Machine Learning Chip Market To Hit US$ 33.02 Bn, Globally, by 2027 at 31.20% CAGR

The global machine learning chip market reached a value of US$ 5.86 Billion in 2021 and is expected to reach a value of US$ 33.02 Billion by 2027 exhibiting a CAGR of 31.20% during 2022-2027.


George Poter

a year ago | 3 min read

According to the latest report by IMARC Group, "Global Machine Learning Chip Market Size, Share, Growth, Industry Trends, Opportunity and Forecast 2022-2027", the global machine learning chip market reached a value of US$ 5.86 Billion in 2021. Looking forward, IMARC Group expects the market to reach a value of US$ 33.02 Billion by 2027 exhibiting a CAGR of 31.20% during 2022-2027.

Machine learning (ML) represents a part of artificial intelligence (AI) that operates on experiential learning instead of programming for making decisions. ML chips are installed to improve intellectual property cores as well as design and tool flows. In addition to this, they assist in automating the tuning and routing of devices to enhance the power, performance, and area (PPA) results via ML, analytics, and optimization. The hardware infrastructure of these chips generally consists of three components, networking, storage, computing, etc. Some of the common ML chips include application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), graphics processing units (GPUs), etc. They are utilized for error prevention and cost-saving purposes across various industries, such as automotive, media and advertising, manufacturing, transportation, finance, etc.

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Machine Learning Chip Market Trends and Drivers:

The widespread adoption of AI in numerous industry verticals and the introduction of quantum computing are primarily driving the machine learning chip market. Additionally, the expanding gaming industry has led to a shift from central processing units (CPUs) towards graphics processing units (GPUs) for simultaneously performing several complex tasks, which is further catalyzing the market growth.

Besides this, the inflating popularity of smart infrastructures in corporate organizations is acting as another significant growth-inducing factor. Moreover, the growing number of machine learning (ML) applications is also positively influencing the global market. Apart from this, the development of human-like robots to reduce human intervention and errors are anticipated to fuel the machine learning chip market over the forecasted period.

Global Machine Learning Chip Market 2022-2027 Analysis and Segmentation:

Competitive Landscape:

The competitive landscape of the market has been studied in the report with the detailed profiles of the key players operating in the market.

Some of these top key players include:

· Advanced Micro Devices Inc.

· Amazon Web Services Inc. ( Spend less. Smile more. Inc.)

· Cerebras Inc.

· Google LLC

· Graphcore

· Intel Corporation

· International Business Machines Corporation

· NVIDIA Corporation

· Qualcomm Incorporated

· Samsung Electronics Co. Ltd.

· Taiwan Semiconductor Manufacturing Company Limited

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The report has segmented the market on the basis of region, technology, chip type and industry vertical.

Breakup by Technology:

  • System-on-Chip (SoC)
  • System-in-Package
  • Multi-chip Module
  • Others

Breakup by Chip Type:

  • GPU
  • ASIC
  • FPGA
  • CPU
  • Others

Breakup by Industry Vertical:

  • BFSI
  • IT and Telecom
  • Media and Advertising
  • Retail
  • Healthcare
  • Automotive
  • Others

Breakup by Region:

  • North America: (United States, Canada)
  • Asia Pacific: (China, Japan, India, South Korea, Australia, Indonesia, Others)
  • Europe: (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
  • Latin America: (Brazil, Mexico, Others)
  • Middle East and Africa

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Key highlights of the report:

  • Market Performance (2016-2021)
  • Market Outlook (2022- 2027)
  • Porter’s Five Forces Analysis
  • Market Drivers and Success Factors
  • SWOT Analysis
  • Value Chain
  • Comprehensive Mapping of the Competitive Landscape

If you need specific information that is not currently within the scope of the report, we can provide it to you as a part of the customization.

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Created by

George Poter







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