The Global Deep Learning Market size is expected to reach $715.2 billion by 2031, rising at a market growth of 34.3% CAGR during the forecast period.
A skilled workforce and favourable government initiatives supporting AI and machine learning advancements have also contributed to North America's dominance in the deep learning market. The Mexican retail sector expands, the demand for innovative solutions powered by deep learning will likely increase, fostering a symbiotic relationship between the two industries. Overall, the strength of the Mexican retail sector is a significant catalyst for developing and adopting deep learning technologies, positioning the country as a burgeoning hub for advanced analytics in the retail space. In conclusion, the Canadian government's significant investment in the aerospace sector and Mexico's strong retail industry are poised to drive growth in the deep learning market. Thus, the North America region witnessed 36% revenue share in the deep learning market in 2023.
The major strategies followed by the market participants are Partnership as the key developmental strategy to keep pace with the changing demands of end users. For instance, In September, 2024, Arm Limited came into partnership with PyTorch and ExecuTorch with the aim of enhancing AI performance on Arm-based hardware, enabling efficient deep learning workloads from edge to cloud. The integration of Kleidi technology supports developers with resources and optimizations, driving advancements in the deep learning market. Additionally, In September, 2024, NVIDIA Corporation has partnered with the U.S. government to launch the Partnership for Global Inclusivity on AI, offering Deep Learning Institute training, GPU credits, and grants to support AI development in emerging economies, promoting sustainable development and equitable access to AI tools.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC. are the forerunners in the Deep Learning Market. In June, 2023, Microsoft Corporation is collaborating with Moody's to enhance risk, data, and analytics solutions through generative AI and Microsoft Azure OpenAI Service. This partnership aims to improve financial services and risk assessment by leveraging advanced data analytics and large language models. Companies such as NVIDIA Corporation, Amazon Web Services, Inc. and Advanced Micro Devices, Inc. are some of the key innovators in Deep Learning Market.
Market Growth Factors
Organizations seeking to optimize their operations may invest in deep learning technologies to develop and enhance these assistants. Intelligent virtual assistants can streamline various business processes, such as appointment scheduling, order processing, and customer inquiries. The efficiency gained from automation drives demand for deep learning solutions that can support these functionalities.
Additionally, Deep learning can be utilized to develop advanced security solutions for IoT devices. For instance, anomaly detection algorithms can identify unusual patterns of behaviour in device usage, helping to prevent cyberattacks or unauthorized access. Therefore, expansion of smart devices and IoT is driving the growth of the market.
Market Restraining Factors
Limited interpretability makes it difficult to identify errors or biases within models. Organizations may struggle to improve model performance or correct issues without understanding how a model reaches its conclusions. The inability to interpret model behaviour can hinder iterative development processes, where insights from previous model runs are crucial for refining and optimizing algorithms. Therefore, the limited interpretability and transparency of deep learning models impede the market's growth.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies to cater to demand coming from the different industries. The key developmental strategies in the market are Partnerships, Collaborations & Agreements.
Solution Outlook
Based on solution, the market is divided into hardware, software, and services. In 2023, the hardware segment garnered 28% revenue share in the market. The demand for specialized hardware like TPUs (Tensor Processing Units) surged as healthcare, automotive, and finance industries adopted deep learning applications, necessitating efficient processing for complex neural networks.
Hardware Outlook
The hardware segment is further subdivided into central processing unit (CPU), graphics processing unit (GPU), field programmable gate array (FPGA), and application-specific integration circuit (ASIC). In 2023, the graphics processing unit (GPU) segment procured 44% revenue share in the learning market. The effectiveness of GPUs in deep learning is primarily due to their ability to perform parallel processing, which enables them to handle multiple computations simultaneously.
Services Outlook
The services segment is further subdivided into installation services, integration services, and maintenance & support services. In 2023, the integration services segment attained 38% revenue share in the market. The increasing complexity of deep learning applications necessitates specialized integration services to ensure that these technologies function seamlessly within existing IT infrastructures.
