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| Report Code: A05450 | Aug 2023 | Pages: 350 | ||
| Tables: 136 | Charts: 91 |
| |
Deep learning is a kind of artificial intelligence and machine learning technology that imitates human behavior to generate human brain cells-generated information. The technology is useful in performing classification tasks and recognizing patterns in photos, text, audio, and other data. In addition, it is utilized to automate jobs that ordinarily call for human intellect, such as annotating photographs and transcribing audio files.
The key factors that drive the growth of deep learning market include improving continuing power along with declining hardware cost and increasing adoption of cloud-based technology. Growing organizational demand for processing power and the deployment of Internet of Things (IoT) devices across a variety of industries are driving deep learning market growth. In addition, 2.5 quintillion bytes of new data are generated daily, and that figure is rising. Huge amounts of data generated by numerous industry sectors are creating profitable opportunities for deep learning solutions to give businesses effective, adaptable, and scalable insights. Furthermore, to assist clients, extract the information they require from a large dataset, cloud analytics combines technological, infrastructural, and analytical tools and methodologies. In addition, cloud-based deep learning analytics aid organizations in lowering their infrastructure and storage costs as well as operational expenditures.
The report focuses on growth prospects, restraints, and trends of the deep learning market analysis. The study provides Porter’s five forces analysis to understand the impact of various factors, such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers, on the deep learning market.
COVID-19 had a major impact on the technological sector in a positive manner. Deep learning algorithms were used to assist in diagnosing and detecting COVID-19 cases from medical images, such as chest X-rays and CT scans. This increased demand for medical imaging analysis tools contributed to the growth of the deep learning market within the healthcare sector. Furthermore, deep learning models were employed in drug discovery and research efforts to identify potential drug compounds and predict protein structures.
The deep learning market is segmented into Component, Application and Industry Vertical.
Segment Review
The deep learning market is segmented on the basis of component, application, industry vertical, technology, and region. In terms of components, the market is bifurcated into hardware, software, and service. By application, the market is divided into image recognition, signal recognition, data mining, and others. Based on industry vertical, it is divided into security, marketing, automotive, retail & e-commerce, healthcare, manufacturing, law, and others. On the basis of region, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
On the basis of application, data mining segment is expected to exhibit fastest CAGR during the deep learning market forecast. This is attributed to the fact that deep learning models can automatically recognize complex patterns, relationships, and correlations in data. This is particularly beneficial for data mining tasks like fraud detection, image recognition, and natural language processing.
On the basis of region, North America dominated the deep learning market size in the year 2022. This is because of high investments and the availability of settled IT infrastructure in the region.
The report analyzes the profiles of key players operating in the deep learning market such as Advanced Micro Devices Inc., Amazon Web Services Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung, and Xilinx. These players have adopted various strategies to increase their market penetration and strengthen their position in the deep learning industry.
Market Landscape and Trends
The expansion of deep learning market is driven by various trends such as continued advances in model architectures, pre-trained models with transfer learning, and explainable artificial intelligence (XAI). Researchers are continuously developing and refining deep neural network architectures to improve performance and efficiency. This includes innovations in convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and more. Furthermore, the use of pre-trained models for transfer learning is becoming increasingly popular. These models, trained on massive datasets, are fine-tuned for specific tasks, reducing the need for large amounts of labeled data. Moreover, there is a growing emphasis on making deep learning models more interpretable and explainable, as AI systems are applied to critical domains, to understand the reasoning behind model decisions.
Top Impacting Factors
Improving computing power and declining hardware cost
Growing organizational demand for processing power and the deployment of IoT devices across a variety of industries are driving market expansion. In addition, 2.5 quintillion bytes of new data are generated daily, and that figure is rising. Huge amounts of data generated by numerous industry sectors are creating profitable opportunities for deep learning solutions to give businesses effective, adaptable, and scalable insights. Furthermore, the banking, financial services, and insurance (BFSI) industry held the largest deep learning market share in 2020 due to the industry high production of sensitive data, rising cyberattack rate, and emphasis on customer data security and legal compliance, all of which contribute to the growth of deep learning industry.
