Deep Learning Chipset Market: Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2024-2032

Description

Persistence Market Research has recently released a comprehensive report on the worldwide market for deep learning chipsets. The report offers a thorough assessment of crucial market dynamics, including drivers, trends, opportunities, and challenges, providing detailed insights into the market structure.

Key Insights:

Deep Learning Chipset Market Size (2024E): USD 10.1 Billion
Projected Market Value (2032F): USD 72.8 Billion
Global Market Growth Rate (CAGR 2024 to 2032): 28.0%

Deep Learning Chipset Market - Report Scope:

Deep learning chipsets are integral components in various applications such as data centers, autonomous vehicles, healthcare, and consumer electronics. These chipsets enable complex computations required for artificial intelligence (AI) and machine learning (ML) tasks, driving advancements in technology and innovation. The deep learning chipset market caters to a broad range of industries, including technology giants, automotive manufacturers, healthcare providers, and consumer electronics companies. Market growth is driven by the increasing adoption of AI and ML, the surge in big data analytics, and advancements in chipset technology enhancing computational power and efficiency.

Market Growth Drivers:

The global deep learning chipset market is propelled by several key factors, including the rising demand for AI and ML applications across various industries. The growing volume of data generated by digital transformation initiatives and the need for real-time data processing drive the adoption of deep learning chipsets. Technological advancements, such as the development of application-specific integrated circuits (ASICs), graphics processing units (GPUs), and tensor processing units (TPUs), offer improved performance, energy efficiency, and scalability, fostering market growth. Moreover, the increasing investment in AI research and development, coupled with the expansion of cloud-based services and edge computing, creates new avenues for market players to reach a wider customer base.

Market Restraints:

Despite promising growth prospects, the deep learning chipset market faces challenges related to high development costs, technical complexities, and regulatory compliance. The substantial investment required for designing and manufacturing advanced chipsets poses financial barriers for small and medium-sized enterprises (SMEs). Additionally, the technical complexities associated with integrating deep learning chipsets into existing infrastructure and ensuring compatibility with various AI frameworks can hinder market penetration. Regulatory compliance and data privacy concerns also pose challenges, particularly in industries such as healthcare and finance, where stringent regulations govern the use of AI and ML technologies.

Market Opportunities:

The deep learning chipset market presents significant growth opportunities driven by technological innovations, emerging applications, and evolving business models. The integration of AI and ML into emerging fields such as autonomous vehicles, robotics, and smart cities enhances market scope and stimulates innovation. Strategic partnerships, mergers, and acquisitions enable companies to leverage complementary technologies and expand their product portfolios. Investment in research and development, coupled with the introduction of cost-effective, energy-efficient chipsets, is essential to capitalize on emerging opportunities and sustain market leadership in the dynamic deep learning landscape.

Key Questions Answered in the Report:

What are the primary factors driving the growth of the deep learning chipset market globally?
Which chipset types and applications are driving deep learning adoption across different industries?
How are technological advancements reshaping the competitive landscape of the deep learning chipset market?
Who are the key players contributing to the deep learning chipset market, and what strategies are they employing to maintain market relevance?
What are the emerging trends and future prospects in the global deep learning chipset market?

Competitive Intelligence and Business Strategy:

Leading players in the global deep learning chipset market, including NVIDIA Corporation, Intel Corporation, and Advanced Micro Devices, Inc., focus on innovation, product differentiation, and strategic partnerships to gain a competitive edge. These companies invest in R&D to develop advanced deep learning chipsets, including GPUs, TPUs, and ASICs, catering to diverse AI and ML applications. Collaborations with technology providers, academic institutions, and regulatory agencies facilitate market access and promote technology adoption. Moreover, emphasis on open-source frameworks, developer communities, and customer education fosters market growth and enhances user experience in the rapidly evolving deep learning landscape.