Application Outlook
On the basis of application, the market is segmented into voice recognition, image recognition, video surveillance & diagnostics, and data mining. In 2023, the video surveillance & diagnostics segment attained 20% revenue share in the market. The increasing emphasis on security and safety has led to the integration of deep learning technologies in video surveillance systems, enabling advanced capabilities such as real-time threat detection and behavioural analysis.
End Use Outlook
By end-use, the market is divided into automotive, aerospace & defense, healthcare, retail, and others. In 2023, the aerospace & defense witnessed 25% revenue share in the market. This expansion is due to the growing dependence on AI-driven applications for predictive maintenance, threat detection, and data analysis to support decision-making.
Regional Outlook
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. In 2023, the Asia Pacific region generated 28% revenue share in the market. The region increasingly focuses on AI initiatives, with countries like China, Japan, and India investing heavily in deep learning research and applications.
Market Competition and Attributes
The market is fiercely competitive, characterized by rapid technological advancements and heavy investment in research and development. Key attributes include sophisticated algorithms for pattern recognition, neural network architectures, and applications across various sectors like healthcare, automotive, and finance. Companies vie for dominance through innovations in computational power, data efficiency, and algorithm complexity. Market leaders focus on scalability, interpretability, and integration capabilities to meet diverse industry demands and drive market expansion.
Recent Strategies Deployed in the Market
- Sep-2024: Samsung launched its 'AI for All' vision, showcasing AI-driven visual displays and smart appliances designed to enhance connected device experiences. These innovations focus on usability, accessibility, and energy efficiency, while also promoting seamless integration with Microsoft for improved PC functionality.
- Sep-2024: NVIDIA's Deep Learning Institute has launched a Generative AI Teaching Kit in collaboration with Dartmouth College. This resource equips educators to teach students essential skills in generative AI, preparing them for careers in industries like healthcare, finance, and entertainment.
- Sep-2024: Arm Limited came into partnership with PyTorch and ExecuTorch with the aim of enhancing AI performance on Arm-based hardware, enabling efficient deep learning workloads from edge to cloud. The integration of Kleidi technology supports developers with resources and optimizations, driving advancements in the deep learning market.
- Sep-2024: NVIDIA Corporation has partnered with the U.S. government to launch the Partnership for Global Inclusivity on AI, offering Deep Learning Institute training, GPU credits, and grants to support AI development in emerging economies, promoting sustainable development and equitable access to AI tools.
- Jul-2024: Advanced Micro Devices, Inc. acquired Silo AI to enhance its AI capabilities and accelerate the development of tailored AI solutions for global enterprises, focusing on open standards and advanced technologies.
List of Key Companies Profiled
- Advanced Micro Devices, Inc.
- Arm Limited (SoftBank Group Corp.)
- NVIDIA Corporation
- Clarifai, Inc.
- Google LLC