Increasing adoption of cloud-based technology
Cloud-analytics is the amalgamation of technological, infrastructural, and analytical tools and techniques to help clients drive necessary information from a massive dataset. In addition, cloud-based deep learning analytics helps institutes to reduce their operational costs as well as to reduce infrastructure and storage costs of the organization. Furthermore, cloud-based deep learning analytics offers institutes superior security and provides enhanced safety to critical data of an organization, which provides lucrative opportunities for the market. In addition, cloud computing also helps institutes in analyzing large quantities of data sets and enhance their analytics skill, which propels the demand for deep learning in the future. Furthermore, the rapid adoption of connected devices across various education institutes and government initiatives to increase digitization across the industry vertically propels the growth of the market. For instance, in July 2020, the Australian Catholic University (ACU) turned its newly united data environment into a data lake to provide a single view of student development. It uses Microsoft’s Power BI and Azure data platform to support students who may need extra help or who are at risk of dropping out of the university entirely. Thus, this is considered as an important factor driving the growth of the market.
Key benefits for stakeholders
Deep Learning Market Report Highlights
| Aspects | Details |
|---|---|
| Market Size By 2032 | USD 406 billion |
| Growth Rate | CAGR of 37.8% |
| Forecast period | 2022 - 2032 |
| Report Pages | 350 |
| By Component |
|
| By Application |
|
| By Industry Vertical |
|
| By Region |
|
| Key Market Players | Google LLC, Advanced Micro Devices Inc.(Xilinx Inc.), Qualcomm Technologies, Inc. , Amazon Web Services, Inc., IBM Corporation, NVIDIA Corporation, Intel Corporation, Xilinx, Microsoft Corporation, Samsung |
Analyst Review
The adoption of deep learning has a profound impact on the ICT sector revolutionizing various aspects of the industry. The technology accounts for numerous uses in the ICT industry such as image and video analysis, natural language processing (NLP), speech recognition, recommendation systems, healthcare, finance, autonomous systems, manufacturing and industry, energy management, cybersecurity, supply chain management and virtual reality (VR)/augmented reality (AR). The technology helps in object detection, image classification, facial recognition, and video content understanding. This is particularly useful in areas like surveillance, autonomous vehicles, medical imaging, and entertainment. In addition, the technology enables better language understanding, sentiment analysis, language translation, text generation, chatbots, and others. These advancements have transformed customer support, content generation, and language-related services. Furthermore, deep learning is at the core of many state-of-the-art speech recognition systems, making voice interfaces more accurate and versatile. This technology is crucial for virtual assistants, voice commands, transcription services, and others.
The CXOs further added that market players are adopting strategies like partnership for enhancing their services in the market and improving customer satisfaction. For instance, in June 2023, Microsoft Corporation collaborated with HCL Technologies Inc. to expand their strategic partnership to assist enterprises leverage generative artificial intelligence (AI) and develop joint solutions to enable businesses to achieve and enhance business transformation. In addition, in March 2023, Qualcomm Technologies Inc. collaborated with Ying Wu College of Computing to produce a federated learning system and zone federated learning the first end-to-end, mobile cloud federated learning systems that function on smartphones. Therefore, such strategies are expected to boost the growth of the deep learning market in the upcoming years.
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A. The deep learning market is estimated to grow at a CAGR of 37.8% from 2023 to 2032.
A. The deep learning market is projected to reach $406.01 billion by 2032.
A. Decline in hardware cost, increase in data availability and advancements in the hardware and increasing investment in research and development to support deep learning majorly contribute toward the growth of the market.
A. The key players profiled in the report include deep learning market analysis includes top companies operating in the market such as Advanced Micro Devices Inc., Amazon Web Services, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung and Xilinx.
A. The key growth strategies of deep learning players include product portfolio expansion, mergers & acquisitions, agreements, geographical expansion, and collaborations.
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