Titles for new handheld game systems from Sony and Nintendo helped drive video game industry sales up 21 percent to $4.1 billion in the first half of 2005, compared with $3.4 billion during the same period last year, according to a report from market research firm NPD Group. Losing ground were game consoles, which saw a 6 percent sales decline, from $631.6 million last year to $594 million in the first half of this year, and PC games, whose sales revenues were down 10.5 percent, to $405.4 million. Overall, however, video game sales for consoles, handhelds and the PC were up 9.2 percent to $2.8 billion; the top-selling title for the period was Sony's "Gran Turismo 4." Driving game sales were titles for Sony's PSP and Nintendo's DS and Game Boy handhelds, which were up 81 percent in the first half of 2005; handheld hardware sales also grew 74 percent. "The robust performance of the portable market certainly contributed to the considerable sales growth of the industry but another significant contributor to industry performance is software," said NPD analyst Anita Frazier.
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...