Digital video recorders will be in 47 percent of U.S. homes by 2010, growing their installed base from 7 million households at the end of 2004 to 55 million in five years, according to a report from New York-based JupiterResearch. "While TV networks and their advertisers may get increasingly anxious about DVRs, some constituencies have another perspective. Pay TV operators will see the DVR playing an increasingly strategic role over the next two to three years," said JupiterResearch analyst Todd Chanko. Jupiter also predicts that HDTV monitors will grow from an installed based of 13 million in 2004, to 74 million by 2010. While less than 4 million of current HDTV households were subscribed to an HDTV service at the end of 2004, that number is expected to grow to 69 million by 2010. "Television networks and pay-TV operators alike are unsure of consumer demand for HDTV," said Chanko. "Behind closed doors the executives are still measuring the real costs to produce and distribute HDTV against the benefits. That's why there are only 26 hours of HDTV programming a day across seven broadcast networks."
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...