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Machine Learning Chip Market by Type (GPU chip, Neuromorphic Chip, Flash Based Chip, and FPGA Chip), and Application (Consumer Electronics, Automotive, Healthcare, Robotics Industry) - Global Opportunity Analysis and Industry Forecast, 2014 - 2022

  • ID: SE 172055
  • Mar 2017
  • 168 pages
  • Price: $4296
$2765

Machine Learning Chip Market Overview:

Machine Learning Chip Market size is expected to reach $8,272 million in 2022 from $4,495 million in 2015, growing at a CAGR of 9.4% from 2016 to 2022.

Machine learning chip is a multi-processor chip, which has the ability to learning, reason, and self-correction its algorithm without being explicitly programed. These integrated circuit chips can detect patterns in the new data and adjust program actions accordingly. These chips help to update the applications without any change in the hardware. Machine learning chips are widely adopted in applications such as robotics, healthcare, automotive, consumer electronics, and others owing to its enhanced efficiency and durability.

Improved productivity, diversified application areas, and trending Artificial Intelligence (AI) have increased the rate of adoption of machine learning chip in robotics, automotive, healthcare, and other sectors. Hence, the global machine learning chip market is expected to witness moderate growth in the near future, owing to compact size and enhanced durability. However, lack of skilled workforce hampers the market growth. Popularity of Internet of Things (IoT) and increase in demand for automated devices are expected to provide lucrative opportunities to the market.

The global machine learning chip market is segmented on the basis of type, application, and geography. Based on packaging type, the market is classified into GPU chip, neuromorphic chip, flash-based memory chip, and FPGA chip. In 2015, Neuromorphic chip was the largest revenue contributor, as it is widely adopted in robotics industry, and is expected to maintain this trend throughout the forecast period, owing to its enhanced efficiency and durability.

Segment Overview

segment overview

Application Overview

APPLICATION OVERVIEW

The consumer electronics segment offers lucrative scope to industry players, and are expected to exhibit higher growth as compared to the other segments during the forecast period. North America accounted for the largest revenue share in the global market in 2015, owing to the increase in demand for semiconductor devices and automated devices.

Top Impacting Factors

Top Impacting Factors

Improved Productivity

The machine-learning technology has driven exceptional increase in productivity. For example, Google has modified cars such as Toyota Prius with its experimental driverless technology. Machine learning chip has currently transformed business management through integration of various tools such as workflow management tools, brand purchase advertising, trend predictions, and others.

Trending Artificial Intelligence (AI)

AI encompasses deep learning, computer vision, robotics, collaborative systems, machine learning, and natural learning process in other things. AI has made significant advances in recent years owing to its devotion towards making machines intelligent and enabling them to function appropriately with foresight in its environment. AI requires machine learning chip to accelerate the system without any human assistant. Companies develop a new computing model that uses parallel processors to accelerate computing through advanced chips.

Competition Analysis

The key players profiled in the report are Advanced Micro Devices, Inc., Google Inc., Graphcore, Intel Corporation, International Business Machines (IBM) Corporation, Nvidia Corporation, Qualcomm Technologies, Inc., Taiwan Semiconductor Manufacturing Company Ltd., Wave Computing, and XILINX Inc. Other players in the value chain include BigML, Inc., FICO. Hewlett-Packard Enterprise Development LP, and Microsoft Corporation.

Key Benefits

  • The study provides an in-depth analysis of the global machine learning chip market to elucidate the prominent investment pockets.
  • Current trends and future estimations are outlined to determine the overall attractiveness, and single out profitable trends to gain a stronger foothold in the market.
  • The report provides information regarding key drivers, restraints, and opportunities along with their impact analysis.
  • The market is analyzed based on various regions, namely, North America, Europe, Asia-Pacific, and LAMEA.

Machine Learning Chip Market Key Segmentation

By Type

  • GPU Chip
  • Neuromorphic Chip
  • Flash Based Memory Chip
  • FPGA Chip

By Application

  • Consumer Electronics
  • Automotive
  • Healthcare
  • Robotics Industry
  • Others

By Geography

  • North America
    • U.S.
    • Mexico
    • Canada
  • Europe
    • UK
    • Germany
    • France
    • Rest of the Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America
    • Middle East
    • Africa

Key Players

  • Advanced Micro Devices, Inc.
  • Google Inc.
  • Graphcore
  • Intel Corporation
  • International Business Machines (IBM) Corporation
  • Nvidia Corporation
  • Qualcomm Technologies, Inc.
  • Taiwan Semiconductor Manufacturing Company Ltd.
  • Wave Computing
  • XILINX Inc.

