Deep Learning Market Analysis And Forecast To 2032: By Component (Hardware, Software, Services), Application (Image Recognition, Voice Recognition, Video Surveillance & Diagnostics, Data Mining), End-User (Automotive, Aerospace & Defense, Healthcare, Manu

Deep Learning Market Analysis And Forecast To 2032: By Component (Hardware, Software, Services), Application (Image Recognition, Voice Recognition, Video Surveillance & Diagnostics, Data Mining), End-User (Automotive, Aerospace & Defense, Healthcare, Manufacturing, Others), And Region

The global Deep Learning Market was valued at USD 47.3 Billion in 2022 and it is anticipated to grow up to USD 379.4 Billion by 2032, at a CAGR of 23.1% during the forecast period.

Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural networks (DNNs), deep learning models are neural networks (algorithms used to simulate the workings of the human brain in order to recognize patterns) that can learn and make predictions on their own by analyzing data, finding patterns, and making decisions.
Global Deep Learning Market Scope and Report Structure
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Market Trends and Drivers
Deep learning technology has grown due to recent developments in neural network architecture and training algorithms, Graphics Processing Units (GPU), and the availability of a significant amount of data across sectors. The increasing adoption of robots, IoT, cybersecurity applications, industrial automation, and machine vision technology led to a large volume of data. This data can serve as a training module in deep learning algorithms, which help diagnose and test purposes. The deep learning algorithms learn from past experiences and create a consolidated data environment. The more data there is, the more accurate the results will be, and the data will be managed consistently.
Market Restraints and Challenges
There are a few key restraints and challenges in deep learning market. Firstly, the data requirements for deep learning are significantly higher than other machine learning methods, which can make it difficult to obtain the necessary data for training. Secondly, deep learning models can be very computationally intensive, which can make them difficult to train and deploy. Finally, deep learning models can be prone to overfitting, which means that they may not generalize well to new data.
Global Deep Learning Market Segmental Overview
The report analyses the global Deep Learning Market based on component, application, end-use, and region.

Global Deep Learning Market by Component

By component, the market is segmented into hardware, software, and services. The hardware segment held the largest revenue share of more than xx% in 2022. The Graphics Processing Unit (GPU) segment held the largest market share of around 57.3% in 2021. GPUs are the widely used hardware for improving training and classification processes in Computer Neural Networks (CNNs) as it holds high memory bandwidth and throughput. GPU provides better computational ability allowing the system to do multiple parallel processes. Multi-GPU enhances the deep learning performance by combining several GPUs in one computer. Moreover, it offers a fast and accurate computational ability to perform a broad set of tasks concurrently in real-time. Multi-GPU helps in object detection for the autonomous car. The system needs to perform a comprehensive set of tasks in quick successions, such as detecting obstacles, determining the boundary lines, and intersection detection. Several innovations are advancing deep learning. For instance, In May 2020, NEUCHIPS corporation announced the World's First Deep Learning Recommendation Model called RecAccelTM. This can perform 500,000 inferences per second.

Global Deep Learning Market by Application

By application, the Deep Learning Market is classified into Image Recognition, Voice Recognition, Video Surveillance & Diagnostics, and Data Mining. Image recognition held the largest market share of around xx% in 2022. Deep learning can be used in stock photography and video websites to make visual content discoverable for the user. The technology can be used in visual search, allowing users to search for similar images or products using a reference image. Moreover, the technology can be used in medical image analysis, facial recognition for security and surveillance, and image detection on social media analytics.

The increasing visual content on social media and the need for content modernization will drive the application of image recognition. For instance, in 2018, Instagram announced a new feature based on deep learning algorithms for describing photos with visual impairments. The feature automatically identifies the photo using image recognition technology and then reads its automated description of the photo. Also, in March 2021, Facebook developed a deep learning solution called SEER (Self-supERvised). This solution can autonomously work its way through the dataset and can learn from any random group of unlabeled images on the internet.

Global Deep Learning Market by End-user

Based on end-use. It is segmented into Automotive, Aerospace & Defense, Healthcare, Manufacturing, and Others. The automotive segment dominated with a revenue share of over xx% in 2022. The autonomous vehicle is a revolutionary technology that requires a massive amount of computation power. A DNN can rapidly help the autonomous vehicle perform various tasks without human interference. Autonomous vehicles are expected to gain momentum in the forthcoming years, and thus various startups and large companies are working on their development. Google Inc.; Uber Technologies, Inc.; and Tesla, Inc. are some prominent companies showing their capabilities in developing autonomous vehicles. For instance, in December 2019, Nvidia launched the NVIDIA DRIVE platform for autonomous vehicles.

