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Machine Learning Chip Market by Chip Type Technology and Industry Vertical - Global Opportunity Analysis and Industry Forecast, 2018-2025

  • ID: 4621187
  • Report
  • August 2018
  • Region: Global
  • 376 Pages
  • Allied Analytics LLP
Machine learning is derived from the field of artificial intelligence (AI), which uses algorithm to find out natural patterns in data for the development of computers. This data is used to take better decisions and make predictions in applications, such as stock trading, medicals, machine load forecasting, and others. For instance, many media sites depend on machine learning technology for the best recommendations of songs and movies from millions of options. Furthermore, retail industries also use this technology to predict purchasing behavior of their customers. The machine learning technology is widely adopted for the applications, such as image processing, face detections, motion & object detections, and others. In addition, it can also be implemented in computation biology for tumor detection and DNA sequencing. Furthermore, machine learning can be used for prediction of maintenance in automotive, manufacturing, and aerospace industries. The machine learning chip market has witnessed significant growth over the years, owing to increase in big data in various fields and rise in rate of deployments in the developing regions. 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 graphics processing unit (GPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), central processing unit (CPU), and others. Based on technology, the market is segmented as system-on-chip, system-in-package, multi-chip module, and others. Based on industry vertical, it is divided into media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and others. Based on region, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA. The key players profiled in the report include AMD (Advanced Micro Devices), Google, Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx, Samsung. KEY BENEFITS FOR STAKEHOLDERS 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 in the market. The report presents information related to key drivers, restraints, and opportunities with a detailed impact analysis. The current market is quantitatively analyzed from 2017 to 2025 to highlight the financial competency of the market. Porters five forces analysis illustrates the potency of the buyers and suppliers. KEY MARKET SEGMENTS BY CHIP TYPE GPU ASIC FPGA CPU Others BY TECHNOLOGY System-on-chip (SoC) System-in-package (SIP) Multi-chip module Others BY INDUSTRY VERTICAL Media & advertising BFSI IT & telecom Retail Healthcare Automotive & transportation Others BY REGION North America U.S. Canada Mexico Europe UK Germany France Russia Rest of Europe Asia-Pacific China Japan India Australia Rest of Asia-Pacific LAMEA Latin America Middle East Africa KEY MARKET PLAYERS PROFILED AMD (Advanced Micro Devices) Google, Inc. Intel Corporation NVIDIA Baidu Bitmain Technologies Qualcomm Amazon Xilinx Samsung
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CHAPTER 1: INTRODUCTION 1.1. REPORT DESCRIPTION 1.2. KEY MARKET SEGMENTS 1.3. RESEARCH METHODOLOGY 1.3.1. Primary research 1.3.2. Secondary research 1.3.3. Analyst tools and models CHAPTER 2: EXECUTIVE SUMMARY 2.1. CXO PERSPECTIVE CHAPTER 3: MARKET OVERVIEW 3.1. MARKET DEFINITION AND SCOPE 3.2. KEY FINDINGS 3.2.1. Top impacting factors 3.2.2. Top investment pockets 3.2.3. Top winning strategies 3.3. PORTERS FIVE FORCES ANALYSIS 3.3.1. Moderate-to-high bargaining power of suppliers 3.3.2. Moderate-to-high threat of new entrants 3.3.3. Low-to-Moderate threat of substitutes 3.3.4. High-to-moderate intensity of rivalry 3.3.5. High-to-moderate