Deep Learning Chipset Market by Type (CPUs, GPUs, FPGAs, ASICs, and Others), Technology, Compute Capacity and Geography - Global Industry Analysis, Opportunities and Forecast up to 2026

The global deep learning chipset market size was valued at $5.46 billion in 2020, and is projected to reach $33.08 billion by 2026, growing at a CAGR of 35.0% during the forecast period.

• Popularity of Internet of Things (IoT), increase in demand for automated devices, increased adoption of cloud based technology, and deep learning usage in big data analytics are the factors driving the growth of the deep learning chipset market.

• Additionally, deep learning technology has arrived many industries around the world and is accomplished through applications like computer vision, speech synthesis, voice recognition, machine translation, drug discovery, game play and robotics which are anticipated to provide lucrative growth opportunities for the key players in the deep learning chipset market..

• However, lack of a skilled workforce is one of the significant restraints of the market. For example, people trading with AI systems should know regarding technologies, such as cognitive computing, ML & machine intelligence, deep learning, and image recognition.

• Moreover, According to Cloud Computing Statistics, 90% of companies use some type of cloud service.  80% of enterprises use Amazon Web Services as their primary cloud platform. Also 77% of enterprises have at least one application or a portion of it in the cloud. With machine learning technologies, computers can be taught to analyze data, identify hidden patterns, make classifications and predict future outcomes.

Deep learning is a subclass of machine learning in artificial intelligence (AI) that involves systems that can learn unsupervised from unstructured or unlabeled data. Deep learning is similar to a brain, and it has been drilling a variety of businesses all over the world. Software such as computer vision, voice recognition, speech synthesis, machine translation, game play, drug discovery, and robots are used to deliver this technology. Deep learning chips are Silicon chips with AI and machine learning technologies built in. Deep learning and machine learning, which are artificial intelligence (AI) subsets, are used to complete AI-related tasks. Deep learning is being used in a variety of applications, including business apps that use picture recognition, open-source platforms with consumer recommendation apps, and medical analysis tools that look into the possibility of repurposing medications for new ailments.

By End User, the Automotive Segment is Expected to Project a Significant Growth over the Forecast Period

The automotive segment is expected to project a significant growth during the forecast period. Deep learning has been considered as a major formidable tool for enterprises that require actionable insights and enable automated responses to large unstructured data. Most of the advanced automation found in enterprise AI platforms is attributed to the growth and adoption of machine learning and deep learning.

By Geography, North America Region is Projected to Strong Presence in the Global Market

North America accounts for the highest market share in the past few years and is also expected to grow at the highest CAGR during the forecast period. Concerns about the security of critical infrastructure and sensitive data have prompted increased government action in recent years, culminating in the use of artificial intelligence (chipsets) in security applications in this region. Government assistance, particularly in the United States, is also fueling the region's expansion of these devices in automotive applications.

List of the Key Players Profiled in the market Include:
• Advanced Micro Devices, Inc.
• Amazon.Com
• Alphabet Inc.
• CEVA, Inc.
• Graphcore Ltd
• IBM Corporation
• Intel Corporation
• Movidius
• NVIDIA Corporation
• QUALCOMM Incorporated
• TeraDeep Inc.
• XILINX INC.
• Samsung Electronics Co., Ltd. (Samsung Group)
• Baidu, Inc

What Can be Explored with this Research Report:

• Understand the key trends that will drive the market, challenges it faces in the current market scenario.
• Identify growth opportunities.
• Porter’s five force analysis.
• In-depth analysis of market segments, and regions/countries predicted to observed promising growth.
• Historical and forecast size of the market in terms of revenue (USD Million).
• Company profiling with key products and solution offerings, key financial information, SWOT analysis, and business strategies adopted.
 
Market Segmentation:

The research report includes in-depth coverage of the industry analysis with size, share, and forecast for the below segments:

Market by, Type:
• Central Processing Units (CPUs)
• Graphics Processing Units (GPUs)
• Field Programmable Gate Arrays (FPGAs)
• Application-Specific Integrated Circuits (ASICs)
• Other Types
   
Market by, Technology:
• System-on-chip (SOC)
• System-in-package (SIP)
• Multi-Chip Module
• Other Technologies
 
Market by, Compute Capacity:
• High
• Low
   
Market by, End User:
• Consumer Electronics
• Industrial
• Aerospace & Defense
• Healthcare
• Automotive
• Other End Users

Market by, Geography:
• North America
• Europe
• Asia Pacific
• South America
• Middle East & Africa

Table Of Content

1 Market Overview           
    1.1 Introduction       
    1.2 Research Objectives      
    1.3 Market Segmentation      
    1.4 Stakeholders       
    1.5 List of Acronyms       
             
2 Executive Summary           
             
3 Research Methodology          
    3.1 Identification of Data      
    3.2 Evaluation of Market Dynamics     
    3.3 Collaboration of Data      
    3.4 Verification and Analysis      
    3.5 Data Sources       
    3.6 Assumptions       
             
4 Market Dynamics            
    4.1 Market Drivers       
            4.1.1 Growing uses of deep learning in big data analytics and rising cloud based technology
            4.1.2 Increasing adoption of deep learning and neural networks
    4.2 Market Restraints       
            4.2.1 Lack of a skilled workforce
    4.3 Impact of COVID-19 on Deep Learning Chipset Market   
             
5 Porter's Five Force Analysis          
    5.1 Bargaining Power of Suppliers      
    5.2 Bargaining Power of Buyers      
    5.3 Threat of New Entrants      
    5.4 Threat of Substitutes      
    5.5 Competitive Rivalry in the Market     
             
6 Global Deep Learning Chipset Market by, Type        
    6.1 Overview       
    6.2 Central Processing Units (CPUs)     
    6.3 Graphics Processing Units (GPUs)     
    6.4 Field Programmable Gate Arrays (FPGAs)     
    6.5 Application-Specific Integrated Circuits (ASICs)    
    6.6 Other Types       
             
7 Global Deep Learning Chipset Market by, Technology        
    7.1 Overview       
    7.2 System-on-chip (SOC)      
    7.3 System-in-package (SIP)      
    7.4 Multi-Chip Module       
    7.5 Other Technologies       
             
8 Global Deep Learning Chipset Market by, Compute Capacity        
    8.1 Overview       
    8.2 High        
    8.3 Low        
             
9 Global Deep Learning Chipset Market by, End User        
    9.1 Overview       
    9.2 Consumer Electronics      
    9.3 Industrial        
    9.4 Aerospace & Defense      
    9.5 Healthcare       
    9.6 Automotive       
    9.7 Other End Users       
             
10 Global Deep Learning Chipset Market by, Geography       
    10.1 Overview       
    10.2 North America       
    10.3 Europe         
    10.4 Asia Pacific       
    10.5 South America       
    10.6 Middle East & Africa      
             
11 Key Developments           
             
12 Company Profiling           
    10.1 Advanced Micro Devices, Inc.      
            10.1.1 Business Overview
            10.1.2 Product/Service Offering
            10.1.3 Financial Overview
            10.1.4 SWOT Analysis
            10.1.5 Key Activities
    10.2 Amazon.Com       
    10.3 Alphabet Inc.       
    10.4 CEVA, Inc.       
    10.5 Graphcore Ltd       
    10.6 IBM Corporation       
    10.7 Intel Corporation       
    10.8 Movidius        
    10.9 NVIDIA Corporation       
    10.10 QUALCOMM Incorporated      
    10.11 TeraDeep Inc.       
    10.12 XILINX INC.        
    10.13 Samsung Electronics Co., Ltd. (Samsung Group)    
    10.14 Baidu, Inc