Global Artificial Intelligence (AI) Chipset Market 2023-2030

Global Artificial Intelligence (AI) Chipset Market 2023-2030- By Hardware (AI Chips and AI Accelerators); By Processors (ASIC, CPU, GPU, FPGA, and Heterogeneous Systems); By Function (Training and Inference); By Technology (System-On-Chip and Multi Chip Module); By Process Technology Node (3 nm, 5 nm, 7 nm, 10 nm, and 12 nm and Above); By Computing (Could AI Computing and Edge AI Computing); (By Use Cases (Data center and Cloud Computing, Edge computing, Autonomous vehicles, Smart Home Devices, Robotics, Financial Services, Healthcare Imaging, Gaming and Graphics Processing, Security and Surveillance, and Smartphone and Mobile Devices); By Geography (APAC, Americas, Europe, and MEA).

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DESCRIPTION

Market Intelligence Summary

According to WDO Consulting, the global shipment of Artificial Intelligence Chipset (AI) is expected to reach XX million units by 2030. The AI chipset Market is expected to grow at a compound annual growth rate (CAGR) of around XX% from 2023 to 2030, reaching a market value of over USD XX million by 2030.
This growth is fueled by the increasing adoption of AI in cloud computing, data centers, edge computing, autonomous vehicles, smart home devices, robotics, medical imaging, financial services, retail, manufacturing, agriculture, education, energy, cybersecurity, and logistics.
Key developments in AI chips and accelerators include the integration of advanced architectures like neuromorphic computing and domain-specific accelerators (DSAs) to achieve higher performance and energy efficiency. There is an emphasis on developing AI accelerators specifically designed for training large-scale machine learning models. This includes innovations in hardware architectures and specialized processors for training.
AI chips are expected to see increased adoption in edge devices, allowing for on-device processing and reducing the reliance on cloud-based services. It is specifically designed for AI computations, incorporating multiple processing units, such as CPUs, GPUs, and FPGAs, optimized for AI tasks like matrix multiplication and convolution. Combining different processing units, such as CPUs, GPUs, and FPGAs enable engineers to achieve optimal performance and efficiency for diverse AI workloads.
Furthermore, several semiconductor companies and AI startups are forming partnerships and collaborations to combine expertise in AI algorithms with hardware design, aiming to create more powerful and efficient AI solutions.The open-source community is also contributing to the development of AI accelerators with open-source hardware designs

Global Artificial Intelligence Chipset (AI) Market Research Report Coverage (2023-2030)

Report coverage Details
Base year 2023
Forecast year 2030
Unit shipment Million units
Revenue USD million
By hardware
  • Hardware
    • AI chipset
    • AI accelerators
By processors
  • ASIC
  • CPU
  • GPU
  • FPGA
  • Heterogeneous Systems
By technology
  • System-on-Chip (SoC)
  • Multichip Module
By process technology node
  • 3nm
  • 5nm
  • 7nm
  • 10nm
  • 12nm and above
By function
  • Training
  • Inference
By computing
  • Cloud AI computing
  • Edge AI computing
By use cases
  • Data center and cloud computing
  • Edge computing
  • Autonomous vehicles
  • Smart home devices
  • Financial services
  • Healthcare imaging
  • Gaming and graphics processing
  • Security and surveillance
  • Smartphone and Mobile Devices
By geography
  • Americas-US, Canada, Mexico, Brazil, Argentina, and Rest of Americas
  • Europe-Germany, UK, France, Italy, Nordic Countries (Sweden, Norway, Denmark, Finland), and Rest of Europe
  • APAC-China, Japan, India, South Korea, and Rest of APAC
  • MEA-UAE, Saudi Arabia, Qatar, Rest of Middle East, and Africa
Market players coverage (Top 5 players market share)
  • Advanced Micro Devices (AMD)
  • Alibaba
  • Alphabet
  • Apple
  • AWS
  • Cerebras
  • FlexLogix
  • GrAI Matter Labs
  • Graphcore
  • Groq
  • Huawei Technologies
  • IBM
  • Intel
  • Meta
  • Microsoft
  • Mythic
  • NXP Semiconductors
  • Nvidia
  • Qualcomm Technologies
  • Rebellions
  • SambaNova Systems
  • Samsung
  • SiMa Technologies
  • Tenstorrent
  • Untether AI

Market Dynamics: Key drivers, trends, and challenges

  • Key market drivers
    • Ongoing advancements in AI algorithms and models
    • Emergence of startups specializing in AI chipsets and significant investments in AI hardware companies
  • Key market trends
    • Integration of AI chipsets into edge computing devices
    • Integration of multiple processing elements, such as CPUs, GPUs, and specialized AI accelerators
  • Key market challenges
    • Limited availability of skilled professionals
    • The complexity of programming and optimizing AI chipsets for specific applications

Key questions to be answered

1. What is the current market size of the Global Artificial Intelligence Chipset (AI) market, and what is its growth potential over the next five years?
2. How many Artificial Intelligence Chipset (AI) were shipped in 2023, and the forecasted shipmnet by 2030?
3. What is the Compound Annual Growth Rate (CAGR) of the Global Artificial Intelligence Chipset (AI) market?
4. Which are the key segments covered in the Global Artificial Intelligence Chipset (AI) market, and which segments are experiencing the fastest growth?
5. Which geographical region offers the highest growth opportunities in the Global Artificial Intelligence Chipset (AI) market?
6. How is the competitive landscape evolving, and who are the key players in the Global Artificial Intelligence Chipset (AI) market?
7. Who are the top five players in the Global Artificial Intelligence Chipset (AI) market, and what is their respective market share?

