What is scope of the report?

The base year for the study has been considered 2019, historic year 2014 and 2018. Read More

What are the significant segments operating in the market?

Market is segmented on the basis. Read More

What are the vital market dynamics?

The report offers in-depth analysis of driving factors, opportunities, restraints, and challenges for gaining the key insight of the market. Read More

What does a company profile includes?

The report provides company profile of the key players operating in the market and a comparative analysis based on their business overviews industry offering. Read More

Global Deep Learning Chip Market 2020 by Company, Regions, Type and Application, Forecast to 2025

Publish Date: Feb, 2020
Report ID: 408562
Category: Technology
Pages: 107

$3480

Market Overview

The global Deep Learning Chip market size is expected to gain market growth in the forecast period of 2020 to 2025, with a CAGR of 35.5% in the forecast period of 2020 to 2025 and will expected to reach USD 5831.7 million by 2025, from USD 1729.7 million in 2019.

The Deep Learning Chip market report provides a detailed analysis of global market size, regional and country-level market size, segmentation market growth, market share, competitive Landscape, sales analysis, impact of domestic and global market players, value chain optimization, trade regulations, recent developments, opportunities analysis, strategic market growth analysis, product launches, area marketplace expanding, and technological innovations.

Market segmentation

Deep Learning Chip market is split by Type and by Application. For the period 2015-2025, the growth among segments provide accurate calculations and forecasts for sales by Type and by Application in terms of volume and value. This analysis can help you expand your business by targeting qualified niche markets.

By Type, Deep Learning Chip market has been segmented into:

Data Mining

Image Recognition

Signal Recognition

Others

By Application, Deep Learning Chip has been segmented into:

Industrial

Automotive

Aerospace & Defense

Medical

IT & Telecommunication

Others

Regions and Countries Level Analysis

Regional analysis is another highly comprehensive part of the research and analysis study of the global Deep Learning Chip market presented in the report. This section sheds light on the sales growth of different regional and country-level Deep Learning Chip markets. For the historical and forecast period 2015 to 2025, it provides detailed and accurate country-wise volume analysis and region-wise market size analysis of the global Deep Learning Chip market.

The report offers in-depth assessment of the growth and other aspects of the Deep Learning Chip market in important countries (regions), including:

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia and Italy)

Asia-Pacific (China, Japan, Korea, India, Southeast Asia and Australia)

South America (Brazil, Argentina, Colombia)

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Competitive Landscape and Deep Learning Chip Market Share Analysis

Deep Learning Chip competitive landscape provides details by vendors, including company overview, company total revenue (financials), market potential, global presence, Deep Learning Chip sales and revenue generated, market share, price, production sites and facilities, SWOT analysis, product launch. For the period 2015-2020, this study provides the Deep Learning Chip sales, revenue and market share for each player covered in this report.

The major players covered in Deep Learning Chip are:

