Artificial Intelligence Chipsets Market by Technology (Machine Learning, Natural Language Processing, Context-Aware Computing, Computer Vision), Hardware (Processor, Memory, Network), End-User Industry, and Geography - Global Forecast to 2025
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Request Now[187 Pages Report] MarketsandMarkets forecasts the artificial intelligence (AI) chipset market to grow the highest CAGR, during the forecast period. The major factors that are expected to be driving the AI chipset market are the demand for increasingly large and complex dataset; the adoption of AI for improving consumer services and reducing operational costs; growing number of AI applications; and improving computing power and declining hardware cost.
By hardware, processor is expected to grow at the highest growth rate during the forecast period
Among the hardware segment, the artificial intelligence chipset market is expected to grow at the highest CAGR during the forecast period. The processor segment consists of graphics processing units (GPUs), microprocessor units (CPUs), field-programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs). GPUs are being conventionally developed by companies such as NVIDIA (US) and ARM (UK) for gaming purposes. High parallel processing capabilities and improved computing power have resulted in their adoption in various AI applications. Tensor processing units (TPUs) were launched by Google (an Alphabet (US) company) in early 2016. Intel (US) has been a leading provider of CPUs, and Xilinx Inc. (US) is a major provider of FPGAs for AI applications.
By technology, machine learning is expected to grow at the highest growth rate during the forecast period
Among the hardware segment, the artificial intelligence chipset market is expected to grow at the highest CAGR during the forecast period. Machine learning’s ability to collect and handle big data, and its applications in real-time speech translation, autonomous robots, and facial analysis are fueling its growth. AI constitutes various technologies that play a vital role in developing its ecosystem. As AI enables machines to perform activities similar to those performed by human beings, enormous market opportunities have opened up. In this study, the AI (chipsets) market has been segmented on the basis of technologies into machine learning (ML), natural language processing (NLP), context-aware computing, and computer vision. ML is further classified into deep learning, supervised learning, unsupervised learning, reinforcement learning, and others (semi-supervised learning, federated learning, and other ML techniques).
By end-user industry, the artificial intelligence chipset segment is expected to grow at the highest growth rate during the forecast period
Among the end-user segment, the artificial intelligence chipset market is expected to grow at the highest CAGR during the forecast period. Improving consumer shopping experience and personalized advertising are the key drivers for the growth of AI (chipsets) in the retail market. Moreover, with rapid developments in technologies such as augmented reality (AR), virtual reality (VR), and innovative service offerings, AI is prepared to revolutionize the financial sector by driving real-time user experience and customer engagement. The AI (chipsets) market for the manufacturing industry is expected to witness the highest growth during the forecast period. This growth is attributed to increasing factory automation and growing demand to reduce operational costs. Additionally, trends such as Industry 4.0 are boosting the growth of AI (chipsets) in the manufacturing sector.
By Region, North America is expected to grow at the highest growth rate during the forecast period
North America accounted for the largest share of the AI (chipsets) market in 2017. Increasing adoption of AI technology in various end-user industries, such as healthcare, manufacturing, automotive, agriculture, retail, marketing, law, and fintech, and strong presence of industry giants and emerging AI companies in the region are key factors supporting the growth of the AI (chipsets) market in North America. The market in APAC is anticipated to grow at the highest CAGR during the forecast period. This growth can be attributed to the adoption of AI services in end-user industries such as manufacturing, healthcare, and automotive in countries such as Japan, China, Australia, and South Korea. Additionally, declining AI hardware cost and increasing demand to improve consumer services are supplementing the growth of the AI (chipsets) market in APAC.
Market Dynamics
Driver: Increasingly large and complex dataset driving the need for AI
Converging data from various sectors, such as healthcare, banking, law, investment management, security, advertising, equity trading, defense, and financial services, has increased the need for autonomous decision-making systems. Additionally, the rising number of devices or nodes as a result of technology trends such as IoT and industrial initiatives such as Industry 4.0 has escalated data generation. Continuous increase in the number of internet users across the globe is expected to further strengthen the overall market for IoT owing to the growth in internet-enabled smart devices, such as radio frequency identification (RFID) devices, barcode scanners, and mobile computers.
