Victoria Gayton

1 week ago | siliconangle.com | Victoria Gayton

Companies chasing innovation are often forced into compromise. Public cloud delivers speed and scale, but at the cost of visibility, control and sometimes even sovereignty. On-prem environments offer stability but struggle to keep pace with modern demands, especially as AI workloads and data complexity surge. Enter the private cloud — a middle path that promises both flexibility and governance, with infrastructure designed for control and scalability.

2 weeks ago | siliconangle.com | Victoria Gayton

Artificial intelligence is becoming more intuitive, interactive and embedded, not just in systems, but in the way companies build, think and create. From live coding and autonomous agents to unified governance and automation, Databricks Inc. is moving AI closer to the application layer and aligning it with developer intent. “You sort of tell the AI engineer, the software developer, an agent, what you want to do,” said George Gilbert, principal analyst for theCUBE Research.

2 weeks ago | siliconangle.com | Victoria Gayton

The modern application development lifecycle is getting a serious stress test. From Day 0 Design to Day 2 Operations, enterprises face increasing pressure to modernize software systems while accelerating delivery, embedding security and reducing tooling friction for developers. Doing it right, without shortcuts or silos, has become a defining challenge of the cloud-native era. The result is a wave of complexity hitting engineering teams across build, release and operations.

2 weeks ago | siliconangle.com | Victoria Gayton

Artificial intelligence isn’t just making headlines; it’s reshaping the foundations of the public sector. From operational efficiencies to significant economic impacts, the integration of AI into government infrastructures fundamentally alters both strategy and stakes. AI in public sector environments faces unique challenges around secure management of sensitive data. Innovation serves as a crucial counterbalance, emerging as a defining challenge.

2 weeks ago | siliconangle.com | Victoria Gayton

Generative AI is no longer just an experimental topic: It’s become a core focus of enterprise strategy. Behind the scenes, companies are moving beyond proofs of concept and into the more challenging work of scaling infrastructure, establishing governance and delivering measurable outcomes. As the excitement settles, the center of gravity is shifting from innovation theater to operational reality.