Strategy Analytics released its report, "Worldwide Cellular User Forecast 2005-2010," forecasting that the worldwide cellular user base will increase from 1.7 billion at the end of 2005 to 2.5 billion by the end of 2010, a 38 percent penetration rate. With average revenues falling 7 percent to $30 per user per month in 2005, Strategy Analytics expects further weakness in global ARPUs as increasingly prepaid-centric and low-ARPU China, India and other emerging markets remain the engine for user growth. Phil Kendall, report author and director of wireless operator research at Strategy Analytics, commented, "Voice usage will increase from 5.6 trillion minutes in 2005 to 12.6 trillion in 2010. GSM-based systems will continue to dominate the cellular landscape, accounting for 81 percent of subscribers and 76 percent of service revenues in 2010, though CDMA's more rapid evolution to 3G will see it dominate 3G subscriber volumes in the medium term." David Kerr, Vice President of the Global Wireless Practice, added, "3G subscribers will pass 50 million at the end of 2005. More importantly, European 3G markets are now outpacing Japan. The outlook for 3G is healthy provided that operators and their handset partners can expand beyond postpaid only users into the larger, but more price elastic, prepaid user segments.
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...