The cable industry long ago widened its ambitions beyond video, addicting millions of customers to cable modems and more recently adding voice over internet protocol telephony to its menu. Insiders call this video-voice-data combo the "triple play" strategy. So with a trifecta of moneymaking schemes on its plate, the cable guys must be pretty satisfied, right? Uh, no. "We're all still waiting for that aha moment in which we have a portable device that came from the cable company," said Dale Fox, vice president of digital phone at Time Warner Cable. That's right. The cable industry wants you to chuck your cable -- at least when you're outside the house. The addition of a fourth wireless component to the cable package is now affectionately known as the "quadruple play." At the annual meeting of CTAM, the cable industry's top sales and marketing folks gathered in Philly this week to figure out new ways to get at your wallet. And while the conference focused on many topics, including better customer service, VOIP, video on demand and improving cable-modem speeds, the big buzz was about mobility. After all, customers now want to take their entertainment and communications with them everywhere they go. The last thing cable operators want is to be left out of that party.
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...