An open network architecture for IPTV has its integration challenges, but prevents vendor lock-in, said Bill DeMuth, CTO of Surewest Communications, in a keynote address at the IPTV 20005 conference -- Surewest has been delivering Triple Play services since July 2002, and IP video since January 2004. The company�s fiber network passes about 70,000 homes and has over 16,000 FTTP subscribers. The active fiber network delivers 100 Mbps Ethernet to each home. Surewest also operates a copper network and has just started to deploy ADSL2+. The IPTV service provides the choice of 260 channels of content, over 75 premium channels, 25 international channels, Pay-per-View and VoD services. �At this point, the market drivers for deploying IPTV are clear,� said DeMuth. These include the desire to retain current customers and reduce churn, acquire new customers, create new revenue streams, and increase the take-rate for all services. Customer demand really exists. For telcos, there is a window of opportunity that is open right now. Surewest competes against SBC and Comcast. DeMuth highlighted several ongoing challenges for IPTV rollouts. For the copper plant, ADSL bandwidth limitations affects the number of set-top boxes deployed per home, and HDTV also presents bandwidth challenges.
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...