Key Highlights
The Machine Learning Chips is growing at 28% and is expected to reach 15Billion by 2031. Below are some of the dynamics shaping the Machine Learning Chips .Machine learning chip is the hardware accelerator or application-based computer system designed to accelerate machine learning applications. Machine learning applications involve algorithms for robotics, the internet of things and other data-intensive or sensor-driven tasks. These chip provides much more data security, latency and consumes much less power. They are designed to do certain AI problems faster at lower power than traditional processors. In the market, more than 100 companies are working on building next-generation chips and hardware architecture that would match the capabilities of algorithms. These machine-learning chips are capable of enabling deep learning applications on smartphones and other edge computing devices. The companies are using machine learning technology to improve business decisions, increase productivity, and detect disease, forecast weather, and others. The applications of machine learning involve virtual personal assistants, predictions while commuting, video surveillance, social media services, email spam and malware filtering, online fraud detection, and others.
The Machine Learning Chips industry study provides important insights in several important ways. To help stakeholders quickly understand key information, it starts with an executive summary that briefly summarizes the results, conclusions, and practical suggestions. The purpose and questions being addressed are guaranteed to be understood when the study objectives are clearly stated. To build credibility, the methodology section explains the research techniques used, such as surveys and focus groups, and why they were chosen. The Machine Learning Chips industry landscape, including market size, growth trends, and major drivers, is presented in a market overview.
The segmentation research also examines different market categories to determine client wants. The competitive analysis highlights the advantages and disadvantages of the main rivals. Key facts and insights are presented at the end of the study, followed by conclusions and suggestions that offer doable tactics to direct future company choices.
Machine Learning Chips Market Size in (USD Billion) CAGR Growth Rate 28%
| Study Period | 2019-2031 |
| Market Size (2023): | 7Billion |
| Market Size (2031): | 15Billion |
| CAGR (2023 - 2031): | 28% |
| Fastest Growing Region | North America |
| Dominating Region | North America |
www.www.htfmarketinsights.com
Schedule a personalized consultation with our industry analysts
Request for Customization
Get Customization
Key Highlights
· The Machine Learning Chips is growing at a CAGR of 28% during the forecasted period of 2019 to 2031· Year on Year growth for the market is 22%
· Based on type, the market is bifurcated into GPU, FPGA, ASIC, Neural processors segment dominated the market share during the forecasted period
· Based on application, the market is segmented into AI, Robotics, Data centers
· Global Import Export in terms of K Tons, K Units, and Metric Tons will be provided if Applicable based on industry best practice
Competitive landscape
The key players in the Machine Learning Chips are intensifying their focus on research and development (R&D) activities to innovate and stay competitive. Major companies, such as- Wave Computing Inc. (United States)
- Graphcore (United Kingdom)
- IBM (United States)
- Alphabet (United States)
- Qualcomm Technologies Inc. (United States)
- Intel Corporation (United States)
- NVIDIA Corporation (United States)
- Taiwan Semiconductor Manufacturing Company Limited (China)
- Xilinx
- Inc. (United States)
- Cerebras Systems (United States)
Moreover, these established industry leaders are actively pursuing acquisitions of smaller companies to expand their regional presence and enhance their market share. These acquisitions not only help in diversifying their product portfolios but also provide access to new technologies and markets. This consolidation trend is a critical factor in the growth of the Machine Learning Chips , as it enables larger companies to streamline operations, reduce costs, and increase their competitive edge.
For the complete companies list, please ask for sample pages
Need More Details on Market Players and Competitors?
DOWNLOAD Sample Report
In addition to R&D and acquisitions, there is a notable shift towards green investments among key players in the Machine Learning Chips . Companies are increasingly committing resources to sustainable practices and the development of environmentally friendly products. This green investment is in response to growing consumer demand for sustainable solutions and stringent environmental regulations. By prioritizing sustainability, these companies are not only contributing to environmental protection but also positioning themselves as leaders in the green chemistry movement, thereby fueling market growth.
