US: ReportsnReports.com adds Deep Learning Market forecast to reach $18.16 billion by 2023 from $3.18 billion in 2018 at a CAGR of 41.7% during (2018-2023) driven by improving computing power, declining hardware cost, the increasing adoption of cloud-based technology, usage in big data analytics and growing AI adoption in customer-centric services.
The deep learning market in APAC expected to grow at highest CAGR. This report covers the deep learning market in North America, Europe, APAC, and RoW. Rise in the adoption of deep learning technology in APAC could be attributed to the increasing applications of deep learning in media & advertising, finance, and retail sectors, among others, in technologically advancing countries such as India, China, and Japan. Growing e-commerce, online streaming, and increasing internet penetration have resulted in the growth of marketing industries. In the security vertical, with increasing incidents of cyber-attacks and a growing cyber-war in the region, organizations and governments are focusing on robust defense infrastructure.
The deep learning market for manufacturing industry will witness highest growth between 2018 and 2023. Deep learning technology is used in industrial robots, machine vision systems, and others to improve the process and product quality, minimize cycle time, and increase the efficiency of the manufacturing process as a whole. North America accounts for a substantial share of the deep learning market, with the US being the major contributor. However, the lack of technical expertise and absence of standards and protocols, and increasing complexity in hardware due to complex algorithm used in deep learning technology are restraining the growth of the deep learning market.
The Deep Learning market for services to grow at highest CAGR from 2018 to 2023. Deep learning technology is highly complex in nature requiring the implementation of sophisticated algorithms. Deep learning systems require installation; training; and support and maintenance services. Installation services allow the software to be integrated with the analytics side to enable data retrieval and generate desired result through computation. The use of computer systems for DL/AI further increases the amount of work involved in installation.
In terms of hardware, processor held the largest size of the deep learning market in 2017. Companies in industries such as healthcare and finance are investing in machine learning infrastructure. High parallel processing capabilities and improved computing power have resulted in the high adoption of GPUs in various DL applications.