Deep Learning Market Analysis by Component, Application, End User and Region| Advanced Machine Learning Algorithms to Drive Deep Learning Market

The global deep learning market is projected to touch a valuation of USD 17.4 billion by 2023 thanks to developments in machine learning. Furthermore, the application of deep learning algorithms in personalized schooling, autonomous cars, and others is likely to bolster the market growth.

Pune, India, May 30, 2019 (GLOBE NEWSWIRE) -- The global deep learning market is bound to grow by leaps by 2023, as per the latest report by Market Research Future (MRFR). Deep learning is a part of machine learning which deals with algorithms similar to the functioning of the neural system in the brain. The language has three major forms of architecture, namely supervised, semi-supervised, and unsupervised. It has been applied in board games, drug design, bioinformatics, and material design.

Market Scope

The deep learning market is projected to exhibit 30.87% CAGR from 2018 to 2023 (forecast period) to touch a valuation of USD 17.4 billion. It is majorly driven by incremental developments in computing power, lowered costs of hardware, and inclination towards cloud technology. The manufacture of deep learning chips for furthering the research in machine learning is likely to bode well for the market. In 2019, Hailo launched a new deep learning chip which can perform at 26 tera operations per second. It has high potential considering it managed to raise USD 12.5 million in funding. The paucity of skilled personnel can be detrimental to its growth.

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Industry News

Generative Adversarial Network – These are a sub-section within machine learning capable of generating images similar to ones found in reality. It had found its prominence when the system managed to create a painting from a set of random images and managed to sell its artwork at a Christie’s auction. Encouraging the technology, DataGrid, a Japanese company has created full-sized virtual renderings of people with no physical existence. These models can be used by apparel or ecommerce companies for advertising their product without any infringement of any copyright laws.


The deep learning market is segmented by component, application, and end-user.

By component, the market is segmented into hardware, software, and services. Among components, the hardware segment is expected to generate maximum revenues for the Deep Learning Market till 2023.

By application, the market is segmented into signal recognition, image recognition, data mining, and others. Image recognition is projected to maintain a healthy market share owing to the distribution of various fake images being circulated in the Internet. The use of deep learning techniques to distinguish between the fake and real images can boost the segment growth. On the other hand, the data mining segment is anticipated to lucrative for the deep learning market owing to its demand across healthcare, BFSI, and retail.

By end-user, the market is segmented into automotive, retail, manufacturing, agriculture, healthcare, BFSI, media & entertainment, and security. The healthcare segment is likely to be one of the biggest revenue generators owing to new algorithms being integrated to answer queries by chatbots or assist doctors in their diagnosis. On the other hand, the automotive segment can use deep learning beyond technological means to generate revenue. Marketing teams within the automotive industry can rely on these codes to pinpoint consumer behavior on the basis of demographic, age, and location. This is exemplified by Hyundai’s 2018 car campaign which could identify social media influencers capable of boosting the company’s image.

Competition Outlook

Prominent names in the deep learning market includes Advanced Micro Devices Inc., Adapteva, Inc., Amazon Inc., Facebook, Sensory Inc., Intel Corporation, Microsoft Corporation, Qualcomm Technologies Inc., Xilinx Inc., Google LLC, IBM Corporation, NVIDIA Corporation, Baidu Inc, Samsung Electronics Co Ltd, Mellanox Technologies, Micron Technology, and Tenstorrent.

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Regional Scope

North America, Europe, Asia Pacific (APAC), and Rest-of-the-World (RoW) are regions of interest to the deep learning market.

The North America region is predicted to be highly lucrative for the market due to heavy investments in deep learning applications, platforms, and systems. Development of humanoid robots combined with applications in video-to-video synthesis, image recognition, and language translations is expected to culminate in a high windfall for the regional deep learning market.

On the other hand, the APAC region is projected to showcase exponential growth thanks to the rise of startups offering solutions in machine learning and artificial intelligence in China, India, and Japan. The rise in number of chatbots and continuous upgradation witnessed in digital personal assistants are other factors which can fan the growth of the market.

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