Deep Learning Market Opportunities and Future Scope Till 2030

Deep Learning Industry Overview

The global deep learning market size was valued at USD 34.8 billion in 2021 and is expected to expand at a compound annual growth rate (CAGR) exceeding 34.3% from 2022 to 2030.

The technology is gaining prominence because of advancements in data center capabilities, high computing power, and the ability to perform tasks without human interactions. Moreover, the rapid adoption of cloud-based technology across several industries is fueling the growth of the market. Deep learning algorithms can perform several repetitive and routine tasks more efficiently within a shorter time than human beings. In addition, the quality of the work is maintained and provides accurate insights. Thus, implementing deep learning in the organization can save time and money, which eventually frees up the employees to perform creative tasks that need human involvement. Therefore, deep learning is considered a disruptive technology across several end-use industries, uplifting the demand for technology.

Gather more insights about the market drivers, restrains and growth of the Global Deep Learning Market

Deep learning technology has grown due to recent developments in neural network architecture and training algorithms, Graphics Processing Units (GPU), and the availability of a significant amount of data across sectors. The increasing adoption of robots, IoT, cybersecurity applications, industrial automation, and machine vision technology led to a large volume of data. This data can serve as a training module in deep learning algorithms, which help diagnose and test purposes. The deep learning algorithms learn from past experiences and create a consolidated data environment. The more data there is, the more accurate the results will be, and the data will be managed consistently.

Deep learning finds applications in machine translation, chatbots, and service bots. A trained Deep Neural Network (DNN) translates the sentence or a word without using a large database. DNNs provide more accurate and better results than conventional machine translation approaches, which improves system performance. Deep learning algorithms can be used in chatbots and service bots to improve customer services and reduce the call center burden. Deep learning platform application in chatbots involves Automatic Speech Recognition (ASR) to translate audio to text and Natural Language Processing (NLP) for the automated call transfer process. According to the survey done by Oracle Corporation in 2018, 80% of businesses are currently using chatbots. Additionally, in 2018 there were 300,000 active chatbots on Facebook Messenger, and the number for the same is expected to increase in the coming years. 

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Market Share Insights

• January 2022: Wayve, a London-based startup, raised USD 200 million. This will help the organizations create deep learning techniques to train and develop artificial intelligence, capable of complex driving situations.
• May 2020: NEUCHIPS corporation announced the World’s First Deep Learning Recommendation Model called RecAccelTM.
• July 2018: Xilinx, Inc. acquired DeePhi Technology Co., Ltd., a Beijing-based startup company working to develop neural networks and provide end-to-end applications on deep-learning processor unit (DPU) platforms.

Key Companies profiled:

Some prominent players in the global deep learning market include:

• Advanced Micro Devices, Inc.
• ARM Ltd.
• Clarifai, Inc.
• Entilic
• Google, Inc.
• HyperVerge
• IBM Corporation
• Intel Corporation
• Microsoft Corporation
• NVIDIA Corporation

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