Deep Learning Market by Hardware (Field Programmable Gate Array, Central Processing Unit, Application Specific Integration Circuit, and Graphics Processing Unit), End-users (Manufacturing, Aerospace & Defense, Automotive, Healthcare, and Others), Applications (Voice Recognition, Data Mining, Image Recognition, and Video Surveillance & Diagnostics), Soloutions (Software, Hardware, and Services [Maintenance & Support Services, Installation Services, and Integration Services]), and Regions (Asia Pacific, North America, Latin America, Europe, and Middle East & Africa) - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast 2021 – 2028

The global deep learning market size is anticipated to register a considerable CAGR during the forecast period, 2021-2028. The growth of the market is attributed to the increasing use of deep learning solutions in automotive and healthcare, human resource management, and agriculture industry for process optimization.

Deep learning is a subfield of machine learning. Deep learning involves a series of algorithms that are inspired by the structure and function of the brain known as artificial neural network with three or more layers. Deep learning offer benefits to numerous Artificial Intelligence services and applications in automation, performing physical, and analytical tasks without human interference. Algorithms of deep learning process unstructured data, such as text, audio, and images. Voice-enabled TV remote, self-driving cars, digital assistant, and credit card fraud detection system are some of the sectors where deep learning is prominently used for automation.

The COVID-19 pandemic outbreak had positive impact on the market owing to the demand for fraud detection, anti-money laundering, and other such solutions increased. Furthermore, during the pandemic, the population surveillance method is used by many government across the globe to trace the COVID-19 cases, which in turn driving the demand of deep learning technology.

Market Trends, Drivers, Restraints, and Opportunities

• Increasing volume of data generating from different end-user industries across the globe is one of the key factors driving the market growth.
• Rising adoption of cloud-based services is projected to boost the market during the forecast period.
• Escalating complexity in hardware due to complex algorithms used in deep learning technology acts as a major challenge that can restrict the market growth in the coming years.
• Lack of technical expertise & absence of standards and protocols is expected to hamper the market growth during the projected timeline.
• Growing investment by market players to incorporate deep learning in their product portfolio is anticipated to create significant growth opportunities for the market.

Scope of the Report

The report on the global deep learning market includes an assessment of the market, trends, segments, and regional markets. Overview and dynamics have also been included in the report.

Market Segment Insights

Faster performance drive the GPU segment

Based on hardware, the global deep learning market is divided into Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), Application Specific Integration Circuit (ASIC), and Graphics Processing Unit (GPU). The GPU segment is expected to grow at a rapid pace during the forecast period due to the performance of GPU, which is faster than any other chipsets. Additionally, the rising need for improved visual content has led to an increased demand for GPUs in deep learning applications. On the other hand, the FPGA segment is anticipated to expand at a substantial CAGR in the coming years owing to higher performance of FPGA per watt of power consumption in deep learning applications.

Applications of deep learning increases the aerospace & defense segment

In terms of end-users, the market is fragmented into manufacturing, aerospace & defense, automotive, healthcare, and others. The aerospace & defense segment is estimated to account for a significant market share during the forecast period attributed to applications of deep learning in malware detection, remote sensing, and object detection. Moreover, the segment growth is further accelerated as these technologies is used in data mining and image recognition to foresee and evaluate future courses of action. On the other hand, the automotive segment is anticipated to grow at a high CAGR during the projected period owing to increasing manufacturing of self-driving cars.

Image recognition segment to expand at robustrate growth

Based on applications, the global deep learning market is segmented into voice recognition, data mining, image recognition, and video surveillance & diagnostics. The image recognition segment is estimated to expand at robust growth rate during the forecast period due to industries, such as automotive and financial services are adopting image recognition to transform their offerings to create more value for business and customers. Additionally, the image recognition technology is used in Facebook’s facial recognition feature, which is driving the segment growth further. However, the data mining segment is projected to expand at a considerable CAGR during the forecast period attributed to the need of identifying patterns and making meaningful predications from the data.

Increasing adoption drives the software segment

On the basis of solutions, the market is segregated into software, hardware, and services. The services segment is further divided into maintenance & support services, installation services, and integration services. The software segment is projected to register at high CAGR in the projected timeline attributed to the increasing adoption of software solutions in numerous applications, such as voice and image recognition software on social media, smartphone assistants, and ATMs that read checks. On the other hand, the hardware segment is anticipated to register a substantial CAGR during the forecast period due to acquisition of both hardware and software for the development of ASIC and FPGA.

North America is to constitute a key market share

In terms of region, the global deep learning market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America is anticipated to constitute a key share of the market during the projected period owing to early adoption of advanced technologies in the region and high adoption of image and pattern recognition technology. However, the Europe market is anticipated to grow at a rapid pace during the forecast period due to the government initiatives to support the artificial intelligence sector for digital economy in the region, which increases the demand of deep learning technology.

Segments

Segments Covered in the Report

The global deep learning market has been segmented on the basis of

Hardware

• Field Programmable Gate Array
• Central Processing Unit
• Application Specific Integration Circuit
• Graphics Processing Unit

End-users

• Manufacturing
• Aerospace & Defense
• Automotive
• Healthcare
• Others

Applications

• Voice Recognition
• Data Mining
• Image Recognition
• Video Surveillance & Diagnostics

Solutions

• Software
• Hardware
• Services
  • Maintenance & Support Services
  • Installation Services
  • Integration Services

Regions

• Asia Pacific
• North America
• Latin America
• Europe
• Middle East & Africa

Key Players

• Intel Corp.
• Google, Inc.
• NVIDIA Corp.
• Microsoft Corp.

Competitive Landscape

Key players competing in the global deep learning market are Intel Corp.; Google, Inc.; NVIDIA Corp.; and Microsoft Corp. Companies have been widely engaged in strategic partnership, merger & acquisition, new product launch, and collaborations to boost their market share and acquiring new buyers.

For instance, in February 2020, Oracle Corporation, a leading technology firm, announced the launch of Oracle Cloud Data Science Platform. The newly launched platform will be assisting businesses in collaboratively managing, building, training, and deploying machine learning models to improve the performance of data science programs. In February 2021, Seed Health, a U.S. based microbial sciences company announced the acquisition of Auggi, a digital health coach. Auggi uses a deep learning algorithm for automated characterization and detection of an individual’s stool. By this acquisition Seed Health will integrate Auggi’s mobile tracking application across their clinical trials for the gut microbiota in irritable bowel syndrome after antibiotic consumption and humans assessing DS-01.