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µö·¯´× ½ÃÀå : ÄÄÆ÷³ÍÆ®º°, ¿ëµµº°, ÃÖÁ¾»ç¿ëÀÚº°, Áö¿ªº°Deep Learning Market, By Component, by Application, By End User, and by Region |
µö·¯´× ½ÃÀåÀº 2025³â¿¡ 210¾ï 3,240¸¸ ´Þ·¯·Î ÃßÁ¤µÇ¸ç, 2032³â±îÁö´Â 1,524¾ï 90¸¸ ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµÇ¸ç, 2025-2032³âÀÇ ¿¬Æò±Õ ¼ºÀå·ü(CAGR)Àº 32.70%·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.
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±âÁØ¿¬µµ | 2024 | 2025³â ½ÃÀå ±Ô¸ð | 210¾ï 3,240¸¸ ´Þ·¯ |
½ÇÀû µ¥ÀÌÅÍ | 2020-2024³â | ¿¹Ãø ±â°£ | 2025-2032³â |
¿¹Ãø ±â°£(2025-2032³â) CAGR : | 32.70% | 2032³â ±Ý¾× ¿¹Ãø | 1,524¾ï 90¸¸ ´Þ·¯ |
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Deep Learning Market is estimated to be valued at USD 21,032.4 Mn in 2025 and is expected to reach USD 152,400.9 Mn by 2032, growing at a compound annual growth rate (CAGR) of 32.70% from 2025 to 2032.
Report Coverage | Report Details | ||
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Base Year: | 2024 | Market Size in 2025: | USD 21,032.4 Mn |
Historical Data for: | 2020 To 2024 | Forecast Period: | 2025 To 2032 |
Forecast Period 2025 to 2032 CAGR: | 32.70% | 2032 Value Projection: | USD 152,400.9 Mn |
Deep Learning is an approach of machine learning that uses neural networks to facilitate unsupervised patterns generated from a large volume of unstructured data. Deep learning or deep structured learning use statistics and predictive modeling for analyzing and interpreting large volumes of unstructured data. It uses many complex structured and unstructured algorithms to generate meaningful insights from the data. It also uses artificial technology to mimic the functioning of the human brain while processing data, patterns, and is helpful in decision making. Deep learning is mainly used in self-driving vehicles, speech recognition software, language translation services, and voice recognition tools. This technology is being adopted in many applications such as healthcare, automotive, retail, aerospace & defense, and others.
The global deep learning market is expected to grow significantly during the forecast period, owing to the increasing adoption of artificial intelligence, deep learning, and IoT technologies in hardware, software, and services components. The increasing demand for artificial intelligence and the internet of things (IoT) created a demand for deep learning technology for high computing technologies. Many companies are manufacturing hardware components such as processor, memory, and network hardware that are optimized with artificial intelligence. For instance, in April 2016, NVIDIA, a U.S.-based technology company, launched DGX-1, the first deep learning supercomputer to meet the unlimited computing demand of artificial intelligence. The deep learning software solutions are used in various applications and compatible platforms for high computing applications such as supercomputer. The software consists of libraries and software development kits that can be used for re-programming. Machine learning in services such as managed and professional help many organizations to understand deep learning algorithms to enhance productivity and efficiency. For instance, as cyber threats across the globe have increased, managed services are used by the companies in order to decrease cyber threats in the organizations. For instance, according to a report published by Hiscox Inc., a Bermuda-based international insurance group, 74% of the organization has a new infrastructure and 10% of the organization has the necessary infrastructure to deal with cyber threats. To overcome threats, managed service is one of the major solutions that will drive the market growth.
Among end user, the banking, financial services, and insurance (BFSI) segment is expected to exhibit the highest growth during the forecast period. The deep learning solutions provide support to the financial service providers to protect their data, customers, meet industry & government compliance standards, and avoid damage caused by data breaches. For instance, in August 2019, Visa Inc., a U.S.-based multinational financial service provider company, launched a security suite to prevent payment frauds. The BFSI segment is continuously focusing on upgrading its processing and transactional technologies, and also focusing on providing end-to-end security for transactions to minimize the fraud. For instance, in September 2016, healthcare and banking, financial services, and insurance (BFSI) used Microsoft cloud platforms to protect employee data, and optimize business processes and models. The industry is facing challenges in maintaining the application, network, and data security. The attackers are targeting these sectors with viruses, malware, and other cyber-attacks. All these factors are expected to drive the deep learning market growth during the forecast period.
Moreover, major global players across different regions are focusing on developing new products with new features and technologies to remain competitive in the market. Industries are focusing on developing new products with new features to cater to the demand from the end users. For instance, in November 2017, Amazon Web Services Inc., (AWS), a subsidiary of Amazon.com Inc., announced a collaboration with Intel Corporation, a U.S.-based multinational technology company and they have launched DeepLens, a deep learning wireless video camera. Through this collaboration, DeepLens camera provides creators great tools to design and build artificial intelligence (AI) and machine learning products.
Key features of the study