Restraint: Lack of skilled workforce and absence of standards and protocols
AI is a complex system, and for developing, managing, and implementing AI systems, companies require a workforce with certain skill sets. For instance, personnel dealing with AI systems should be aware of technologies such as cognitive computing, ML and machine intelligence, deep learning, and image recognition. In addition, the integration of AI solutions into the existing systems is a difficult task, which requires extensive data processing to replicate the behavior of a human brain. Even a minor error can result in system failure or can adversely affect the desired result. Furthermore, the absence of professional standards and certifications in AI/ML technologies is restraining the growth of AI. Additionally, AI service providers are facing challenges with regard to deploying/servicing their solutions at their customer site. This is because of the lack of technology awareness and the limitation of AI experts.
As AI technology is still in the nascent stage of its product life cycle, the workforce possessing in-depth knowledge of this technology is limited. Thus, the impact of this restraining factor will likely remain high during the initial years of the forecast period.
The lack of standards and protocols is further hindering the growth of the AI chipsets market. New metrics and standards must be developed to deploy secure, usable, reliable, and interoperable AI technologies that make decisions based on data-driven models, such as machine learning. This can be done by collaborating with stakeholders to develop AI evaluation methodologies, best practices, and standard testing/working protocols.
Opportunity: Increasing focus on developing human-aware AI systems
The actual projections aimed at during the emergence of AI technologies were to make them human-aware, i.e., developing models with the characteristics of human thinking. However, creating interactive and scalable machines remains a challenge for the developers of AI machines. Additionally, increasing human interference with AI techniques has introduced new research challenges, i.e., interpretation and presentation challenges, such as interaction issues with automating parts and intelligent control of crowdsourcing parts. Interpretation challenges include challenges faced by AI machines in understanding human input, such as knowledge and specific directives. Presentation challenges include issues related to delivering the AI system’s output and feedback. Thus, the development of human-aware AI systems remains the foremost opportunity for AI developers.
Challenge: Low return on investment
Stakeholders in AI have predominately invested to develop AI technologies. This has resulted in the development of new AI algorithms, acquisitions, and development tools. Developments have particularly been observed in diverse applications, such as computer vision, autonomous vehicles, and video game playing. However, evidence about the return on investment is still gloomy. Ambitious AI products, which are still in the research papers and academics stage, are far from reality. For instance, software programs currently compiled for one architecture cannot run on another architecture. Similarly, high error rates—with respect to computational efficiency of AI algorithms—are challenging the growth of the AI market. Moreover, issues such as privacy and security are among the prime causes of concern in AI.
Scope of the Report
The research report categorizes the Artificial Intelligence Chipset Market to forecast the revenues and analyze the trends in each of the following sub-segments:
Artificial Intelligence (Chipset) Market, By Technology
- Machine Learning
- Natural Language Processing
- Context–Aware Computing
- Computer Vision
Artificial Intelligence Chipset Market, By Hardware
- Processor
- Memory
- Network
Artificial Intelligence Chipset Market, By End User Industry
- Healthcare
- Manufacturing
- Automotive
- Agriculture
- Retail
- Security
- Human Resources
- Marketing
- Law
- Fintech
Artificial Intelligence (Chipset) Market, By Region
- North America
- Europe
- APAC
- Rest of the World
Key Market Players
Nvidia (US), Intel (US), Xilink (US), Samsung Electronics (South Korea), Micron Technology (US), Qualcomm Technologies (US), IBM (US), Google (US), Microsoft (US), and Amazon Web Services (US).
NVIDIA develops GPUs and delivers value to its consumers through PC, mobile, and cloud architectures. From focus on PC graphics, the company now emphasizes on machine learning and various other technologies of AI. NVIDIA was incorporated in California in 1993 and reincorporated in Delaware in 1998.
