A Flood of Low-Spending Users Dilute Profit Margins -- "The latest quarterly Strategy Analytics wireless operator benchmarking study indicates potentially serious global operator profit slides, as global margins fell below 40 percent for the first time in eight quarters. While subscriber volumes rose by 24 percent, year on year EBITDA was up by less than 4 percent, resulting in a 15 percent decline in average margins per user (AMPU). Globally, AMPU among the operators fell by 15 percent over the previous year, to a low of $11.54 in Q4 2004, from 2003's $15-plus figure. The heaviest declines were in Central & Eastern Europe and Asia-Pacific, both regions where exceptionally high subscriber growth among lower-value customers has outstripped profitability. Even more mature markets have not been immune to AMPU declines, with 3 percent declines in North America and Western Europe as competitive pressures and, in the case of Europe, regulatory interconnect rate cuts, left their mark."
Enterprise AI adoption keeps running into the same wall: the moment sensitive data, model weights, or agent memory leave a tightly controlled environment, security teams lose visibility into what happens to them while the workload is actually running. Confidential computing exists to close that gap, and new research from ABI Research shows the technology has matured enough, across CPUs, GPUs, containers, and now agentic AI, to become a foundational requirement for enterprises building sovereign AI infrastructure: computing environments they control end to end rather than simply rent. Protection is Moving From CPUs to GPUs ABI Research finds that CPU-based confidential computing is closest to mass-market adoption, the product of years spent hardening chip-level isolation for general workloads. GPU-based confidential computing is now generating the strongest momentum, and for good reason. It addresses one of the largest unresolved gaps in AI security: protecting data and models while inf...