According to the new research report published by The Insight Partners, titled “Artificial Intelligence Chip Market to 2027 – Global Analysis and Forecasts by Segment (Data Center, Edge); Type (CPU, GPU, ASIC, FPGA, and Others); and Industry Vertical (BFSI, Retail, IT & Telecom, Automotive & Transportation, Healthcare, Media & Entertainment, and Others) and Geography– Global Analysis and Forecast”, the Artificial Intelligence Chip market is estimated to reach US$ 83,252.7 Mn by 2027 from US$ 5,658.1 Mn in 2018. The report includes key understanding on the driving factors of this market and also highlights the prominent players in the market and their developments.
The global market for artificial intelligence chips is anticipated to exhibit very high growth in the near future. Some of the major driving factors contributing to the market growth include increasing investments in AI chip start-ups, and the availability of a massive amount of data due to the proliferation of digital services across the globe. Real-time consumer behavior insights increased operational efficiency, and improved sales revenue are some of the factors responsible for the rising adoption of AI chips across major industry verticals. Also, growing spending on enhanced IT security is expected to drive the growth of AI Chip market.
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However, there are a few factors that are expected to restrain the market growth such as data privacy & security concerns and lack of infrastructure and technology know-how in third world countries. During the forecast period, the rising adoption of cloud-based computing across industries and the adoption of artificial intelligence chips in edge devices will present significant opportunities for market players operating in the AI chip market.
Availability of massive amounts of data, demand for superior customer service, efficient operations, and better sales revenue are some of the key factors driving the growth of the Artificial intelligence market. With the advancement in computing and storage technology, computing power has increased multi-fold during the last decade. This computing power has created new opportunities for managing and computing the big sets of data, and when coupled with artificial intelligence technology, it can deliver useful insights to businesses. Major artificial intelligence applications for which AI chips are being used include Machine Learning (ML), Natural Language Processing (NLP), Expert Systems, Automated Speech Recognition, AI Planning, and Computer Vision. Machine Learning is a branch of artificial intelligence that enables machines to develop the ability to self-learning and adaption through experience without being explicitly programmed. It is a method of data analysis that automates analytical model building. Machine Learning is one of the most used cases of application of artificial intelligence chips.
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Increasing Investments in AI Chip Start-Ups will Fuel the Market during the forecast period
Artificial intelligence and its applications such as machine learning and deep learning have been growing tremendously over the last few years. AI is being utilized extensively in numerous areas ranging from cloud computing applications to digital assistants and self-driving/autonomous vehicles. With ever-increasing use cases of AI and the evolving market landscape, the advancements in present chips have become a necessity. AI is majorly used in the data center training market where NVIDIA is a market leader. However, the demand for application-specific custom AI chips and inference on edge and data center are the fast-growing segments in the AI chip market, and many new startups are coming up to tap this market
Artificial Intelligence Chip Market Type Insights
Based on type, the artificial intelligence chip market is bifurcated into CPU, ASIC, GPU, FPGA, and others. The GPU type segment accounted for the largest share in the global market share in 2018. Presently in artificial intelligence applications, Graphics Processing Units or GPUs are the most widely used hardware. The high parallelism and memory bandwidth of GPUs make them the most viable option for machine and deep learning applications, especially in training. GPUs were initially used to accelerate a large number of multiplying and adding calculations executed in graphics rendering. With the increase in demand for high-performance graphics, the demand for powerful GPUs also grew.
Artificial Intelligence Chip Market: Competitive Landscape and Key Developments
Advanced Micro Devices, Inc., Alphabet Inc. (Google), Huawei Technologies Co., Ltd., IBM Corporation, Intel Corporation, Micron Technology, Inc., NVIDIA Corporation, Qualcomm Incorporated, Samsung Electronics Co., Ltd, and Xilinx, Inc are among the key players in the global Artificial Intelligence Chip market. The leading companies focus on the expansion and diversification of their market presence, and acquisition of new customer base, thereby tapping prevailing business opportunities.
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In March 2019, AMD entered into a partnership with ScaleMP to enable AMD server OEMs to create systems with 4, 8, and up to 128 processor sockets, up to 8,192 CPUs, and 256 terabytes of shared memory.
In July 2018, Google unveiled tiny new AI chips, Edge TPU, for on-device machine learning. Edge TPU is Google’s purpose-built application-specific integrated circuit (ASIC) designed to run AI at the edge. It delivers high performance in a small physical and power footprint, enabling the deployment of high-accuracy AI at the edge.
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