Conventional wisdom says that until the advent of 802.16e mobile WiMAX systems -- still some time in the future -- the wireless broadband standard will be more or less confined to the great outdoors. Some "near-outdoor" systems involving window-mounted receivers may be feasible, but for practical purposes WiMAX is considered an outdoor last-mile replacement technology. However, ABI Research analysts say that there are optional specifications built into the 802.16 standard which can boost the sensitivity of receiving equipment to the extent of making WiMAX PC cards and built-in receivers a practical proposition for laptops, PDAs and other portable devices. Generally these optional specifications have not been implemented by the largest vendors of WiMAX equipment. According to senior analyst Philip Solis, what this means is that "There may be WiMAX PC cards on the market earlier than many observers have expected. These will result from superior chipsets permitting the use of WiMAX in laptops and similar devices in homes and offices within the reach of fixed WiMAX transmissions. You will not have full mobility as you will with 802.16e, but you will have some portability."
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...