TABLE OF CONTENTS

  • 1. Project scope
    • 1.1 Market definition
    • 1.2 Study objective
    • 1.3 Scope inclusions
    • 1.4 Scope exclusions
    • 1.5 Assumptions
    • 1.6 Limitations
  • 2. Executive summary
    • 2.1 Key findings of the study
    • 2.2 Key insights from industry experts
    • 2.3 Analyst opinion
  • 3. Research methodology
    • 3.1 Supply-side research methodology
    • 3.2 Demand-side research methodology
  • 4. Market dynamics
    • 4.1 Trends
    • 4.2 Drivers
    • 4.3 Challenges
    • 4.4 Ecosystem
    • 4.5 Use cases
    • 4.6 Market developments
      • 4.6.1 Macroeconomic factors
        • 4.6.1.1 Currency fluctuations
        • 4.6.1.2 Supply chain disruptions
        • 4.6.1.3 Government regulations
        • 4.6.1.4 Others
      • 4.6.2 Microeconomic factors
        • 4.6.2.1 Price fluctuations
        • 4.6.2.2 Technological advancements
  • 5. Artificial Intelligence Chipset (AI) market size and forecast, by hardware
    • 5.1 Unit shipment 2023-2030 (Million units)
      • 5.1.1 AI chipset
      • 5.1.2 AI Accelerators
    • 5.2 Revenue 2023-2030 (USD million)
      • 5.2.1 AI chipset
      • 5.2.1 AI accelerators
  • 6. Artificial Intelligence Chipset (AI) market size and forecast, by processors
    • 6.1 Unit shipment 2023-2030 (Million units)
      • 6.1.1 ASIC
      • 6.1.2 CPU
      • 6.1.3 GPU
      • 6.1.4 FPGA
      • 6.1.5 Heterogeneous Systems
    • 6.2 Revenue 2023-2030 (USD million)
      • 6.2.1 ASIC
      • 6.2.2 CPU
      • 6.2.3 GPU
      • 6.2.4 FPGA
      • 6.2.5 Heterogeneous Systems
  • 7. Artificial Intelligence Chipset (AI) market size and forecast, by technology
    • 7.1 Unit shipment 2023-2030 (Million units)
      • 7.1.1 System-on-Chip (SoC)
      • 7.1.2 Multichip Module
    • 7.2 Revenue 2023-2030 (USD million)
      • 7.2.1 System-on-Chip (SoC)
      • 7.2.2 Multichip Module
  • 8. Artificial Intelligence Chipset (AI) market size and forecast, by process technology node
    • 8.1 Unit shipment 2023-2030 (Million units)
      • 8.1.1 3nm
      • 8.1.2 5nm
      • 8.1.3 7nm
      • 8.1.4 10nm
      • 8.1.5 12nm and above
    • 8.2 Revenue 2023-2030 (USD million)
      • 8.2.1 3nm
      • 8.2.2 5nm
      • 8.2.3 7nm
      • 8.2.4 10nm
      • 8.2.5 12nm and above
  • 9. Artificial Intelligence Chipset (AI) market size and forecast, by function
    • 9.1 Unit shipment 2023-2030 (Million units)
      • 9.1.1 Training
      • 9.1.2 Inference
    • 9.2 Revenue 2023-2030 (USD million)
      • 9.2.1 Training
      • 9.2.2 Inference
  • 10. Artificial Intelligence Chipset (AI) market size and forecast, by computing
    • 10.1 Unit shipment 2023-2030 (Million units)
      • 10.1.1 Cloud AI computing
      • 10.1.2 Edge AI computing
    • 10.2 Revenue 2023-2030 (USD million)
      • 10.2.1 Cloud AI computing
      • 10.2.2 Edge AI computing
  • 11. Artificial Intelligence Chipset (AI) market size and forecast, by use cases
    • 11.1 Unit shipment 2023-2030 (Million units)
      • 11.1.1 Data center and cloud computing
      • 11.1.2 Edge computing
      • 11.1.3 Autonomous vehicles
      • 11.1.4 Smart home devices
      • 11.1.5 Financial services
      • 11.1.6 Healthcare imaging
      • 11.1.7 Gaming and graphics processing
      • 11.1.8 Security and surveillance
      • 11.1.9 Smartphone and mobile devices
    • 11.2 Revenue 2023-2030 (USD million)
      • 11.2.1 Data center and cloud computing
      • 11.2.2 Edge computing
      • 11.2.3 Autonomous vehicles
      • 11.2.4 Smart home devices
      • 11.2.5 Financial services
      • 11.2.6 Healthcare imaging
      • 11.2.7 Gaming and graphics processing
      • 11.2.8 Security and surveillance
      • 11.2.9 Smartphone and mobile devices
  • 12. Artificial Intelligence Chipset (AI) market size and forecast, by geography
    • 12.1 Americas
      • 12.1.1 US
      • 12.1.2 Canada
      • 12.1.3 Mexico
