Growth Factors of Artificial Intelligence Chipsets Market
The Artificial Intelligence Chipsets market size was valued at USD 8.14 billion in 2023, and the market is now projected tgrow tUSD 695.16 billion by 2032, exhibiting a CAGR of 37.7% during the forecast period of 2024-2032.
This has affected the overall supply and demand chains of the particular market. As a result of the government's lockdown and other steps tstop the coronavirus from spreading, all supply activities were postponed, which decreased the amount of product related tinformation and communication technology. The market has suffered as a result of the pandemic and will continue tsuffer in the years tcome. This is ascribed tthe industrial sector, the impacted supply chain procedures, and the developing industries' partial use of AI. Numerous manufacturing companies have halted their output due tthe lockdown regulations, which has negatively impacted the global supply chain process. These factors affceted the Artificial Intelligence Chipsets market growth.
This is the major factor attributing the growth of this particular market. This factor is majorly involved in taking the revenue numbers above the skies and soaring greater heights and alsthe sales and demands have been proliferation and increased its value tgreater extent. Three key factors are driving the market for artificial intelligence (AI) chipsets: the development of semiconductor nanowire laser technology, the increasing use of deep learning and neural networks, and 3D technology. The need for chipsets is alsanticipated tbe fueled by the increasing number of smart home, smart building, and smart city projects being undertaken worldwide. Leading companies are more concerned with creating cutting-edge chipsets for AI applications with many uses. These particular growth driving factors have been recorded tattribute the Artificial Intelligence Chipsets market share.
A latest trend has been witnessed tproliferate the market growth. This particular trend has been recorded tbe the most profiting trends that have been upgraded taugment the overall market growth. AI chipsets that are cloud-based are computational chipsets made especially for AI inference and training tasks. Opportunities would arise for major participants in the market for artificial intelligence chipsets as cloud technology advanced. The increasing number of data centers throughout the world in industries is probably going tincrease demand for cloud-based AI chipsets. Moreover, the creation and development of lightweight, reasonably priced propeller shafts is another new trend.
Comprehensive Analysis of Artificial Intelligence Chipsets Market
Applications requiring immediate data response, risk management, fraud detection, and portfolioptimization. As a result, complex calculations can be completed in a matter of seconds by a single processor. Thus, it is anticipated that these factors would accelerate the expansion of the global market for AI chipsets. The increasing use of medical lasers, self-driving cars, sophisticated microdevices, virtual assistance devices, and others are some of the secondary drivers of this market. This is one of the most important growth factor of the market which has enhanced the growth of the particular market.
The North American region has augmented a lot in the past few years in this particular product market. The North American region held the biggest revenue share.During the anticipated period, North America is anticipated thold a dominant position in the global market with respect trevenue share. Growing R&D expenditures by the government and the presence of well-established IT infrastructure are anticipated tsupport market expansion in North America. This particular region is actually growing a lot and is anticipated taugment more over the years.
Global markets are fiercely competitive and highly fragmented. Due ttheir creative packaging solutions, a few group of large market companies hold a fair amount of market share. Some of the major Companies includes NVIDIA Corporation (California, United States), Intel Corporation (California, United States), Xilinx, Inc. (California, United States), Samsung Electronics Co., Ltd. (Suwon-si, South Korea), Micron Technology, Inc. (Idaho, United States)
In August 2019, Kneron introduced the Kneron KL 720 SoC, a cutting-edge chipset-based AI. With the Arm Cortex M4 as its primary control unit, the chipset's SoC enables 1.5 TOPS in performance. This was a development happened in the industry which increased the demand for the product and made it grow all over in the market leading the sector.
ATTRIBUTE DETAILS
Study Period 2016 – 2027
Base Year 2019
Forecast Period 2020 – 2027
Historical Period 2016 – 2018
Unit Value (USD billion)
Segmentation By Chipset Type
Graphics Processing Unit (GPU)
Field Programmable Gate Arrays (FPGAs)
Application-specific Integrated Circuit (ASIC)
Others (Central Processing Unit (CPU), etc.)
By Application
Natural Language Processing (NLP)
Robotic Process Automation (RPA)
Machine Learning
Computer Vision
Others (Context-aware Computing, etc.)
By Computing Technology
Cloud Computing
Edge Computing
By Function
Training
Inference
By Industry
Consumer Electronics
Healthcare
BFSI
IT & Telecom
Manufacturing
Automotive
Retail
Others (Government, etc.)
By Region
North America
By Chipset Type
By Application
By Computing Technology
By Function
By Industry
By Country
■ The U.S.