NVIDIA has 2 reportable segments: GPU and Tegra Processor. The GPU segment consists of GeForce, Quadro, GeForce NOW, Quadro, Tesla, and GRID. GeForce is used for visual computing in PC gaming. Quadro is used for computer-aided design, video editing, and other applications. GeForce NOW is for cloud-based game-streaming service. Quadro is for designers in the field of computer-aided design, special effects, video editing, and other applications. Tesla is designed to meet deep learning and accelerated computing applications, and GRID is used to power NVIDIA graphics through the cloud and data centers. The Tegra Processor segment includes Tegra, DRIVE PX, and SHIELD. Tegra processors are high-performance processors designed to enable DRIVE and SHIELD platforms. Automotive computers use DRIVE PX processors for self-driving capabilities, while mobile cloud gaming applications use SHIELD processors. The company targets gaming, professional visualization, data center, and automotive markets.
NVIDIA has more than 40 offices spread across the Americas, Asia, and Europe. NVIDIA has wide geographic reach through subsidiaries such as ADEIA Technologies Switzerland AG (Switzerland), Icera Canada ULC (Canada), NVIDIA Brasil Computação Visual Limitada (Brazil), NVIDIA Development UK Limited (England and Wales), NVIDIA Entertainment Devices Co., Ltd. (China), NVIDIA Graphics Private Limited (India), and NVIDIA GmbH (Germany).
Recent Developments
- In December 2017, NVIDIA introduced TITAN V, the world’s most powerful GPU for the PC, driven by the world’s most advanced GPU architecture, NVIDIA Volta. TITAN V excels at computational processing for scientific simulation. Its 21.1-billion transistors deliver 110 teraflops of raw horsepower, 9x that of its predecessor, and extreme energy efficiency
- In December 2017, IBM unveiled its next-generation Power Systems Servers incorporating its newly designed POWER9 processor. Built specifically for compute-intensive AI workloads, the new POWER9 systems are capable of improving the training times of deep learning frameworks by nearly 4x, allowing enterprises to build more accurate AI applications faster
- In December 2017, Qualcomm Technologies introduced the new Qualcomm Snapdragon 845 Mobile Platform. Snapdragon 845 utilizes Qualcomm Technologies’ industry-leading wireless heterogeneous compute expertise to design a platform for immersive multimedia experiences, including eXtended reality (XR), on-device artificial intelligence (AI), and lightning-fast connectivity, and introduces new secure processing unit (SPU) delivering vault-like security for premium, flagship mobile devices
- In November 2017, AWS launched 3 language-oriented services—Amazon Comprehend (analyzes text for key phrases and sentiments), Amazon Translate (translates text), and Amazon Transcribe (converts speech into text)
- In October 2017, Intel is likely to ship the industry’s first silicon for neural network processing, Intel Nervana Neural Network Processor (NNP), before the end of 2017. Intel has collaborated with Facebook to bring Facebook’s technical insights to develop this new AI hardware. Intel Nervana NNP promises to revolutionize AI computing across industries. Using Intel Nervana technology, end-user companies will be able to develop entirely new classes of AI applications that maximize the amount of data processed and enable customers to find greater insights—transforming their businesses.
Key Questions Answered
- Where will all these developments take the industry in the long term?
- What are the upcoming trends for the Artificial Intelligence (Chipset) market?
- Which segment provides the most opportunity for growth?
- Who are the leading vendors operating in this market?
- What are the opportunities for new market entrants?
