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Global Deep Learning Chipset Market By Type (Graphics Processing Units (GPUs), Central Processing Units (CPUs), and Others), By Application (Consumer, Aerospace, and Others), By Region and Key Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends and Forecast 2019–2028

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    The report on Deep Learning Chipset Market offers in-depth analysis on market trends, drivers, restraints, opportunities etc. Along with qualitative information, this report include the quantitative analysis of various segments in terms of market share, growth, opportunity analysis, market value, etc. for the forecast years. The global deep learning chipset market is segmented on the basis of type, application and geography.

    The worldwide market for Deep Learning Chipset Market is expected to grow at a CAGR of roughly 25.2% over the next ten years, and will reach US$ 30,559.2 Mn in 2028, from US$ 3,222.1 Mn in 2018, according to a new Market.us (Prudour Research) study.

    Deep Learning Chipset Market Scope:

    By type, the market is segmented into Graphics Processing Units (GPUs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs) and Field Programmable Gate Arrays (FPGAs). By application, the market is divided into Consumer, Aerospace, Military & Defense, Automotive, Industrial and Medical. Based on geography, market is analyzed across North America, Europe, Asia-Pacific, Latin America and Middle East and Africa. Major players profiled in the report include NVIDIA, Intel, IBM, Qualcomm, CEVA, KnuEdge, AMD, Xilinx, ARM, Google, Graphcore, TeraDeep, Wave Computing and BrainChip.

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    trending_up Total Revenue in 2018

    $3,222.1 Mn

    trending_up Market CAGR of the Next Ten Years

    25.2%

    no_encryption Market Value (US$ Mn), Share (%) and Growth Rate (%) Comparison 2012-2028

    Purchase this report or a membership to unlock the market value (US$ Mn), share (%) and growth rate (%) comparison for this industry.
    • By Type
    • By Region
    • By Application
    no_encryption Leading Companies Financial Highlights

    Purchase this report or a membership to unlock the leading companies financial highlights for this industry.

    trending_up Market Revenue of the Next Ten Years

    $30,559.2 Mn

    Key Market Segments:

    Type

    • Graphics Processing Units (GPUs)
    • Central Processing Units (CPUs)

    Application

     

    • Field Programmable Gate Arrays (FPGAs) Application
    • Specific Integrated Circuits (ASICs)
    • Consumer
    • Aerospace, Military & Defense
    • Automotive
    • Industrial
    • Medical

    Key Market Players included in the report:

    • NVIDIA
    • Intel
    • IBM
    • Qualcomm
    • CEVA
    • KnuEdge
    • AMD
    • Xilinx
    • ARM
    • Google
    • Graphcore
    • TeraDeep
    • Wave Computing
    • BrainChip

    Reasons to Get this Report:

    In an insight outlook, this research report has dedicated to several quantities of analysis - industry research (global industry trends) and Deep Learning Chipset Market share analysis of high players, along with company profiles and which collectively include about the fundamental opinions regarding the market landscape. Emerging and high-growth sections of Deep Learning Chipset Market, high-growth regions, and market drivers, restraints and also market chances.

    The analysis covers Deep Learning Chipset Market and its advancements across different industry verticals as well as regions. It targets estimating the current market size and growth potential of the global Deep Learning Chipset Market across sections such as also application and representatives.

    Additionally, the analysis also has a comprehensive review of the crucial players on the Deep Learning Chipset Market together side their company profiles, SWOT analysis, latest advancements and business plans.

    The analysis objectives of the report are:

    • To equitably share in-depth info regarding the crucial elements impacting the increase of industry (growth capacity, chances, drivers and industry-specific challenges and risks).
    • To know the Deep Learning Chipset Market by pinpointing its many subsegments.
    • To profile the important players and analyze their growth plans.
    • To endeavor the amount and value of Deep Learning Chipset sub-markets, depending on key regions (various vital states).
    • To analyze Deep Learning Chipset Market concerning growth trends, prospects and also their participation in the entire sector.
    • To examine and study the Deep Learning Chipset Market size (volume & value) from the company, essential regions/countries, products and application, background information from 2012 to 2018 and also prediction to 2028.
    • Primary worldwide Deep Learning Chipset Market manufacturing companies, to specify, clarify and analyze the product sales amount, value and market share, market rivalry landscape, SWOT analysis and development plans next coming years.
    • To examine competitive progress such as expansions, arrangements, new product launches and acquisitions on the market.

