The global deep learning chip market accounted to US$ 2.04 Bn in 2018 and is expected to grow at a CAGR of 30.0% during the forecast period 2019 – 2027, to account to US$ 21.31 Bn by 2027.
North America leads the global deep learning chip market, and it is anticipated to be the highest revenue contributor throughout the forecast period. Deep learning chip development is backed by large-scale investment from technological giants to develop patterns from a huge amount of generated data. The rise of quantum computing and the implementation of deep learning chips in robotics is driving the growth of the deep learning chip market in the North American countries.
Lucrative Regional Deep Learning Chip Market
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Market Insights
The prominence of Quantum Computing contribute to the deep learning chip market growth
Quantum computing takes seconds to finish a calculation that would otherwise take more time. Quantum computers are an innovative transformation of artificial intelligence, machine learning, and big data. Therefore, the prominence of quantum computing is expected to drive the growth of the deep learning chip market. Furthermore, quantum computing is beneficial for various factors including, portfolio optimization, fraud detection, and risk management, and the areas where immediate data feedback is required. Thus, it is easier for a single processor to perform complex calculations in seconds. Additionally, with the internet's scale and size, deep learning helps to maintain large data sets at a very low cost. Hence, these factors expected to boost the growth of the global deep learning chip market
Real-time consumer behavior insights and increased operational efficiency to propel the overall growth of deep learning chip market
The nature of business is becoming very competitive and to compete efficiently, enterprises nowadays relying on useful information and business analytics. Traditionally, business analytical tools were used to project sales from the data about events that were a week or month old. With the advent of artificial intelligence technology which learns in real-time and provides recommendations based on patterns, businesses have a tremendous opportunity to apply deep learning in various processes to better understand the business environment and customers.
Considering these factors, artificial intelligence enables businesses to improve operational efficiency, lower operating costs, enhance service quality and customer experience.
Chip Type Insights
Graphic Processing Units (GPUs) held the major deep learning chip market share in 2018, whereas Application-Specific Integrated Circuits (ASICs) is expected to be the fastest-growing segment during the forecast period. Owing to the factor that ASICs are very specific and less flexible but they are one of the highest performing hardware options available for artificial intelligence applications.
Technology Insights
The deep learning chipsets include system-on-chip, system-in-package, multi-chip module, and others, and other chipsets. The system-on-chip segment held the major deep learning chip market share in 2018, as it helps in reducing energy waste, space occupied by the large systems, and costs.
Industry Vertical Insights
The global deep learning chip market is categorized into BFSI, Retail, IT & Telecom, Automotive & Transportation, Healthcare, Media & Entertainment, and Others. BFSI held the major market share in the deep learning chip market, whereas healthcare is expected to be the fastest-growing segment in the market. The factors such as lessening the operational cost, adapting to changing compliances and regulations, focusing on core business, and integrating automation in business processes are other major factors that are fueling the growth BFSI segment in the deep learning chip market
Rest of EU Deep Learning Chip Market by Industry Vertical
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Rest of EU Deep Learning Chip Market by Industry Vertical
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Deep Learning Chip Market: Strategic Insights
Market Size Value in US$ 2.04 Billion in 2018 Market Size Value by US$ 21.31 Billion by 2027 Growth rate CAGR of 30.0% from 2019-2027 Forecast Period 2019-2027 Base Year 2019
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We can optimize and tailor the analysis and scope which is unmet through our standard offerings. This flexibility will help you gain the exact information needed for your business planning and decision making.
Deep Learning Chip Market: Strategic Insights
Market Size Value in | US$ 2.04 Billion in 2018 |
Market Size Value by | US$ 21.31 Billion by 2027 |
Growth rate | CAGR of 30.0% from 2019-2027 |
Forecast Period | 2019-2027 |
Base Year | 2019 |
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Speak to AnalystThe market players present in the deep learning chip market are mainly focusing on product enhancements by implementing advanced technologies. By signing partnerships, contracts, joint ventures, funding, and inaugurating new offices across the world permit the company to maintain its brand name globally. Few of the recent developments are listed below;
2019: NVIDIA has partnered with Hackster.io to launch the AI at the Edge Challenge, a competition where developers utilize the NVIDIA Jetson Nano Developer Kit for building creative and unique projects and earn a chance to win from $100K in prizes.