To speak to our analyst for a discussion on the above findings, click Speak to Analyst
Table of Contents
1 Introduction (Page No. - 16)
1.1 Objectives of the Study
1.2 Definition
1.3 Study Scope
1.3.1 Market Covered
1.3.2 Years Considered for Study
1.4 Currency
1.5 Package Size
1.6 Stakeholders
2 Research Methodology (Page No. - 19)
2.1 Research Data
2.1.1 Secondary Data
2.1.1.1 Secondary Sources
2.1.2 Primary Data
2.1.2.1 Primary Interviews With Experts
2.1.2.2 Primary Sources
2.1.2.3 Breakdown of Primaries
2.1.2.4 Key Industry Insights
2.2 Market Size Estimation
2.2.1 Bottom-Up Approach
2.2.2 Top-Down Approach
2.3 Market Breakdown and Data Triangulation
2.4 Assumptions
3 Executive Summary (Page No. - 28)
4 Premium Insights (Page No. - 33)
4.1 Attractive Opportunities in AI Chip Market
4.2 AI Chip market, By Hardware
4.3 Machine Learning Market, By Subtype
4.4 Asia Pacific: Market, By End-User Industry and Country
4.5 AI Chipsets Market, By Country
5 Market Overview (Page No. - 37)
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasingly Large and Complex Dataset Driving the Need for AI
5.2.1.2 Adoption of AI for Improving Consumer Services and Reducing Operational Costs
5.2.1.3 Growing Number of AI Applications
5.2.1.4 Improving Computing Power and Declining Hardware Cost
5.2.2 Restraints
5.2.2.1 Lack of Skilled Workforce and Absence of Standards and Protocols
5.2.3 Opportunities
5.2.3.1 Increasing Focus on Developing Human-Aware AI Systems
5.2.3.2 Bringing AI to Edge Devices
5.2.4 Challenges
5.2.4.1 Low Return on Investment
5.2.4.2 Creating Models and Mechanisms for AI
5.2.4.3 Limited Structured training Data
6 AI Chip Market, By Technology (Page No. - 46)
6.1 Introduction
6.2 Machine Learning
6.2.1 Deep Learning
6.2.2 Supervised Learning
6.2.3 Unsupervised Learning
6.2.4 Reinforcement Learning
6.2.5 Others
6.3 Natural Language Processing
6.4 Context-Aware Computing
6.5 Computer Vision
7 Artificial Intelligence Chipset Market, By Hardware (Page No. - 52)
7.1 Introduction
7.2 Processor
7.3 Memory
7.4 Network
8 AI Chipsets Market, By End-User Industry (Page No. - 57)
8.1 Introduction
8.2 Healthcare
8.2.1 Patient Data & Risk Analysis
8.2.2 Lifestyle Management & Monitoring
8.2.3 Precision Medicine
8.2.4 Inpatient Care & Hospital Management
8.2.5 Medical Imaging & Diagnostics
8.2.6 Drug Discovery
8.2.7 Virtual Assistant
8.2.8 Wearables
8.2.9 Research
8.3 Manufacturing
8.3.1 Material Movement
8.3.2 Predictive Maintenance and Machinery Inspection
8.3.3 Production Planning
8.3.4 Field Services
8.3.5 Reclamation
8.3.6 Quality Control
8.4 Automotive
8.4.1 Autonomous Driving
8.4.2 Human–Machine Interface
8.4.3 Semiautonomous Driving
8.5 Agriculture
8.5.1 Precision Farming
8.5.2 Livestock Monitoring
8.5.3 Drone Analytics
8.5.4 Agricultural Robots
8.5.5 Others
8.6 Retail
8.6.1 Product Recommendation and Planning
8.6.2 Customer Relationship Management
8.6.3 Visual Search
8.6.4 Virtual Assistant
8.6.5 Price Optimization
8.6.6 Payment Services Management
8.6.7 Supply Chain Management and Demand Planning
8.6.8 Others
8.7 Security
8.7.1 Identity and Access Management (IAM)
8.7.2 Risk and Compliance Management
8.7.3 Encryption
8.7.4 Data Loss Prevention
8.7.5 Unified Threat Management
8.7.6 Antivirus/Antimalware
8.7.7 Intrusion Detection/Prevention Systems
8.7.8 Others
8.8 Human Resources
8.8.1 Virtual Assistant
8.8.2 Sentiment Analysis
8.8.3 Scheduling Group Meetings and Interviews
8.8.4 Personalized Learning and Development