NVDIA

Qualcomm

IBM

Google

Sensory

Intel

Baidu

Microsoft

General Vision

Hewlett Packard

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Table of Contents

1 Deep Learning Chip Market Overview

1.1 Product Overview and Scope of Deep Learning Chip

1.2 Classification of Deep Learning Chip by Type

1.2.1 Global Deep Learning Chip Revenue by Type: 2015 VS 2019 VS 2025

1.2.2 Global Deep Learning Chip Revenue Market Share by Type in 2019

1.2.3 Data Mining

1.2.4 Image Recognition

1.2.5 Signal Recognition

1.2.6 Others

1.3 Global Deep Learning Chip Market by Application

1.3.1 Overview: Global Deep Learning Chip Revenue by Application: 2015 VS 2019 VS 2025

1.3.2 Industrial

1.3.3 Automotive

1.3.4 Aerospace & Defense

1.3.5 Medical

1.3.6 IT & Telecommunication

1.3.7 Others

1.4 Global Deep Learning Chip Market by Regions

1.4.1 Global Deep Learning Chip Market Size by Regions: 2015 VS 2019 VS 2025

1.4.2 Global Market Size of Deep Learning Chip (2015-2025)

1.4.3 North America (USA, Canada and Mexico) Deep Learning Chip Status and Prospect (2015-2025)

1.4.4 Europe (Germany, France, UK, Russia and Italy) Deep Learning Chip Status and Prospect (2015-2025)

1.4.5 Asia-Pacific (China, Japan, Korea, India and Southeast Asia) Deep Learning Chip Status and Prospect (2015-2025)

1.4.6 South America (Brazil, Argentina, Colombia) Deep Learning Chip Status and Prospect (2015-2025)

1.4.7 Middle East & Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) Deep Learning Chip Status and Prospect (2015-2025)

