Will mobile music significantly increase operator mobile data ARPS? In the hopes of replicating the success of online music download services, the mobile industry sees Full Track Downloads (FTDs) as a promising strategy to grow revenues by increasing mobile data usage and reducing churn. Ultimately, the success of mobile music will rest heavily on the value it presents to all its stakeholders. Pyramid Research's new report "Get on Track With Mobile Music: Exploring Mobile Music Best Practices" analyzes two successful mobile music business models - SK Telecom's 'MelOn' and KDDI's 'Chaku-Uta Full' - and provides strategic advice for operators to maximize the opportunity. By analyzing KDDI's and SK Telecom's success, this report charts the evolutionary path of mobile music services through an examination of business models, enabling technologies, stakeholders, and global developments. Full Track Downloads will be popular and - if managed correctly - profitable for 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...