According to the latest research from Strategy Analytics, global mobile phone shipments grew a striking 18 percent year-over-year, to 188 million units during Q2 2005 (April - June). Mega-vendors Nokia and Motorola outperformed in emerging markets, to grab an impressive, combined 50 percent share of total sales. Chris Ambrosio, Director of Strategy Analytics' Wireless Device Strategies service, noted, "Strong growth in emerging mobile phone markets, such as South America and Africa, is driving demand for increasing numbers of entry-level devices, precisely the mass-market segments where Nokia and Motorola are among the strongest." "The worldwide handset market is once again becoming concentrated in the hands of just a few major brands," said Neil Mawston, Associate Director of the Wireless Device Strategies (WDS) service at Strategy Analytics. "For example, Nokia and Motorola accounted for exactly half the global market in Q2 2005, leaving more than 60 other brands to fight for the remaining 50 percent." Following 361 million handsets sold globally in the first half of 2005, Strategy Analytics forecasts 775 million units for the full-year 2005.
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...