Various investments are being made to enhance the use of deep learning in improving the features of the autonomous vehicle. For instance, in January 2022, Wayve, a London-based startup, raised USD 200 million. This will help the organizations create deep learning techniques to train and develop artificial intelligence, capable of complex driving situations.
Geographical Analysis of Global Deep Learning Market
Region-wise, it is studied across North America, Europe, Asia Pacific, and the Rest of the World. North America dominated the market with a revenue share of over xx% in 2022, which is attributed to increased investments in artificial intelligence and neural networks. The high adoption of image and pattern recognition in the region is expected to open new growth opportunities over the forecast period. Moreover, the region is one of the early adopters of advanced technologies, rendering organizations adopt deep learning capabilities at a faster pace. Furthermore, increased government support is expected to provide a positive impact on the growth of the industry in the region. The establishment of subcommittees on artificial intelligence and machine learning within the federal government is providing traction for the growth.

Europe has contributed significantly to the market growth as several new measures have been taken to support the artificial intelligence sector in the region to boost growth and deliver a digital economy. This, in turn, has offered considerable growth opportunities in the deep learning space. The U.K. is underpinning the technology to grow further in the areas of autonomous vehicles, smart devices, and cyber security.
Major Players in the Global Deep Learning Market
The key players in the Deep Learning Market  Advanced Micro Devices Inc., Amazon Web Services, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung, and Xilinx, among others.
COVID-19 Impact:
According to our deep learning industry analysis, deep learning has helped during the COVID-19 pandemic in aspects such as early disease diagnosing, fraud detection, and money laundering. Deep learning models enable researchers to handle enormous amounts of data thanks to increased inexpensive data storage capacities, the development of computers with powerful processors, and other computational advancements. According to recent studies, deep learning models have already been used to classify, predict, identify, and diagnose COVID-19 using medical imaging (such as X-ray images and CT scans). Deep learning has also helped with disease forecasting and tracking, social distance monitoring, and the development of drugs and vaccines (sometimes taking mutations/variants into account). In this way, deep learning assisted in saving a huge amount of money and saved millions of lives during the coronavirus outbreak.
Recent Developments:

In January 2022, Wayve, a London-based startup, raised USD 200 million. This will help the organizations create deep learning techniques to train and develop artificial intelligence, capable of complex driving situations.
In October 2020, NVIDIA AI and Microsoft Azure team worked together to improve the AI-powered grammar checker in Microsoft Word. The web version of Microsoft Word can now tap into NVIDIA Triton Inference Server, ONNX Runtime, and Microsoft Azure Machine Learning to provide this smart experience.
In December 2019, Nvidia launched the NVIDIA DRIVE platform for autonomous vehicles.
In December 2019, Intel Corp. acquired Habana Labs Ltd., an Israel-based startup working on deep learning algorithms for data center applications strengthening the AI capability of Intel Corporation
In November 2018, Amazon Web Services announced Amazon Elastic Inference, allowing users to add elastic GPU support, reducing deep learning costs by up to 75%.



Frequently Asked Questions
Q1. How big is the Deep Learning Market?

Ans. The global Deep Learning Market was valued at USD 47.3 Billion in 2022 and it is anticipated to grow up to USD 379.4 Billion by 2032, at a CAGR of 23.1% during the forecast period.

Q2. What is the Deep Learning Market growth rate?

Ans. The growth rate of the deep learning market is 23.1%

Q3. Which region holds a major market share for the market?

Ans. North America holds a major market share of the Deep Learning Market in 2022.

Q4. Which segment accounted for the largest Deep Learning Market share?

Ans. By end-use, the automotive segment accounted for the largest Deep Learning Market share.

Q5. Who are the key players in the kidney stones management market?

Ans. The global Deep Learning Market report includes players such  Advanced Micro Devices Inc., Amazon Web Services, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung, and Xilinx. among others.

Q6. What are the factors driving the Deep Learning Market growth?

Ans. The major factors driving the growth of the market are the rapid adoption of cloud-based technology across several industries is fueling the growth of the market.

Q7. What are the key growth strategies of Deep Learning Market players?

Ans. The key growth strategies of Deep Learning Market players are product launch and product approval.

Q8. Which region will provide more business opportunities for the Deep Learning Market during the forecast period?

Ans. The Asia-Pacific region will provide more business opportunities for the Deep Learning Market during the forecast period.

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