Key Emerging Trends in Deep Learning Market

According to the latest market research report “Deep Learning Market by Offering (Hardware, Software, and Services), Application (Image Recognition, Signal Recognition, Data Mining), End-User Industry (Security, Marketing, Healthcare, Fintech, Automotive, Law), and Geography – Global Forecast to 2023″, the deep learning market, the overall deep learning market is estimated to be valued at USD 3.18 Billion in 2018 and is expected to be worth USD 18.16 Billion by 2023, at a CAGR of 41.7% from 2018 to 2023. Improving computing power, declining hardware cost, and the increasing adoption of cloud-based technology are fueling the growth of the deep learning market. Usage in big data analytics and growing AI adoption in customer-centric services are the other key factors driving this market.

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Software to hold largest market share from 2018 to 2023

Software currently holds the largest market share, while the market for services is expected to grow at the highest CAGR between 2018 and 2023. The software segment consists of software frameworks and platforms/APIs developed using algorithms and codes that enable hardware to carry out deep learning programs. Manufacturers and software providers offer different solutions (frameworks/software development kits (SDKs)) and APIs/platforms that are open to developers working on deep learning programs. For example, Qualcomm offers Zeroth SDK, which helps users and developers use Snapdragon 820 capabilities for deep learning applications such as image and sound processing, including speech recognition. The hardware segment consists of processor chips used for running deep learning algorithms based on neuromorphic architecture and/or von Neumann architecture.

Deep learning market for data mining to grow at highest CAGR from 2018 to 2023

Data mining abstracts related data from files, such as image, video, and audio. With the advent of new technologies, natural language processing and visual data mining have been developed using deep learning techniques. Data mining is used in the following applications: sentiment analysis, machine translation, fingerprint identification, cybersecurity, and bioinformatics. Deep learning offers faster and better memory utilization than traditional computing systems. As data mining is a complex operation, it requires complex hardware architecture and algorithms to perform computational functions, along with service and maintenance of systems. Thus, the demand for services in data mining is expected to grow significantly between 2018 and 2023.

Security to account for largest market size among other end-user industries between 2018 and 2023

Deep learning- and AI-based systems are being significantly used in antivirus and antimalware solutions owing to the rise in cybersecurity attacks across the world. The increasing use of mobile devices for a wide range of applications, such as social networking, emails, remote monitoring, phone banking, and data storage, opens doors for hackers to attack, thereby making networks more vulnerable to risks. The rapid adoption of cloud-based services, along with the user-friendly approach of antivirus/antimalware solutions, is contributing to the growth of this application in the deep learning market for security. The adoption of DL technologies for encryption is likely to witness growth in the coming years.

North America to lead deep learning market in terms of market size

North America accounts for a substantial share of the deep learning market, with the US being the major contributor. The increasing adoption of deep learning technology in various end-user industries, such as security, marketing, healthcare, fintech, automotive, law, retail, agriculture, and manufacturing, and the strong presence of industry giants and emerging deep learning companies/start-ups in the region are the key factors supporting the growth of the deep learning market in North America.

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Companies that are profiled in this report are NVIDIA (US), Intel (US), Xilinx (US), Samsung Electronics (South Korea), Micron Technology (US), Qualcomm (US), IBM (US), Google (US), Microsoft (US), and AWS (US). Some of the key start-ups included in this report are Graphcore (UK), Mythic (US), Adapteva (US), and Koniku (US).