Deep learning, a subfield of machine learning (ML), has led to significant advances in a variety of artificial intelligence tasks, including speech and image recognition. The ability to automate predictive analytics is also a contributing factor to the hype surrounding machine learning.
Many factors, including improved support for new and improved products as well as process optimization and functional workflows, as well as improved support for sales optimization, have prompted businesses across industries to invest in deep learning applications. Aside from that, recent advances in machine learning techniques have significantly improved the accuracy of models, and new classes of neural networks have been developed for use in applications such as image classification and text translation.
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Key Driving Factors: A significant amount of growth is predicted for the industry.
The increasing number of deep learning applications in recent years, such as image/speech recognition, data mining, and language translation, as well as the increasing number of humanoid robots, such as Sophia, developed by Hanson Robotics, are some of the major drivers of the deep learning market. Sophia is a humanoid robot developed by Hanson Robotics that can recognise images and speech.The expanding information technology (IT) industry, along with the rising trend of digitalization, is one of the key factors driving the growth of the market.
Key Driving Factors: During the projection period, the cloud segment is expected to rise at a faster CAGR.
Key market players are expected to increase their investments in the development of machine learning and deep learning applications in the region, resulting in faster market growth. The rapid increase in the amount of data being generated across a variety of end-use industries is also expected to add momentum to the industry's expansion. The growing demand for human-machine interaction also presents new growth opportunities for solution providers, who can capitalise on this demand by providing better solutions and capabilities.
NVIDIA (US), Intel (US), General Vision (US), Graphcore (UK), Xilinx (US), and Qualcomm (US); and solution providers such as Google (US), Microsoft (US), AWS (US), Sensory Inc. (US), and IBM (US), Samsung Electronics (South Korea), Micron Technology (US), and Mellanox Technologies (Israel).
Opportunities: It is becoming more common to see cloud-based security solutions in use.
With the growing use of cloud-based services and the massive generation of unstructured data, the demand for deep learning solutions has skyrocketed. Machine learning and deep learning account for a significant portion of the total investment in artificial intelligence. It consists of both artificial intelligence platforms and cognitive applications, which include tagging, clustering, categorization, hypothesis generation, alerting, filtering, navigation, and visualisation, and which make it possible to develop advisory, intelligent, and cognitively-enabled solutions more quickly and efficiently. Because of the increasing use of cloud-based computing platforms and on-premises hardware equipment for the safe and secure restoration of large volumes of data, it has become possible to expand and improve the capabilities of the analytics platform. In addition, increasing investments in research and development by major players will be critical in accelerating the adoption of artificial intelligence technologies.
On the basis of End-User:
The deep learning market was dominated by the security segment, which accounted for the majority of end-user share. The increasing level of security concern as a result of the evolving cybersecurity ecosystem is assisting in the segment's expansion. New types of cyberattacks are discovered in organisations, prompting them to invest in preventative measures. Deep learning, which assists organisations in protecting their critical information without causing data loss, is also helping to boost the value of the deep learning market.
The Global Deep Learning market report has been categorized as below
Others (TPU, DPU, VPU, BPU, and IPU)
Solution (Software Framework/SDK)
Support & Maintenance
• Signal Recognition
• Data Mining
• Image Recognition
Others (Intellectual Property, e-Billing, Knowledge Management)
Product Recommendation and Planning
Customer Relationship Management
Payment Services Management
Rest of the World
Published Date : July-2021