Machine Learning Chips Dynamics
GROWTH DRIVERS: The Machine Learning Chips is propelled by several key drivers, including the demand from diverse industrial sectors such as automotive, construction, and pharmaceuticals. Technological advancements and continuous innovation in chemical processes enhance efficiency and open new market opportunities. Economic growth, particularly in emerging markets, along with rapid urbanization and population growth, increases the need for chemicals in infrastructure and consumer goods. Additionally, stricter environmental regulations and the push for sustainable products drive the development of green chemicals. Global trade, raw material availability, and investments in research and development further shape the industry's growth, while supportive government policies and evolving consumer trends also play crucial roles.- Rising Demand For Machine Learning Chips Owing To The Development Of Autonomous Robots And Vehicles That Control Themselves Ithout Human Intervention Also Propelling The Market Growth
- High Power Consumption
- Technological Advancement In Micro Electronic And Wireless Chips
TRENDS: Key trends in the Machine Learning Chips include a focus on sustainability and green chemistry, driven by environmental regulations and consumer demand. Digital transformation is enhancing efficiency through AI and automation, while advanced materials are being developed for various industries. The shift towards a circular economy promotes recycling and reuse, and personalized medicine is increasing demand for specialty chemicals. Investments in renewable energy create new opportunities, and emerging markets offer growth potential. Evolving regulations and consumer preferences for sustainable products are influencing innovation, and supply chain advancements are improving efficiency. These trends are reshaping the chemical industry and driving its growth.
- AI integration
Regulatory Framework
Several regulatory bodies oversee the chemical industry globally to ensure safety, environmental protection, and compliance with standards. Notable among these are the Environmental Protection Agency (EPA) in the United States, the European Chemicals Agency (ECHA) in the European Union, and the Occupational Safety and Health Administration (OSHA) in the United States. Other significant entities include the Health and Safety Executive (HSE) in the United Kingdom, the National Institute of Chemical Safety (NICS) in South Korea, and the Ministry of Environmental Protection (MEP) in China.Additionally, the National Industrial Chemicals Notification and Assessment Scheme (NICNAS) in Australia, the Japan Chemical Industry Association (JCIA), the Canadian Environmental Protection Act (CEPA), and the Central Pollution Control Board (CPCB) in India play crucial roles. These organizations establish regulations, conduct inspections, and enforce compliance to ensure the safe production, handling, and disposal of chemicals.
Regional Coverage
The North America leads the market share, largely due to rising consumption, a growing population, and strong economic momentum that boosts demand. In contrast, the North America is emerging as the fastest-growing area, driven by rapid infrastructure development, the expansion of industrial sectors, and heightened consumer demand, making it a critical factor for future market growth. The regions covered in our report areThis report also splits the market by region:
Regions
- North America
- LATAM
- West Europe
- Central & Eastern Europe
- Northern Europe
- Southern Europe
- East Asia
- Southeast Asia
- South Asia
- Central Asia
- Oceania
- MEA
Dominating Region
North America
{FASTEST_ROWING_REGION_MAP}
Market Segmentation Analysis
Segmentation by Type
- GPU
- FPGA
- ASIC
- Neural processors
Machine Learning Chips Market Segmentation by Type
www.htfmarketinsights.com
Segmentation by Application
- AI
- Robotics
- Data centers
Machine Learning Chips Market Segmentation by Application
www.htfmarketinsights.com
Key & Emerging Players Analyzed