8.8.5 Applicant Tracking & Assessment
8.8.6 Employee Engagement
8.8.7 Resume Analysis
8.9 Marketing
8.9.1 Social Media Advertising
8.9.2 Search Advertising
8.9.3 Dynamic Pricing
8.9.4 Virtual Assistant
8.9.5 Content Curation
8.9.6 Sales & Marketing Automation
8.9.7 Analytics Platform
8.9.8 Others
8.10 Law
8.10.1 Ediscovery
8.10.2 Legal Research
8.10.3 Contract Analysis
8.10.4 Case Prediction
8.10.5 Compliance
8.10.6 Others
8.11 Fintech
8.11.1 Virtual Assistant
8.11.2 Business Analytics and Reporting
8.11.3 Customer Behavior Analytics
8.11.4 Others
9 Artificial Intelligence Chipset Market, By Region (Page No. - 97)
9.1 Introduction
9.2 North America
9.2.1 US
9.2.2 Canada
9.2.3 Mexico
9.3 Europe
9.3.1 UK
9.3.2 Germany
9.3.3 France
9.3.4 Italy
9.3.5 Spain
9.3.6 Rest of Europe
9.4 APAC
9.4.1 China
9.4.2 Japan
9.4.3 South Korea
9.4.4 India
9.4.5 Rest of APAC
9.5 Rest of the World
9.5.1 Middle East and Africa
9.5.2 South America
10 AI Chipsets Market, by Competitive Landscape (Page No. - 127)
10.1 Overview
10.2 Ranking of Players, 2017
10.3 Competitive Scenario
10.3.1 New Product Developments and Launches
10.3.2 Collaborations and Partnerships
10.3.3 Acquisitions
11 AI Chip Market, by Company Profiles (Page No. - 134)
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
11.1 Key Players
11.1.1 Nvidia
11.1.2 Intel
11.1.3 Xilinx
11.1.4 Samsung Electronics
11.1.5 Micron Technology
11.1.6 Qualcomm Technologies
11.1.7 IBM
11.1.8 Google
11.1.9 Microsoft
11.1.10 Amazon Web Services (AWS)
11.2 Other Companies
11.2.1 AMD
11.2.2 General Vision
11.2.3 Graphcore
11.2.4 Mellanox Technologies
11.2.5 Huawei Technologies
11.2.6 Fujitsu
11.2.7 Wave Computing
11.2.8 Mythic
11.2.9 Adapteva
11.2.10 Koniku
11.2.11 Tenstorrent
*Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM view Might Not Be Captured in Case of Unlisted Companies.
12 Appendix (Page No. - 177)
12.1 Insights From Industry Experts
12.2 Discussion Guide
12.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
12.4 Introducing RT: Real-Time Market Intelligence
12.5 Available Customizations
12.6 Related Reports
12.7 Author Details
List of Tables (66 Tables)
Table 1 Major Secondary Sources
Table 2 Average Number of Connected Devices Per Capita
Table 3 Price Comparison: AI Chipsets (Leading Companies)
Table 4 Some Prominent Investments in AI Market in Past 3 Years
Table 5 AI Chipsets Market, By Technology, 2015–2025 (USD Billion)
Table 6 AI Chip Market for Machine Learning, By Type, 2015–2025 (USD Million)
Table 7 AI Chip Market, By Hardware, 2015–2025 (USD Billion)
Table 8 AI Chip Market, By Processor, 2015–2025 (USD Million)
Table 9 AI Chip Market, By Processor, 2015–2025 (Thousand Units)
Table 10 AI Chipsets Market, By End-User Industry, 2015–2025 (USD Million)
Table 11 AI Chipsets Market for Healthcare, By Region, 2015–2025 (USD Million)
Table 12 AI Chipsets Market for Healthcare, By Technology, 2015–2025 (USD Million)
Table 13 AI Chipset Market for Healthcare, By Application, 2015–2025 (USD Million)
Table 14 AI Chip Market for Manufacturing, By Region, 2015–2025 (USD Million)
Table 15 AI Chip Market for Manufacturing, By Technology, 2015–2025 (USD Million)
Table 16 AI Chip Market for Manufacturing, By Application, 2015–2025 (USD Million)
Table 17 AI Chip Market for Automotive, By Region, 2015–2025 (USD Million)
Table 18 Market for Automotive, By Technology, 2015–2025 (USD Million)
Table 19 Market for Automotive, By Application, 2015–2025 (USD Million)