*Other companies in value chain

  • BigML, Inc.
  • FICO.
  • Hewlett-Packard Enterprise Development LP
  • Microsoft Corporation

*Profiles of these players are not included. The same will be included on request

 

 

Chapter: 1 INTRODUCTION

1.1. Report Description
1.2. Key Benefits
1.3. Key Market Segments
1.4. Research Methodology

1.4.1. Secondary Research
1.4.2. Primary Research
1.4.3. Analyst Tools and Models

Chapter: 2 EXECUTIVE SUMMARY

2.1. CXPerspective

Chapter: 3 MARKET OVERVIEW

3.1. Market Definition and Scope
3.2. Key Findings

3.2.1. Top Impacting Factors
3.2.2. Top Winning Strategies
3.2.3. Top Investment Pockets

3.3. Porter’s Five Forces Analysis

3.3.1. Bargaining Power of Suppliers
3.3.2. Bargaining Power of Buyers
3.3.3. Threat of Substitutes
3.3.4. Threat of New Entrants
3.3.5. Intensity of Competitive Rivalry

3.4. Key Market Players Positioning, 2015
3.5. Market Dynamics

3.5.1. Drivers
3.5.2. Restraints
3.5.3. Opportunities

Chapter: 4 MACHINE LEARNING CHIP MARKET, BY TYPE

4.1. Overview

4.1.1. Market Size and Forecast

4.2. Graphics Processing Unit (GPU) Chip

4.2.1. Introduction
4.2.2. Key Market Trends, Growth Factors, and Opportunities
4.2.3. Market Size and Forecast

4.3. Neuromorphic Chip

4.3.1. Introduction
4.3.2. Key Market Trends, Growth Factors, and Opportunities
4.3.3. Market Size and Forecast

4.4. Flash Based Chip

4.4.1. Introduction
4.4.2. Key Market Trends, Growth Factors, and Opportunities
4.4.3. Market Size and Forecast

4.5. Field Programmable Gate Array (FPGA) Chip

4.5.1. Introduction
4.5.2. Key Market Trends, Growth Factors, and Opportunities
4.5.3. Market Size and Forecast

Chapter: 5 MACHINE LEARNING CHIP MARKET, BY APPLICATION

5.1. Overview
5.2. Consumer Electronics

5.2.1. Introduction
5.2.2. Key Market Trends, Growth Factors, and Opportunities
5.2.3. Market Size and Forecast

5.3. Automotive

5.3.1. Introduction
5.3.2. Key Market Trends, Growth Factors, and Opportunities
5.3.3. Market Size and Forecast

5.4. Healthcare

5.4.1. Introduction
5.4.2. Key Market Trends, Growth Factors, and Opportunities
5.4.3. Market Size and Forecast

5.5. Robotics Industry

5.5.1. Introduction
5.5.2. Key Market Trends, Growth Factors, and Opportunities
5.5.3. Market Size and Forecast

5.6. Others

5.6.1. Introduction
5.6.2. Key Market Trends, Growth Factors, and Opportunities
5.6.3. Market Size and Forecast

Chapter: 6 MACHINE LEARNING CHIP MARKET, BY GEOGRAPHY

6.1. Overview

6.1.1. Market Size and Forecast

6.2. North America

6.2.1. Introduction
6.2.2. Key Market Trends, Growth Factors, and Opportunities
6.2.3. Market Size and Forecast

6.2.4. U.S.

6.2.4.1. Market Size and Forecast

6.2.5. Canada

6.2.5.1. Market Size and Forecast

6.2.6. Mexico

6.2.6.1. Market Size and Forecast

6.3. Europe

6.3.1. Introduction
6.3.2. Key Market Trends, Growth Factors, and Opportunities
6.3.3. Market Size and Forecast
6.3.4. UK

6.3.4.1. Market Size and Forecast

6.3.5. Germany

6.3.5.1. Market Size and Forecast

6.3.6. France

6.3.6.1. Market Size and Forecast

6.3.7. Rest of Europe

6.3.7.1. Market Size and Forecast

6.4. Asia-Pacific

6.4.1. Introduction
6.4.2. Key Market Trends, Growth Factors, and Opportunities
6.4.3. Market Size and Forecast
6.4.4. China

6.4.4.1. Market Size and Forecast

6.4.5. Japan

6.4.5.1. Market Size and Forecast

6.4.6. India

6.4.6.1. Market Size and Forecast

6.4.7. South Korea

6.4.7.1. Market Size and Forecast

6.4.8. Rest of Asia-Pacific

6.4.8.1. Market Size and Forecast

6.5. LAMEA

6.5.1. Introduction
6.5.2. Key Market Trends, Growth Factors, and Opportunities
6.5.3. Market Size and Forecast
6.5.4. Latin America