- IBM Corporation
- Intel Corporation
- Microsoft Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Samsung Electronics Co., Ltd. (Samsung Group)
Global Deep Learning Market Report Segmentation
By Solution
- Software
- Hardware
- Graphics Processing Unit (GPU)
- Central Processing Unit (CPU)
- Field Programmable Gate Array (FPGA)
- Application-Specific Integration Circuit (ASIC)
- Services
- Integration Services
- Installation Services
- Maintenance & Support Services
By Application
- Image recognition
- Voice Recognition
- Video Surveillance & Diagnostics
- Data Mining
By End-use
- Aerospace & Defense
- Healthcare
- Automotive
- Retail
- Other End-use
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
- 1.1 Market Definition
- 1.2 Objectives
- 1.3 Market Scope
- 1.4 Segmentation
- 1.4.1 Global Deep Learning Market, by Solution
- 1.4.2 Global Deep Learning Market, by Application
- 1.4.3 Global Deep Learning Market, by End-use
- 1.4.4 Global Deep Learning Market, by Geography
- 1.5 Methodology for the research
Chapter 2. Market at a Glance
Chapter 3. Market Overview
- 3.1 Introduction
- 3.1.1 Overview
- 3.1.1.1 Market Composition and Scenario
- 3.2 Key Factors Impacting the Market
- 3.2.1 Market Drivers
- 3.2.2 Market Restraints
- 3.2.3 Market Opportunities
- 3.2.4 Market Challenges
Chapter 4. Competition Analysis - Global
- 4.1 KBV Cardinal Matrix
- 4.2 Recent Industry Wide Strategic Developments
- 4.2.1 Partnerships, Collaborations and Agreements
- 4.2.2 Product Launches and Product Expansions
- 4.2.3 Acquisition and Mergers
- 4.3 Market Share Analysis, 2023
- 4.4 Top Winning Strategies
- 4.4.1 Key Leading Strategies: Percentage Distribution (2020-2024)
- 4.4.2 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2021, Apr - 2024, Sep) Leading Players
- 4.5 Porter Five Forces Analysis
Chapter 5. Global Deep Learning Market by Solution
- 5.1 Global Software Market by Region
- 5.2 Global Hardware Market by Region
- 5.3 Global Deep Learning Market by Hardware Type
- 5.3.1 Global Graphics Processing Unit (GPU) Market by Region
- 5.3.2 Global Central Processing Unit (CPU) Market by Region
- 5.3.3 Global Field Programmable Gate Array (FPGA) Market by Region
- 5.3.4 Global Application-Specific Integration Circuit (ASIC) Market by Region
- 5.4 Global Services Market by Region
- 5.5 Global Deep Learning Market by Services Type
- 5.5.1 Global Integration Services Market by Region
- 5.5.2 Global Installation Services Market by Region
- 5.5.3 Global Maintenance & Support Services Market by Region
Chapter 6. Global Deep Learning Market by Application
- 6.1 Global Image recognition Market by Region
- 6.2 Global Voice Recognition Market by Region
- 6.3 Global Video Surveillance & Diagnostics Market by Region
- 6.4 Global Data Mining Market by Region
Chapter 7. Global Deep Learning Market by End-use
- 7.1 Global Aerospace & Defense Market by Region
- 7.2 Global Healthcare Market by Region
- 7.3 Global Automotive Market by Region
- 7.4 Global Retail Market by Region
- 7.5 Global Other End-use Market by Region
Chapter 8. Global Deep Learning Market by Region
- 8.1 North America Deep Learning Market
- 8.1.1 North America Deep Learning Market by Solution
- 8.1.1.1 North America Software Market by Country
- 8.1.1.2 North America Hardware Market by Country
- 8.1.1.3 North America Deep Learning Market by Hardware Type
- 8.1.1.3.1 North America Graphics Processing Unit (GPU) Market by Country