      • 12.1.4 Brazil
      • 12.1.5 Argentina
      • 12.1.6 Rest of Americas
    • 12.2 Europe
      • 12.2.1 Germany
      • 12.2.2 UK
      • 12.2.3 France
      • 12.2.4 Italy
      • 12.2.5 Nordic countries (Sweden, Norway, Denmark, Finland)
      • 12.2.6 Rest of Europe
    • 12.3 APAC
      • 12.3.1 China
      • 12.3.2 Japan
      • 12.3.3 India
      • 12.3.4 South Korea
      • 12.3.5 Rest of APAC
    • 12.4 MEA
      • 12.4.1 UAE
      • 12.4.2 Saudi Arabia
      • 12.4.3 Qatar
      • 12.4.4 Rest of Middle East
      • 12.4.5 Africa
  • 13. Competitive scenario
    • 13.1 Market concentration
    • 13.2 Top five companies market share 2023
    • 13.3 Key strategies
    • 13.4 Key investments
  • 14. Company profiles
    • 14.1 Advanced Micro Devices (AMD
      • 14.1.1 Business overview
      • 13.1.2 Product portfolio
      • 13.1.3 Key developments
    • 14.2 Alibaba
      • 14.2.1 Business overview
      • 14.2.2 Product portfolio
      • 14.2.3 Key developments
    • 14.3 Alphabet
      • 14.3.1 Business overview
      • 14.3.2 Product portfolio
      • 14.3.3 Key developments
    • 14.4 Apple
      • 14.4.1 Business overview
      • 14.4.2 Product portfolio
      • 14.4.3 Key developments
    • 14.5 AWS
      • 14.5.1 Business overview
      • 14.5.2 Product portfolio
      • 14.5.3 Key developments
    • 14.6 Cerebras
      • 14.6.1 Business overview
      • 14.6.2 Product portfolio
      • 14.6.3 Key developments
    • 14.7 FlexLogix
      • 14.7.1 Business overview
      • 14.7.2 Product portfolio
      • 14.7.3 Key developments
    • 14.8 GrAI Matter Labs
      • 14.8.1 Business overview
      • 14.8.2 Product portfolio
      • 14.8.3 Key developments
    • 14.9 Graphcore
      • 14.9.1 Business overview
      • 14.9.2 Product portfolio
      • 14.9.3 Key developments
    • 14.10 Groq
      • 14.10.1 Business overview
      • 14.10.2 Product portfolio
      • 14.10.3 Key developments
    • 14.11 Huawei Technologies
      • 14.11.1 Business overview
      • 14.11.2 Product portfolio
      • 14.11.3 Key developments
    • 14.12 IBM
      • 14.12.1 Business overview
      • 14.12.2 Product portfolio
      • 14.12.3 Key developments
    • 14.13 Intel
      • 14.13.1 Business overview
      • 14.13.2 Product portfolio
      • 14.13.3 Key developments
    • 14.14 Meta
      • 14.14.1 Business overview
      • 14.14.2 Product portfolio
      • 14.14.3 Key developments
    • 14.15 Microsoft
      • 14.15.1 Business overview
      • 14.15.2 Product portfolio
      • 14.15.3 Key developments
    • 14.16 Mythic
      • 14.16.1 Business overview
      • 14.16.2 Product portfolio
      • 14.16.3 Key developments
    • 14.17 NXP Semiconductors
      • 14.17.1 Business overview
      • 14.17.2 Product portfolio
      • 14.17.3 Key developments
    • 14.18 Nvidia
      • 14.18.1 Business overview
      • 14.18.2 Product portfolio
      • 14.18.3 Key developments
    • 14.19 Qualcomm Technologies
      • 14.19.1 Business overview
      • 14.19.2 Product portfolio
      • 14.19.3 Key developments
    • 14.20 Rebellions
      • 14.20.1 Business overview
      • 14.20.2 Product portfolio
      • 14.20.3 Key developments
    • 14.21 SambaNova Systems
      • 14.21.1 Business overview
      • 14.21.2 Product portfolio
      • 14.21.3 Key developments
    • 14.22 Samsung
      • 14.22.1 Business overview
      • 14.22.2 Product portfolio
      • 14.22.3 Key developments
    • 14.23 SiMa Technologies
      • 14.23.1 Business overview
      • 14.23.2 Product portfolio
      • 14.23.3 Key developments
    • 14.24 Tenstorrent
      • 14.24.1 Business overview
      • 14.24.2 Product portfolio
      • 14.24.3 Key developments
    • 14.25 Untether AI
      • 14.25.1 Business overview
      • 14.25.2 Product portfolio
      • 14.25.3 Key developments

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