Despite intensifying concerns about declining DVD sales, boxoffice receipts and advertiser spending, traditional media executives attending Herbert Allen's exclusive Sun Valley summit this month didn't exactly flock to the so-called new media moguls, whose emerging venues could be critical in offsetting the industry's mounting economic risks. That uniform observation from elite executive conference attendees begs the question: "Why not?" When presented with the opportunity to aggressively explore viable new alternatives to their challenged business models, why didn't traditional media players respond as if their existence depends on it, as suggested by a recent flood of troubling statistics? "There was almost no interaction between traditional media companies and new media companies," one high-level Sun Valley conference attendee says. "Google was talking about video search and Intel talked about WiMax, and all the new media companies were talking about changing the existing business models. The traditional media companies sat there and listened to them with their heads in the sand, like it's business as usual," another conference attendee says. "It was really bizarre."
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...