■ By Chipset Type
■ Canada
■ By Chipset Type
■ Mexico
■ By Chipset Type
Europe
By Chipset Type
By Application
By Computing Technology
By Function
By Industry
By Country
■ UK
■ By Chipset Type
■ Germany
■ By Chipset Type
■ France
■ By Chipset Type
■ Italy
■ By Chipset Type
■ Spain
■ By Chipset Type
■ Russia
■ By Chipset Type
■ Benelux
■ By Chipset Type
■ Nordics
■ By Chipset Type
■ Rest of Europe
Asia Pacific
By Chipset Type
By Application
By Computing Technology
By Function
By Industry
By Country
■ China
■ By Chipset Type
■ India
■ By Chipset Type
■ Japan
■ By Chipset Type
■ South Korea
■ By Chipset Type
■ ASEAN
■ By Chipset Type
■ Oceania
■ By Chipset Type
■ Rest of Asia Pacific
Middle East & Africa
By Chipset Type
By Application
By Computing Technology
By Function
By Industry
By Country
■ Turkey
■ By Chipset Type
■ Israel
■ By Chipset Type
■ GCC
■ By Chipset Type
■ North Africa
■ By Chipset Type
■ South Africa
■ By Chipset Type
■ Rest of MEA
South America
By Chipset Type
By Application
By Computing Technology
By Function
By Industry
By Country
■ Brazil
■ By Chipset Type
■ Argentina
■ By Chipset Type
■ Rest of South America
- 1. Introduction
- 1.1. Definition, By Segment
- 1.2. Research Methodology/Approach
- 1.3. Data Sources
- 2. Key Takeaways
- 3. Market Dynamics
- 3.1. Macro and Micro Economic Indicators
- 3.2. Drivers, Restraints, Opportunities and Trends
- 3.3. Impact of COVID-19
- 3.3.1. Short-term Impact
- 3.3.2. Long-term Impact
- 4. Competition Landscape
- 4.1. Business Strategies Adopted by Key Players
- 4.2. Consolidated SWOT Analysis of Key Players
- 4.3. Porter’s Five Force Analysis
- 4.4. Global Market Share Analysis and Matrix, 2019
- 5. Key Market Insights and Strategic Recommendations
- 6. Profiles of Key Players (Would be provided for 10 players only)
- 6.1. Overview
- 6.1.1. Key Management
- 6.1.2. Headquarters etc.
- 6.2. Offerings/Business Segments
- 6.3. Key Details (Key details are subjected to data availability in public domain and/or on paid databases)
- 6.3.1. Employee Size
- 6.3.2. Key Financials
- 6.3.2.1. Past and Current Revenue
- 6.3.2.2. Gross Margin
- 6.3.2.3. Geographical Share
- 6.3.2.4. Business Segment Share
- 6.4. Recent Developments
- 7. Primary Interview Responses
- 8. Annexure / Appendix
- 8.1. Global Artificial Intelligence (AI) Chipset Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 8.1.1. By Chipset Type (Value)
- 8.1.1.1. Graphics Processing Unit (GPU)
- 8.1.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.1.1.3. Application-specific Integrated Circuit (ASIC)
- 8.1.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.1.2. By Application (Value)
- 8.1.2.1. Natural Language Processing (NLP)
- 8.1.2.2. Robotic Process Automation (RPA)
- 8.1.2.3. Machine Learning
- 8.1.2.4. Computer Vision
- 8.1.2.5. Others (Context-aware Computing, etc.)
- 8.1.3. By Computing Technology (Value)
- 8.1.3.1. Cloud Computing
- 8.1.3.2. Edge Computing
- 8.1.4. By Function (Value)
- 8.1.4.1. Training
- 8.1.4.2. Inference
- 8.1.5. By Industry (Value)
- 8.1.5.1. Consumer Electronics
- 8.1.5.2. Healthcare
- 8.1.5.3. BFSI
- 8.1.5.4. IT & Telecom
- 8.1.5.5. Manufacturing
- 8.1.5.6. Automotive
- 8.1.5.7. Retail
- 8.1.5.8. Others (Government, etc.)
- 8.1.6. By Region (Value)
- 8.1.6.1. North America
- 8.1.6.2. South America
- 8.1.6.3. Europe
- 8.1.6.4. Middle East & Africa
- 8.1.6.5. Asia Pacific
- 8.2. North America Artificial Intelligence (AI) Chipset Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 8.2.1. By Chipset Type (Value)
- 8.2.1.1. Graphics Processing Unit (GPU)
- 8.2.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.2.1.3. Application-specific Integrated Circuit (ASIC)
- 8.2.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.2.2. By Application (Value)
- 8.2.2.1. Natural Language Processing (NLP)
- 8.2.2.2. Robotic Process Automation (RPA)
- 8.2.2.3. Machine Learning
- 8.2.2.4. Computer Vision
- 8.2.2.5. Others (Context-aware Computing, etc.)
