Deep Learning Chipset Market by Type (Application Specific Integrated Circuits, Central Processing Units, Field Programmable Gate Arrays), End-User (Aerospace & Defense, Automotive, Consumer Electronics) - Global Forecast 2024-2030
The Deep Learning Chipset Market size was estimated at USD 10.23 billion in 2023 and expected to reach USD 11.82 billion in 2024, at a CAGR 15.69% to reach USD 28.39 billion by 2030.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Deep Learning Chipset Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Deep Learning Chipset Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Deep Learning Chipset Market, highlighting leading vendors and their innovative profiles. These include Advanced Micro Devices, Inc., ARM Holdings, Google LLC, Graphcore, Huawei Technologies, Intel Corporation, International Business Machines Corporation, LG Electronics, Mythic AI, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung Electronics Co., Ltd., Taiwan Semiconductor Manufacturing Company, Xilinx, Inc., and Zero ASIC Corporation.
Market Segmentation & Coverage
This research report categorizes the Deep Learning Chipset Market to forecast the revenues and analyze trends in each of the following sub-markets:
Type
Application Specific Integrated Circuits
Central Processing Units
Field Programmable Gate Arrays
Graphics Processing Units
End-User
Aerospace & Defense
Automotive
Consumer Electronics
Healthcare
Industrial
Region
Americas
Argentina
Brazil
Canada
Mexico
United States
California
Florida
Illinois
New York
Ohio
Pennsylvania
Texas
Asia-Pacific
Australia
China
India
Indonesia
Japan
Malaysia
Philippines
Singapore
South Korea
Taiwan
Thailand
Vietnam
Europe, Middle East & Africa
Denmark
Egypt
Finland
France
Germany
Israel
Italy
Netherlands
Nigeria
Norway
Poland
Qatar
Russia
Saudi Arabia
South Africa
Spain
Sweden
Switzerland
Turkey
United Arab Emirates
United Kingdom
The report offers valuable insights on the following aspects:
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
The report addresses key questions such as:
1. What is the market size and forecast of the Deep Learning Chipset Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Deep Learning Chipset Market?
3. What are the technology trends and regulatory frameworks in the Deep Learning Chipset Market?
4. What is the market share of the leading vendors in the Deep Learning Chipset Market?
5. Which modes and strategic moves are suitable for entering the Deep Learning Chipset Market?PDF E-mail From Publisher (2-5)Users License
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency & Pricing
- 1.5. Language
- 1.6. Limitations
- 1.7. Assumptions
- 1.8. Stakeholders
- 2. Research Methodology
- 2.1. Define: Research Objective
- 2.2. Determine: Research Design
- 2.3. Prepare: Research Instrument
- 2.4. Collect: Data Source
- 2.5. Analyze: Data Interpretation
- 2.6. Formulate: Data Verification
- 2.7. Publish: Research Report
- 2.8. Repeat: Report Update
- 3. Executive Summary
- 4. Market Overview
- 4.1. Introduction
- 4.2. Deep Learning Chipset Market, by Region
- 5. Market Insights
- 5.1. Market Dynamics
- 5.1.1. Drivers
- 5.1.1.1. Growing acceptance of cloud-based technology
- 5.1.1.2. Increasing application of big data analytics across industries
- 5.1.1.3. Rising quantum computing and enhanced implementation of deep learning chips in robotics
- 5.1.2. Restraints
- 5.1.2.1. Lack of skilled expertise and trained professional
- 5.1.3. Opportunities
- 5.1.3.1. Ongoing need to develop human-aware AI systems
- 5.1.3.2. Emerging development of autonomous robots
- 5.1.4. Challenges
- 5.1.4.1. Reduced return on investment and limited structural data available
- 5.2. Market Segmentation Analysis
- 5.3. Market Trend Analysis
- 5.4. Cumulative Impact of High Inflation
- 5.5. Porter’s Five Forces Analysis
- 5.5.1. Threat of New Entrants
- 5.5.2. Threat of Substitutes
- 5.5.3. Bargaining Power of Customers
