
AI costs are becoming one of the most difficult aspects of enterprise AI adoption. Unlike traditional cloud or software-as-a-service spend, AI costs are shaped by dynamic usage patterns, model behavior and external interactions, making it harder to keep investments aligned with business value. As enterprise AI adoption grows, organizations are reevaluating traditional cost governance models, ...
Three insights you may have missed from theCUBE’s coverage of Snowflake Summit
If the first wave of enterprise artificial intelligence was about compute and foundation models, the next is shaping up to be about the software and data infrastructure needed to make those models useful in real businesses. The first AI winners sold compute: graphics processing units, servers, networks and cloud capacity — the “picks and shovels” ...
What to expect during Nutanix .NEXT: Join theCUBE April 7-8
Artificial intelligence workloads are scaling rapidly across enterprise environments, putting infrastructure under increasing pressure to keep pace. As organizations push further into production, enterprise AI infrastructure is emerging as a key layer for managing how applications, data and compute come together to support those demands. The shift is prompting enterprises to reassess how workloads are ...
The new control plane: How the cloud-native ecosystem is shaping production AI
The era of artificial intelligence experimentation is giving way to the realities of production infrastructure. As enterprises move past early large language model deployments, the conversation in the cloud-native ecosystem is shifting from what these models can do to how they can run securely, affordably and at scale. This shift to production-grade AI is exposing ...
What to expect during Chainguard Assemble: Join theCUBE on March 19
As enterprises accelerate development across cloud-native and AI-driven environments, software supply chain risk has moved from a background concern to a boardroom priority. The pressure to ship faster hasn’t disappeared, but the tolerance for hidden vulnerabilities inside open-source components and container images has shifted. What once felt like a security team problem now shapes architecture ...
Four insights you may have missed from theCUBE’s coverage of MWC Barcelona
Modern artificial intelligence’s requirements highlight a significant gap between the locations where intelligence must be applied and the places where existing infrastructure was originally designed to support it. As inference workloads multiply and agentic systems require tighter real-time controls, edge AI is emerging not as a niche application but as a foundational architectural shift — ...
What to expect at KubeCon + CloudNativeCon EU: Join theCUBE March 24–26
The enterprise AI story of 2026 isn’t about who’s experimenting anymore. Across cloud-native AI environments, the infrastructure question has shifted from whether AI can run on Kubernetes to whether it can run repeatably and at scale, with proof of measurable business value. That shift is rewriting competitive priorities, and the cloud-native stack is where the ...