2 Company Profiles

2.1 NVDIA

2.1.1 NVDIA Details

2.1.2 NVDIA Major Business and Total Revenue (Financial Highlights) Analysis

2.1.3 NVDIA SWOT Analysis

2.1.4 NVDIA Product and Services

2.1.5 NVDIA Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.2 Qualcomm

2.2.1 Qualcomm Details

2.2.2 Qualcomm Major Business and Total Revenue (Financial Highlights) Analysis

2.2.3 Qualcomm SWOT Analysis

2.2.4 Qualcomm Product and Services

2.2.5 Qualcomm Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.3 IBM

2.3.1 IBM Details

2.3.2 IBM Major Business and Total Revenue (Financial Highlights) Analysis

2.3.3 IBM SWOT Analysis

2.3.4 IBM Product and Services

2.3.5 IBM Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.4 Google

2.4.1 Google Details

2.4.2 Google Major Business and Total Revenue (Financial Highlights) Analysis

2.4.3 Google SWOT Analysis

2.4.4 Google Product and Services

2.4.5 Google Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.5 Sensory

2.5.1 Sensory Details

2.5.2 Sensory Major Business and Total Revenue (Financial Highlights) Analysis

2.5.3 Sensory SWOT Analysis

2.5.4 Sensory Product and Services

2.5.5 Sensory Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.6 Intel

2.6.1 Intel Details

2.6.2 Intel Major Business and Total Revenue (Financial Highlights) Analysis

2.6.3 Intel SWOT Analysis

2.6.4 Intel Product and Services

2.6.5 Intel Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.7 Baidu

2.7.1 Baidu Details

2.7.2 Baidu Major Business and Total Revenue (Financial Highlights) Analysis

2.7.3 Baidu SWOT Analysis

2.7.4 Baidu Product and Services

2.7.5 Baidu Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.8 Microsoft

2.8.1 Microsoft Details

2.8.2 Microsoft Major Business and Total Revenue (Financial Highlights) Analysis

2.8.3 Microsoft SWOT Analysis

2.8.4 Microsoft Product and Services

2.8.5 Microsoft Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.9 General Vision

2.9.1 General Vision Details

2.9.2 General Vision Major Business and Total Revenue (Financial Highlights) Analysis

2.9.3 General Vision SWOT Analysis

2.9.4 General Vision Product and Services

2.9.5 General Vision Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

2.10 Hewlett Packard

2.10.1 Hewlett Packard Details

2.10.2 Hewlett Packard Major Business and Total Revenue (Financial Highlights) Analysis

2.10.3 Hewlett Packard SWOT Analysis

2.10.4 Hewlett Packard Product and Services

2.10.5 Hewlett Packard Deep Learning Chip Revenue, Gross Margin and Market Share (2018-2019)

3 Market Competition, by Players

3.1 Global Deep Learning Chip Revenue and Share by Players (2015-2020)

3.2 Market Concentration Rate

3.2.1 Top 5 Deep Learning Chip Players Market Share

3.2.2 Top 10 Deep Learning Chip Players Market Share

3.3 Market Competition Trend

4 Market Size by Regions

4.1 Global Deep Learning Chip Revenue and Market Share by Regions

4.2 North America Deep Learning Chip Revenue and Growth Rate (2015-2020)

4.3 Europe Deep Learning Chip Revenue and Growth Rate (2015-2020)

4.4 Asia-Pacific Deep Learning Chip Revenue and Growth Rate (2015-2020)

4.5 South America Deep Learning Chip Revenue and Growth Rate (2015-2020)

4.6 Middle East & Africa Deep Learning Chip Revenue and Growth Rate (2015-2020)

5 North America Deep Learning Chip Revenue by Countries

5.1 North America Deep Learning Chip Revenue by Countries (2015-2020)

5.2 USA Deep Learning Chip Revenue and Growth Rate (2015-2020)

5.3 Canada Deep Learning Chip Revenue and Growth Rate (2015-2020)

5.4 Mexico Deep Learning Chip Revenue and Growth Rate (2015-2020)

6 Europe Deep Learning Chip Revenue by Countries

6.1 Europe Deep Learning Chip Revenue by Countries (2015-2020)

6.2 Germany Deep Learning Chip Revenue and Growth Rate (2015-2020)

6.3 UK Deep Learning Chip Revenue and Growth Rate (2015-2020)

6.4 France Deep Learning Chip Revenue and Growth Rate (2015-2020)

6.5 Russia Deep Learning Chip Revenue and Growth Rate (2015-2020)

6.6 Italy Deep Learning Chip Revenue and Growth Rate (2015-2020)

7 Asia-Pacific Deep Learning Chip Revenue by Countries

7.1 Asia-Pacific Deep Learning Chip Revenue by Countries (2015-2020)

7.2 China Deep Learning Chip Revenue and Growth Rate (2015-2020)

7.3 Japan Deep Learning Chip Revenue and Growth Rate (2015-2020)

7.4 Korea Deep Learning Chip Revenue and Growth Rate (2015-2020)

7.5 India Deep Learning Chip Revenue and Growth Rate (2015-2020)

7.6 Southeast Asia Deep Learning Chip Revenue and Growth Rate (2015-2020)

8 South America Deep Learning Chip Revenue by Countries

8.1 South America Deep Learning Chip Revenue by Countries (2015-2020)

8.2 Brazil Deep Learning Chip Revenue and Growth Rate (2015-2020)

8.3 Argentina Deep Learning Chip Revenue and Growth Rate (2015-2020)

9 Middle East & Africa Revenue Deep Learning Chip by Countries

9.1 Middle East & Africa Deep Learning Chip Revenue by Countries (2015-2020)

9.2 Saudi Arabia Deep Learning Chip Revenue and Growth Rate (2015-2020)

9.3 UAE Deep Learning Chip Revenue and Growth Rate (2015-2020)