- 5.5.4. Bargaining Power of Suppliers
- 5.5.5. Industry Rivalry
- 5.6. Value Chain & Critical Path Analysis
- 5.7. Regulatory Framework
- 6. Deep Learning Chipset Market, by Type
- 6.1. Introduction
- 6.2. Application Specific Integrated Circuits
- 6.3. Central Processing Units
- 6.4. Field Programmable Gate Arrays
- 6.5. Graphics Processing Units
- 7. Deep Learning Chipset Market, by End-User
- 7.1. Introduction
- 7.2. Aerospace & Defense
- 7.3. Automotive
- 7.4. Consumer Electronics
- 7.5. Healthcare
- 7.6. Industrial
- 8. Americas Deep Learning Chipset Market
- 8.1. Introduction
- 8.2. Argentina
- 8.3. Brazil
- 8.4. Canada
- 8.5. Mexico
- 8.6. United States
- 9. Asia-Pacific Deep Learning Chipset Market
- 9.1. Introduction
- 9.2. Australia
- 9.3. China
- 9.4. India
- 9.5. Indonesia
- 9.6. Japan
- 9.7. Malaysia
- 9.8. Philippines
- 9.9. Singapore
- 9.10. South Korea
- 9.11. Taiwan
- 9.12. Thailand
- 9.13. Vietnam
- 10. Europe, Middle East & Africa Deep Learning Chipset Market
- 10.1. Introduction
- 10.2. Denmark
- 10.3. Egypt
- 10.4. Finland
- 10.5. France
- 10.6. Germany
- 10.7. Israel
- 10.8. Italy
- 10.9. Netherlands
- 10.10. Nigeria
- 10.11. Norway
- 10.12. Poland
- 10.13. Qatar
- 10.14. Russia
- 10.15. Saudi Arabia
- 10.16. South Africa
- 10.17. Spain
- 10.18. Sweden
- 10.19. Switzerland
- 10.20. Turkey
- 10.21. United Arab Emirates
- 10.22. United Kingdom
- 11. Competitive Landscape
- 11.1. FPNV Positioning Matrix
- 11.2. Market Share Analysis, By Key Player
- 11.3. Competitive Scenario Analysis, By Key Player
- 12. Competitive Portfolio
- 12.1. Key Company Profiles
- 12.1.1. Advanced Micro Devices, Inc.
- 12.1.2. ARM Holdings
- 12.1.3. Google LLC
- 12.1.4. Graphcore
- 12.1.5. Huawei Technologies
- 12.1.6. Intel Corporation
- 12.1.7. International Business Machines Corporation
- 12.1.8. LG Electronics
- 12.1.9. Mythic AI
- 12.1.10. NVIDIA Corporation
- 12.1.11. Qualcomm Technologies, Inc.
- 12.1.12. Samsung Electronics Co., Ltd.
- 12.1.13. Taiwan Semiconductor Manufacturing Company
- 12.1.14. Xilinx, Inc.
- 12.1.15. Zero ASIC Corporation
- 12.2. Key Product Portfolio
- 13. Appendix
- 13.1. Discussion Guide
- 13.2. License & Pricing
- FIGURE 1. DEEP LEARNING CHIPSET MARKET RESEARCH PROCESS
- FIGURE 2. DEEP LEARNING CHIPSET MARKET SIZE, 2023 VS 2030
- FIGURE 3. DEEP LEARNING CHIPSET MARKET SIZE, 2018-2030 (USD MILLION)
- FIGURE 4. DEEP LEARNING CHIPSET MARKET SIZE, BY REGION, 2023 VS 2030 (%)
- FIGURE 5. DEEP LEARNING CHIPSET MARKET SIZE, BY REGION, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 6. DEEP LEARNING CHIPSET MARKET DYNAMICS
- FIGURE 7. DEEP LEARNING CHIPSET MARKET SIZE, BY TYPE, 2023 VS 2030 (%)
- FIGURE 8. DEEP LEARNING CHIPSET MARKET SIZE, BY TYPE, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 9. DEEP LEARNING CHIPSET MARKET SIZE, BY END-USER, 2023 VS 2030 (%)
- FIGURE 10. DEEP LEARNING CHIPSET MARKET SIZE, BY END-USER, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 11. AMERICAS DEEP LEARNING CHIPSET MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
- FIGURE 12. AMERICAS DEEP LEARNING CHIPSET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 13. UNITED STATES DEEP LEARNING CHIPSET MARKET SIZE, BY STATE, 2023 VS 2030 (%)
- FIGURE 14. UNITED STATES DEEP LEARNING CHIPSET MARKET SIZE, BY STATE, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 15. ASIA-PACIFIC DEEP LEARNING CHIPSET MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
- FIGURE 16. ASIA-PACIFIC DEEP LEARNING CHIPSET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 17. EUROPE, MIDDLE EAST & AFRICA DEEP LEARNING CHIPSET MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
- FIGURE 18. EUROPE, MIDDLE EAST & AFRICA DEEP LEARNING CHIPSET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 19. DEEP LEARNING CHIPSET MARKET, FPNV POSITIONING MATRIX, 2023
- FIGURE 20. DEEP LEARNING CHIPSET MARKET SHARE, BY KEY PLAYER, 2023
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