Global Deep Learning Market Research Report: By Component (Hardware, Software, Services), By Application (Image Recognition, Data Mining, Signal Recognition), By End User (Security, Manufacturing, BFSI, Healthcare, Agriculture) - Forecast till 2027
Deep learning is a subset of machine learning that tries to mimic human behavior without supervision. Construction of large neural networks and feeding of large volumes of data for distinguishing between humans and objects forms a vital point of this technology. The global deep learning market report by Market Research Future (MRFR) covers latest updates and prospects in novel applications in the industry for the period of 2018 to 2023 (forecast period). The COVID-19 outbreak and its implications are outlined in the report.
The global deep learning market is expected to expand at 30.60% CAGR during the forecast period. Generation of large volumes of unstructured data and cloud services has compelled the need for deep learning. This is evident with applications in robotics, artificial intelligence, and image and speech recognition. For instance, Hanson Robotics has developed Sophia, a humanoid robot, with features and habits close to humans.
The increasing need for human and machine interaction in the coming years can provide abundant opportunities to the market. Investments of multinational corporations into the technology can provide stimulus to the market. Agreements and partnerships between companies for developing and improving new technologies will lead to new avenues for the market to expand. Government initiatives and increased budget for new technologies can buttress the trend in the forthcoming years.
But the need for large amount of data can pose a challenge to the market.
Based on component, the market has been classified into hardware (processors, memory, and network), software (solution and platform) and services (installation, training, and support maintenance). The hardware segment is expected to dominate the deep learning market during the forecast period.
By application, it is segmented into signal recognition, image recognition, data mining, and others.
End-users in the global deep learning market are agriculture, automotive, healthcare, manufacturing, retail, security, and others.
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Within North America region, the growing adoption of deep learning technology for applications, namely signal recognition, voice and image recognition, data mining, and diagnostics purpose in the U.S., Canada, and Mexico is driving the market growth. Huge demand for realistic visuals in gaming and edutech can trigger the demand for deep learning. Graphics processing units are being produced on a large scale to cater to high-speed computing applications.
The APAC deep learning market is driven by the growing development and penetration of deep learning technology in Australia, China, Japan, India, New Zealand, South Korea, and Taiwan. Extensive use of chatbots and virtual assistants for smartphones and other smart devices can drive the demand for deep learning. The insights into human behavior, resolution of normal queries, and improvements of security in public places can bolster the market growth exponentially during the forecast period.
Additionally, the adoption of deep learning technology by governments in the European countries for fraud detection, surveillance, and data mining are expected to propel the market growth in the region.
Micron Technology, Advanced Micro Devices Inc., Baidu Inc, Tenstorrent, Samsung Electronics Co Ltd, Sensory Inc., Adapteva, Inc., IBM Corporation, Mellanox Technologies, Intel Corporation, Google LLC, Qualcomm Technologies Inc., Amazon Inc., Microsoft Corporation, NVIDIA Corporation, Xilinx Inc., and Facebook are key players of the global deep learning market.
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