bargaining power of buyers 3.4. MARKET SHARE ANALYSIS, 2017 (%) 3.5. MARKET DYNAMICS 3.5.1. Drivers 3.5.1.1. Emergence of quantum computing 3.5.1.2 Growth in number of machine learning applications 3.5.1.3 Trending Artificial Intelligence (AI) 3.5.2. Restraints 3.5.2.1 Dearth of skilled workforce 3.5.2.2 AI Phobia 3.5.3. Opportunities 3.5.3.1 Increase in demand for smart homes & smart cities 3.5.3.2 Increase in efforts to make more human-like robots 3.5.3.3 Popularity of IoT across the globe CHAPTER 4: MACHINE LEARNING CHIP MARKET, BY CHIP TYPE 4.1. OVERVIEW 4.2. GPU 4.2.1. Key market trends, growth factors and opportunities 4.2.2. Market size and forecast, by region 4.2.3. Market analysis by country 4.3. ASIC 4.3.1. Key market trends, growth factors, and opportunities 4.3.2. Market size and forecast, by region 4.3.3. Market analysis by country 4.4. FPGA 4.4.1. Key market trends, growth factors, and opportunities 4.4.2. Market size and forecast, by region 4.4.3. Market analysis by country 4.5. CPU 4.5.1. Key market trends, growth factors, and opportunities 4.5.2. Market size and forecast, by region 4.5.3. Market analysis by country 4.6. OTHERS (NPU & HYBRID CHIP) 4.6.1. Key market trends, growth factors, and opportunities 4.6.2. Market size and forecast, by region 4.6.3. Market analysis by country CHAPTER 5: MACHINE LEARNING CHIP MARKET, BY TECHNOLOGY 5.1. OVERVIEW 5.2. SYSTEM-ON-CHIP (SOC) 5.2.1. Key market trends, growth factors and opportunities 5.2.2. Market size and forecast, by region 5.2.3. Market analysis by country 5.3. SYSTEM-IN-PACKAGE (SIP) 5.3.1. Key market trends, growth factors, and opportunities 5.3.2. Market size and forecast, by region 5.3.3. Market analysis by country 5.4. MULTI-CHIP MODULE 5.4.1. Key market trends, growth factors, and opportunities 5.4.2. Market size and forecast, by region 5.4.3. Market analysis by country 5.5. OTHERS (PACKAGE IN PACKAGE, TSV) 5.5.1. Key market trends, growth factors, and opportunities 5.5.2. Market size and forecast, by region 5.5.3. Market analysis by country CHAPTER 6: MACHINE LEARNING CHIP MARKET, BY INDUSTRY VERTICAL 6.1. OVERVIEW 6.2. MEDIA & ADVERTISING 6.2.1. Key market trends, growth factors and opportunities 6.2.2. Market size and forecast, by region 6.2.3. Market analysis by country 6.3. BFSI 6.3.1. Key market trends, growth factors and opportunities 6.3.2. Market size and forecast, by region 6.3.3. Market analysis by country 6.4. IT & TELECOM 6.4.1. Key market trends, growth factors and opportunities 6.4.2. Market size and forecast, by region 6.4.3. Market analysis by country 6.5. RETAIL 6.5.1. Key market trends, growth factors and opportunities 6.5.2. Market size and forecast, by region 6.5.3. Market analysis by country 6.6. HEALTHCARE 6.6.1. Key market trends, growth factors and opportunities 6.6.2. Market size and forecast, by region 6.6.3. Market analysis by country 6.7. AUTOMOTIVE 6.7.1. Key market trends, growth factors and opportunities 6.7.2. Market size and forecast, by region 6.7.3. Market analysis by country 6.8. OTHERS 6.8.1. Key market trends, growth factors and opportunities 6.8.2. Market size and forecast, by region 6.8.3. Market analysis by country CHAPTER 7: MACHINE LEARNING CHIP MARKET, BY REGION 7.1. OVERVIEW 7.2. NORTH AMERICA 7.2.1. Key market trends, growth factors, and opportunities 7.2.2. Market size and forecast, by chip type 7.2.3. Market size and forecast, by technology 7.2.4. Market size and forecast, by industry vertical 7.2.5. Market analysis by country 7.2.5.1. U.S. 7.2.5.1.1. Market size and forecast, by chip type 7.2.5.1.2. Market size and forecast, by technology 7.2.5.1.3. Market size and forecast, by industry vertical 7.2.5.2. Canada 7.2.5.2.1. Market size and forecast, by chip type 7.2.5.2.2. Market size