- 8.2.3. By Computing Technology (Value)
- 8.2.3.1. Cloud Computing
- 8.2.3.2. Edge Computing
- 8.2.4. By Function (Value)
- 8.2.4.1. Training
- 8.2.4.2. Inference
- 8.2.5. By Industry (Value)
- 8.2.5.1. Consumer Electronics
- 8.2.5.2. Healthcare
- 8.2.5.3. BFSI
- 8.2.5.4. IT & Telecom
- 8.2.5.5. Manufacturing
- 8.2.5.6. Automotive
- 8.2.5.7. Retail
- 8.2.5.8. Others (Government, etc.)
- 8.2.6. By Country (Value)
- 8.2.6.1. United States
- 8.2.6.1.1. By Chipset Type (Value)
- 8.2.6.1.1.1. Graphics Processing Unit (GPU)
- 8.2.6.1.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.2.6.1.1.3. Application-specific Integrated Circuit (ASIC)
- 8.2.6.1.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.2.6.2. Canada
- 8.2.6.2.1. By Chipset Type (Value)
- 8.2.6.2.1.1. Graphics Processing Unit (GPU)
- 8.2.6.2.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.2.6.2.1.3. Application-specific Integrated Circuit (ASIC)
- 8.2.6.2.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.2.6.3. Mexico
- 8.2.6.3.1. By Chipset Type (Value)
- 8.2.6.3.1.1. Graphics Processing Unit (GPU)
- 8.2.6.3.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.2.6.3.1.3. Application-specific Integrated Circuit (ASIC)
- 8.2.6.3.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.3. South America Artificial Intelligence (AI) Chipset Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 8.3.1. By Chipset Type (Value)
- 8.3.1.1. Graphics Processing Unit (GPU)
- 8.3.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.3.1.3. Application-specific Integrated Circuit (ASIC)
- 8.3.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.3.2. By Application (Value)
- 8.3.2.1. Natural Language Processing (NLP)
- 8.3.2.2. Robotic Process Automation (RPA)
- 8.3.2.3. Machine Learning
- 8.3.2.4. Computer Vision
- 8.3.2.5. Others (Context-aware Computing, etc.)
- 8.3.3. By Computing Technology (Value)
- 8.3.3.1. Cloud Computing
- 8.3.3.2. Edge Computing
- 8.3.4. By Function (Value)
- 8.3.4.1. Training
- 8.3.4.2. Inference
- 8.3.5. By Industry (Value)
- 8.3.5.1. Consumer Electronics
- 8.3.5.2. Healthcare
- 8.3.5.3. BFSI
- 8.3.5.4. IT & Telecom
- 8.3.5.5. Manufacturing
- 8.3.5.6. Automotive
- 8.3.5.7. Retail
- 8.3.5.8. Others (Government, etc.)
- 8.3.6. By Country (Value)
- 8.3.6.1. Brazil
- 8.3.6.1.1. By Chipset Type (Value)
- 8.3.6.1.1.1. Graphics Processing Unit (GPU)
- 8.3.6.1.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.3.6.1.1.3. Application-specific Integrated Circuit (ASIC)
- 8.3.6.1.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.3.6.2. Argentina
- 8.3.6.2.1. By Chipset Type (Value)
- 8.3.6.2.1.1. Graphics Processing Unit (GPU)
- 8.3.6.2.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.3.6.2.1.3. Application-specific Integrated Circuit (ASIC)
- 8.3.6.2.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.3.6.3. Rest of South America
- 8.4. Europe Artificial Intelligence (AI) Chipset Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 8.4.1. By Chipset Type (Value)
- 8.4.1.1. Graphics Processing Unit (GPU)
- 8.4.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.2. By Application (Value)
- 8.4.2.1. Natural Language Processing (NLP)
- 8.4.2.2. Robotic Process Automation (RPA)
- 8.4.2.3. Machine Learning
- 8.4.2.4. Computer Vision
- 8.4.2.5. Others (Context-aware Computing, etc.)