6.5.4.1. Market Size and Forecast

6.5.5. Middle East

6.5.5.1. Market Size and Forecast

6.5.6. Africa

6.5.6.1. Market Size and Forecast

Chapter: 7 RELATED INDUSTRY INSIGHTS

7.1. Flip Chip Market

7.1.1. Executive Summary

7.2. 3D Semiconductor Packaging Market

7.2.1. Executive Summary

Chapter: 8 COMPANY PROFILES

8.1. ADVANCE MICRDEVICES, INC.

8.1.1. Company Overview
8.1.2. Company Snapshot
8.1.3. Operating Business Segments
8.1.4. Business Performance
8.1.5. Key Strategic Moves and Developments

8.2. GOOGLE INC

8.2.1. Company Overview
8.2.2. Company Snapshot
8.2.3. Operating Business Segments
8.2.4. Business Performance

8.3. GRAPHCORE LTD

8.3.1. Company Overview
8.3.2. Company Snapshot
8.3.3. Operating Business Segments
8.3.4. Business Performance

8.4. INTEL CORPORATION

8.4.1. Company Overview
8.4.2. Company Snapshot
8.4.3. Operating Business Segments
8.4.4. Business Performance

8.5. INTERNATIONAL BUSINESS MACHINES CORPORATION

8.5.1. Company Overview
8.5.2. Company Snapshot
8.5.3. Operating Business Segments
8.5.4. Business Performance
8.5.5. Key Strategic Moves and Developments

8.6. NVIDIA CORPORATION

8.6.1. Company Overview
8.6.2. Company Snapshot
8.6.3. Operating Business Segments
8.6.4. Business Performance
8.6.5. Key Strategic Moves and Developments

8.7. QUALCOMM INC.

8.7.1. Company Overview
8.7.2. Company Snapshot
8.7.3. Operating Business Segments
8.7.4. Business Performance
8.7.5. Key Strategic Moves and Developments

8.8. TAIWAN SEMICONDUCTOR MANUFACTURING COMPANY LTD.

8.8.1. Company Overview
8.8.2. Company Snapshot
8.8.3. Operating Business Segments
8.8.4. Business Performance

8.9. WAVE COMPUTING

8.9.1. Company Overview
8.9.2. Company Snapshot
8.9.3. Operating Business Segments
8.9.4. Business Performance

8.10. XILINX INC.

8.10.1. Company Overview
8.10.2. Company Snapshot
8.10.3. Operating Business Segments
8.10.4. Business Performance
8.10.5. Key Strategic Moves and Developments

OTHER PLAYERS IN THE VALUE CHAIN INCLUDE

  • BigML, Inc.
  • FICO.
  • Hewlett-Packard Enterprise Development LP
  • Microsoft Corporation