- 8.1.1.3.2 North America Central Processing Unit (CPU) Market by Country
- 8.1.1.3.3 North America Field Programmable Gate Array (FPGA) Market by Country
- 8.1.1.3.4 North America Application-Specific Integration Circuit (ASIC) Market by Country
- 8.1.1.4 North America Services Market by Country
- 8.1.1.5 North America Deep Learning Market by Services Type
- 8.1.1.5.1 North America Integration Services Market by Country
- 8.1.1.5.2 North America Installation Services Market by Country
- 8.1.1.5.3 North America Maintenance & Support Services Market by Country
- 8.1.2 North America Deep Learning Market by Application
- 8.1.2.1 North America Image recognition Market by Country
- 8.1.2.2 North America Voice Recognition Market by Country
- 8.1.2.3 North America Video Surveillance & Diagnostics Market by Country
- 8.1.2.4 North America Data Mining Market by Country
- 8.1.3 North America Deep Learning Market by End-use
- 8.1.3.1 North America Aerospace & Defense Market by Country
- 8.1.3.2 North America Healthcare Market by Country
- 8.1.3.3 North America Automotive Market by Country
- 8.1.3.4 North America Retail Market by Country
- 8.1.3.5 North America Other End-use Market by Country
- 8.1.4 North America Deep Learning Market by Country
- 8.1.4.1 US Deep Learning Market
- 8.1.4.1.1 US Deep Learning Market by Solution
- 8.1.4.1.1.1 US Deep Learning Market by Hardware Type
- 8.1.4.1.1.2 US Deep Learning Market by Services Type
- 8.1.4.1.2 US Deep Learning Market by Application
- 8.1.4.1.3 US Deep Learning Market by End-use
- 8.1.4.2 Canada Deep Learning Market
- 8.1.4.2.1 Canada Deep Learning Market by Solution
- 8.1.4.2.1.1 Canada Deep Learning Market by Hardware Type
- 8.1.4.2.1.2 Canada Deep Learning Market by Services Type
- 8.1.4.2.2 Canada Deep Learning Market by Application
- 8.1.4.2.3 Canada Deep Learning Market by End-use
- 8.1.4.3 Mexico Deep Learning Market
- 8.1.4.3.1 Mexico Deep Learning Market by Solution
- 8.1.4.3.1.1 Mexico Deep Learning Market by Hardware Type
- 8.1.4.3.1.2 Mexico Deep Learning Market by Services Type
- 8.1.4.3.2 Mexico Deep Learning Market by Application
- 8.1.4.3.3 Mexico Deep Learning Market by End-use
- 8.1.4.4 Rest of North America Deep Learning Market
- 8.1.4.4.1 Rest of North America Deep Learning Market by Solution
- 8.1.4.4.1.1 Rest of North America Deep Learning Market by Hardware Type
- 8.1.4.4.1.2 Rest of North America Deep Learning Market by Services Type
- 8.1.4.4.2 Rest of North America Deep Learning Market by Application
- 8.1.4.4.3 Rest of North America Deep Learning Market by End-use
- 8.2 Europe Deep Learning Market
- 8.2.1 Europe Deep Learning Market by Solution
- 8.2.1.1 Europe Software Market by Country
- 8.2.1.2 Europe Hardware Market by Country
- 8.2.1.3 Europe Deep Learning Market by Hardware Type
- 8.2.1.3.1 Europe Graphics Processing Unit (GPU) Market by Country
- 8.2.1.3.2 Europe Central Processing Unit (CPU) Market by Country
- 8.2.1.3.3 Europe Field Programmable Gate Array (FPGA) Market by Country
- 8.2.1.3.4 Europe Application-Specific Integration Circuit (ASIC) Market by Country
- 8.2.1.4 Europe Services Market by Country
- 8.2.1.5 Europe Deep Learning Market by Services Type
- 8.2.1.5.1 Europe Integration Services Market by Country
- 8.2.1.5.2 Europe Installation Services Market by Country
- 8.2.1.5.3 Europe Maintenance & Support Services Market by Country
- 8.2.2 Europe Deep Learning Market by Application
- 8.2.2.1 Europe Image recognition Market by Country