and forecast, by technology 7.2.5.2.3. Market size and forecast, by industry vertical 7.2.5.3. Mexico 7.2.5.3.1. Market size and forecast, by chip type 7.2.5.3.2. Market size and forecast, by technology 7.2.5.3.3. Market size and forecast, by industry vertical 7.3. EUROPE 7.3.1. Key market trends, growth factors, and opportunities 7.3.2. Market size and forecast, by chip type 7.3.3. Market size and forecast, by technology 7.3.4. Market size and forecast, by industry vertical 7.3.5. Market analysis by country 7.3.5.1. U.K. 7.3.5.1.1. Market size and forecast, by chip type 7.3.5.1.2. Market size and forecast, by technology 7.3.5.1.3. Market size and forecast, by industry vertical 7.3.5.2. Germany 7.3.5.2.1. Market size and forecast, by chip type 7.3.5.2.2. Market size and forecast, by technology 7.3.5.2.3. Market size and forecast, by industry vertical 7.3.5.3. France 7.3.5.3.1. Market size and forecast, by chip type 7.3.5.3.2. Market size and forecast, by technology 7.3.5.3.3. Market size and forecast, by industry vertical 7.3.5.4. Russia 7.3.5.4.1. Market size and forecast, by chip type 7.3.5.4.2. Market size and forecast, by technology 7.3.5.4.3. Market size and forecast, by industry vertical 7.3.5.5. Rest of Europe 7.3.5.5.1. Market size and forecast, by chip type 7.3.5.5.2. Market size and forecast, by technology 7.3.5.5.3. Market size and forecast, by industry vertical 7.4. ASIA-PACIFIC 7.4.1. Key market trends, growth factors, and opportunities 7.4.2. Market size and forecast, by chip type 7.4.3. Market size and forecast, by technology 7.4.4. Market size and forecast, by industry vertical 7.4.5. Market analysis by country 7.4.5.1. China 7.4.5.1.1. Market size and forecast, by chip type 7.4.5.1.2. Market size and forecast, by technology 7.4.5.1.3. Market size and forecast, by industry vertical 7.4.5.2. Japan 7.4.5.2.1. Market size and forecast, by chip type 7.4.5.2.2. Market size and forecast, by technology 7.4.5.2.3. Market size and forecast, by industry vertical 7.4.5.3. India 7.4.5.3.1. Market size and forecast, by chip type 7.4.5.3.2. Market size and forecast, by technology 7.4.5.3.3. Market size and forecast, by industry vertical 7.4.5.4. Australia 7.4.5.4.1. Market size and forecast, by chip type 7.4.5.4.2. Market size and forecast, by technology 7.4.5.4.3. Market size and forecast, by industry vertical 7.4.5.5. Rest of Asia-Pacific 7.4.5.5.1. Market size and forecast, by chip type 7.4.5.5.2. Market size and forecast, by technology 7.4.5.5.3. Market size and forecast, by industry vertical 7.5. LAMEA 7.5.1. Key market trends, growth factors, and opportunities 7.5.2. Market size and forecast, by chip type 7.5.3. Market size and forecast, by technology 7.5.4. Market size and forecast, by industry vertical 7.5.5. Market analysis by country 7.5.5.1. Latin America 7.5.5.1.1. Market size and forecast, by chip type 7.5.5.1.2. Market size and forecast, by technology 7.5.5.1.3. Market size and forecast, by industry vertical 7.5.5.2. Middle East 7.5.5.2.1. Market size and forecast, by chip type 7.5.5.2.2. Market size and forecast, by technology 7.5.5.2.3. Market size and forecast, by industry vertical 7.5.5.3. Africa 7.5.5.3.1. Market size and forecast, by chip type 7.5.5.3.2. Market size and forecast, by technology 7.5.5.3.3. Market size and forecast, by industry vertical CHAPTER 8: COMPANY PROFILES 8.1. ALPHABET INC. (GOOGLE INC.) 8.1.1. Company overview 8.1.2. Company snapshot 8.1.3. Operating business segments 8.1.4. Product portfolio 8.1.5. Business performance 8.1.6. Key strategic moves and developments 8.1.7. Technological insights and key architecture 8.2. AMAZON.COM, INC. 8.2.1. Company overview 8.2.2. Company snapshot 8.2.3. Operating business segments 8.2.4. Product portfolio 8.2.5. Business performance 