- 8.4.3. By Computing Technology (Value)
- 8.4.3.1. Cloud Computing
- 8.4.3.2. Edge Computing
- 8.4.4. By Function (Value)
- 8.4.4.1. Training
- 8.4.4.2. Inference
- 8.4.5. By Industry (Value)
- 8.4.5.1. Consumer Electronics
- 8.4.5.2. Healthcare
- 8.4.5.3. BFSI
- 8.4.5.4. IT & Telecom
- 8.4.5.5. Manufacturing
- 8.4.5.6. Automotive
- 8.4.5.7. Retail
- 8.4.5.8. Others (Government, etc.)
- 8.4.6. By Country (Value)
- 8.4.6.1. United Kingdom
- 8.4.6.1.1. By Chipset Type (Value)
- 8.4.6.1.1.1. Graphics Processing Unit (GPU)
- 8.4.6.1.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.1.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.1.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.2. Germany
- 8.4.6.2.1. By Chipset Type (Value)
- 8.4.6.2.1.1. Graphics Processing Unit (GPU)
- 8.4.6.2.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.2.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.2.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.3. France
- 8.4.6.3.1. By Chipset Type (Value)
- 8.4.6.3.1.1. Graphics Processing Unit (GPU)
- 8.4.6.3.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.3.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.3.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.4. Italy
- 8.4.6.4.1. By Chipset Type (Value)
- 8.4.6.4.1.1. Graphics Processing Unit (GPU)
- 8.4.6.4.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.4.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.4.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.5. Spain
- 8.4.6.5.1. By Chipset Type (Value)
- 8.4.6.5.1.1. Graphics Processing Unit (GPU)
- 8.4.6.5.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.5.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.5.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.6. Russia
- 8.4.6.6.1. By Chipset Type (Value)
- 8.4.6.6.1.1. Graphics Processing Unit (GPU)
- 8.4.6.6.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.6.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.6.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.7. Benelux
- 8.4.6.7.1. By Chipset Type (Value)
- 8.4.6.7.1.1. Graphics Processing Unit (GPU)
- 8.4.6.7.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.7.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.7.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.8. Nordics
- 8.4.6.8.1. By Chipset Type (Value)
- 8.4.6.8.1.1. Graphics Processing Unit (GPU)
- 8.4.6.8.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.4.6.8.1.3. Application-specific Integrated Circuit (ASIC)
- 8.4.6.8.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.4.6.9. Rest of Europe
- 8.5. Middle East & Africa Artificial Intelligence (AI) Chipset Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 8.5.1. By Chipset Type (Value)
- 8.5.1.1. Graphics Processing Unit (GPU)
- 8.5.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.5.1.3. Application-specific Integrated Circuit (ASIC)
- 8.5.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.5.2. By Application (Value)
- 8.5.2.1. Natural Language Processing (NLP)
- 8.5.2.2. Robotic Process Automation (RPA)
- 8.5.2.3. Machine Learning
- 8.5.2.4. Computer Vision
- 8.5.2.5. Others (Context-aware Computing, etc.)
- 8.5.3. By Computing Technology (Value)
- 8.5.3.1. Cloud Computing
- 8.5.3.2. Edge Computing
- 8.5.4. By Function (Value)
- 8.5.4.1. Training
- 8.5.4.2. Inference
- 8.5.5. By Industry (Value)
- 8.5.5.1. Consumer Electronics
- 8.5.5.2. Healthcare
- 8.5.5.3. BFSI
- 8.5.5.4. IT & Telecom
- 8.5.5.5. Manufacturing
- 8.5.5.6. Automotive
- 8.5.5.7. Retail
- 8.5.5.8. Others (Government, etc.)
- 8.5.6. By Country (Value)
- 8.5.6.1. Turkey
- 8.5.6.1.1. By Chipset Type (Value)
- 8.5.6.1.1.1. Graphics Processing Unit (GPU)
- 8.5.6.1.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.5.6.1.1.3. Application-specific Integrated Circuit (ASIC)
- 8.5.6.1.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.5.6.2. Israel
- 8.5.6.2.1. By Chipset Type (Value)
- 8.5.6.2.1.1. Graphics Processing Unit (GPU)
- 8.5.6.2.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.5.6.2.1.3. Application-specific Integrated Circuit (ASIC)
- 8.5.6.2.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.5.6.3. GCC
- 8.5.6.3.1. By Chipset Type (Value)
- 8.5.6.3.1.1. Graphics Processing Unit (GPU)
- 8.5.6.3.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.5.6.3.1.3. Application-specific Integrated Circuit (ASIC)
- 8.5.6.3.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.5.6.4. North Africa
- 8.5.6.4.1. By Chipset Type (Value)
- 8.5.6.4.1.1. Graphics Processing Unit (GPU)
- 8.5.6.4.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.5.6.4.1.3. Application-specific Integrated Circuit (ASIC)
- 8.5.6.4.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.5.6.5. South Africa
- 8.5.6.5.1. By Chipset Type (Value)
- 8.5.6.5.1.1. Graphics Processing Unit (GPU)
- 8.5.6.5.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.5.6.5.1.3. Application-specific Integrated Circuit (ASIC)
- 8.5.6.5.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.5.6.6. Rest of MEA
- 8.6. Asia Pacific Artificial Intelligence (AI) Chipset Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 8.6.1. By Chipset Type (Value)
- 8.6.1.1. Graphics Processing Unit (GPU)
- 8.6.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.2. By Application (Value)
- 8.6.2.1. Natural Language Processing (NLP)
- 8.6.2.2. Robotic Process Automation (RPA)
- 8.6.2.3. Machine Learning
- 8.6.2.4. Computer Vision
- 8.6.2.5. Others (Context-aware Computing, etc.)