LIST OF TABLES

TABLE 1. GLOBAL MACHINE LEARNING CHIP MARKET, BY TYPE, 2014-2022 ($MILLION)
TABLE 2. MACHINE LEARNING MARKET FOR GPU CHIP, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 3. MACHINE LEARNING CHIP MARKET FOR NEUROMORPHIC CHIP, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 4. MACHINE LEARNING CHIP MARKET FOR FLASH BASED CHIP, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 5. MACHINE LEARNING CHIP MARKET FOR FPGA CHIP, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 6. GLOBAL MACHINE LEARNING CHIP MARKET, BY APPLICATION, 2014-2022 ($MILLION)
TABLE 7. MACHINE LEARNING CHIP MARKET FOR CONSUMER ELECTRONICS APPLICATION, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 8. MACHINE LEARNING CHIP MARKET FOR AUTOMOTIVE APPLICATION, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 9. MACHINE LEARNING CHIP MARKET FOR HEALTHCARE APPLICATION, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 10. MACHINE LEARNING CHIP MARKET FOR ROBOTICS INDUSTRY APPLICATION, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 11. MACHINE LEARNING CHIP MARKET FOR OTHER APPLICATIONS, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 12. MACHINE LEARNING CHIP MARKET, BY GEOGRAPHY, 2014-2022 ($MILLION)
TABLE 13. NORTH AMERICA MACHINE LEARNING CHIP MARKET, BY TYPE, 2014-2022 ($MILLION)
TABLE 14. NORTH AMERICA MACHINE LEARNING CHIP MARKET, BY APPLICATION, 2014-2022 ($MILLION)
TABLE 15. NORTH AMERICA MACHINE LEARNING CHIP MARKET, BY COUNTRY, 2014-2022 ($MILLION)
TABLE 16. EUROPE MACHINE LEARNING CHIP MARKET, BY TYPE, 2014-2022 ($MILLION)
TABLE 17. EUROPE MACHINE LEARNING CHIP MARKET, BY APPLICATION, 2014-2022 ($MILLION)
TABLE 18. EUROPE MACHINE LEARNING CHIP MARKET, BY COUNTRY, 2014-2022 ($MILLION)
TABLE 19. ASIA-PACIFIC MACHINE LEARNING CHIP MARKET, BY TYPE, 2014-2022 ($MILLION)
TABLE 20. ASIA-PACIFIC MACHINE LEARNING CHIP MARKET, BY APPLICATION, 2014-2022 ($MILLION)
TABLE 21. ASIA-PACIFIC MACHINE LEARNING CHIP MARKET, BY COUNTRY, 2014-2022 ($MILLION)
TABLE 22. LAMEA MACHINE LEARNING CHIP MARKET, BY TYPE, 2014-2022 ($MILLION)
TABLE 23. LAMEA MACHINE LEARNING CHIP MARKET, BY APPLICATION, 2014-2022 ($MILLION)
TABLE 24. LAMEA MACHINE LEARNING CHIP MARKET, BY COUNTRY, 2014-2022 ($MILLION)
TABLE 25. ADVANCED MICRDEVICES, INC.: COMPANY SNAPSHOT
TABLE 26. ADVANCED MICRDEVICES, INC.: OPERATING SEGMENTS
TABLE 27. GOOGLE INC: COMPANY SNAPSHOT
TABLE 28. GOOGLE INC: OPERATING SEGMENTS
TABLE 29. GRAPHCORE LTD: COMPANY SNAPSHOT
TABLE 30. GRAPHCORE LTD.: OPERATING SEGMENTS
TABLE 31. INTEL CORPORATION CORP: COMPANY SNAPSHOT
TABLE 32. INTEL CORPORATION: OPERATING SEGMENTS
TABLE 33. IBM CORPORATION: COMPANY SNAPSHOT
TABLE 34. IBM CORPORATION: OPERATING SEGMENTS
TABLE 35. NVIDIA CORP: COMPANY SNAPSHOT
TABLE 36. NVIDIA CORP: OPERATING SEGMENTS
TABLE 37. QUALCOMM INC COMPANY SNAPSHOT
TABLE 38. QUALCOMM INC: OPERATING SEGMENTS
TABLE 39. TAIWAN SEMICONDUCTOR MANUFACTURING COMPANY, LTD: COMPANY SNAPSHOT
TABLE 40. TAIWAN SEMICONDUCTOR MANUFACTURING COMPANY, LTD: OPERATING SEGMENTS
TABLE 41. WAVE COMPUTING: COMPANY SNAPSHOT
TABLE 42. WAVE COMPUTING: OPERATING SEGMENTS
TABLE 43. XILINX INC.: COMPANY SNAPSHOT
TABLE 44. XILINX INC.: OPERATING SEGMENTS

