Data typically forms 6-10 percent of US mobile operators� total revenues. Total messaging traffic is up 59 percent over the last 12 months -- The value of the US mobile data market increased by around 80 percent during the year to March 2005, according to Informa Telecoms & Media�s World Cellular Data Metrics, as interoperability agreements finally helped SMS make a significant impact on the market, which has traditionally lagged behind Europe and Asia. Total revenues from non-voice services for the four largest US mobile operators totaled more than $1.2 billion in Q1 2005, compared to $689 million in the same period of 2004. GSM operator T-Mobile was particularly noteworthy; its subscribers sent a total of 3.6 billion messages during Q1 2005, equivalent to around 67 per subscription per month, more than double the volume 12 Months ago. The operator�s recent launch of bundled SMS packages, including one offering unlimited messages for $15 per month, is sure to drive traffic still higher. As well as interoperability, continued subscriber education and growth in popularity of interactive TV programmes have boosted SMS traffic levels in the USA.
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...