- 8.2.2.2 Europe Voice Recognition Market by Country
- 8.2.2.3 Europe Video Surveillance & Diagnostics Market by Country
- 8.2.2.4 Europe Data Mining Market by Country
- 8.2.3 Europe Deep Learning Market by End-use
- 8.2.3.1 Europe Aerospace & Defense Market by Country
- 8.2.3.2 Europe Healthcare Market by Country
- 8.2.3.3 Europe Automotive Market by Country
- 8.2.3.4 Europe Retail Market by Country
- 8.2.3.5 Europe Other End-use Market by Country
- 8.2.4 Europe Deep Learning Market by Country
- 8.2.4.1 Germany Deep Learning Market
- 8.2.4.1.1 Germany Deep Learning Market by Solution
- 8.2.4.1.1.1 Germany Deep Learning Market by Hardware Type
- 8.2.4.1.1.2 Germany Deep Learning Market by Services Type
- 8.2.4.1.2 Germany Deep Learning Market by Application
- 8.2.4.1.3 Germany Deep Learning Market by End-use
- 8.2.4.2 UK Deep Learning Market
- 8.2.4.2.1 UK Deep Learning Market by Solution
- 8.2.4.2.1.1 UK Deep Learning Market by Hardware Type
- 8.2.4.2.1.2 UK Deep Learning Market by Services Type
- 8.2.4.2.2 UK Deep Learning Market by Application
- 8.2.4.2.3 UK Deep Learning Market by End-use
- 8.2.4.3 France Deep Learning Market
- 8.2.4.3.1 France Deep Learning Market by Solution
- 8.2.4.3.1.1 France Deep Learning Market by Hardware Type
- 8.2.4.3.1.2 France Deep Learning Market by Services Type
- 8.2.4.3.2 France Deep Learning Market by Application
- 8.2.4.3.3 France Deep Learning Market by End-use
- 8.2.4.4 Russia Deep Learning Market
- 8.2.4.4.1 Russia Deep Learning Market by Solution
- 8.2.4.4.1.1 Russia Deep Learning Market by Hardware Type
- 8.2.4.4.1.2 Russia Deep Learning Market by Services Type
- 8.2.4.4.2 Russia Deep Learning Market by Application
- 8.2.4.4.3 Russia Deep Learning Market by End-use
- 8.2.4.5 Spain Deep Learning Market
- 8.2.4.5.1 Spain Deep Learning Market by Solution
- 8.2.4.5.1.1 Spain Deep Learning Market by Hardware Type
- 8.2.4.5.1.2 Spain Deep Learning Market by Services Type
- 8.2.4.5.2 Spain Deep Learning Market by Application
- 8.2.4.5.3 Spain Deep Learning Market by End-use
- 8.2.4.6 Italy Deep Learning Market
- 8.2.4.6.1 Italy Deep Learning Market by Solution
- 8.2.4.6.1.1 Italy Deep Learning Market by Hardware Type
- 8.2.4.6.1.2 Italy Deep Learning Market by Services Type
- 8.2.4.6.2 Italy Deep Learning Market by Application
- 8.2.4.6.3 Italy Deep Learning Market by End-use
- 8.2.4.7 Rest of Europe Deep Learning Market
- 8.2.4.7.1 Rest of Europe Deep Learning Market by Solution
- 8.2.4.7.1.1 Rest of Europe Deep Learning Market by Hardware Type
- 8.2.4.7.1.2 Rest of Europe Deep Learning Market by Services Type
- 8.2.4.7.2 Rest of Europe Deep Learning Market by Application
- 8.2.4.7.3 Rest of Europe Deep Learning Market by End-use
- 8.3 Asia Pacific Deep Learning Market
- 8.3.1 Asia Pacific Deep Learning Market by Solution
- 8.3.1.1 Asia Pacific Software Market by Country
- 8.3.1.2 Asia Pacific Hardware Market by Country
- 8.3.1.3 Asia Pacific Deep Learning Market by Hardware Type
- 8.3.1.3.1 Asia Pacific Graphics Processing Unit (GPU) Market by Country
- 8.3.1.3.2 Asia Pacific Central Processing Unit (CPU) Market by Country
- 8.3.1.3.3 Asia Pacific Field Programmable Gate Array (FPGA) Market by Country
- 8.3.1.3.4 Asia Pacific Application-Specific Integration Circuit (ASIC) Market by Country
- 8.3.1.4 Asia Pacific Services Market by Country
- 8.3.1.5 Asia Pacific Deep Learning Market by Services Type
- 8.3.1.5.1 Asia Pacific Integration Services Market by Country
