Voice over wireless LANs (VoWLAN) is fast emerging as one of the most potentially significant converged technologies of the future, seamlessly combining WLANs with VoIP. Although it faces several challenges in its path to wide-scale adoption, consulting company Frost & Sullivan says developments such as the introduction of dual-mode handsets and the ratification of various 802.11 standards indicate a positive market outlook for the rest of this year. The company estimates that revenues for the European VoWLAN market will grow from �6.6 million in 2004 to �1.99 billion in 2010. The 14 mobile phone manufacturers and telcos that comprise the Unlicensed Mobile Access (UMA) group have taken the initiative to allow 802.11-equipped handsets to make calls through their Wi-Fi hotspots. This, says Frost & Sullivan, is a major driver for the VoWLAN market. "It is no surprise, therefore, that the momentum behind UMA is upbeat within the mobile domain, especially from the carriers that stand to gain tremendously from such an initiative," said Luke Thomas, Research Analyst with Frost & Sullivan. "Fixed-line carriers could also use the UMA to provide mobility solutions to their customers, provided they have a Mobile Virtual Network Operator agreement."
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...