United States Industrial IoT (IIoT) Chipsets Market Research Report 2017 to 2022 presents an in-depth assessment of the Industrial IoT (IIoT) Chipsets Market including enabling key trends, market drivers, challenges, standardization, regulatory landscape, deployment models, operator case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents forecasts for Industrial IoT (IIoT) Chipsets Market investments from 2017 till 2022.
Following reports from earlier this month, today Xiaomi confirmed on Weibo that it will be announcing its very own mobile chipset, named after its subsidiary "Pinecone," in Beijing on February 28th. Little else is mentioned, but rumors going as far back as October are pointing to a Mi 5c aka "Meri" as the first device to carry this chip. Multiple Geekbench results suggest that the phone features an octa-core processor, 3GB of RAM and runs on Android 7.1.1 According to Chinese semiconductor expert Laoyao, Pinecone Electronics is a joint venture set up by Xiaomi and chipset maker Leadcore back in November 2014, with Xiaomi owning 51 percent of the shares. In other words, this project has been under way for over two years.
During the last two years, several cloud service providers, including Alibaba, Amazon, Facebook, Google, Huawei, and Tencent, have been busy designing their own in-house chipsets for handling Artificial Intelligence (AI) workloads in their data centers. ABI Research, a global tech market advisory firm, estimates that cloud service providers commanded 3.3% market share of the total AI Cloud chip shipments in the first half of 2019. These players will increasingly rely on their own in-house AI chips and will be producing a total of 300,000 cloud AI chips by 2024, representing 18% of the global cloud AI chipsets shipped in 2024. The increasing requirements for intelligent services by many enterprise verticals are pushing cloud service providers to rapidly upgrade their data centers with AI capabilities, which has already created an enormous demand for cloud AI chipsets in recent years. ABI Research expects revenues from these chipset shipments to increase significantly in the next five years, from US$4.2 billion in 2019 to US$10 billion in 2024.
Artificial intelligence (AI) technology is progressing at a rapid pace, as is the application of the technology to solve real-world problems. While the market for chipsets to address deep learning training and inference workloads is still a new one, the landscape is changing quickly – in the past year, more than 60 companies of all sizes have announced some sort of deep learning chipset or intellectual property (IP) design. A new report from Tractica finds that virtually every prominent name in the technology industry has acknowledged the need for hardware acceleration of AI algorithms and the semiconductor industry has responded by offering a wide variety of solutions. Tractica forecasts that the market for deep learning chipsets will increase from $1.6 billion in 2017 to $66.3 billion by 2025. System-on-a-chip (SoC) accelerators such as those found in mobile devices will lead the market in terms of sheer volumes by the end of the forecast period, followed by application-specific integrated circuits (ASICs) and graphics processing units (GPUs).