Global Deep Learning Market Size, Share, and COVID-19 Impact Analysis, By Component (Hardware, Software & Service), By Application (Image recognition, Signal recognition, Data mining & Others), By Vertical (IT & Telecommunications, Automotive, Retail, Healthcare, Manufacturing, Banking, financial services and insurance (BFSI) & Others), and by Region (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa) Analysis and Forecast 2022-2030

KEY MARKET INSIGHTS

The Deep Learning Market was valued at USD 2.8 Bn in 2021. The market is projected to grow USD 18.1 Bn in 2030, at a CAGR of 34.6%. Deep learning is a kind of machine learning that focuses on teaching computers basic human instincts. Furthermore, using deep learning, a computer algorithm may learn to execute categorization tasks by directly evaluating complicated data, which can be in the form of images, text, or voice. Deep learning also assists end users in developing algorithms that achieve state-of-the-art (SOTA) accuracy, which is even higher than human performance. Additionally, the capacity to automate predictive analytics is fueling ML's popularity. Enterprises across industries have been investing in deep learning applications due to factors such as improved support in product creation and enhancement, process optimization and functional workflows, and sales optimization, among others.

The growing application of artificial intelligence (AI) and machine learning (ML) technologies in numerous end-use industries such as healthcare, automotive, retail, and manufacturing, among others, is driving market expansion. In addition, numerous governments have implemented quarantine and social distancing rules to reduce the pandemic's impact by 2020. The developers and researchers want to examine the effects of these measures using machine learning methods.

COVID-19 ANALYSIS

With the unprecedented COVID-19 pandemic, demand for deep learning solutions has increased, owing to a growing craze for digital voice assistance among the younger generation of developing countries, as well as an increased focus on virtual reality and augmented technologies by various key vendors from various countries, which has boosted demand for deep learning solutions in the pandemic situation. The government's lockdown resulted in a significant halt of market activity, with the participants bearing the brunt of the consequences in the form of losses, less skilled personnel, unavailability of raw materials for production.

LATEST TREND

Increasing Advancements in the Capabilities of Data Centers

Companies are likely to increase their spending in developing machine learning and deep learning applications in the area, accelerating market growth. Furthermore, the rapid development in the volume of data generated in various end-use industries is likely to propel the business forward. Furthermore, the growing demand for human-machine interaction is presenting solution providers with new opportunities to expand their offerings and capabilities.

DRIVING FACTORS

Integration of Deep learning with Big Data Analytics

The integration of deep learning with big data analytics, as well as the growing need to improve computing power and lower hardware costs due to deep learning algorithms' ability to run or execute faster. Many possible uses in healthcare, education, communication, media, and entertainment are covered. Issues such as appropriate data storage, semantic indexing, data tagging, and quick data retrieval from big data can be achieved.

Shifting Focus to Cloud-Based Technology Across Different Industries

Deep learning solutions are in high demand due to the growing use of cloud-based services and the large-scale creation of unstructured data. In addition, the expanding use of deep learning in recent years for image/speech recognition, data mining, and language translations, as well as the growing number of humanoid robots, such as Hanson Robotics' Sophia, are some of the key drivers of the deep learning Market.

RESTRAINTS

Lack of Skilled Workforce Impacting Market Growth

Lack of skilled professionals would likely to get hampered for the growth of the global deep learning market. The market's growth is being limited by the increased hardware complexity due to complicated algorithms utilized in technology, as well as a lack of technical experience and a lack of standards and protocols.

SEGMENTATION

The global deep learning market is segmented by Component (Hardware, Software & Service), By Application (Image recognition, Signal recognition, Data mining & Others), By Vertical (IT & Telecommunications, Automotive, Retail, Healthcare, Manufacturing, Banking, financial services and insurance (BFSI) & Others) and Region. Based on the component, the market is categorized into hardware, software & service. Based on application, the market is categorized into image recognition, signal recognition, data mining & others. Based on vertical, the market is categorized into It & telecommunications, automotive, retail, healthcare, manufacturing, banking, financial services and insurance (bfsi) & others. Based on the region, the market is categorized into North America, Europe, Asia-Pacific, South America, Middle East and Africa.