Table 20 Market for Agriculture, By Region, 2015–2025 (USD Million)
Table 21 Market for Agriculture, By Technology, 2015–2025 (USD Million)
Table 22 Market for Agriculture, By Application, 2015–2025 (USD Million)
Table 23 Market for Retail, By Region, 2015–2025 (USD Million)
Table 24 AI Chip Market for Retail, By Technology, 2015–2025 (USD Million)
Table 25 AI Chipsets Market for Retail, By Application, 2015–2025 (USD Million)
Table 26 Market for Security, By Region, 2015–2025 (USD Million)
Table 27 Market for Security, By Technology, 2015–2025 (USD Million)
Table 28 Market for Security, By Application, 2015–2025 (USD Million)
Table 29 Market for Hr, By Region, 2015–2025 (USD Million)
Table 30 Market for Hr, By Technology, 2015–2025 (USD Million)
Table 31 Market for Hr, By Application, 2015–2025 (USD Million)
Table 32 Market for Marketing, By Region, 2015–2025 (USD Million)
Table 33 Market for Marketing, By Technology, 2015–2025 (USD Million)
Table 34 Market for Marketing, By Application, 2015–2025 (USD Million)
Table 35 Market for Law, By Region, 2015–2025 (USD Million)
Table 36 Market for Law, By Technology, 2015–2025 (USD Million)
Table 37 AI Chipsets Market for Law, By Application, 2015–2025 (USD Million)
Table 38 AI Chip Market for Fintech, By Region, 2015–2025 (USD Million)
Table 39 Market for Fintech, By Technology, 2015–2025 (USD Million)
Table 40 Market for Fintech, By Application, 2015–2025 (USD Million)
Table 41 Market, By Region, 2015–2025 (USD Billion)
Table 42 AI Chipsets Market in North America, By Country, 2015–2025(USD Million)
Table 43 Market in North America, By End-User Industry, 2015–2025 (USD Million)
Table 44 Market in US, By End-User Industry, 2015–2025 (USD Million)
Table 45 Market in Canada, By End-User Industry, 2015–2025 (USD Million)
Table 46 Market in Mexico, By End-User Industry, 2015–2025 (USD Million)
Table 47 Market in Europe, By Country, 2015–2025 (USD Million)
Table 48 Market in Europe, By End-User Industry, 2015–2025 (USD Million)
Table 49 AI Chipsets Market in Uk, By End-User Industry, 2015–2025 (USD Million)
Table 50 AI Chip Market in Germany, By End-User Industry, 2015–2025 (USD Million)
Table 51 Market in France, By End-User Industry, 2015–2025 (USD Million)
Table 52 Market in Italy, By End-User Industry, 2015–2025 (USD Million)
Table 53 Market in Spain, By End-User Industry, 2015–2025 (USD Million)
Table 54 Market in Rest of Europe, By End-User Industry, 2015–2025 (USD Million)
Table 55 Market in APAC, By Country, 2015–2025 (USD Million)
Table 56 Market in APAC, By End-User Industry, 2015–2025 (USD Million)
Table 57 Market in China, By End-User Industry, 2015–2025 (USD Million)
Table 58 Market in Japan, By End-User Industry, 2015–2025 (USD Million)
Table 59 Market in South Korea, By End-User Industry, 2015–2025 (USD Million)
Table 60 AI Chipsets Market in India, By End-User Industry, 2015–2025 (USD Million)
Table 61 AI Chip Market in Rest of APAC, By End-User Industry, 2015–2025 (USD Million)
Table 62 Market in RoW, By Region, 2015–2025(USD Million)
Table 63 Market in RoW, By End-User Industry, 2015–2025 (USD Million)
Table 64 Market in Middle East and Africa, By End-User Industry, 2015–2025 (USD Million)
Table 65 AI Chipsets Market in South America, By End-User Industry, 2015–2025 (USD Million)
Table 66 Ranking of Key Companies in AI Chipsets Market (2017)
List of Figures (48 Figures)
Figure 1 Research Design
Figure 2 Bottom-Up Approach
Figure 3 Top-Down Approach
Figure 4 Data Triangulation
