As telecom operators push hard to roll out Internet Protocol (IP) television services worldwide, they face major roadblocks in the shape of licensing and franchising issues, according to new studies from ABI Research. On one side, content providers worry about the security of IP networks, which are certainly not immune to hacking. These concerns affect the license arrangements they must reach with telcos wishing to distribute their intellectual property. From another quarter, cable operators -- justifiably fearing Telco IPTV encroachment on their traditional turf -- are lobbying governments fiercely to ensure that the telcos pay the same sort of franchise fees and go through the same degree of legal bureaucracy that they do. According to ABI principal analyst, Michael Arden, "In the US, this means thousands and thousands of individual contracts. Overseas, with lower cable penetration and less stringent government regulations, it is often a smaller problem." A partial solution -- at least for those telcos that can access fiber-to-the-home networks -- is "RF overlay", in which the TV signals are sent down the fiber network in a format equivalent to that used by cable services themselves. RF overlay is "a next-best solution to get content to the market quickly."
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...