Victoria Gayton
Latest from Victoria Gayton
Three insights you may have missed from theCUBE’s coverage of the Neo4j GraphTalk event
Graph intelligence is fast becoming the enterprise’s missing connective tissue — the knowledge layer that lets models move from clever prototypes to reliable, decision‑grade systems. By preserving relationships across fragmented data, it gives artificial intelligence the context needed to produce more accurate answers and support informed action. At the Neo4j GraphTalk event, the conversation wasn’t ...
Agentic AI infrastructure shifts enterprise focus from model choice to platform control
As agentic AI infrastructure moves from experimentation into production, enterprises are confronting a more complex question than which model to use: how to control the cost, data exposure and infrastructure supporting production AI applications. That shift is pushing organizations to rethink how much they should rely on public cloud AI services alone, especially as agentic ...
Real-time tax compliance puts agentic AI accuracy to the test
AI-powered tax compliance has to meet a standard that many artificial intelligence applications don’t: The answers must be exactly right. While large language models can generate unpredictable results, tax calculations require accuracy, speed and reliability across thousands of jurisdictions. That tension has shaped the way Avalara Inc. applies agentic AI to its transactional tax and compliance ...
Three insights you may have missed from theCUBE’s coverage of the AMD Advancing AI event
The momentum behind full-stack AI infrastructure reflects a broader shift in enterprise thinking. The value of AI now comes from integrated systems — not isolated accelerators — and from the ability to shape intelligence around how people actually work. That shift was a central theme at the AMD Advancing AI event, where discussions focused on how ...
Inside Cisco’s approach to edge AI: Tune in to theCUBE on July 29
Organizations are expanding their use of edge AI infrastructure as workloads move beyond traditional data centers, creating new demands on systems designed for an earlier era of computing. Cisco Systems Inc.’s Unified Edge platform, winner of the 2026 Tech Innovation CUBEd Award for the most innovative IoT or edge platform, was designed to address this ...
Three insights you may have missed from theCUBE’s coverage of RAISE Summit
Agentic inference is reshaping the center of gravity in artificial intelligence infrastructure. What began as a race to scale training has shifted into a phase defined by expanding context windows, memory‑augmented reasoning and the need to keep graphics processing units continuously fed with data. As enterprises push deeper into agentic systems, storage has moved into ...
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, ...