Market Overview:
The Global Deep Learning Market size is expected to grow from USD 86.46 billion in 2022 to USD 1239.96 billion by 2030, at a CAGR of 39.5% during the forecast period (2023-2030).
Deep learning also referred to as deep structured learning is a subset of machine learning and artificial intelligence. It is an important component of data science which contain statistics and predictive modeling. It is very useful for those data scientists who are engaged in collecting, analyzing, and interpreting huge amounts of data, and data learning assists to make this process faster and easier. Deep learning manages several applications of artificial intelligence and services that develop automation, performing analytical, and physical tasks without interruption of humans.
Top Key Players for Deep Learning Market:
Advanced Micro Devices (US), ARM Ltd (UK), Clarifai (US), Entilic(US), Google (US), HyperVerge(US), IBM (US), Intel (US), Microsoft (US), NVIDIA (US) and other major players.
Market Dynamics and Factors for Deep Learning Market:
Drivers:
The Growing Use of Autonomous Vehicles and Healthcare Industries
The deep learning technology used in autonomous vehicles is self-driving. The main role of deep learning in an autonomous vehicle is to interpret complex vision tasks, enhance perception, localize itself in the environment, and actuate kinematic maneuvers. This assures road safety and also commutes easily. In addition to this, deep learning is also used in the healthcare sector. It is already seen in medical imaging solutions, and chatbots that can help to find the patient’s symptoms and identify the types of cancer, rare diseases, and pathology types.
Opportunities:
Growing Demand for Human-Machine Interaction
The human-machine interaction demand is rising which offers a lucrative opportunity for the market of deep learning. The human-machine interaction (HMI) is termed communication and interaction between the human and a machine through a user interface. The human-machine interface provides numerous advantages such as enhancing the efficiency of the machine, the ability to effectively control any system or device, high efficiency in recording the data, and assistance to translate the industrial control system data into readable and visual representations by human and decline the hardware cost.
Segmentation Analysis of the Deep Learning Market:
By Type, the software segment is projected to have the maximum market share in deep learning in the analysis period. This is owing to the growing adoption of software solutions in different applications like ATMs that can read checks, voice and image recognition systems, and smartphone assistants on social networks.
By Application, the Image recognition segment dominates the deep learning market. It is one of the crucial fields of image processing and computer vision. The rising demand for pattern recognition, optical character recognition, code recognition, facial recognition, object recognition, and digital image processing propels the growth of the market.
Regional Analysis of the Deep Learning Market:
North America has projected too high market growth in deep learning owing to growing investments in artificial intelligence and neural networks by major players in this region. For the purpose of image recognition, voice recognition, data mining, signal recognition, and diagnostic purposes cognition, the adoption of DL application models is increasing. The digital businesses in this region are rising rapidly. These factors supported the growth of the deep learning market over the forecast period. Mexico, Canada, and the United States are the dominating country in this region.
Key Industry Development:
In March 2021, Facebook established SEER (Self-supERvised) as a deep learning solution. This solution works independently works its way through the dataset and can learn from any random group of unlabelled images on the internet.
In May 2020, IBM declared that it would utilize the range of artificial intelligence (AI) technologies in the automation of the management of IT operations and modernize applications, also referred to as AIOps. It applies the machine and deep learning algorithms to time series data, semi-structured logs , structured data, and unstructured data spanning IT incidents and human conversations to track the timeline of an issue.
Regional Outlook (Revenue in USD Million; Volume in Units, 2023-2030)
North America
- US
- Canada
- Mexico
Eastern Europe
- Bulgaria
- The Czech Republic
- Hungary
- Poland
- Romania
- Rest of Eastern Europe
Western Europe
- Germany
- UK
- France
- Netherlands
- Italy
- Russia
- Spain
- Rest of Western Europe
Asia Pacific
- China
- India
- Japan
- South Korea
- Malaysia
- Thailand
- Vietnam
- The Philippines
- Australia
- New Zealand
- Rest of APAC
Middle East & Africa
- Turkey
- Bahrain
- Kuwait
- Saudi Arabia
- Qatar
- UAE
- Israel
- South Africa
South America
- Brazil
- Argentina
- Rest of SA