9.4 Egypt Deep Learning Chip Revenue and Growth Rate (2015-2020)

9.5 South Africa Deep Learning Chip Revenue and Growth Rate (2015-2020)

10 Market Size Segment by Type

10.1 Global Deep Learning Chip Revenue and Market Share by Type (2015-2020)

10.2 Global Deep Learning Chip Market Forecast by Type (2019-2024)

10.3 Data Mining Revenue Growth Rate (2015-2025)

10.4 Image Recognition Revenue Growth Rate (2015-2025)

10.5 Signal Recognition Revenue Growth Rate (2015-2025)

10.6 Others Revenue Growth Rate (2015-2025)

11 Global Deep Learning Chip Market Segment by Application

11.1 Global Deep Learning Chip Revenue Market Share by Application (2015-2020)

11.2 Deep Learning Chip Market Forecast by Application (2019-2024)

11.3 Industrial Revenue Growth (2015-2020)

11.4 Automotive Revenue Growth (2015-2020)

11.5 Aerospace & Defense Revenue Growth (2015-2020)

11.6 Medical Revenue Growth (2015-2020)

11.7 IT & Telecommunication Revenue Growth (2015-2020)

11.8 Others Revenue Growth (2015-2020)

12 Global Deep Learning Chip Market Size Forecast (2021-2025)

12.1 Global Deep Learning Chip Market Size Forecast (2021-2025)

12.2 Global Deep Learning Chip Market Forecast by Regions (2021-2025)

12.3 North America Deep Learning Chip Revenue Market Forecast (2021-2025)

12.4 Europe Deep Learning Chip Revenue Market Forecast (2021-2025)

12.5 Asia-Pacific Deep Learning Chip Revenue Market Forecast (2021-2025)

12.6 South America Deep Learning Chip Revenue Market Forecast (2021-2025)

12.7 Middle East & Africa Deep Learning Chip Revenue Market Forecast (2021-2025)

13 Research Findings and Conclusion

14 Appendix

14.1 Methodology

14.2 Data Source

14.3 Disclaimer

14.4 About US

List of Tables

Table 1. Global Deep Learning Chip Revenue (USD Million) by Type: 2015 VS 2019 VS 2025

Table 2. Breakdown of Deep Learning Chip by Company Type (Tier 1, Tier 2 and Tier 3)

Table 3. Global Deep Learning Chip Revenue (USD Million) by Application: 2015 VS 2019 VS 2025

Table 4. Global Market Deep Learning Chip Revenue (Million USD) Comparison by Regions 2015-2025

Table 5. NVDIA Corporate Information, Location and Competitors

Table 6. NVDIA Deep Learning Chip Major Business

Table 7. NVDIA Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 8. NVDIA SWOT Analysis

Table 9. NVDIA Deep Learning Chip Product and Solutions

Table 10. NVDIA Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 11. Qualcomm Corporate Information, Location and Competitors

Table 12. Qualcomm Deep Learning Chip Major Business

Table 13. Qualcomm Deep Learning Chip Total Revenue (USD Million) (2018-2019)

Table 14. Qualcomm SWOT Analysis

Table 15. Qualcomm Deep Learning Chip Product and Solutions

Table 16. Qualcomm Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 17. IBM Corporate Information, Location and Competitors

Table 18. IBM Deep Learning Chip Major Business

Table 19. IBM Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 20. IBM SWOT Analysis

Table 21. IBM Deep Learning Chip Product and Solutions

Table 22. IBM Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 23. Google Corporate Information, Location and Competitors

Table 24. Google Deep Learning Chip Major Business

Table 25. Google Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 26. Google SWOT Analysis

Table 27. Google Deep Learning Chip Product and Solutions

Table 28. Google Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 29. Sensory Corporate Information, Location and Competitors

Table 30. Sensory Deep Learning Chip Major Business

Table 31. Sensory Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 32. Sensory SWOT Analysis

Table 33. Sensory Deep Learning Chip Product and Solutions

Table 34. Sensory Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 35. Intel Corporate Information, Location and Competitors

Table 36. Intel Deep Learning Chip Major Business

Table 37. Intel Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 38. Intel SWOT Analysis

Table 39. Intel Deep Learning Chip Product and Solutions

Table 40. Intel Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 41. Baidu Corporate Information, Location and Competitors

Table 42. Baidu Deep Learning Chip Major Business

Table 43. Baidu Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 44. Baidu SWOT Analysis

Table 45. Baidu Deep Learning Chip Product and Solutions

Table 46. Baidu Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 47. Microsoft Corporate Information, Location and Competitors

Table 48. Microsoft Deep Learning Chip Major Business

Table 49. Microsoft Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 50. Microsoft SWOT Analysis

Table 51. Microsoft Deep Learning Chip Product and Solutions

Table 52. Microsoft Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 53. General Vision Corporate Information, Location and Competitors

Table 54. General Vision Deep Learning Chip Major Business

Table 55. General Vision Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 56. General Vision SWOT Analysis