The companies highlighted in this profile were selected based on insights from primary experts and an evaluation of their market penetration, product offerings, and geographical reach.- Wave Computing Inc. (United States)
- Graphcore (United Kingdom)
- IBM (United States)
- Alphabet (United States)
- Qualcomm Technologies Inc. (United States)
- Intel Corporation (United States)
- NVIDIA Corporation (United States)
- Taiwan Semiconductor Manufacturing Company Limited (China)
- Xilinx
- Inc. (United States)
- Cerebras Systems (United States)
Machine Learning Chips Market Segmentation by Players
www.htfmarketinsights.com
Machine Learning Chips - Table of Contents
Chapter 1: Market Preface
- 1.1 Global Machine Learning Chips Market Landscape
- 1.2 Scope of the Study
- 1.3 Relevant Findings & Stakeholder Advantages
Chapter 2: Strategic Overview
- 2.1 Global Machine Learning Chips Market Outlook
- 2.2 Total Addressable Market versus Serviceable Market
- 2.3 Market Rivalry Projection
Chapter 3 : Global Machine Learning Chips Market Business Environment & Changing Dynamics
-
3.1 Growth Drivers
- 3.1.1 Rising Demand for Machine Learning Chips Owing to the Development of Autonomous Robots and Vehicles that Control themselves ithout Human Intervention also Propelling the Market Growth
-
3.2 Available Opportunities
- 3.2.1 Technological Advancement in Micro Electronic and Wireless Chips
- 3.2.2
-
3.3 Influencing Trends
- 3.3.1 AI integration
- 3.3.2 Edge computing
-
3.4 Challenges
- 3.4.1 High power consumption
- 3.4.2 Competition
- 3.5 Regional Dynamics
Need only Qualitative Analysis? Get Prices
Sectional Purchase
Chapter 4 : Global Machine Learning Chips Industry Factors Assessment
- 4.1 Current Scenario
- 4.2 PEST Analysis
- 4.3 Business Environment - PORTER 5-Forces Analysis
- 4.3.1 Supplier Leverage
- 4.3.2 Bargaining Power of Buyers
- 4.3.3 Threat of Substitutes
- 4.3.4 Threat from New Entrant
- 4.3.5 Market Competition Level
- 4.4 Roadmap of Machine Learning Chips Market
- 4.5 Impact of Macro-Economic Factors
- 4.6 Market Entry Strategies
- 4.7 Political and Regulatory Landscape
- 4.8 Supply Chain Analysis
- 4.9 Impact of Tariff War
Chapter 5: Machine Learning Chips : Competition Benchmarking & Performance Evaluation
- 5.1 Global Machine Learning Chips Market Concentration Ratio
- 5.1.1 CR4, CR8 and HH Index
- 5.1.2 % Market Share - Top 3
- 5.1.3 Market Holding by Top 5
- 5.2 Market Position of Manufacturers by Machine Learning Chips Revenue 2023
- 5.3 BCG Matrix
- 5.3 Market Entropy
- 5.4 FPNV Positioning Matrix
- 5.5 Heat Map Analysis
Chapter 6: Global Machine Learning Chips Market: Company Profiles
- 6.1 Wave Computing Inc. (United States)
- 6.1.1 Wave Computing Inc. (United States) Company Overview
- 6.1.2 Wave Computing Inc. (United States) Product/Service Portfolio & Specifications
- 6.1.3 Wave Computing Inc. (United States) Key Financial Metrics
- 6.1.4 Wave Computing Inc. (United States) SWOT Analysis
- 6.1.5 Wave Computing Inc. (United States) Development Activities
- 6.2 Graphcore (United Kingdom)
- 6.3 IBM (United States)
- 6.4 Alphabet (United States)
- 6.5 Qualcomm Technologies Inc. (United States)
- 6.6 Intel Corporation (United States)
- 6.7 NVIDIA Corporation (United States)
- 6.8 Taiwan Semiconductor Manufacturing Company Limited (China)
- 6.9 Xilinx
- 6.10 Inc. (United States)
- 6.11 Cerebras Systems (United States)
- 6.12
To View a Complete List of Players? Inquiry Now
Sectional Purchase
Chapter 7 : Global Machine Learning Chips by Type & Application (2019-2031)
-
7.1 Global Machine Learning Chips Market Revenue Analysis (USD Million) by Type (2019-2023)
- 7.1.1 GPU
- 7.1.2 FPGA
- 7.1.3 ASIC
- 7.1.4 Neural Processors
- 7.1.5 Embedded Chips
-
7.2 Global Machine Learning Chips Market Revenue Analysis (USD Million) by Application (2019-2023)
- 7.2.1 AI
- 7.2.2 Robotics
- 7.2.3 Data Centers
- 7.3 Global Machine Learning Chips Market Revenue Analysis (USD Million) by Type (2023-2031)
- 7.4 Global Machine Learning Chips Market Revenue Analysis (USD Million) by Application (2023-2031)
Chapter 8 : North America Machine Learning Chips Market Breakdown by Country, Type & Application
- 8.1 North America Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 8.1.1 United States