Key Companies Profiled:

Alphabet Inc.
Amazon.Com, Inc.
Advanced Micro Devices, Inc.
Baidu, Inc.
Bitmain Technologies Ltd.
Intel Corporation
Nvidia Corporation
Qualcomm Incorporated
Samsung Electronics Co. Ltd.
Xilinx, Inc.

Global Deep Learning Chipset Market Outlook by Category

By Type:

Central Processing Units (CPUs)
Graphics Processing Units (GPUs)
Field Programmable Gate Arrays (FPGAs)
Application-Specific Integrated Circuits (ASICs)
Others (NPU & Hybrid Chip)

By Technology:

System-on-chip (SOC)
System-in-package (SIP)
Multi-Chip Module

By Region:

North America
Latin America
Europe
Asia Pacific
Middle East and Africa

Product Code: PMRREP33373

1. Executive Summary

1.1. Global Market Outlook
1.2. Demand-side Trends
1.3. Supply-side Trends
1.4. Technology Roadmap Analysis
1.5. Analysis and Recommendations

2. Market Overview

2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations

3. Market Background

3.1. Market Dynamics
- 3.1.1. Drivers
- 3.1.2. Restraints
- 3.1.3. Opportunity
- 3.1.4. Trends
3.2. Scenario Forecast
- 3.2.1. Demand in Optimistic Scenario
- 3.2.2. Demand in Likely Scenario
- 3.2.3. Demand in Conservative Scenario
3.3. Opportunity Map Analysis
3.4. Product Life Cycle Analysis
3.5. Supply Chain Analysis
- 3.5.1. Supply Side Participants and their Roles
  - 3.5.1.1. Producers
  - 3.5.1.2. Mid-Level Participants (Traders/ Agents/ Brokers)
  - 3.5.1.3. Wholesalers and Distributors
- 3.5.2. Value Added and Value Created at Node in the Supply Chain
- 3.5.3. List of Raw Material Suppliers
- 3.5.4. List of Existing and Potential Buyer's
3.6. Investment Feasibility Matrix
3.7. Value Chain Analysis
- 3.7.1. Profit Margin Analysis
- 3.7.2. Wholesalers and Distributors
- 3.7.3. Retailers
3.8. PESTLE and Porter's Analysis
3.9. Regulatory Landscape
- 3.9.1. By Key Regions
- 3.9.2. By Key Countries
3.10. Regional Parent Market Outlook
3.11. Production and Consumption Statistics
3.12. Import and Export Statistics

4. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast, 2024-2032

4.1. Historical Market Size Value (US$ billion) & Volume (Units) Analysis, 2019-2023
4.2. Current and Future Market Size Value (US$ billion) & Volume (Units) Projections, 2024-2032
- 4.2.1. Y-o-Y Growth Trend Analysis
- 4.2.2. Absolute $ Opportunity Analysis

5. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Type

5.1. Introduction / Key Findings
5.2. Historical Market Size Value (US$ billion) & Volume (Units) Analysis By Type, 2019-2023
5.3. Current and Future Market Size Value (US$ billion) & Volume (Units) Analysis and Forecast By Type, 2024-2032
- 5.3.1. Central Processing Units (CPUs)
- 5.3.2. Graphics Processing Units (GPUs)
- 5.3.3. Field Programmable Gate Arrays (FPGAs)
- 5.3.4. Application-Specific Integrated Circuits (ASICs)
- 5.3.5. Others (NPU & Hybrid Chip)
5.4. Y-o-Y Growth Trend Analysis By Type, 2019-2023
5.5. Absolute $ Opportunity Analysis By Type, 2024-2032

6. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Technology

6.1. Introduction / Key Findings
6.2. Historical Market Size Value (US$ billion) & Volume (Units) Analysis By Technology, 2019-2023
6.3. Current and Future Market Size Value (US$ billion) & Volume (Units) Analysis and Forecast By Technology, 2024-2032
- 6.3.1. System-on-chip (SOC))
- 6.3.2. System-in-package (SIP
- 6.3.3. Multi-Chip Module
- 6.3.4. Others
6.4. Y-o-Y Growth Trend Analysis By Technology, 2019-2023
6.5. Absolute $ Opportunity Analysis By Technology, 2024-2032

7. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Region

7.1. Introduction
7.2. Historical Market Size Value (US$ billion) & Volume (Units) Analysis By Region, 2019-2023
7.3. Current Market Size Value (US$ billion) & Volume (Units) Analysis and Forecast By Region, 2024-2032
- 7.3.1. North America
- 7.3.2. Latin America
- 7.3.3. Europe
- 7.3.4. Asia Pacific
- 7.3.5. Middle East and Africa
7.4. Market Attractiveness Analysis By Region

8. North America Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

8.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
8.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
- 8.2.1. By Country
  - 8.2.1.1. USA
  - 8.2.1.2. Canada
- 8.2.2. By Type
- 8.2.3. By Technology
8.3. Market Attractiveness Analysis
- 8.3.1. By Country
- 8.3.2. By Type
- 8.3.3. By Technology
8.4. Key Takeaways

9. Latin America Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

9.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
9.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
- 9.2.1. By Country
  - 9.2.1.1. Brazil
  - 9.2.1.2. Mexico
  - 9.2.1.3. Rest of Latin America
- 9.2.2. By Type
- 9.2.3. By Technology
9.3. Market Attractiveness Analysis
- 9.3.1. By Country
- 9.3.2. By Type
- 9.3.3. By Technology
9.4. Key Takeaways

10. Europe Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

10.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
10.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
- 10.2.1. By Country
  - 10.2.1.1. Germany
  - 10.2.1.2. United Kingdom
  - 10.2.1.3. France
  - 10.2.1.4. Spain
  - 10.2.1.5. Italy
  - 10.2.1.6. Rest of Europe
- 10.2.2. By Type
- 10.2.3. By Technology
10.3. Market Attractiveness Analysis
- 10.3.1. By Country
- 10.3.2. By Type
- 10.3.3. By Technology
10.4. Key Takeaways

11. Asia Pacific Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

11.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
11.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
- 11.2.1. By Country
  - 11.2.1.1. China
  - 11.2.1.2. Japan
  - 11.2.1.3. South Korea
  - 11.2.1.4. Singapore
  - 11.2.1.5. Thailand
  - 11.2.1.6. Indonesia
  - 11.2.1.7. Australia
  - 11.2.1.8. New Zealand
  - 11.2.1.9. Rest of Asia Pacific
- 11.2.2. By Type
- 11.2.3. By Technology
11.3. Market Attractiveness Analysis
- 11.3.1. By Country
- 11.3.2. By Type
- 11.3.3. By Technology
11.4. Key Takeaways

12. Middle East and Africa Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

12.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
12.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
- 12.2.1. By Country
  - 12.2.1.1. Gulf Cooperation Council Countries
  - 12.2.1.2. South Africa
  - 12.2.1.3. Israel
  - 12.2.1.4. Rest of Middle East and Africa
- 12.2.2. By Type
- 12.2.3. By Technology
12.3. Market Attractiveness Analysis
- 12.3.1. By Country
- 12.3.2. By Type
- 12.3.3. By Technology
12.4. Key Takeaways