- 8.6.3. By Computing Technology (Value)
- 8.6.3.1. Cloud Computing
- 8.6.3.2. Edge Computing
- 8.6.4. By Function (Value)
- 8.6.4.1. Training
- 8.6.4.2. Inference
- 8.6.5. By Industry (Value)
- 8.6.5.1. Consumer Electronics
- 8.6.5.2. Healthcare
- 8.6.5.3. BFSI
- 8.6.5.4. IT & Telecom
- 8.6.5.5. Manufacturing
- 8.6.5.6. Automotive
- 8.6.5.7. Retail
- 8.6.5.8. Others (Government, etc.)
- 8.6.6. By Country (Value)
- 8.6.6.1. China
- 8.6.6.1.1. By Chipset Type (Value)
- 8.6.6.1.1.1. Graphics Processing Unit (GPU)
- 8.6.6.1.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.6.1.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.6.1.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.6.2. India
- 8.6.6.2.1. By Chipset Type (Value)
- 8.6.6.2.1.1. Graphics Processing Unit (GPU)
- 8.6.6.2.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.6.2.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.6.2.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.6.3. Japan
- 8.6.6.3.1. By Chipset Type (Value)
- 8.6.6.3.1.1. Graphics Processing Unit (GPU)
- 8.6.6.3.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.6.3.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.6.3.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.6.4. South Korea
- 8.6.6.4.1. By Chipset Type (Value)
- 8.6.6.4.1.1. Graphics Processing Unit (GPU)
- 8.6.6.4.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.6.4.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.6.4.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.6.5. ASEAN
- 8.6.6.5.1. By Chipset Type (Value)
- 8.6.6.5.1.1. Graphics Processing Unit (GPU)
- 8.6.6.5.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.6.5.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.6.5.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.6.6. Oceania
- 8.6.6.6.1. By Chipset Type (Value)
- 8.6.6.6.1.1. Graphics Processing Unit (GPU)
- 8.6.6.6.1.2. Field Programmable Gate Arrays (FPGAs)
- 8.6.6.6.1.3. Application-specific Integrated Circuit (ASIC)
- 8.6.6.6.1.4. Others (Central Processing Unit (CPU), etc.)
- 8.6.6.7. Rest of Asia Pacific
- 9. Please note that the segmentations and scope in the ToC is subjected to revisions (if needed) based to the primary and secondary insights with an aim to make it more relevant and in line with the market ecosystem
- 10. Following are some of the companies (to name a few and not limited to) considered in the scope for understanding the market ecosystem/value chain.
- 11. Note that the purpose of the below list is to highlight the exhaustiveness of coverage. This does not necessarily mean that all the below companies would be profile in the scope.
- 12. However, at the same, we are open to profile additional company(s) on specific request
- 13. NVIDIA Corporation
- 14. Intel Corporation
- 15. Xilinx, Inc.
- 16. International Business Machines Corporation
- 17. Google LLC
- 18. Microsoft Corporation
- 19. Samsung Electronics Co., Ltd.
- 20. Micron Technology, Inc.
- 21. Qualcomm Technologies, Inc.
- 22. Amazon Web Services (an Amazon.com, Inc. subsidiary)
- 23. Zero ASIC
- 24. Koniku, Inc.
- 25. Tenstorrent, Inc.
- 26. SambaNova Systems, Inc.
- 27. Kalray Corporation
- 28. MediaTek, Inc.
- 29. Fujitsu Limited
- 30. Advanced Micro Devices, Inc.
- 31. General Vision, Inc.
- 32. Huawei Technologies Co., Ltd.
- 33. Graphcore Limited Wave Computing Inc.
- 34. Mythic
- 35. XMOS Limited
- 36. GreenWaves Technologies "
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