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."
The global semiconductor industry is experiencing a historic acceleration driven by surging investment in artificial intelligence (AI) infrastructure and computing power. According to the latest IDC worldwide market study, 2025 marks a defining year in which AI's pervasive impact reconfigures industry economics and propels record growth across the compute segment of the semiconductor market. Semiconductor Market Development IDC’s latest data reveals an insightful projection: The compute segment of the semiconductor market is on track to grow 36 percent in 2025, reaching $349 billion. This segment, which encompasses logic chips powering CPUs, GPUs, and AI accelerators, will sustain a robust 12 percent compound annual growth rate (CAGR) through 2030. These numbers underscore not only current momentum but a structural shift driven by large-scale adoption of AI workloads spanning cloud, edge, and on-premises deployment models. The scale of investment is unprecedented. As organizations ...