Table 57. General Vision Deep Learning Chip Product and Solutions

Table 58. General Vision Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 59. Hewlett Packard Corporate Information, Location and Competitors

Table 60. Hewlett Packard Deep Learning Chip Major Business

Table 61. Hewlett Packard Deep Learning Chip Total Revenue (USD Million) (2017-2018)

Table 62. Hewlett Packard SWOT Analysis

Table 63. Hewlett Packard Deep Learning Chip Product and Solutions

Table 64. Hewlett Packard Deep Learning Chip Revenue (USD Million), Gross Margin and Market Share (2018-2019)

Table 65. Global Deep Learning Chip Revenue (Million USD) by Players (2015-2020)

Table 66. Global Deep Learning Chip Revenue Share by Players (2015-2020)

Table 67. Global Deep Learning Chip Revenue (Million USD) by Regions (2015-2020)

Table 68. Global Deep Learning Chip Revenue Market Share by Regions (2015-2020)

Table 69. North America Deep Learning Chip Revenue by Countries (2015-2020)

Table 70. North America Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Table 71. Europe Deep Learning Chip Revenue (Million USD) by Countries (2015-2020)

Table 72. Asia-Pacific Deep Learning Chip Revenue (Million USD) by Countries (2015-2020)

Table 73. South America Deep Learning Chip Revenue by Countries (2015-2020)

Table 74. South America Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Table 75. Middle East and Africa Deep Learning Chip Revenue (Million USD) by Countries (2015-2020)

Table 76. Middle East and Africa Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Table 77. Global Deep Learning Chip Revenue (Million USD) by Type (2015-2020)

Table 78. Global Deep Learning Chip Revenue Share by Type (2015-2020)

Table 79. Global Deep Learning Chip Revenue Forecast by Type (2021-2025)

Table 80. Global Deep Learning Chip Revenue by Application (2015-2020)

Table 81. Global Deep Learning Chip Revenue Share by Application (2015-2020)

Table 82. Global Deep Learning Chip Revenue Forecast by Application (2021-2025)

Table 83. Global Deep Learning Chip Revenue (Million USD) Forecast by Regions (2021-2025)

List of Figures

Figure 1. Deep Learning Chip Picture

Figure 2. Global Deep Learning Chip Revenue Market Share by Type in 2019

Figure 3. Data Mining Picture

Figure 4. Image Recognition Picture

Figure 5. Signal Recognition Picture

Figure 6. Others Picture

Figure 7. Deep Learning Chip Revenue Market Share by Application in 2019

Figure 8. Industrial Picture

Figure 9. Automotive Picture

Figure 10. Aerospace & Defense Picture

Figure 11. Medical Picture

Figure 12. IT & Telecommunication Picture

Figure 13. Others Picture

Figure 14. Global Deep Learning Chip Revenue (USD Million) and Growth Rate (2015-2025)

Figure 15. North America Deep Learning Chip Revenue (Million USD) and Growth Rate (2015-2025)

Figure 16. Europe Deep Learning Chip Revenue (Million USD) and Growth Rate (2015-2025)

Figure 17. Asia-Pacific Deep Learning Chip Revenue (Million USD) and Growth Rate (2015-2025)

Figure 18. South America Deep Learning Chip Revenue (Million USD) and Growth Rate (2015-2025)

Figure 19. Middle East and Africa Deep Learning Chip Revenue (Million USD) and Growth Rate (2015-2025)

Figure 20. Global Deep Learning Chip Revenue (Million USD) and Growth Rate (2015-2025)

Figure 21. Global Deep Learning Chip Revenue Share by Players in 2019

Figure 22. Global Top 5 Players Deep Learning Chip Revenue Market Share in 2019

Figure 23. Global Top 10 Players Deep Learning Chip Revenue Market Share in 2019

Figure 24. Key Players Market Share Trend

Figure 25. Global Deep Learning Chip Revenue (Million USD) and Growth Rate (%) (2015-2020)

