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.
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.
Gather more insights about the market drivers, restraints, and growth of the Global Deep Learning Market
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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Deep Learning Industry Segmentation
Grand View Research has segmented the global deep learning market based on solution, hardware, application, end use, and region:
Deep Learning Solution Outlook (Revenue, USD Million, 2017 - 2030)
- Hardware
- Software
- Services
Deep Learning Hardware Outlook (Revenue, USD Million, 2017 - 2030)
- Central Processing Unit (CPU)
- Graphics Processing Unit (GPU)
- Field Programmable Gate Array (FPGA)
- Application-Specific Integration Circuit (ASIC)
Deep Learning Application Outlook (Revenue, USD Million, 2017 - 2030)
- Image Recognition
- Voice Recognition
- Video Surveillance & Diagnostics
- Data Mining
Deep Learning End-use Outlook (Revenue, USD Million, 2017 - 2030)
- Automotive
- Aerospace & Defense
- Healthcare
- Manufacturing
- Others
Deep Learning Regional Outlook (Revenue, USD Million, 2017 - 2030)
- North America
- Europe
- Asia Pacific
- South America
- MEA (Middle East & Africa)
Market Share Insights:
October 2020, NVIDIA AI and Microsoft Azure team worked together to improve the AI-powered grammar checker in Microsoft Word.
December 2019: Intel Corp. acquired Habana Labs Ltd., an Israel-based startup working on deep learning algorithms for data center applications strengthening the AI capability of Intel Corporation.
Key Companies profiled:
Some prominent players in the global Deep Learning Industry 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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