- 8.3.1.5.2 Asia Pacific Installation Services Market by Country
- 8.3.1.5.3 Asia Pacific Maintenance & Support Services Market by Country
- 8.3.2 Asia Pacific Deep Learning Market by Application
- 8.3.2.1 Asia Pacific Image recognition Market by Country
- 8.3.2.2 Asia Pacific Voice Recognition Market by Country
- 8.3.2.3 Asia Pacific Video Surveillance & Diagnostics Market by Country
- 8.3.2.4 Asia Pacific Data Mining Market by Country
- 8.3.3 Asia Pacific Deep Learning Market by End-use
- 8.3.3.1 Asia Pacific Aerospace & Defense Market by Country
- 8.3.3.2 Asia Pacific Healthcare Market by Country
- 8.3.3.3 Asia Pacific Automotive Market by Country
- 8.3.3.4 Asia Pacific Retail Market by Country
- 8.3.3.5 Asia Pacific Other End-use Market by Country
- 8.3.4 Asia Pacific Deep Learning Market by Country
- 8.3.4.1 China Deep Learning Market
- 8.3.4.1.1 China Deep Learning Market by Solution
- 8.3.4.1.1.1 China Deep Learning Market by Hardware Type
- 8.3.4.1.1.2 China Deep Learning Market by Services Type
- 8.3.4.1.2 China Deep Learning Market by Application
- 8.3.4.1.3 China Deep Learning Market by End-use
- 8.3.4.2 Japan Deep Learning Market
- 8.3.4.2.1 Japan Deep Learning Market by Solution
- 8.3.4.2.1.1 Japan Deep Learning Market by Hardware Type
- 8.3.4.2.1.2 Japan Deep Learning Market by Services Type
- 8.3.4.2.2 Japan Deep Learning Market by Application
- 8.3.4.2.3 Japan Deep Learning Market by End-use
- 8.3.4.3 India Deep Learning Market
- 8.3.4.3.1 India Deep Learning Market by Solution
- 8.3.4.3.1.1 India Deep Learning Market by Hardware Type
- 8.3.4.3.1.2 India Deep Learning Market by Services Type
- 8.3.4.3.2 India Deep Learning Market by Application
- 8.3.4.3.3 India Deep Learning Market by End-use
- 8.3.4.4 South Korea Deep Learning Market
- 8.3.4.4.1 South Korea Deep Learning Market by Solution
- 8.3.4.4.1.1 South Korea Deep Learning Market by Hardware Type
- 8.3.4.4.1.2 South Korea Deep Learning Market by Services Type
- 8.3.4.4.2 South Korea Deep Learning Market by Application
- 8.3.4.4.3 South Korea Deep Learning Market by End-use
- 8.3.4.5 Singapore Deep Learning Market
- 8.3.4.5.1 Singapore Deep Learning Market by Solution
- 8.3.4.5.1.1 Singapore Deep Learning Market by Hardware Type
- 8.3.4.5.1.2 Singapore Deep Learning Market by Services Type
- 8.3.4.5.2 Singapore Deep Learning Market by Application
- 8.3.4.5.3 Singapore Deep Learning Market by End-use
- 8.3.4.6 Malaysia Deep Learning Market
- 8.3.4.6.1 Malaysia Deep Learning Market by Solution
- 8.3.4.6.1.1 Malaysia Deep Learning Market by Hardware Type
- 8.3.4.6.1.2 Malaysia Deep Learning Market by Services Type
- 8.3.4.6.2 Malaysia Deep Learning Market by Application
- 8.3.4.6.3 Malaysia Deep Learning Market by End-use
- 8.3.4.7 Rest of Asia Pacific Deep Learning Market
- 8.3.4.7.1 Rest of Asia Pacific Deep Learning Market by Solution
- 8.3.4.7.1.1 Rest of Asia Pacific Deep Learning Market by Hardware Type
- 8.3.4.7.1.2 Rest of Asia Pacific Deep Learning Market by Services Type
- 8.3.4.7.2 Rest of Asia Pacific Deep Learning Market by Application
- 8.3.4.7.3 Rest of Asia Pacific Deep Learning Market by End-use
- 8.4 LAMEA Deep Learning Market
- 8.4.1 LAMEA Deep Learning Market by Solution
- 8.4.1.1 LAMEA Software Market by Country
- 8.4.1.2 LAMEA Hardware Market by Country
- 8.4.1.3 LAMEA Deep Learning Market by Hardware Type
- 8.4.1.3.1 LAMEA Graphics Processing Unit (GPU) Market by Country