Figure 26. Global Deep Learning Chip Revenue Market Share by Regions (2015-2020)

Figure 27. Global Deep Learning Chip Revenue Market Share by Regions in 2018

Figure 28. North America Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 29. Europe Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 30. Asia-Pacific Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 31. South America Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 32. Middle East and Africa Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 33. North America Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Figure 34. North America Deep Learning Chip Revenue Market Share by Countries in 2019

Figure 35. USA Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 36. Canada Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 37. Mexico Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 38. Europe Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Figure 39. Europe Deep Learning Chip Revenue Market Share by Countries in 2019

Figure 40. Germany Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 41. UK Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 42. France Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 43. Russia Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 44. Italy Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 45. Asia-Pacific Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Figure 46. Asia-Pacific Deep Learning Chip Revenue Market Share by Countries in 2019

Figure 47. China Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 48. Japan Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 49. Korea Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 50. India Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 51. Southeast Asia Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 52. South America Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Figure 53. South America Deep Learning Chip Revenue Market Share by Countries in 2019

Figure 54. Brazil Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 55. Argentina Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 56. Middle East and Africa Deep Learning Chip Revenue Market Share by Countries (2015-2020)

Figure 57. Middle East and Africa Deep Learning Chip Revenue Market Share by Countries in 2019

Figure 58. Saudi Arabia Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 59. UAE Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 60. Egypt Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 61. South Africa Deep Learning Chip Revenue and Growth Rate (2015-2020)

Figure 62. Global Deep Learning Chip Revenue Share by Type (2015-2020)

Figure 63. Global Deep Learning Chip Revenue Share by Type in 2019

Figure 64. Global Deep Learning Chip Market Share Forecast by Type (2021-2025)

Figure 65. Global Data Mining Revenue Growth Rate (2015-2020)

Figure 66. Global Image Recognition Revenue Growth Rate (2015-2020)

Figure 67. Global Signal Recognition Revenue Growth Rate (2015-2020)

Figure 68. Global Others Revenue Growth Rate (2015-2020)

Figure 69. Global Deep Learning Chip Revenue Share by Application (2015-2020)

Figure 70. Global Deep Learning Chip Revenue Share by Application in 2019

Figure 71. Global Deep Learning Chip Market Share Forecast by Application (2021-2025)

Figure 72. Global Industrial Revenue Growth Rate (2015-2020)

Figure 73. Global Automotive Revenue Growth Rate (2015-2020)

Figure 74. Global Aerospace & Defense Revenue Growth Rate (2015-2020)

Figure 75. Global Medical Revenue Growth Rate (2015-2020)

Figure 76. Global IT & Telecommunication Revenue Growth Rate (2015-2020)

Figure 77. Global Others Revenue Growth Rate (2015-2020)

Figure 78. Global Deep Learning Chip Revenue (Million USD) and Growth Rate Forecast (2021-2025)

Figure 79. Global Deep Learning Chip Revenue (Million USD) Forecast by Regions (2021-2025)

Figure 80. Global Deep Learning Chip Revenue Market Share Forecast by Regions (2021-2025)

Figure 81. North America Deep Learning Chip Revenue Market Forecast (2021-2025)

Figure 82. Europe Deep Learning Chip Revenue Market Forecast (2021-2025)

Figure 83. Asia-Pacific Deep Learning Chip Revenue Market Forecast (2021-2025)

Figure 84. South America Deep Learning Chip Revenue Market Forecast (2021-2025)

Figure 85. Middle East and Africa Deep Learning Chip Revenue Market Forecast (2021-2025)

Figure 86. Sales Channel: Direct Channel vs Indirect Channel

Research Methodology

Market research is a method of gathering, assessing and deducing data & information about a particular market. Market research is very crucial in these days. The techniques analyze about how a product/service can be offered to the market to its end-customers, observe the impact of that product/service based on the past customer experiences, and cater their needs and demands. Owing to the successful business ventures, accurate, relevant and thorough information is the base for all the organizations because market research report/study offers specific market related data & information about the industry growth prospects, perspective of the existing customers, and the overall market scenario prevailed in past, ongoing present and developing future. It allows the stakeholders and investors to determine the probability of a business before committing substantial resources to the venture. Market research helps in solving the marketing issues challenges that a business will most likely face.