2019: Intel announced its plans to expand the Oregon factory to produce a 7nm chip. Intel’s new factory will be the third phase of D1X, a massive factory Intel began in 2010. Each of the first two phases was 1.1. Million square feet, creating a combined facility equivalent to 15 Costco warehouse stores. The third phase will apparently increase D1X’s manufacturing space by about 50 percent. Further, Intel says its factory expansion will enable it to respond 60 percent faster to chip shortages.
2019: Huawei launched HiSecEngine USG12000, Industry's first T-level AIFW. The HiSecEngine USG12000 is equipped with Ascend AI chips, which provides intelligent detection capabilities as well as intelligent border defense for enterprise networks.
GLOBAL DEEP LEARNING CHIP MARKET SEGMENTATION
By Chip Type
- GPU
- ASIC
- FPGA
- CPU
- Others
By Technology
- System-on-Chip
- System-in-Package
- Multi-chip Module
- Others
By Industry Vertical
- Media & Advertising
- BFSI, IT & Telecom
- Retail
- Healthcare
- Automotive & Transportation
- Others
By Geography
North America
- U.S.
- Canada
- Mexico
Europe
- France
- Germany
- UK
- Russia
- Italy
- Rest of Europe
Asia Pacific (APAC)
- Australia
- China
- India
- Japan
- South Korea
- Rest of APAC
Middle East & Africa (MEA)
- Saudi Arabia
- South Africa
- UAE
- Rest of MEA
South America (SAM)
- Brazil
- Argentina
- Rest of SAM
Company Profiles
- Advanced Micro Devices, Inc.
- Alphabet Inc. (Google)
- Amazon.com, Inc.
- Baidu, Inc.
- Huawei Technologies Co., Ltd
- Intel Corporation
- NVIDIA Corporation
- Qualcomm Incorporated
- Samsung Electronics Co., Ltd.
- Xilinx, Inc.
Report Coverage
Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends
Segment Covered
Chip Type ; Technology ; Industry Vertical
Regional Scope
North America, Europe, Asia Pacific, Middle East & Africa, South & Central America
Country Scope
US, Canada, Mexico, UK, Germany, Spain, Italy, France, India, China, Japan, South Korea, Australia, UAE, Saudi Arabia, South Africa, Brazil, Argentina
Frequently Asked Questions
North America is one of the fastest-growing regions in terms of technological development. In the past 3 years, the region witnessed significant adoption of AI solutions across all the sectors. North America contributes the largest market share in terms of revenue, and it is estimated that it will continue its dominance in the market share during the forecast period. Deep learning chip development is backed by large-scale investment from technological giants to develop patterns from huge amount of generated data. The rise of quantum computing and implementation of deep learning chips in robotics drive the growth of the deep learning chip market in the North American countries.
Presently, the major applications of deep learning chips are in the data center/cloud computing segment, and this trend is expected to continue during the forecast period. Also, majorly due to rising adoption of AI in developing regions, evolving architectures of deep learning chips and increasing applications across various industry verticals. Owing to this growing trend, the companies are anticipated to produce high-quality service by adopting cloud-based artificial intelligence services.
The BFSI industry dominated the deep learning chip market in the year 2018. Banking, financial services, and insurance (BFSI) industries have great potential for deep learning chips due to the presence of huge financial and personal data of customers. In this sector, a high amount of sensitive data is generated and exchanged every day. There is growing volume and creation of endpoints and mobile devices in banks, credit card companies, and credit reporting institutions, thus, it becomes important for these industry verticals to harness this data to gain insights about various business aspects.
The List of Companies - Deep Learning Chip Market
- Advanced Micro Devices, Inc.
- Alphabet Inc. (Google)
- Amazon.com, Inc.
- Baidu, Inc.
- Huawei Technologies Co., Ltd
- Intel Corporation
- NVIDIA Corporation
- Qualcomm Incorporated
- Samsung Electronics Co., Ltd.
- Xilinx, Inc.
The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.
- Data Collection and Secondary Research:
As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.
Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.
- Primary Research:
The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.
For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.
A typical research interview fulfils the following functions:
- Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
- Validates and strengthens in-house secondary research findings
- Develops the analysis team’s expertise and market understanding
Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:
- Industry participants: VPs, business development managers, market intelligence managers and national sales managers
- Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.
Below is the breakup of our primary respondents by company, designation, and region:
Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.
- Data Analysis:
Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.
- 3.1 Macro-Economic Factor Analysis:
We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.
- 3.2 Country Level Data:
Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.
- 3.3 Company Profile:
The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.
- 3.4 Developing Base Number:
Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.
- Data Triangulation and Final Review:
The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.
We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.
We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.
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