According to Informa Telecoms & Media, the number of mobile subscriptions worldwide will reach 2.14 billion by the end of 2005, having already surpassed the 1.8 billion mark. Building on record growth of 354 million in 2004, net additions are again expected to exceed 350 million in 2005. Rapid growth in key developing markets will not be offset by a decline in mature markets to the extent previously expected. Reductions in access fees in expanding markets such as Nigeria and Mexico have had an impact on short-term growth. The Russian mobile market grew by 89 percent in 2004 on the back of four previous years of annual growth in excess of 100 percent, and Russia alone is forecast to account for 43 percent of net additions in Central and Eastern Europe in 2005-2010. The Chinese mobile market, which exceeded the 400-million-subscription mark in March 2005, is forecast to grow by 65 percent by the end of 2010. Indonesia is forecast to exceed 50 million subscriptions in 2007. According to Informa the global penetration rate is just 28 percent, meaning that there are still more than four billion potential new mobile users worldwide.
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...