- 8.1.2 Canada
-
8.2 North America Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 8.2.1 GPU
- 8.2.2 FPGA
- 8.2.3 ASIC
- 8.2.4 Neural Processors
- 8.2.5 Embedded Chips
-
8.3 North America Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 8.3.1 AI
- 8.3.2 Robotics
- 8.3.3 Data Centers
- 8.4 North America Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 8.5 North America Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 8.6 North America Machine Learning Chips Market by Application (USD Million) [2024-2031]
Looking for Section Purchase? Get Quote Now
Sectional Purchase
Chapter 9 : LATAM Machine Learning Chips Market Breakdown by Country, Type & Application
- 9.1 LATAM Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 9.1.1 Brazil
- 9.1.2 Argentina
- 9.1.3 Chile
- 9.1.4 Mexico
- 9.1.5 Rest of LATAM
-
9.2 LATAM Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 9.2.1 GPU
- 9.2.2 FPGA
- 9.2.3 ASIC
- 9.2.4 Neural Processors
- 9.2.5 Embedded Chips
-
9.3 LATAM Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 9.3.1 AI
- 9.3.2 Robotics
- 9.3.3 Data Centers
- 9.4 LATAM Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 9.5 LATAM Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 9.6 LATAM Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 10 : West Europe Machine Learning Chips Market Breakdown by Country, Type & Application
- 10.1 West Europe Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 10.1.1 Germany
- 10.1.2 France
- 10.1.3 Benelux
- 10.1.4 Switzerland
- 10.1.5 Rest of West Europe
-
10.2 West Europe Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 10.2.1 GPU
- 10.2.2 FPGA
- 10.2.3 ASIC
- 10.2.4 Neural Processors
- 10.2.5 Embedded Chips
-
10.3 West Europe Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 10.3.1 AI
- 10.3.2 Robotics
- 10.3.3 Data Centers
- 10.4 West Europe Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 10.5 West Europe Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 10.6 West Europe Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 11 : Central & Eastern Europe Machine Learning Chips Market Breakdown by Country, Type & Application
- 11.1 Central & Eastern Europe Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 11.1.1 Bulgaria
- 11.1.2 Poland
- 11.1.3 Hungary
- 11.1.4 Romania
- 11.1.5 Rest of CEE
-
11.2 Central & Eastern Europe Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 11.2.1 GPU
- 11.2.2 FPGA
- 11.2.3 ASIC
- 11.2.4 Neural Processors
- 11.2.5 Embedded Chips
-
11.3 Central & Eastern Europe Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 11.3.1 AI
- 11.3.2 Robotics
- 11.3.3 Data Centers
- 11.4 Central & Eastern Europe Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 11.5 Central & Eastern Europe Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 11.6 Central & Eastern Europe Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 12 : Northern Europe Machine Learning Chips Market Breakdown by Country, Type & Application
- 12.1 Northern Europe Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 12.1.1 The United Kingdom
- 12.1.2 Sweden
- 12.1.3 Norway
- 12.1.4 Baltics
- 12.1.5 Ireland
- 12.1.6 Rest of Northern Europe
-
12.2 Northern Europe Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 12.2.1 GPU
- 12.2.2 FPGA
- 12.2.3 ASIC
- 12.2.4 Neural Processors
- 12.2.5 Embedded Chips
-
12.3 Northern Europe Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 12.3.1 AI
- 12.3.2 Robotics
- 12.3.3 Data Centers
- 12.4 Northern Europe Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 12.5 Northern Europe Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 12.6 Northern Europe Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 13 : Southern Europe Machine Learning Chips Market Breakdown by Country, Type & Application
- 13.1 Southern Europe Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 13.1.1 Spain
- 13.1.2 Italy
- 13.1.3 Portugal
- 13.1.4 Greece
- 13.1.5 Rest of Southern Europe
-
13.2 Southern Europe Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 13.2.1 GPU
- 13.2.2 FPGA
- 13.2.3 ASIC
- 13.2.4 Neural Processors
- 13.2.5 Embedded Chips