Market research is valuable because of the following reasons:

Market research helps businesses strengthen a company’s position
Market research helps in minimizing the investment risks associated with the businesses in any industry vertical
Market research helps in identifying the potential threats and opportunities associated with the business industry
Market research aids in spotting the emerging trends and facilitates strategic planning in order to stay ahead in the competition

Our research report features both the aspects; qualitative and quantitative. Qualitative part provides insights about the market driving forces, potential opportunities, customer’s demands and requirement which in turn help the companies to come up with new strategies in order to survive in the long run competition. The quantitative segment offers the most credible information related to the industry. Based on the data gathering, we use to derive the market size and estimate their future growth prospects on the basis of global, region and country.

Our market research process involves with the four specific stages.

Data Collection
Data Synthesis
Market Deduction & Formulation
Data Screening & Validation

Data Collection: This stage of the market research process involves with the gathering and collecting of the market/industry related data from the sources. There are basically two types of research methods:

Primary Research: By conducting primary research, it involves with the two types of data gathering; exploratory and specific. Exploratory data is open-ended and helps us to define a particular problem involving surveys, and pilot study to the specific consumer group, knowing their needs and wants catering to the industry related product/service offering. Explanatory data gathering follows with the bit of unstructured way. Our analyst group leads the study by focusing on the key crowd, in this manner picking up bits of knowledge from them. In light of the points of view of the clients, this data is used to plan advertise techniques. In addition, showcase overviews causes us to comprehend the current scenario of the business. Specific data gathering on the hand, involves with the more structured and formal way. The primary research usually includes in telephonic conversations, E-mail collaborations and up close and personal meetings/interviews with the raw material suppliers, industrial wholesalers, and independent consultants/specialists. The interviews that we conduct offers important information on showcase size and industry development patterns. Our company likewise conducts interviews with the different business specialists so as to increase generally bits of knowledge of the business/showcase.
Secondary Research: The secondary research incorporates with the data gathering from the non-profit associations and organizations, for example, World bank, WHO, investor relations and their presentations, statistical databases, yearly(annual reports) reports, national government records, factual databases, websites, articles, white papers, press releases, blogs and others. From the annual report, we deduce an organization's income/revenue generation to comprehend the key product segment related to the market. We examine the organization sites and implement product mapping strategy which is significant for determining the segment revenue. In the product mapping technique, we choose and categorize the products offered by the companies catering to the industry specific market, derive the segment revenue for each of the organizations to get the market estimation. We also gather data & Information based on the supply and demand side of the value chain involved with the domain specific market. The supply side denotes the distributors, wholesalers, suppliers and the demand side denotes the end-consumers/customers of the value chain. The supply side of the market is analyzed by examining the product growth across industry in each of the region followed by its pricing analysis. The demand side is analyzed by the evaluating the penetration level and adoption rates of the product by referring to the historical/past data, examine the present usage and forecasting the future trends.
Purchased Database: Our purchased data provides insights about the key market players/companies along with their financial analysis. Additionally, our data base also includes market related information.

We also have the agreements with various reputed data providers, consultants and third party vendors who provide information which are not limited to:

Export & Import Data
Business Information related to trade and its statistics
Penetration level of a particular product/service based on geography mainly focusing on the unmet prerequisites of the customers.