Component Insights

Based on the component segment, the global deep learning market is categorized into hardware, software & service. The software segment has dominated the market share in 2020 of global deep learning market owing to the growing demand of software in a variety of applications, including as smartphone assistants, ATMs that read checks, social media voice and picture recognition software, and software that displays adverts on a variety of websites, is propelling deep learning market forward. Depending on the application, most organizations that manufacture and design systems and accompanying software provide both online and offline assistance.

Application Insights

Based on the application segment, the global deep learning market is categorized into image recognition, signal recognition, data mining & others. The image recognition segment has dominated the market share in 2020 of global deep learning market owing to gaining popularity for code recognition, optical character recognition, pattern recognition, facial recognition, and digital image processing. Increase in visual content on social media and the demand for content modernization. In 2018, Instagram, for example, unveiled a new function for explaining photographs with visual impairments based on deep learning algorithms.

Vertical Insights

Based on the vertical segment, the global deep learning market is categorized into It & telecommunications, automotive, retail, healthcare, others. The retail segment has dominated the market share in 2020 of global deep learning market owing to minimize the number of onsite offerings in favor of online service in recent years, signaling a significant shift in its base of operations. E-commerce has proven to be a key force in the retail trade industry. Machine intelligence is used by retailers to collect data, evaluate it, and use it to provide customers with individualized shopping experiences.

REGIONAL INSIGHTS

The global deep learning market is categorized into North America, Europe, Asia-Pacific, Latin America, Middle East and Africa. North America region is dominating the market share of global deep learning market owing to the heavy investments in AI-based technologies and easy availability of proper IT infrastructure. High adoption of image and pattern recognition is expected to open up new potential prospects. Furthermore, the region is one of the early adopters of modern technology, allowing businesses to quickly implement deep learning capabilities. However, Europe region is anticipated to grow over the next few years of global deep learning market owing to increased usage of machine learning technologies in emerging economies with significant populations of skilled employees. Improved customer access to AI-enabled services and goods is influencing the regional market is in demand. The European Union proposed a Digital Europe Program with a budget of 10.4 billion dollars for the years 2021-2027 in June 2018. Such proactive actions in Europe are likely to open up new market prospects and boost industry growth.

PLAYERS PROFILED:

· NVIDIA

· Intel Corporation

· General Vision

· Graphcore

· Xilinx

· Qualcomm

· Google LLC

· Microsoft

· Meta, Inc.

· Amazon Web Services Inc.

· Sensory Inc.

· IBM Corporation

· Samsung Electronics

· Micron Technology

· Mellanox Technologies

· Others

Key Developments:

March 2022- Microsoft acquired Nuance Communications to empower enterprises across industries to accelerate their business goals with security-focused, cloud-based solutions packed with strong, vertically tuned AI.

June 2021- IBM Corporation acquired Turbonomic to offer comprehensive AIOps capabilities to help customers accelerate their journey to hybrid cloud and AI.

December 2019- Intel Corporation has acquired Habana Labs to expand the company’s artificial intelligence (AI) portfolio.

SEGMENTATION

By Component

• Hardware
• Software
• Service

By Application

• Image recognition
• Signal recognition
• Data mining
• Others

By Vertical

• IT & Telecommunications
• Automotive
• Retail
• Healthcare
• Manufacturing
• Banking, financial services and insurance (BFSI)
• Others

By Region

• North America- U.S., Mexico, Canada
• Europe- UK, France, Germany, Italy
• Asia-Pacific- China, Japan, India
• Latin America- Brazil, Argentina, Colombia
• The Middle East and Africa- United Arab Emirates, Saudi Arabia