Viacom's Nickelodeon children's cable TV network announced the launch of TurboNick, a broadband video service on Nick.com that will offer full-length episodes of TV shows. The free, ad-supported service will offer shows like "SpongeBob SquarePants," "The Fairly OddParents," "Zoey 101," "Ren & Stimpy" and "Double Dare" -- in addition to video-on-demand shows for parents and shorter clips for younger children. TurboNick has already garnered over 1.25 million streams since a soft launch on July 1, and is scheduled to officially launch on July 17. TurboNick features up to 20 hours of new programming every week, allowing kids to watch programming clips and full length episodes ranging from 30 seconds to 22 minutes in length, including occasional world premieres of new series beginning with the animated program Catscratch. TurboNick is organized by six separate areas, each containing up to five different series with two or more episodes to choose form. According to Viacom's spokesperson "The TurboNick platform compliments our on-air programming by giving kids and parents Nickelodeon video content any time they want it. Whether it's all-new long-form programming, exclusive video, classic shows or current programming favorites, we will be able to utilize TurboNick as a vehicle to deliver what kids want, when they want it, using up-to-the minute technology."
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...