According to Red Herring and ChangeWave Research, "Voice Over Internet Protocol (VoIP) appears to be a popular alternative to traditional home telephone services. But just how quickly are consumers adopting this technology? And which companies are winning and losing share in the VoIP market? During the week of June 28 � July 5, 2005, we surveyed 1,901 ChangeWave Alliance members on their personal experience with VoIP technology and service providers. We note that the ChangeWave Alliance is primarily composed of early technology adopters. Bottom Line: The survey results show home VoIP use surging in both the local and long distance telephone markets. A total of 14 percent of respondents now report they use VoIP at home � double the amount in our September 2004 survey, while another 22 percent say they plan on using it at home within the next year. Importantly, VoIP is no longer considered a supplementary home phone service � half of current VoIP users now report they use it as their primary or only home telephone service. Another positive indicator was found among respondents who report they are likely to change their home long distance providers in the next six months. Within this group, three-in-ten (30 percent) say they plan to switch to Stand Alone VoIP � 9 points more than previously."
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...