- 8.4.1.3.2 LAMEA Central Processing Unit (CPU) Market by Country
- 8.4.1.3.3 LAMEA Field Programmable Gate Array (FPGA) Market by Country
- 8.4.1.3.4 LAMEA Application-Specific Integration Circuit (ASIC) Market by Country
- 8.4.1.4 LAMEA Services Market by Country
- 8.4.1.5 LAMEA Deep Learning Market by Services Type
- 8.4.1.5.1 LAMEA Integration Services Market by Country
- 8.4.1.5.2 LAMEA Installation Services Market by Country
- 8.4.1.5.3 LAMEA Maintenance & Support Services Market by Country
- 8.4.2 LAMEA Deep Learning Market by Application
- 8.4.2.1 LAMEA Image recognition Market by Country
- 8.4.2.2 LAMEA Voice Recognition Market by Country
- 8.4.2.3 LAMEA Video Surveillance & Diagnostics Market by Country
- 8.4.2.4 LAMEA Data Mining Market by Country
- 8.4.3 LAMEA Deep Learning Market by End-use
- 8.4.3.1 LAMEA Aerospace & Defense Market by Country
- 8.4.3.2 LAMEA Healthcare Market by Country
- 8.4.3.3 LAMEA Automotive Market by Country
- 8.4.3.4 LAMEA Retail Market by Country
- 8.4.3.5 LAMEA Other End-use Market by Country
- 8.4.4 LAMEA Deep Learning Market by Country
- 8.4.4.1 Brazil Deep Learning Market
- 8.4.4.1.1 Brazil Deep Learning Market by Solution
- 8.4.4.1.1.1 Brazil Deep Learning Market by Hardware Type
- 8.4.4.1.1.2 Brazil Deep Learning Market by Services Type
- 8.4.4.1.2 Brazil Deep Learning Market by Application
- 8.4.4.1.3 Brazil Deep Learning Market by End-use
- 8.4.4.2 Argentina Deep Learning Market
- 8.4.4.2.1 Argentina Deep Learning Market by Solution
- 8.4.4.2.1.1 Argentina Deep Learning Market by Hardware Type
- 8.4.4.2.1.2 Argentina Deep Learning Market by Services Type
- 8.4.4.2.2 Argentina Deep Learning Market by Application
- 8.4.4.2.3 Argentina Deep Learning Market by End-use
- 8.4.4.3 UAE Deep Learning Market
- 8.4.4.3.1 UAE Deep Learning Market by Solution
- 8.4.4.3.1.1 UAE Deep Learning Market by Hardware Type
- 8.4.4.3.1.2 UAE Deep Learning Market by Services Type
- 8.4.4.3.2 UAE Deep Learning Market by Application
- 8.4.4.3.3 UAE Deep Learning Market by End-use
- 8.4.4.4 Saudi Arabia Deep Learning Market
- 8.4.4.4.1 Saudi Arabia Deep Learning Market by Solution
- 8.4.4.4.1.1 Saudi Arabia Deep Learning Market by Hardware Type
- 8.4.4.4.1.2 Saudi Arabia Deep Learning Market by Services Type
- 8.4.4.4.2 Saudi Arabia Deep Learning Market by Application
- 8.4.4.4.3 Saudi Arabia Deep Learning Market by End-use
- 8.4.4.5 South Africa Deep Learning Market
- 8.4.4.5.1 South Africa Deep Learning Market by Solution
- 8.4.4.5.1.1 South Africa Deep Learning Market by Hardware Type
- 8.4.4.5.1.2 South Africa Deep Learning Market by Services Type
- 8.4.4.5.2 South Africa Deep Learning Market by Application
- 8.4.4.5.3 South Africa Deep Learning Market by End-use
- 8.4.4.6 Nigeria Deep Learning Market
- 8.4.4.6.1 Nigeria Deep Learning Market by Solution
- 8.4.4.6.1.1 Nigeria Deep Learning Market by Hardware Type
- 8.4.4.6.1.2 Nigeria Deep Learning Market by Services Type
- 8.4.4.6.2 Nigeria Deep Learning Market by Application
- 8.4.4.6.3 Nigeria Deep Learning Market by End-use
- 8.4.4.7 Rest of LAMEA Deep Learning Market
- 8.4.4.7.1 Rest of LAMEA Deep Learning Market by Solution
- 8.4.4.7.1.1 Rest of LAMEA Deep Learning Market by Hardware Type
- 8.4.4.7.1.2 Rest of LAMEA Deep Learning Market by Services Type
- 8.4.4.7.2 Rest of LAMEA Deep Learning Market by Application
- 8.4.4.7.3 Rest of LAMEA Deep Learning Market by End-use
Chapter 9. Company Profiles
- 9.1 Advanced Micro Devices, Inc.
