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).
The global artificial intelligence chipset market size is expected to reach USD 59.2 billion by 2025, according to a new report by Grand View Research, Inc. The artificial intelligence (AI) chipset market is anticipated to expand at a CAGR of 33.6% from 2019 to 2025. An Artificial Intelligence chipset is built on the concept of adding a dedicated component in an electronic device, to execute Machine Learning tasks. In addition, an increased amount of data has led to the need for high-speed processors and faster computing, which is addressed by incorporating Artificial Intelligence into the set of electronic components. For instance, Apple has implemented a neural engine in its A11 Bionic chip's GPU to speed-up the third-party applications.
The points that are discussed within the report are the major market players that are involved in the Deep Learning Chipset market such as manufacturers, raw material suppliers, equipment suppliers, end users, traders, distributors and etc.The growth factors of the market is discussed in detail wherein the different end users of the market are explained in detail.Data and information by manufacturer, by region, by type, by application is given and custom research can be added according to specific requirements. The Research projects that the Deep Learning Chipset market size will grow from in 2017 to by 2023, at an estimated CAGR of XX%. The base year considered for the study is 2017, and the market size is projected from 2018 to 2023.Akin to Artificial Intelligence (AI), the concept and possibilities of deep learning are being contemplated and harnessed for several decades. But, in the recent times, the technology pertaining to algorithmic chips has improved considerably, promising to revolutionize major applications such as data centers to the simplest of microcontrollers. "This report can be customized to meet the desired requirements. Please connect with our Team, who will ensure that you get a report that Fulfils your requirements."
Definition: The A-List in AI Chipset Index includes companies providing software and hardware components of AI chipsets. AI chipset products include central processing unit (CPU), graphic processing unit (GPU), neural network processor (NNP), application specific integrated circuit (ASIC), field programmable gate array (FPGA), reduced instruction set computer (RISC) processor, accelerators and more. Some of the chipsets are directed at edge processing or devices, some are for servers used in cloud computing and others are directed at machine vision and autonomous vehicle platforms. Some of the products are computational framework for AI and others are for AI training platforms. The edge and server chipsets are optimized for high performance and ultra-low power running sub one trillion operations per seconds (TOPs) to 30 TOPs.
The opportunity for AI accelerator chips is much-hyped, but how big is the market, and which companies are actually selling chips today? EETimes spoke to the reports' author, Principal Analyst Lian Jye Su, to gain some insight into which companies and technologies are making inroads into this potentially lucrative market. AI in the Cloud The first report, "Cloud AI Chipsets: Market Landscape and Vendor Positioning," highlights how cloud AI inference and training services are growing rapidly. The resulting AI chipset market is expected to grow from US$4.2 billion in 2019 to US$10 billion in 2024. Nvidia and Intel, the current leaders in this space, are being challenged by companies including Cambricon Technologies, Graphcore, Habana Labs and Qualcomm.