Victoria Gayton

Victoria is a field editor for theCUBE, SiliconANGLE Media's livestreaming studio. As a writer for IBM Global Services, she produced thought-leadership white papers on diverse topics, ranging from internet security to AI to cloud computing, for nearly two decades. Today, Victoria's enthusiasm for exploring and writing about emerging technologies continues unabated. In her spare time, she works with an animal rescue group, listens to podcasts that inspire her and prepares (easy) recipes that make her seem like a far better cook than she is.

Latest from Victoria Gayton

What to expect during Chainguard Assemble: Join theCUBE on March 19

AI By VICTORIA GAYTON6 MONTHS AGO

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 …

Four insights you may have missed from theCUBE’s coverage of MWC Barcelona

AI By VICTORIA GAYTON6 MONTHS AGO

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 …

What to expect at KubeCon + CloudNativeCon EU: Join theCUBE March 24–26

AI By VICTORIA GAYTON6 MONTHS AGO

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. …

What to expect during theCUBE’s coverage of Google Cloud at HIMSS26: Join us March 18

AI By VICTORIA GAYTON6 MONTHS AGO

After years of experimentation and pilot programs, AI in healthcare is entering a new, more demanding phase of operational scrutiny. Organizations now face pressure to embed artificial intelligence into clinical and operational workflows in ways that are secure, interoperable and measurable. Healthcare …

The platform that ate the pipeline: Vast Data’s rethink of AI infrastructure

AI By VICTORIA GAYTON7 MONTHS AGO

The enterprise data stack wasn’t designed for continuous, autonomous agentic AI. For years, the challenge was storing and organizing information. Now the challenge is delivering that data — consistently, globally and in real time — to systems that reason and act without …

What to expect during the AI Trust & Cyber Resiliency Summit: Join theCUBE October 15

AI By VICTORIA GAYTON7 MONTHS AGO

AI trust increasingly determines whether enterprise AI scales. As organizations move beyond pilots and into operational systems, the question is no longer whether models perform well in isolation, but whether the infrastructure beneath them can withstand cyber risk, data integrity failures and …

What to expect during Vast Forward: Join theCUBE Feb. 25

AI By VICTORIA GAYTON7 MONTHS AGO

The AI arms race has centered on compute: Who has the most graphics processing units, the fastest chips and the biggest clusters? But a different pressure point is emerging as enterprises move AI from pilot programs into continuous, production-grade operations. Vast Data …

Escaping the pilot trap: How composable AI data platforms move enterprise AI to production

AI By VICTORIA GAYTON7 MONTHS AGO

Enterprise artificial intelligence has a completion problem. Even with strong models, ambition and executive support, most initiatives fail when implemented in real operations. The persistent gap between a promising proof of concept and a production system that delivers repeatable business value has …

Dell’s approach to the data architecture problem standing between AI pilots and production

AI By VICTORIA GAYTON7 MONTHS AGO

Generative artificial intelligence is no longer an experiment tucked away in innovation labs. Enterprises now push toward production-scale systems that can reason, retrieve and act across vast data estates. The shift exposes the fact that existing data architectures must evolve to meet …

Enterprise AI adoption, demystified: What enterprises learned building with Google Cloud

CLOUD By VICTORIA GAYTON8 MONTHS AGO

Enterprise AI didn’t slow because the technology wasn’t ready. It slowed because people weren’t sure what to trust, what to learn or where to begin. Over the past year, conversations with Google Cloud leaders and industry experts revealed a consistent pattern: Enterprise …

Victoria Gayton

Latest from Victoria Gayton

What to expect during Chainguard Assemble: Join theCUBE on March 19

Four insights you may have missed from theCUBE’s coverage of MWC Barcelona

What to expect during the AI Trust & Cyber Resiliency Summit: Join theCUBE October 15

What to expect during Vast Forward: Join theCUBE Feb. 25

Dell’s approach to the data architecture problem standing between AI pilots and production

Enterprise AI adoption, demystified: What enterprises learned building with Google Cloud

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