| A05450 | Pages: 286 | Dec 2021 | 5208 Views | ||
| Author(s) : Pramod Borasi, Shadaab Khan, Beesetty Yogendra , Vineet Kumar | Tables: 127 | Charts: 89 |
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Pandemic disrupted the entire world and affected many industries.
Get detailed COVID-19 impact analysis on the Deep Learning Market
Request Now !The global deep learning market size was valued at $6.85 billion in 2020, and is projected to reach $179.96 billion by 2030, registering a CAGR of 39.2% from 2021 to 2030. Deep learning is a category of machine learning that deals with training computer about basic instincts of human beings. In addition, with the help of deep learning, computer algorithm learns to perform classification tasks by analyzing complex data directly, which is available in the form of images, text, or sound. Furthermore, deep learning helps end users to build algorithms to accomplish state-of-the-art (SOTA) accuracy, which are even more than human-level performance.
With an unprecedented COVID-19 pandemic, demand for deep learning has witnessed a rise, owing to growing craze of digital voice assistance among the younger generation of developing nation and increasing focus on virtual reality and augmented technologies by various key vendors of different countries have boosted the demand for deep learning solutions in the pandemic situation.
Improving computing power, declining hardware cost, and increasing adoption of cloud-based technology propel growth of the global deep learning market. In addition, deep learning usage in big data analytics positively impacts growth of the market. However, increasing complexity in hardware due to complex algorithm used in technology and lack of technical expertise & absence of standards and protocols hampers the market growth. On the contrary, cumulative spending in healthcare, travel, tourism, and hospitality industries is expected to offer remunerative opportunities for expansion of the market during the forecast period.
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In terms of applications, image recognition holds largest share of the deep learning market. This is attributed to growing demand for pattern recognition, optical character recognition, code recognition, facial recognition, object recognition, and digital image processing. However, the data mining segment is expected to grow at the highest rate during the forecast period, owing to growth in demand for advanced technologies, natural language processing, and visual data mining, which is developed using deep learning techniques.
Region wise, the deep learning market was dominated by North America in 2020, and is expected to retain its position during the forecast period, owing to high investments and availability of settled IT infrastructure. However, Europe is expected to witness significant growth during the forecast period, owing to availability of large population of skilled workers in developing nations of the UK and Germany is expected to drive the deep learning market in Asia-Pacific.
The report focuses on growth prospects, restraints, and trends of the global deep learning market analysis. The study provides Porter’s five forces analysis to understand 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 global deep learning market share.
The global deep learning market is segmented on the basis of component, application, industry vertical and region. By component, the market is divided into hardware, software, and service. By application, the market is segmented into image recognition, signal recognition, data mining, and others. By industry vertical, it is categorized into security, marketing, automotive, retail & e-commerce, healthcare, manufacturing, law, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The key players profiled in the deep learning market analysis are 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.
The COVID-19 pandemic has led to a significant increase in the revenue of deep learning market owing to rise in demand for anti-money laundering (AML), fraud detection solutions and various others solutions during the pandemic situation.
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In addition, the COVID-19 pandemic has resulted in changes in model performance, as more continuous monitoring and validation is required to mitigate various types of risk, compared to static validation and testing methods, which in turn drive the development of deep learning models. Furthermore, with rising digital transformation various governments have introduced stringent regulations to protect end users data such as General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) which is driving the growth of the market.
Surge in need for computing power among enterprises and growing adoption of IoT devices across various industries propels growth of the market. Moreover, there are 2.5 quintillion bytes of data created each day and that number is increasing each day. Vast volumes of data produced by various business verticals are providing lucrative opportunities for deep learning solutions for providing companies with efficient, flexible, and scalable insights. Furthermore, the banking, financial services, and insurance (BFSI) sector held the largest deep learning market share in 2020, as this sector is generating high amounts of confidential data, increasing number of cyber-attacks, and focusing on customer data security, and regulatory compliance, which drives the market growth. Furthermore, it is becoming cheaper and easier than ever to instrument everything and send that data in real-time through a messaging system allowing organizations to make informed decisions at a faster rate that positively impacting growth of the market.
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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 help institutes to reduce their operational costs as well as to reduce infrastructure & storage cost of the organization. Furthermore, cloud-based deep learning analytics offers institutes with 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 quantity of data set and to enhance their analytics skill, which propels demand for deep learning in the future.
Furthermore, rapid adoption of connected devices across various education institutes and government initiatives to increase digitization across the industry vertical propels growth of the market. For instance, in July 2020, the Australian Catholic University (ACU) has 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 from the university entirely. Thus, this is considered as an important factor driving growth of the market.
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Key Market Segments
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Adoption of deep learning has increased, owing to industries realizing the potential of deep learning and are incorporating it as a core technology for simplifying complex decision making. In addition, constant evolution of deep learning has made it the go-to technology for many sectors. Right from robotic process automation to technical expertise, deep learning technology is extensively used to make predictions and get valuable insight into business operations. Moreover, emergence of various technologies and rapid adoption of digitalization by small and medium enterprises has led to growth of the market.
Key providers of deep learning market such as Google IBM and Microsoft Corporation account for a significant share in the market. Increase in adoption of deep learning in the North America, owing to increase in adoption of technologically advanced products, which leads to increase in merger, partnership, collaboration, and business expansion. For instance, August 2021, Samsung collaborated with Google and NIVDIA and other tech companies are using AI to design its upcoming processors. Samsung uses this AI-assisted chip design in its smartphones, tablets, smartwatches, Chromebooks, and cameras. Thus, growing number of such developments across the globe drives growth of the market.
In addition, various educational institutes are involved in strategic partnership to increase capabilities of research and development by adoption of deep learning platform. For instance, in January 2021, Microsoft Corporation partnered with Broad Institute of MIT and Harvard, Verily, and an Alphabet company to accelerate new innovations in biomedicine through its Terra platform. This AI driven deep learning platform brings together Microsoft’s cloud, data and AI technologies, and global network of more than 168,000 health and life sciences partners to accelerate development of global biomedical research through the Terra platform provides greater access and empower the open-source community.
Moreover, market players are expanding their partnership term looking at the future growth and opportunity. For instance, in December 2021, Amazon Web Services, Inc. and Meta expanded its partnership as a strategic cloud provider. Meta is using AWS services and global infrastructure to innovate faster, scale research & development, facilitate third party collaborations, and drive operational efficiency. In addition, companies working together to improve performance for customers running PyTorch on AWS, bringing deep learning models from research into production faster and easier.
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