13. Key Countries Deep Learning Chipset Market Analysis

13.1. USA
- 13.1.1. Pricing Analysis
- 13.1.2. Market Share Analysis, 2024
  - 13.1.2.1. By Type
  - 13.1.2.2. By Technology
13.2. Canada
- 13.2.1. Pricing Analysis
- 13.2.2. Market Share Analysis, 2024
  - 13.2.2.1. By Type
  - 13.2.2.2. By Technology
13.3. Brazil
- 13.3.1. Pricing Analysis
- 13.3.2. Market Share Analysis, 2024
  - 13.3.2.1. By Type
  - 13.3.2.2. By Technology
13.4. Mexico
- 13.4.1. Pricing Analysis
- 13.4.2. Market Share Analysis, 2024
  - 13.4.2.1. By Type
  - 13.4.2.2. By Technology
13.5. Germany
- 13.5.1. Pricing Analysis
- 13.5.2. Market Share Analysis, 2024
  - 13.5.2.1. By Type
  - 13.5.2.2. By Technology
13.6. United Kingdom
- 13.6.1. Pricing Analysis
- 13.6.2. Market Share Analysis, 2024
  - 13.6.2.1. By Type
  - 13.6.2.2. By Technology
13.7. France
- 13.7.1. Pricing Analysis
- 13.7.2. Market Share Analysis, 2024
  - 13.7.2.1. By Type
  - 13.7.2.2. By Technology
13.8. Spain
- 13.8.1. Pricing Analysis
- 13.8.2. Market Share Analysis, 2024
  - 13.8.2.1. By Type
  - 13.8.2.2. By Technology
13.9. Italy
- 13.9.1. Pricing Analysis
- 13.9.2. Market Share Analysis, 2024
  - 13.9.2.1. By Type
  - 13.9.2.2. By Technology
13.10. China
- 13.10.1. Pricing Analysis
- 13.10.2. Market Share Analysis, 2024
  - 13.10.2.1. By Type
  - 13.10.2.2. By Technology
13.11. Japan
- 13.11.1. Pricing Analysis
- 13.11.2. Market Share Analysis, 2024
  - 13.11.2.1. By Type
  - 13.11.2.2. By Technology
13.12. South Korea
- 13.12.1. Pricing Analysis
- 13.12.2. Market Share Analysis, 2024
  - 13.12.2.1. By Type
  - 13.12.2.2. By Technology
13.13. Singapore
- 13.13.1. Pricing Analysis
- 13.13.2. Market Share Analysis, 2024
  - 13.13.2.1. By Type
  - 13.13.2.2. By Technology
13.14. Thailand
- 13.14.1. Pricing Analysis
- 13.14.2. Market Share Analysis, 2024
  - 13.14.2.1. By Type
  - 13.14.2.2. By Technology
13.15. Indonesia
- 13.15.1. Pricing Analysis
- 13.15.2. Market Share Analysis, 2024
  - 13.15.2.1. By Type
  - 13.15.2.2. By Technology
13.16. Australia
- 13.16.1. Pricing Analysis
- 13.16.2. Market Share Analysis, 2024
  - 13.16.2.1. By Type
  - 13.16.2.2. By Technology
13.17. New Zealand
- 13.17.1. Pricing Analysis
- 13.17.2. Market Share Analysis, 2024
  - 13.17.2.1. By Type
  - 13.17.2.2. By Technology
13.18. Gulf Cooperation Council Countries
- 13.18.1. Pricing Analysis
- 13.18.2. Market Share Analysis, 2024
  - 13.18.2.1. By Type
  - 13.18.2.2. By Technology
13.19. South Africa
- 13.19.1. Pricing Analysis
- 13.19.2. Market Share Analysis, 2024
  - 13.19.2.1. By Type
  - 13.19.2.2. By Technology
13.20. Israel
- 13.20.1. Pricing Analysis
- 13.20.2. Market Share Analysis, 2024
  - 13.20.2.1. By Type
  - 13.20.2.2. By Technology

14. Market Structure Analysis

14.1. Competition Dashboard
14.2. Competition Benchmarking
14.3. Market Share Analysis of Top Players
- 14.3.1. By Regional
- 14.3.2. By Type
- 14.3.3. By Technology

