The global deep learning market size is expected to reach USD 10.2 billion by 2025, according to a new report by Grand View Research, Inc. Considerable improvements in machine learning algorithms and advancements in deep learning chipsets are driving the industry growth.
Rapid improvements in fast information storage capacity, high computing power, and parallelization have contributed to the swift uptake of the deep learning technology in end-use industries such as automotive and healthcare. Further, the need for understanding and analyzing visual contents among enterprises in order to gain meaningful insights, is expected to provide traction to the industry over the forecast period.
The increasing prominence of Graphics Processing Unit (GPU)-accelerated applications is leading to increased adoption of the technology in scientific disciplines such as deep learning and data science. Organizations are utilizing deep learning neural networks to extract valuable insights from enormous amounts of data for providing innovative products and improving customer experience; thereby, increasing revenue opportunities.
The technology is expected to gain prominence among key players and researchers, owing to its use in improvising artificial intelligence capabilities in Natural Language Processing (NLP), image & speech recognition, and computer vision areas. Solution providers are resorting to partnerships and collaborations to enter the deep learning space. For instance, in January 2016, Movidius collaborated with Google, Inc. to enhance its deep learning capabilities on mobile devices. In September 2016, Intel Corporation announced the acquisition of Movidius for improvising its computer vision and deep learning solutions.
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Further key findings from the report suggest:
- The hardware segment is expected to witness the fastest growth due to increased demand for high computing chipsets which are used to run deep learning algorithms
- The Field Programmable Gate Array (FPGA) segment is expected to witness considerable growth on account of its enhanced power efficiency and capability to bridge the GPU performance gap using multiple FPGAs
- The healthcare segment is anticipated to grow at a significant rate of over 55%, as the technology is outspreading the translational bioinformatics, medical imaging, and sensor-driven analysis
- The Asia Pacific deep learning market is expected to be the fastest-growing regional market due to increasing spending on artificial intelligence and cognitive computing technologies
- The key industry players include Intel Corporation, NVIDIA Corporation, IBM Corporation, and Microsoft Corporation
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Grand View Research has segmented the deep learning market based on solutions, hardware, services, applications, end-uses, and regions:
Deep Learning Solution Outlook (Revenue, USD Million; 2014 – 2025)
- Installation services
- Integration services
- Maintenance & support services
Deep Learning Hardware Outlook (Revenue, USD Million; 2014 – 2025)
- Central Processing Unit (CPU)
- Graphics Processing Unit (GPU)
- Field Programmable Gate Array (FPGA)
- Application-Specific Integrated Circuit (ASIC)
Deep Learning Application Outlook (Revenue, USD Million; 2014 – 2025)
- Image recognition
- Voice recognition
- Video surveillance & diagnostics
- Data mining
Deep Learning End-use Outlook (Revenue, USD Million; 2014 – 2025)
- Aerospace & defense
Deep Learning Regional Outlook (Revenue, USD Million; 2014 – 2025)
- North America
- Asia Pacific
- Latin America
- Middle East and Africa
Browse Press Release of this Report: http://www.grandviewresearch.com/press-release/global-deep-learning-market
About Grand View Research
Grand View Research, Inc. is a U.S. based market research and consulting company, registered in the State of California and headquartered in San Francisco. The company provides syndicated research reports, customized research reports, and consulting services. To help clients make informed business decisions, we offer market intelligence studies ensuring relevant and fact-based research across a range of industries, from technology to chemicals, materials and healthcare.
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