The number of U.S. wireless subscribers with compatible handsets who played games on their cell phones increased from 20 percent last year to 27 percent in 2005, according to a survey of 8,500 subscribers conducted by market research firm NPD Group. However, only one-third of these mobile gamers actually purchased game downloads; the rest played free games or titles that came pre-loaded on their phones. The most common motivation cited among respondents for playing mobile games was "to kill time or alleviate boredom," with the average gaming session lasting 11 minutes. The survey found more kids between the ages of 13 and 17 (60 percent) said they played mobile games than did adults (23 percent), while mobile gamers were twice as likely to be African-American, Hispanic or Asian. "The world of mobile gaming is like the Wild West," said NPD Group vice president Clint Wheelock. "In this time of rapid growth, and with the industry in such a formative stage, it's especially important for wireless operators and game publishers to understand the mindsets of mobile gamers, in order to best position themselves for long-term success."
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...