Figure 5 AI Chip Market, By Hardware, 2018 vs 2025 (USD Billion)
Figure 6 AI Chipsets Market, By Processor, 2018 vs 2025 (USD Billion)
Figure 7 Market, By Technology, 2015-2025 (USD Billion)
Figure 8 Market, By End-User Industry, 2018 vs 2025 (%)
Figure 9 AI Chip Market, By Geography, 2018
Figure 10 Improving Computing Efficiency of the AI Chipsets is Expected to Drive the Market Between 2018 and 2025
Figure 11 Processor to Hold the Largest Share of Artificial Intelligence Chipsets Market During the Forecast Period
Figure 12 Artificial Intelligence Chipsets Market for Supervised Learning to Hold Largest Size Between 2018 and 2025
Figure 13 China Expected to Hold Largest Share of APAC AI Chip Market in 2018
Figure 14 US to Hold Largest Share of Artificial Intelligence Chipsets Market in 2018
Figure 15 Growing Number of Applications of AI Technologies in Various Industry Verticals Driving Market Growth
Figure 16 IP Traffic Growth Projections Till 2021
Figure 17 Supervised Learning to Hold Largest Size of AI (Chipsets) Market for Machine Learning Throughout Forecast Period
Figure 18 AI (Chipsets) Processor Market for GPU to Grow at Highest CAGR During Forecast Period
Figure 19 AI Chipsets Market for Manufacturing to Grow at Highest CAGR During Forecast Period
Figure 20 Predictive Maintenance and Machinery Inspection to Hold Largest Share of Artificial Intelligence Chipsets Market for Manufacturing During Forecast Period
Figure 21 North America to Hold Largest Share of AI Chip Market for Automotive During Forecast Period
Figure 22 Machine Learning Technology to Dominate Artificial Intelligence Chipsets Market for Agriculture Throughout Forecast Period
Figure 23 Retail AI Chipsets Market for Visual Search to Grow at Highest CAGR From 2018 to 2025
Figure 24 Antivirus/Antimalware to Hold Largest Size of AI Chip Market for Security in 2018
Figure 25 Applicant Tracking & Assessment to Grow the Highest CAGR in AI Chipsets Market for Hr Throughout Forecast Period
Figure 26 Artificial Intelligence Chipsets Market for Virtual Assistant to Grow at Highest CAGR Between 2018 and 2025
Figure 27 Legal Research Held Largest Market Share in 2018
Figure 28 Virtual Assistant Projected to Witness Highest Growth Between 2018 and 2025
Figure 29 Rapidly Growing Markets Such as China, Japan, Germany, and India Emerging as New Hot Spots in AI (Chipsets) Market
Figure 30 Artificial Intelligence Chipsets Market in APAC to Grow at Highest CAGR From 2018 to 2025
Figure 31 Market Snapshot: North America
Figure 32 Marketing to Hold Largest Size of Canadian AI Chip Market Between 2018 and 2025
Figure 33 Market Snapshot: Europe
Figure 34 Healthcare to Hold Largest Size of German Artificial Intelligence Chipsets Market By 2025
Figure 35 Market Snapshot: Asia Pacific
Figure 36 Marketing to Hold Largest Share of South Korean Artificial Intelligence Chipsets Market in 2025
Figure 37 Market Snapshot: Rest of the World
Figure 38 Key Developments Adopted By the Top Players in the AI (Chipsets) Market Between 2015 and 2017
Figure 39 Nvidia: Company Snapshot
Figure 40 Intel: Company Snapshot
Figure 41 Xilinx: Company Snapshot
Figure 42 Samsung Electronics: Company Snapshot
Figure 43 Micron Technology: Company Snapshot
Figure 44 Qualcomm Technologies: Company Snapshot
Figure 45 IBM: Company Snapshot
Figure 46 Google: Company Snapshot
Figure 47 Microsoft: Company Snapshot
Figure 48 AWS: Company Snapshot
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