- 9.1.1 Company Overview
- 9.1.2 Financial Analysis
- 9.1.3 Segmental and Regional Analysis
- 9.1.4 Research & Development Expenses
- 9.1.5 Recent strategies and developments:
- 9.1.5.1 Partnerships, Collaborations, and Agreements:
- 9.1.5.2 Product Launches and Product Expansions:
- 9.1.5.3 Acquisition and Mergers:
- 9.1.6 SWOT Analysis
- 9.2 Arm Limited (SoftBank Group Corp.)
- 9.2.1 Company Overview
- 9.2.2 Financial Analysis
- 9.2.3 Recent strategies and developments:
- 9.2.3.1 Partnerships, Collaborations, and Agreements:
- 9.2.3.2 Product Launches and Product Expansions:
- 9.2.4 SWOT Analysis
- 9.3 NVIDIA Corporation
- 9.3.1 Company Overview
- 9.3.2 Financial Analysis
- 9.3.3 Segmental and Regional Analysis
- 9.3.4 Research & Development Expenses
- 9.3.5 Recent strategies and developments:
- 9.3.5.1 Partnerships, Collaborations, and Agreements:
- 9.3.5.2 Product Launches and Product Expansions:
- 9.3.5.3 Acquisition and Mergers:
- 9.3.6 SWOT Analysis
- 9.4 Clarifai, Inc.
- 9.4.1 Company Overview
- 9.4.2 Recent strategies and developments:
- 9.4.2.1 Partnerships, Collaborations, and Agreements:
- 9.4.2.2 Product Launches and Product Expansions:
- 9.4.3 SWOT Analysis
- 9.5 Google LLC
- 9.5.1 Company Overview
- 9.5.2 Financial Analysis
- 9.5.3 Segmental and Regional Analysis
- 9.5.4 Research & Development Expense
- 9.5.5 Recent strategies and developments:
- 9.5.5.1 Partnerships, Collaborations, and Agreements:
- 9.5.6 SWOT Analysis
- 9.6 IBM Corporation
- 9.6.1 Company Overview
- 9.6.2 Financial Analysis
- 9.6.3 Regional & Segmental Analysis
- 9.6.4 Research & Development Expenses
- 9.6.5 Recent strategies and developments:
- 9.6.5.1 Partnerships, Collaborations, and Agreements:
- 9.6.5.2 Acquisition and Mergers:
- 9.6.6 SWOT Analysis
- 9.7 Intel Corporation
- 9.7.1 Company Overview
- 9.7.2 Financial Analysis
- 9.7.3 Segmental and Regional Analysis
- 9.7.4 Research & Development Expenses
- 9.7.5 Recent strategies and developments:
- 9.7.5.1 Product Launches and Product Expansions:
- 9.7.5.2 Acquisition and Mergers:
- 9.7.6 SWOT Analysis
- 9.8 Microsoft Corporation
- 9.8.1 Company Overview
- 9.8.2 Financial Analysis
- 9.8.3 Segmental and Regional Analysis
- 9.8.4 Research & Development Expenses
- 9.8.5 Recent strategies and developments:
- 9.8.5.1 Partnerships, Collaborations, and Agreements:
- 9.8.6 SWOT Analysis
- 9.9 Amazon Web Services, Inc. (Amazon.com, Inc.)
- 9.9.1 Company Overview
- 9.9.2 Financial Analysis
- 9.9.3 Segmental Analysis
- 9.9.4 Recent strategies and developments:
- 9.9.4.1 Partnerships, Collaborations, and Agreements:
- 9.9.4.2 Product Launches and Product Expansions:
- 9.9.5 SWOT Analysis
- 9.10. Samsung Electronics Co., Ltd. (Samsung Group)
- 9.10.1 Company Overview
- 9.10.2 Financial Analysis
- 9.10.3 Segmental and Regional Analysis
- 9.10.4 Research & Development Expenses
- 9.10.5 Recent strategies and developments:
- 9.10.5.1 Product Launches and Product Expansions:
- 9.10.6 SWOT Analysis
Chapter 10. Winning Imperatives of Deep Learning Market