    For the Deep Learning Chipset Market research study, the following years have been considered to estimate the market size:

    Particular Scope
    Region

    • North America

    • Europe

    • Asia Pacific

    • Latin America

    • Middle East and Africa

    Historic Year 2015 to 2020
    Estimated Year 2021
    Forecast Year 2022 to 2031

    Deep Learning Chipset Market

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    • 1. Deep Learning Chipset Market Introduction
      • 1.1. Definition
      • 1.2. Taxonomy
      • 1.3. Research Scope
    • 2. Executive Summary
      • 2.1. Key Findings by Major Segments
      • 2.2. Top strategies by Major Players
    • 3. Global Deep Learning Chipset Market Overview
      • 3.1. Deep Learning Chipset Market Dynamics
        • 3.1.1. Drivers
        • 3.1.2. Opportunities
        • 3.1.3. Restraints
        • 3.1.4. Challenges
      • 3.2. PESTLE Analysis
      • 3.3. Opportunity Map Analysis
      • 3.4. PORTER'S Five Forces Analysis
      • 3.5. Market Competition Scenario Analysis
      • 3.6. Product Life Cycle Analysis
      • 3.7. Opportunity Orbits
      • 3.8. Manufacturer Intensity Map
    • 4. Global Deep Learning Chipset Market Value (US$ Mn), Share (%), and Growth Rate (%) Comparison by Type, 2012-2028
      • 4.1. Global Deep Learning Chipset Market Analysis by Type: Introduction
      • 4.2. Market Size and Forecast by Region
      • 4.3. Graphics Processing (US$ Mn)s (GPUs)
      • 4.4. Central Processing (US$ Mn)s (CPUs)
      • 4.5. Application Specific Integrated Circuits (ASICs)
      • 4.6. Field Programmable Gate Arrays (FPGAs)
    • 5. Global Deep Learning Chipset Market Value (US$ Mn), Share (%), and Growth Rate (%) Comparison by Application, 2012-2028
      • 5.1. Global Deep Learning Chipset Market Analysis by Application: Introduction
      • 5.2. Market Size and Forecast by Region
      • 5.3. Consumer
      • 5.4. Aerospace, Military & Defense
      • 5.5. Automotive
      • 5.6. Industrial
      • 5.7. Medical
    • 6. Global Deep Learning Chipset Market Value (US$ Mn), Share (%), and Growth Rate (%) Comparison by Region, 2012-2028
      • 6.1. North America
        • 6.1.1. North America Deep Learning Chipset Market: Regional Trend Analysis
          • 6.1.1.1. US
          • 6.1.1.2. Canada
          • 6.1.1.3. Mexico
      • 6.2. Europe
        • 6.2.1. Europe Deep Learning Chipset Market: Regional Trend Analysis
          • 6.2.1.1. Germany
          • 6.2.1.2. France
          • 6.2.1.3. UK
          • 6.2.1.4. Russia
          • 6.2.1.5. Italy
          • 6.2.1.6. Rest of Europe
      • 6.3. Asia-Pacific
        • 6.3.1. Asia-Pacific Deep Learning Chipset Market: Regional Trend Analysis
          • 6.3.1.1. China
          • 6.3.1.2. Japan
          • 6.3.1.3. Korea
          • 6.3.1.4. India
          • 6.3.1.5. Rest of Asia
      • 6.4. Latin America
        • 6.4.1. Latin America Deep Learning Chipset Market: Regional Trend Analysis
          • 6.4.1.1. Brazil
          • 6.4.1.2. Argentina
          • 6.4.1.3. Rest of Latin America
      • 6.5. Middle East and Africa
        • 6.5.1. Middle East and Africa Deep Learning Chipset Market: Regional Trend Analysis
          • 6.5.1.1. GCC
          • 6.5.1.2. South Africa
          • 6.5.1.3. Israel
          • 6.5.1.4. Rest of MEA
    • 7. Global Deep Learning Chipset Market Competitive Landscape, Market Share Analysis, and Company Profiles
