Deep learning or deep neural learning is a family of machine learning based on artificial intelligence (AI) neural network with representation learning. Neuron network is a set of algorithms that help to recognize the relationship between the data through the process that mimics the way the human brain operates. These networks are used to solve many problems such as data validation, sales forecasting, customer research, and risk management. There are different types of learning such as supervised, semi-supervised, and unsupervised. Deep learning is a class or subset of machine learning that uses its algorithms to solve complex data structures. Deep learning applications are used in many industries such as automated driving. Automotive researchers use deep learning algorithms to detect various objects such as traffic signals, stop signs, etc. In addition, deep learning is also used to detect pedestrians that help in reducing number of accidents. There are many features of deep learning such as face recognition, signal diagnosing, weather forecast, google maps, antivirus, and others. These factors are expected to drive the market growth during the forecast period.
The global deep learning market is expected to witness significant growth during the forecast period (2020–2027) due to the adoption of advanced technologies such as the internet of things (IoT). IoT is also going to be one of the factors that is expected to drive the market growth during the forecast period. Nowadays, companies have large amount of data, which makes it difficult to handle. Cyber-attacks are also increasing due to connectivity through the usage of big data, cloud, social media, and other mobile services. Adoption of social media, cloud, and many other applications has also increased insider threat into networks, which can cause significant loss to the IT industry. Deep learning solutions in security helps organizations to protect important information and avoid data loss. Moreover, gaining popularity in the field of social media advertisement, search advertising, sales, and marketing automation is driving the market growth. For instance, in May 2020, Microsoft, a U.S.-based multinational technology company, announced a partnership with Intel Corporation, a U.S.-based multinational technology company. Through this partnership, Microsoft threat protection intelligent team worked with Intel Labs to explore new innovative approaches to detect threats through deep learning algorithms.
Complexity of software and lack of skilled resources are expected to hamper the deep learning market growth. A major challenge hampering growth of the deep learning market is complexity in IT infrastructure, which leads to cost required for employing skilled IT personnel. The deployment of hardware, software, and system integration requires experts who can handle and integrate these models into applications. It requires high cost to hire highly skilled resources in organizations. These factors are expected to hamper the market growth during the forecast period.
Deep Learning Market - Impact of Coronavirus (Covid-19) Pandemic
COVID-19 pandemic is expected to drive growth of the market during the forecast period. Due to the Covid-19 pandemic, several industries have witnessed a significant shift in terms of security in their business. There has been a significant impact on the growth of the deep learning market. Moreover, several cases of cybercrimes have been observed. Cyber threat has been increasing, as every part of the demographic has searched information related to COVID-19 by using a malicious domain name registered with names such as COVID-19 or coronavirus. For instance, according to Palo Alto Networks Inc., around 40,261 suspicious registered domain names were identified at the end of March 2020. Moreover, in recent times, the use of identical business email addresses are also used to carry out cyber-attacks. Due to the rise in cyber threats, several organizations are adopting deep learning solutions and configuring malware protection, detection, and mitigation strategies, and deep learning can be very useful for organizations to save from threats and attack.
|Base Year:||2019||Market Size in 2019:||US$ 5.6 Bn|
|Historical Data for:||2017 to 2019||Forecast Period:||2020 to 2027|
|Forecast Period 2020 to 2027 CAGR:||25.8%||2027 Value Projection:||US$ 31.3 Bn|
NVIDIA Corporation, Intel Corporation, Xilinx, Micron Technology, Inc., Qualcomm Technologies, Inc., IBM Corporation, Google Inc., Microsoft, Facebook, Inc., Samsung Electronics Co., Ltd., Sensory Inc., Pathmind, Inc., Baidu Inc, Nuance Communications, Cisco Systems, Inc., Apple, Inc., and Wipro Limited
|Restraints & Challenges:||
North America held dominant position in the global deep learning market during the forecast period
North America held dominant position in the global deep learning market in 2019, accounting for 43.2% share in terms of value, followed Europe.
Figure 1: Global Deep Learning Market Share (%), By Region, 2019
North America is expected to account for the largest market share during the forecast period, owing to the presence of key players in the region such as NVIDIA Corporation, Microsoft, Google, Inc., Amazon.com, Inc. Micron Technology, Inc. and others. For instance, Micron Technology Inc., a U.S.-based company who provides computer memories, acquired FWDNXT, an Indiana-based company who manufactures hardware and software tools for deep learning solutions. Through this acquisition, FWDNXT provides high efficient hardware and software solutions based on deep learning and neural networks.
Asia Pacific region is expected to exhibit highest growth during the forecast period, owing to the growing digital connectivity. According to a report by the Data Security Council of India (DSCI), India was the second most affected country between 2016 and 2018 by cyber-attacks. Furthermore, the average cost for a data breach in India has increased by 7.9% and the average cost per breach rose to US$ 64. The rising adoption of internet of things (IoT) has increased cyber-attacks in the IT industries. For instance, unauthorized access and malicious software updates have increased the risk related to cyber-attacks. These factors are expected to drive demand for deep learning solutions to reduce or mitigate these losses.