8.2.6. Key strategic moves and developments 8.2.7. Technological insights and key architecture 8.3. ADVANCED MICRO DEVICES, INC. 8.3.1. Company overview 8.3.2. Company snapshot 8.3.3. Operating business segments 8.3.4. Product portfolio 8.3.5. Business performance 8.3.6. Key strategic moves and developments 8.3.7. Technological insights and key architecture 8.4. BAIDU, INC. 8.4.1. Company overview 8.4.2. Company snapshot 8.4.3. Operating business segments 8.4.4. Product portfolio 8.4.5. Business performance 8.4.6. Key strategic moves and developments 8.4.7. Technological insights and key architecture 8.5. BITMAIN TECHNOLOGIES LTD. 8.5.1. Company overview 8.5.2. Company snapshot 8.5.3. Product portfolio 8.5.4. Key strategic moves and developments 8.5.5. Technological insights and key architecture 8.6. INTEL CORPORATION 8.6.1. Company overview 8.6.2. Company snapshot 8.6.3. Operating business segments 8.6.4. Product portfolio 8.6.5. Business performance 8.6.6. Key strategic moves and developments 8.6.7. Technological insights and key architecture 8.7. NVIDIA CORPORATION 8.7.1. Company overview 8.7.2. Company snapshot 8.7.3. Operating business segments 8.7.4. Product portfolio 8.7.5. Business performance 8.7.6. Key strategic moves and developments 8.7.7. Technological insights and key architecture 8.8. QUALCOMM INCORPORATED 8.8.1. Company overview 8.8.2. Company snapshot 8.8.3. Operating business segments 8.8.4. Product portfolio 8.8.5. Business performance 8.8.6. Key strategic moves and developments 8.8.7. Technological insights and key architecture 8.9. SAMSUNG ELECTRONICS CO. LTD. 8.9.1. Company overview 8.9.2. Company snapshot 8.9.3. Operating business segments 8.9.4. Product portfolio 8.9.5. Business performance 8.9.6. Key strategic moves and developments 8.9.7. Technological insights and key architecture 8.10. XILINX, INC. 8.10.1. Company overview 8.10.2. Company snapshot 8.10.3. Operating business segments 8.10.4. Product portfolio 8.10.5. Business performance 8.10.6. Key strategic moves and developments 8.10.7. Technological insights and key architecture
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According to a recent report titled, Machine Learning Chip Market by Chip type, Technology, and Industry vertical: Global Opportunity Analysis and Industry Forecast, 2018-2025, 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. 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. In addition, 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. Key Findings of the Machine Learning Chip Market: Based on chip type, the GPU segment dominated the global machine learning chip market in 2017. However, the ASIC segment is anticipated to overtake the GPU segment in future, in terms of revenue. North America held the major market share in 2017. Based on industry vertical, the BFSI segment dominated the global machine learning chip market in 2017. However, the others segment is expected to grow at the highest CAGR during the forecast period. Asia Pacific is anticipated to exhibit the highest CAGR during the forecast period.
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The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.

They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.

They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:

  • Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
  • Scientific and technical writings for product information and related preemptions
  • Regional government and statistical databases for macro analysis
  • Authentic news articles and other related releases for market evaluation
  • Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast

Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.

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