15. Competition Analysis

15.1. Competition Deep Dive
- 15.1.1. Alphabet Inc.
  - 15.1.1.1. Overview
  - 15.1.1.2. Product Portfolio
  - 15.1.1.3. Profitability by Market Segments
  - 15.1.1.4. Sales Footprint
  - 15.1.1.5. Strategy Overview
    - 15.1.1.5.1. Marketing Strategy
    - 15.1.1.5.2. Product Strategy
    - 15.1.1.5.3. Channel Strategy
- 15.1.2. Amazon.Com, Inc.
  - 15.1.2.1. Overview
  - 15.1.2.2. Product Portfolio
  - 15.1.2.3. Profitability by Market Segments
  - 15.1.2.4. Sales Footprint
  - 15.1.2.5. Strategy Overview
    - 15.1.2.5.1. Marketing Strategy
    - 15.1.2.5.2. Product Strategy
    - 15.1.2.5.3. Channel Strategy
- 15.1.3. Advanced Micro Devices, Inc.
  - 15.1.3.1. Overview
  - 15.1.3.2. Product Portfolio
  - 15.1.3.3. Profitability by Market Segments
  - 15.1.3.4. Sales Footprint
  - 15.1.3.5. Strategy Overview
    - 15.1.3.5.1. Marketing Strategy
    - 15.1.3.5.2. Product Strategy
    - 15.1.3.5.3. Channel Strategy
- 15.1.4. Baidu, Inc.
  - 15.1.4.1. Overview
  - 15.1.4.2. Product Portfolio
  - 15.1.4.3. Profitability by Market Segments
  - 15.1.4.4. Sales Footprint
  - 15.1.4.5. Strategy Overview
    - 15.1.4.5.1. Marketing Strategy
    - 15.1.4.5.2. Product Strategy
    - 15.1.4.5.3. Channel Strategy
- 15.1.5. Bitmain Technologies Ltd.
  - 15.1.5.1. Overview
  - 15.1.5.2. Product Portfolio
  - 15.1.5.3. Profitability by Market Segments
  - 15.1.5.4. Sales Footprint
  - 15.1.5.5. Strategy Overview
    - 15.1.5.5.1. Marketing Strategy
    - 15.1.5.5.2. Product Strategy
    - 15.1.5.5.3. Channel Strategy
- 15.1.6. Intel Corporation
  - 15.1.6.1. Overview
  - 15.1.6.2. Product Portfolio
  - 15.1.6.3. Profitability by Market Segments
  - 15.1.6.4. Sales Footprint
  - 15.1.6.5. Strategy Overview
    - 15.1.6.5.1. Marketing Strategy
    - 15.1.6.5.2. Product Strategy
    - 15.1.6.5.3. Channel Strategy
- 15.1.7. Nvidia Corporation
  - 15.1.7.1. Overview
  - 15.1.7.2. Product Portfolio
  - 15.1.7.3. Profitability by Market Segments
  - 15.1.7.4. Sales Footprint
  - 15.1.7.5. Strategy Overview
    - 15.1.7.5.1. Marketing Strategy
    - 15.1.7.5.2. Product Strategy
    - 15.1.7.5.3. Channel Strategy
- 15.1.8. Qualcomm Incorporated
  - 15.1.8.1. Overview
  - 15.1.8.2. Product Portfolio
  - 15.1.8.3. Profitability by Market Segments
  - 15.1.8.4. Sales Footprint
  - 15.1.8.5. Strategy Overview
    - 15.1.8.5.1. Marketing Strategy
    - 15.1.8.5.2. Product Strategy
    - 15.1.8.5.3. Channel Strategy
- 15.1.9. Samsung Electronics Co. Ltd.
  - 15.1.9.1. Overview
  - 15.1.9.2. Product Portfolio
  - 15.1.9.3. Profitability by Market Segments
  - 15.1.9.4. Sales Footprint
  - 15.1.9.5. Strategy Overview
    - 15.1.9.5.1. Marketing Strategy
    - 15.1.9.5.2. Product Strategy
    - 15.1.9.5.3. Channel Strategy
- 15.1.10. Xilinx, Inc
  - 15.1.10.1. Overview
  - 15.1.10.2. Product Portfolio
  - 15.1.10.3. Profitability by Market Segments
  - 15.1.10.4. Sales Footprint
  - 15.1.10.5. Strategy Overview
    - 15.1.10.5.1. Marketing Strategy
    - 15.1.10.5.2. Product Strategy
    - 15.1.10.5.3. Channel Strategy