KPMG Technology Lead Phil Wong stated that as enterprises move toward Agentic AI, inference workloads will drive demand for high-speed, low-latency connections and change traffic patterns between cloud and AI infrastructure. Power shortages are becoming the biggest bottleneck for AI infrastructure expansion, and new data center locations are creating urgent demand for fiber routing and edge networks.
In June 2026, AI governance moves from theory to operationalization: the three control planes of model access, infrastructure capacity, and network governance converge, redefining the security, cost, and strategic layout of enterprise IT architecture.
OpenAI and Broadcom jointly launched the first self-developed AI inference chip, Jalapeño, marking the extension of AI infrastructure competition from the model layer to the chip layer. This article analyzes the chip's technical features, industry impact, and implications for cloud providers and enterprises.
In enterprise AI deployment, low GPU utilization is often attributed to insufficient computing power, but the actual bottleneck lies in the efficiency of data transfer from storage to compute. This article analyzes the impact of data transfer architecture on AI performance, cost, and reliability, and explores how loosely coupled architectures and intelligent control layers can address this challenge.
Unity Software reported its fourth-quarter financial results, with revenue increasing 35% year-over-year to $609 million, exceeding market expectations. Analysts pointed out that the growth in demand for AI-driven game development tools and cloud services was the main driving force.
As AI chip density continues to rise, data centers are shifting from traditional "compute capacity expansion" to "power architecture reconstruction." Driven by the rapid increase in GPU rack power, the adoption of liquid cooling, simplified power distribution links, and 800V DC power supply, the design logic of enterprise IT infrastructure is being redefined.