      • 7.1. Market Share Analysis
      • 7.2. Company Profiles
      • 7.3. NVIDIA
        • 7.3.1. Company Overview
        • 7.3.2. Financial Highlights
        • 7.3.3. Product Portfolio
        • 7.3.4. SWOT Analysis
        • 7.3.5. Key Strategies and Developments
      • 7.4. Intel
        • 7.4.1. Company Overview
        • 7.4.2. Financial Highlights
        • 7.4.3. Product Portfolio
        • 7.4.4. SWOT Analysis
        • 7.4.5. Key Strategies and Developments
      • 7.5. IBM
        • 7.5.1. Company Overview
        • 7.5.2. Financial Highlights
        • 7.5.3. Product Portfolio
        • 7.5.4. SWOT Analysis
        • 7.5.5. Key Strategies and Developments
      • 7.6. Qualcomm
        • 7.6.1. Company Overview
        • 7.6.2. Financial Highlights
        • 7.6.3. Product Portfolio
        • 7.6.4. SWOT Analysis
        • 7.6.5. Key Strategies and Developments
      • 7.7. CEVA
        • 7.7.1. Company Overview
        • 7.7.2. Financial Highlights
        • 7.7.3. Product Portfolio
        • 7.7.4. SWOT Analysis
        • 7.7.5. Key Strategies and Developments
      • 7.8. KnuEdge
        • 7.8.1. Company Overview
        • 7.8.2. Financial Highlights
        • 7.8.3. Product Portfolio
        • 7.8.4. SWOT Analysis
        • 7.8.5. Key Strategies and Developments
      • 7.9. AMD
        • 7.9.1. Company Overview
        • 7.9.2. Financial Highlights
        • 7.9.3. Product Portfolio
        • 7.9.4. SWOT Analysis
        • 7.9.5. Key Strategies and Developments
      • 7.10. Xilinx
        • 7.10.1. Company Overview
        • 7.10.2. Financial Highlights
        • 7.10.3. Product Portfolio
        • 7.10.4. SWOT Analysis
        • 7.10.5. Key Strategies and Developments
      • 7.11. ARM
        • 7.11.1. Company Overview
        • 7.11.2. Financial Highlights
        • 7.11.3. Product Portfolio
        • 7.11.4. SWOT Analysis
        • 7.11.5. Key Strategies and Developments
      • 7.12. Google
        • 7.12.1. Company Overview
        • 7.12.2. Financial Highlights
        • 7.12.3. Product Portfolio
        • 7.12.4. SWOT Analysis
        • 7.12.5. Key Strategies and Developments
      • 7.13. Graphcore
        • 7.13.1. Company Overview
        • 7.13.2. Financial Highlights
        • 7.13.3. Product Portfolio
        • 7.13.4. SWOT Analysis
        • 7.13.5. Key Strategies and Developments
      • 7.14. TeraDeep
        • 7.14.1. Company Overview
        • 7.14.2. Financial Highlights
        • 7.14.3. Product Portfolio
        • 7.14.4. SWOT Analysis
        • 7.14.5. Key Strategies and Developments
      • 7.15. Wave Computing
        • 7.15.1. Company Overview
        • 7.15.2. Financial Highlights
        • 7.15.3. Product Portfolio
        • 7.15.4. SWOT Analysis
        • 7.15.5. Key Strategies and Developments
      • 7.16. BrainChip
        • 7.16.1. Company Overview
        • 7.16.2. Financial Highlights
        • 7.16.3. Product Portfolio
        • 7.16.4. SWOT Analysis
        • 7.16.5. Key Strategies and Developments
    • 8. Assumptions and Acronyms
    • 9. Research Methodology
    • 10. Contact
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    • NVIDIA
    • Intel
    • IBM
    • Qualcomm
    • CEVA
    • KnuEdge
    • AMD
    • Xilinx
    • ARM
    • Google
    • Graphcore
    • TeraDeep
    • Wave Computing
    • BrainChip

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