According to TDG, it was only a few years ago that XM and Sirius were the buzz of the music industry - a new business model capable of challenging the establishment, offering listeners advertising-free content in exchange for a small monthly fee. While the early buzz was impressive, most analysts predicted that satellite radio would never be able to compete with established radio stations and, as such, be lucky to last a few years. Well, XM and Sirius have succeeded in proving the pundits wrong. As of Q2 2005, XM had close to four million subscribers and is predicting 20 million by 2010. In the same period, Sirius reported 1.5 million subscribers and has raised year-end 2005 estimates to 2.7 million, 200,000 more than prior guidance. By year-end 2005, the two companies combined will have almost eight million subscribers, each of which pays around $13 per month to receive music content free of advertising and packaged according to their tastes. While such progress is noteworthy, it only scratches the surface of what these companies are really up to. Although not widely discussed, both XM and Sirius have their eyes set on much larger prizes - in particular, providing a range of media services including music, video, and even data services to both mobile and fixed subscribers. Yes, they intend to compete head-to-head with existing satellite TV and data service providers.
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...