Software segment is expected to drive the market growth during the forecast period
Among component, the software segment is expected to hold dominant position in the global deep learning market during the forecast period. The increasing adoption of software solutions in various applications such as smartphone assistant, ATM that read cheque and voice and image recognition software are driving the deep learning market growth. Most of the companies who develop software that provide online offline support are depending on these applications. For instance, in May 2020, Kensho Technologies, LLC, a U.S.-based data analytics and machine intelligence, announced collaboration with NVIDIA Corporation, a U.S.-based multinational technology company. Through this collaboration, Kensho Technologies and NVIDIA Corporation launched Scribe, an advanced automatic speech recognition solution. This solution leverages deep learning techniques to process audio in less time with more accuracy.
Figure 2: Global Deep Learning Market Value (US$ Bn) Analysis and Forecast, 2017 - 2027
The global deep learning market was valued at US$ 5.6 Bn in 2019 and is expected to reach US$ 31.3 Bn by 2027 at a CAGR of 25.8% between 2020 and 2027.
Major players operating in the global deep learning market include NVIDIA Corporation, Intel Corporation, Xilinx, Micron Technology, Inc., Qualcomm Technologies, Inc., IBM Corporation, Google Inc., Microsoft, Facebook, Inc., Samsung Electronics Co., Ltd., Sensory Inc., Pathmind, Inc., Baidu Inc, Nuance Communications, Cisco Systems, Inc., Apple, Inc., and Wipro Limited.
Deep Learning is an approach of machine learning that uses neural networks to facilitate unsupervised patterns generated from a large volume of unstructured data. Deep learning or deep structured learning use statistics and predictive modeling for analyzing and interpreting large volumes of unstructured data. It uses many complex structured and unstructured algorithms to generate meaningful insights from the data. It also uses artificial technology to mimic the functioning of the human brain while processing data, patterns, and is helpful in decision making. Deep learning is mainly used in self-driving vehicles, speech recognition software, language translation services, and voice recognition tools. This technology is being adopted in many applications such as healthcare, automotive, retail, aerospace & defense, and others.
The global deep learning market is expected to grow significantly during the forecast period, owing to the increasing adoption of artificial intelligence, deep learning, and IoT technologies in hardware, software, and services components. The increasing demand for artificial intelligence and the internet of things (IoT) created a demand for deep learning technology for high computing technologies. Many companies are manufacturing hardware components such as processor, memory, and network hardware that are optimized with artificial intelligence. For instance, in April 2016, NVIDIA, a U.S.-based technology company, launched DGX-1, the first deep learning supercomputer to meet the unlimited computing demand of artificial intelligence. The deep learning software solutions are used in various applications and compatible platforms for high computing applications such as supercomputer. The software consists of libraries and software development kits that can be used for re-programming. Machine learning in services such as managed and professional help many organizations to understand deep learning algorithms to enhance productivity and efficiency. For instance, as cyber threats across the globe have increased, managed services are used by the companies in order to decrease cyber threats in the organizations. For instance, according to a report published by Hiscox Inc., a Bermuda-based international insurance group, 74% of the organization has a new infrastructure and 10% of the organization has the necessary infrastructure to deal with cyber threats. To overcome threats, managed service is one of the major solutions that will drive the market growth.
Among end user, the banking, financial services, and insurance (BFSI) segment is expected to exhibit the highest growth during the forecast period. The deep learning solutions provide support to the financial service providers to protect their data, customers, meet industry & government compliance standards, and avoid damage caused by data breaches. For instance, in August 2019, Visa Inc., a U.S.-based multinational financial service provider company, launched a security suite to prevent payment frauds. The BFSI segment is continuously focusing on upgrading its processing and transactional technologies, and also focusing on providing end-to-end security for transactions to minimize the fraud. For instance, in September 2016, healthcare and banking, financial services, and insurance (BFSI) used Microsoft cloud platforms to protect employee data, and optimize business processes and models. The industry is facing challenges in maintaining the application, network, and data security. The attackers are targeting these sectors with viruses, malware, and other cyber-attacks. All these factors are expected to drive the deep learning market growth during the forecast period.
Moreover, major global players across different regions are focusing on developing new products with new features and technologies to remain competitive in the market. Industries are focusing on developing new products with new features to cater to the demand from the end users. For instance, in November 2017, Amazon Web Services Inc., (AWS), a subsidiary of Amazon.com Inc., announced a collaboration with Intel Corporation, a U.S.-based multinational technology company and they have launched DeepLens, a deep learning wireless video camera. Through this collaboration, DeepLens camera provides creators great tools to design and build artificial intelligence (AI) and machine learning products.
Key features of the study:
“*” marked represents similar pointers for each company