-
13.3 Southern Europe Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 13.3.1 AI
- 13.3.2 Robotics
- 13.3.3 Data Centers
- 13.4 Southern Europe Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 13.5 Southern Europe Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 13.6 Southern Europe Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 14 : East Asia Machine Learning Chips Market Breakdown by Country, Type & Application
- 14.1 East Asia Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 14.1.1 China
- 14.1.2 Japan
- 14.1.3 South Korea
- 14.1.4 Taiwan
- 14.1.5 Others
-
14.2 East Asia Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 14.2.1 GPU
- 14.2.2 FPGA
- 14.2.3 ASIC
- 14.2.4 Neural Processors
- 14.2.5 Embedded Chips
-
14.3 East Asia Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 14.3.1 AI
- 14.3.2 Robotics
- 14.3.3 Data Centers
- 14.4 East Asia Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 14.5 East Asia Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 14.6 East Asia Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 15 : Southeast Asia Machine Learning Chips Market Breakdown by Country, Type & Application
- 15.1 Southeast Asia Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 15.1.1 Vietnam
- 15.1.2 Singapore
- 15.1.3 Thailand
- 15.1.4 Malaysia
- 15.1.5 Indonesia
- 15.1.6 Philippines
- 15.1.7 Rest of SEA Countries
-
15.2 Southeast Asia Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 15.2.1 GPU
- 15.2.2 FPGA
- 15.2.3 ASIC
- 15.2.4 Neural Processors
- 15.2.5 Embedded Chips
-
15.3 Southeast Asia Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 15.3.1 AI
- 15.3.2 Robotics
- 15.3.3 Data Centers
- 15.4 Southeast Asia Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 15.5 Southeast Asia Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 15.6 Southeast Asia Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 16 : South Asia Machine Learning Chips Market Breakdown by Country, Type & Application
- 16.1 South Asia Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 16.1.1 India
- 16.1.2 Bangladesh
- 16.1.3 Others
-
16.2 South Asia Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 16.2.1 GPU
- 16.2.2 FPGA
- 16.2.3 ASIC
- 16.2.4 Neural Processors
- 16.2.5 Embedded Chips
-
16.3 South Asia Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 16.3.1 AI
- 16.3.2 Robotics
- 16.3.3 Data Centers
- 16.4 South Asia Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 16.5 South Asia Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 16.6 South Asia Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 17 : Central Asia Machine Learning Chips Market Breakdown by Country, Type & Application
- 17.1 Central Asia Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 17.1.1 Kazakhstan
- 17.1.2 Tajikistan
- 17.1.3 Others
-
17.2 Central Asia Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 17.2.1 GPU
- 17.2.2 FPGA
- 17.2.3 ASIC
- 17.2.4 Neural Processors
- 17.2.5 Embedded Chips
-
17.3 Central Asia Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 17.3.1 AI
- 17.3.2 Robotics
- 17.3.3 Data Centers
- 17.4 Central Asia Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 17.5 Central Asia Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 17.6 Central Asia Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 18 : Oceania Machine Learning Chips Market Breakdown by Country, Type & Application
- 18.1 Oceania Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 18.1.1 Australia
- 18.1.2 New Zealand
- 18.1.3 Others
-
18.2 Oceania Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 18.2.1 GPU
- 18.2.2 FPGA
- 18.2.3 ASIC
- 18.2.4 Neural Processors
- 18.2.5 Embedded Chips
-
18.3 Oceania Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 18.3.1 AI
- 18.3.2 Robotics
- 18.3.3 Data Centers
- 18.4 Oceania Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 18.5 Oceania Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 18.6 Oceania Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 19 : MEA Machine Learning Chips Market Breakdown by Country, Type & Application
- 19.1 MEA Machine Learning Chips Market by Country (USD Million) [2019-2023]
