Press Release

The deep learning market is projected to grow USD 18.1 Bn in 2030, at a CAGR of 34.6%. Developments in data center capabilities, high computing power, and the capacity to conduct jobs without human intervention, the technology is gaining traction. Furthermore, the market is being fueled by the rising use of cloud-based technologies across a variety of industries. Deep learning algorithms are capable of doing a variety of repetitive and routine jobs more efficiently and in less time than humans. Furthermore, the work's quality is maintained, and precise information is provided. As a result, applying deep learning in the workplace can save time and money, allowing employees to focus on innovative tasks that require human interaction. As a result, deep learning is viewed as a disruptive technology in a variety of end-use sectors, increasing demand for technology.

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The market is expected to develop due to an increase in the demand for processing power among businesses and the increased usage of IoT devices across various industries. Furthermore, 2.5 quintillion bytes of data are created every day, and the quantity is growing. Massive amounts of data generated by numerous business verticals are presenting attractive prospects for deep learning solutions to provide businesses with efficient, flexible, and scalable insights.

Rise due to the rapid usage of connected devices across various educational institutes and government initiatives to enhance digitization across all industry verticals. For example, the Australian Catholic University (ACU) created a data lake in July 2020 to provide a single picture of student development after unifying its data environment. It makes use of Microsoft's Power BI and Azure data platform to help students who might need more help or are on the verge of dropping out. As a result, this is seen as a key driver of market expansion.

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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. 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. The retail segment has dominated the market share in 2020 of global deep learning market owing to minimize the number of onsite offerings in favour of online service in recent years, signalling a significant shift in its base of operations. E-commerce has proven to be a key force in the retail trade industry.

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.

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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.

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