LIST OF FIGURES

FIGURE 1. SEGMENTATION
FIGURE 2. TOP IMPACTING FACTORS
FIGURE 3. TOP WINNING STRATEGIES: PERCENTAGE DISTRIBUTION (2013-2016)
FIGURE 4. TOP WINNING STRATEGIES: NATURE AND TYPE
FIGURE 5. TOP INVESTMENT POCKETS IN GLOBAL MACHINE LEARNING CHIP MARKET, BY APPLICATION
FIGURE 6. PORTER’S FIVE FORCES ANALYSIS
FIGURE 7. MARKET SHARE ANALYSIS, 2015
FIGURE 8. COMPARATIVE REGIONAL SHARE ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR GPU CHIP, 2015 & 2022 (%)
FIGURE 9. GLOBAL MACHINE LEARNING CHIP MARKET FOR GPU CHIP, 2014-2022 ($MILLION)
FIGURE 10. COMPARATIVE REGIONAL SHARE ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR NEUROMORPHIC CHIP, 2015 & 2022 (%)
FIGURE 11. GLOBAL MACHINE LEARNING CHIP MARKET FOR NEUROMORPHIC CHIP, 2014-2022 ($MILLION)
FIGURE 12. COMPARATIVE REGIONAL SHARE ANALYSIS OF GLOBAL MACHINE LEARNING CHIP MARKET FOR FLASH BASED CHIP, 2015 & 2022 (%)
FIGURE 13. GLOBAL MACHINE LEARNING CHIP MARKET FOR FLASH BASED CHIP, 2014-2022 ($MILLION)
FIGURE 14. COMPARATIVE REGIONAL SHARE ANALYSIS OF GLOBAL MACHINE LEARNING CHIP MARKET FOR FPGA CHIP, 2015 & 2022 (%)
FIGURE 15. GLOBAL MACHINE LEARNING CHIP MARKET FOR FPGA CHIP, 2014-2022 ($MILLION)
FIGURE 16. COMPARATIVE REGIONAL SHARE ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR CONSUMER ELECTRONICS APPLICATION, 2015 & 2022 (%)
FIGURE 17. GLOBAL MACHINE LEARNING CHIP MARKET FOR CONSUMER ELECTRONICS APPLICATION, 2014-2022 ($MILLION)
FIGURE 18. COMPARATIVE REGIONAL ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR AUTOMOTIVE APPLICATION, 2015 & 2022 (%)
FIGURE 19. GLOBAL MACHINE LEARNING CHIP MARKET FOR AUTOMOTIVE APPLICATION, 2014-2022 ($MILLION)
FIGURE 20. COMPARATIVE REGIONAL SHARE ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR HEALTHCARE APPLICATION, 2015 & 2022 (%)
FIGURE 21. GLOBAL MACHINE LEARNING CHIP MARKET FOR HEALTHCARE APPLICATION, 2014-2022 ($MILLION)
FIGURE 22. COMPARATIVE REGIONAL SHARE ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR ROBOTICS INDUSTRY APPLICATION, 2015 & 2022 (%)
FIGURE 23. GLOBAL MACHINE LEARNING CHIP MARKET FOR ROBOTICS INDUSTRY APPLICATION, 2014-2022 ($MILLION)
FIGURE 24. COMPARATIVE REGIONAL SHARE ANALYSIS OF MACHINE LEARNING CHIP MARKET FOR OTHER APPLICATIONS, 2015 & 2022 (%)
FIGURE 25. GLOBAL MACHINE LEARNING CHIP MARKET FOR OTHER APPLICATIONS, 2014-2022 ($MILLION)
FIGURE 26. U.S. MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 27. CANADA MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 28. MEXICMACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 29. UK MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 30. GERMANY MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 31. FRANCE MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 32. REST OF EUROPE MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 33. CHINA MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 34. JAPAN MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 35. INDIA MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 36. SOUTH KOREA MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 37. REST OF ASIA-PACIFIC MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 38. LATIN AMERICA MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 39. MIDDLE EAST MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 40. AFRICA MACHINE LEARNING CHIP MARKET SIZE, 2014-2022 ($MILLION)
FIGURE 41. ADVANCED MICRDEVICES, INC:  COMPANY SNAPSHOT
FIGURE 42. GOOGLE INC: COMPANY SNAPSHOT
FIGURE 43. INTEL CORPORATION: COMPANY SNAPSHOT
FIGURE 44. IBM CORPORATION: COMPANY SNAPSH
FIGURE 45. NVIDIA CORP: COMPANY SNAPSHOT
FIGURE 46. QUALCOMM INC: COMPANY SNAPSHOT
FIGURE 47. TAIWAN SEMICONDUCTOR MANUFACTURING COMPANY, LTD: COMPANY SNAPSHOT
FIGURE 48. XILINX INC.: COMPANY SNAPSHOT

 

The global machine learning chip market is expected to witness massive growth in the near future due to improved productivity and diversified application areas. Machine learning plays a crucial role in extracting meaningful data out of the zetabytes of sensor data collected every day. Numerous industries, such as robotics, healthcare, automotive, and consumer electronics adopt machine learning chip to enable features such as learning, reasoning, and self-correction. Market players have focused on developing innovative chips for applications in healthcare and electronic appliances to enhance their efficiency. Leading users of machine learning technology in the market such as Facebook, Renaissance Technologies, and Google rely on techniques from machine learning to generate huge profits. Furthermore, Neuromorphic chip, which are used for gaming, driverless vehicles, drones and air transport, security & cyber security, speech and image recognition, stimulate the growth of the machine learning chip market.

Machine learning chips can be operated at high insensitive data transmission. However, lack of skilled workforce for maintenance adversely affects their performance. Nevertheless, the implementation of a reliable and effective technology can reduce complexity. However, prominent players have developed low-cost, compact, affordable, and energy-efficient chips to increase the efficiency and durability of the applications. Increase in demand for automated chips provide growth opportunities to market players. Public and private organizations have substantially invested in R&D activities to develop advance chip with reduced power consumption. In addition, North America is the major revenue contributor to the global market, followed by Asia-Pacific. Significant increase in the growth of the machine learning chip market in Asia-Pacific and LAMEA is projected during the forecast period.

 

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