- 19.1.1 Turkey
- 19.1.2 South Africa
- 19.1.3 Egypt
- 19.1.4 UAE
- 19.1.5 Saudi Arabia
- 19.1.6 Israel
- 19.1.7 Rest of MEA
-
19.2 MEA Machine Learning Chips Market by Type (USD Million) [2019-2023]
- 19.2.1 GPU
- 19.2.2 FPGA
- 19.2.3 ASIC
- 19.2.4 Neural Processors
- 19.2.5 Embedded Chips
-
19.3 MEA Machine Learning Chips Market by Application (USD Million) [2019-2023]
- 19.3.1 AI
- 19.3.2 Robotics
- 19.3.3 Data Centers
- 19.4 MEA Machine Learning Chips Market by Country (USD Million) [2024-2031]
- 19.5 MEA Machine Learning Chips Market by Type (USD Million) [2024-2031]
- 19.6 MEA Machine Learning Chips Market by Application (USD Million) [2024-2031]
Chapter 20: Research Findings & Conclusion
- 20.1 Key Findings
- 20.2 Conclusion
Chapter 21: Methodology and Data Source
-
21.1 Research Methodology & Approach
- 21.1.1 Research Program/Design
- 21.1.2 Market Size Estimation
- 21.1.3 Market Breakdown and Data Triangulation
-
21.2 Data Source
- 21.2.1 Secondary Sources
- 21.2.2 Primary Sources
Chapter 22: Appendix & Disclaimer
- 22.1 Acronyms & bibliography
- 22.2 Disclaimer
Frequently Asked Questions (FAQ):
The Global Machine Learning Chips market is estimated to see a CAGR of 28% and may reach an estimated market size of 28% 15Billion by 2031.
The Machine Learning Chips Market is growing at a CAGR of 28% over the forecasted period 2023 - 2031.
AI Integration, Edge Computing are seen to make big Impact on Machine Learning Chips Market Growth.
- Rising Demand For Machine Learning Chips Owing To The Development Of Autonomous Robots And Vehicles That Control Themselves Ithout Human Intervention Also Propelling The Market Growth
Some of the major roadblocks that industry players have identified are High Power Consumption, Competition.
The market opportunity is clear from the flow of investment into Global Machine Learning Chips Market, some of them are Technological Advancement In Micro Electronic And Wireless Chips,,
.
New entrants, including competitors from unrelated industries along with players such as Wave Computing Inc. (United States), Graphcore (United Kingdom), IBM (United States), Alphabet (United States), Qualcomm Technologies Inc. (United States), Intel Corporation (United States), NVIDIA Corporation (United States), Taiwan Semiconductor Manufacturing Company Limited (China), Xilinx, Inc. (United States), Cerebras Systems (United States), Instituting a robust process in Global Machine Learning Chips Market.
The Global Machine Learning Chips Market Study is Broken down by applications such as AI, Robotics, Data centers.
The Global Machine Learning Chips Market Study is segmented by GPU, FPGA, ASIC, Neural processors, Embedded chips.
The Global Machine Learning Chips Market Study includes regional breakdown as North America, LATAM, West Europe,Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA
Historical Year: 2019 - 2023; Base year: 2023; Forecast period: 2025 to 2031
Machine learning chip is the hardware accelerator or application-based computer system designed to accelerate machine learning applications. Machine learning applications involve algorithms for robotics, the internet of things and other data-intensive or sensor-driven tasks. These chip provides much more data security, latency and consumes much less power. They are designed to do certain AI problems faster at lower power than traditional processors. In the market, more than 100 companies are working on building next-generation chips and hardware architecture that would match the capabilities of algorithms. These machine-learning chips are capable of enabling deep learning applications on smartphones and other edge computing devices. The companies are using machine learning technology to improve business decisions, increase productivity, and detect disease, forecast weather, and others. The applications of machine learning involve virtual personal assistants, predictions while commuting, video surveillance, social media services, email spam and malware filtering, online fraud detection, and others.
HTF Market Intelligence, All right reserved 2025.
Designed By S3World