Emergence of quantum computing & Trending Artificial Intelligence Dominating Machine Learning Chip Market by 2025

The development of autonomous robots that can control themselves without human intervention is anticipated to provide potential growth opportunities for the market. However, dearth of skilled workforce and AI phobia are the major restraints of the market. Moreover, increase in demand for smart homes & cities, rise in efforts to make more human-like robots and popularity of IoT across the globe are expected to create tremendous opportunities for the market expansion.

According to a recent report published by Allied Market Research, the global machine learning chip market was valued at $2,425.6 million in 2017, and is projected to reach $37,849.8 million by 2025, registering a CAGR of 40.8% from 2018 to 2025.

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At present, North America dominates the market, followed by Europe. In 2017, the U.S. dominated the North America market, and the UK led the overall market in Europe. While, in Asia-Pacific, China currently dominates the market. The trend in artificial intelligence (AI), use of machine learning in numerous applications and emergence of quantum computing are the factors which increase the demand for machine learning chip market.

Key Benefits:
•This study comprises an analytical depiction of the global machine learning chip market with current trends and future estimations to depict the imminent investment pockets.
•The overall market potential is determined to understand the profitable trends to gain a strong foothold.
•The report presents information related to key drivers, restraints, and opportunities with a detailed impact analysis.
•Porter’s five forces analysis illustrates the potency of the buyers and suppliers in the industry.
•The report includes the market share of key vendors and machine learning chip market trends.

The current business scenario has witnessed an increase in the adoption of this technology, particularly in the developing regions. The companies have been adopting innovative techniques to provide customers with advanced and innovated product offerings.

The global machine learning chip market is segmented based on chip type, industry vertical, technology, and geography. Based on chip type, the market is categorized into GPU, ASIC, FPGA, CPU, and others. Based on technology, the market is divided into system-on-chip, system-in-package, multi-chip module, and others. Based on industry vertical, it is classified into media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and others.

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Machine learning chip can initiate smart city programs in the developing countries, such as India, China, and more. The tools and technologies already have an inbuilt machine learning chip that possess a huge potential to promote interconnected digital homes and smart cities. Furthermore, the creation of a chip with an embedded inbuilt AI network has emerged as an opportunity for the machine learning chip market.

The major companies profiled in the report include AMD (Advanced Micro Devices), Google Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx, Samsung.

About Allied Market Research
Allied Market Research, a market research and advisory company of Allied Analytics LLP, provides business insights and market research reports to large as well as small & medium enterprises. The company assists its clients to strategize business policies and achieve sustainable growth in their respective market domain.

Allied Market Research provides one stop solution from the beginning of data collection to investment advice. The analysts at Allied Market Research dig out factors that help clients to understand the significance and impact of market dynamics. The company amplies client’s insight on the factors, such as strategies, future estimations, growth or fall forecasting, opportunity analysis, and consumer surveys among others. As follows, the company offers consistent business intelligent support to aid the clients to turn into prominent business firm.

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This release was published on openPR.