In-house Library: Apart from these third-party sources, we have our in-house library of quantitative and qualitative data & information. Our in-house database includes market data for various industry and domains. These data are updated on regular basis as per the changing market scenario. Our library includes, internal audit reports, historic databases, archives and journal publications. Sometimes there are instances where there is no metadata or raw data available for any domain specific market. For those particular cases, we utilize our expertise to forecast and estimate the market size in order to generate comprehensive data sets. Our analyst team adopts a robust research technique in order to deduce the market size and its estimates:
Examining demographic along with psychographic segmentation for market evaluation
Analyzing the macro and micro-economic indicators for each demography
Evaluating the current industry trends popular in the market.

Data Synthesis: This stage includes the evaluation and assessment of all the data acquired from the primary and secondary research. It likewise includes in evaluating the information for any disparity watched while information gathering identified with the market. The data & information is gathered with consideration to the heterogeneity of sources. Scientific and statistical methods are implemented for synthesizing dissimilar information sets and provide the relevant data which is fundamental for formulating strategies. Our organization has broad involvement with information amalgamation where the information goes through different stages:

Information Screening: Information screening is the way toward examining information/data gathered from the sources for errors/mistakes and amending it before data integration process. The screening includes in looking at raw information, identifying and distinguishing mistakes and managing missing information. The reason for the information screening is to ensure information is effectively entered or not. Our organization utilizes objective and precise information screening grades through repetitive quality checks.
Data Integration: The data integration method involves with the incorporation of numerous information streams. The data streams is important so as to deliver investigate examines that give overall market scenario to the investors. These information streams originate from different research contemplates and our in house database. After the screening of the information, our analysts conduct efficient integration of the data streams, optimizing connections between integrated surveys and syndicated data sources. There are two research approaches that we follow so as to coordinate our information; top down methodology and bottom up methodology.

Top-down analysis generally refers to using broad factors as a basis for decision making. The top-down approach helps in identifying the overall market scenario along with the external and internal factors effecting the market growth.

The bottom-up approach takes a completely different approach. Generally, the bottom-up approach focuses its analysis on micro attributes and specific characteristics of the domain specific market.

Market Formulation & Deduction: The last stage includes assigning the data & information in a suitable way in order to derive market size. Analyst reviews and domain based opinions based on holistic approach of market estimation combined with industry investigation additionally features a crucial role in this stage.

This stage includes with the finalization of the market size and numbers that we have gathered from primary and secondary research. With the data & information addition, we ensure that there is no gap in the market information. Market trend analysis is finished by our analysts by utilizing data extrapolation procedures, which give the most ideal figures to the market.

Data Validation: Validation is the most crucial step in the process. Validation & re-validation through scientifically designed technique and process that helps us finalize data-points to be used for final calculations. This stage also involves with the data triangulation process. Data triangulation generally implicates the cross validation and matching the data which has been collected from primary and secondary research methods.

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ProactiveWe manage our resources 24/7 to identify issues and address them before they become problems

Quality & ReliabilityWe are committed to providing reliable and highly accurate data with an excellent quality control system

Global Outreach6 Major regions and 40+ countries level analysis accomplished

Competitive PricingOur pricing strategy is highly competitive in the market, without compensating on the quality and the timeline of project delivery

Testimonials

Hi John,
Thanks for the report. We've been going through it and see some good data on the market and players. –

Kennedy Brown
Health Technology Innovation
United States

Hi Rahul,
Thank You for the report it is good and beneficial for me.
Thank You in Advance

Mika Salomäki

Dear Siddhartha,
Thank you for your fast reply. The report arrived safe and sound, evrything looks all right.
Thank you very much for your assitance and I will be looking forward to another opportunity for cooperation.

ONDŘEJ ŠUPKA
Analytics Department
ČESKÁ ZBROJOVKA A.S.

Dear Siddhartha,
The report looks good, and we believe the material mix is more realistic now. It is good to know you report “Net” Manufacturing Selling Price, as that can make a difference in how we view the numbers. The reports were great and we appreciate your working with us.
Thanks for all your help!