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Deep Learning Processor Market by Type (GPU, ASIC, CPU, and FPGA), Technology (System-on-chip (SIC), System-in-package (SIP), Multi-chip Module, and Others), and End User (Consumer Electronics, HealthCare, Automotive, Industrial, and Others): Global Opportunity Analysis and Industry Forecast, 2021–2030

A12135
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Sep 2021 | 107 Views
   
Author(s) : Vijay Poola
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COVID-19

Pandemic disrupted the entire world and affected many industries.

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Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy. Deep learning drives many artificial intelligence (AI) applications and services that improve automation, performing analytical and physical tasks without human intervention.

The deep learning processor market share is segmented on the basis of type, technology, end user, and region. Based on type, the market is bifurcated into GPU, ASIC, CPU, and FPGA. By technology, it is categorized into System-on-chip (SIC), System-in-package (SIP), Multi-chip Module, and others. By end user, it is categorized into consumer electronics, healthcare, automotive, industrial, and others. Based on region, the market is analyzed across North America (the U.S. and Canada), Europe (Germany, the UK, France, and Rest of Europe), Asia-Pacific (China, Japan, India, and Rest of Asia-Pacific), and LAMEA (Latin America, Middle East, and Africa).

Key players operating in the deep learning processor market include Microsoft Corporation, Google LLC, Intel Corporation, Oracle Corporation, Amazon Web Services Inc., Salesforce.com, Inc., SAP SE, Zest AI, IBM, DataRobot Inc., and Accenture. These players adopt collaboration, partnership, and agreement as their key developmental strategies to increase revenue of the deep learning processor industry and develop new products for enhancing product portfolio.

COVID-19 Scenario Analysis

The COVID-19 pandemic has impacted the society and overall economy across the globe. The impact of this outbreak is growing day-by-day as well as affecting the supply chain. It is creating uncertainty in the stock market, declining the business confidence, slowing down supply chain, and increasing panic among customers. European countries under lockdowns have suffered a major loss of business and revenue due to shutdown of manufacturing units in the region. The impact of the pandemic can be easily observed from the less demand of consumer electronics like gaming phones, laptops etc. which use deep learning processor.

In response of COVID-19's long-term implications, governments are attempting to address the problem by enacting beneficial initiatives and policies such as financial packages, lower interest rates, and tax exemptions. Significant growth in the deep learning processors can be expected during the forecast period once the lockdown is be over and the production rate is anticipated come to its previous pace.

Top Impacting Factors: Market Scenario Analysis, Trends, Drivers, and Impact Analysis

The market for deep learning processors is experiencing growth due to reasons such as the expansion in the volume of big data and the growth in popularity of artificial intelligence &machine learning. AI is being used in a variety of industries, which has fueled the need for deep learning processors. As more data is created from many technical sources, the demand for faster and more advanced deep learning computers for faster processing is expanding. The growth in interest in quantum computing presents a huge chance for the deep learning processor market to grow. Increased investments in smart homes and smart city initiatives in many nations would result in a surge in the usage of deep learning processors, which is expected to boost market growth in the near future.

The absence of a competent workforce has limited the market expansion of deep learning processors. A worker with the ability to process or carry out sophisticated algorithms for AI development is required to handle deep learning software and its applications. Furthermore, AI and automated systems can be challenging to control at times.

The Global Deep Learning Processor Market Trends

Increase in the Demand for GPU

By chip type, GPUs (graphics processing units) account for a large market share. It is becoming more popular for gaming and watching videos. However, as technology advances, GPUs are now mostly utilized for high-resolution images and artificial intelligence (AI). Due to the widespread usage of low-power technology, demand has increased. Because of the growth in use of quantum computing systems, the CPU chip category is expected to increase at a significant CAGR throughout the projection period. Due to its capacity to perform complicated algorithms in the shortest time feasible, quantum computing is increasingly being adopted by large multinational and information technology businesses, favorably boosting the deep learning processor market.

Rapid Development in Use of Consumer Electronics

The consumer electronics industry makes extensive use of deep learning processors. The market for better gadgets with improved applications is growing in response to technological advancements. The market for deep learning processors is developing as artificial intelligence and machine learning become more widely used in this sector. Machine learning chips are being used in smartphones to increase features and maximize capabilities such as a quicker CPU and better multitasking ability. AI applications are increasingly being implemented in smartphones and tablets to improve user interface and customer experience, driving up demand for deep learning processors. New devices with advanced technologies are being introduced for areas such as healthcare and communication and technology, which heavily rely on deep learning processors for faster work and improved efficiency. Deep learning processors are increasingly being used in this industry to improve customer experience through AI and augmented reality, which is driving the growth of the deep learning processor market.

Market Scope and Structure Analysis

Report Metric

Details

 Market Size Available for Years

 2020–2030

 Base Year Considered

 2020

 Forecast Period

 2021–2030

 Forecast Units

 Value (USD)

 Segments Covered

 Type, Technology, End User, and Region

 Regions Covered

North America (U.S., Canada, and Mexico), Europe (Germany, UK, France, Italy, and the rest of Europe), Asia-Pacific (China, Japan, India, South Korea, and the rest of Asia-Pacific), LAMEA (Latin America, Middle East, and Africa)

 Companies Covered

NVIDIA, Intel, IBM, CEVA, KnuEdge, AMD, Google, TeraDeep, BrainChip, and Wave Computing.

 

Key Benefits of the Report

  • This study presents the analytical depiction of the global deep learning processor industry along with the current trends and future estimations to determine the imminent investment pockets.
  • The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the deep learning processor market share.
  • The current market is quantitatively analyzed from 2020 to 2030 to highlight the growth scenario of the deep learning processor industry.
  • Porter’s five forces analysis illustrates the potency of buyers and suppliers in the market.
  • The report provides a detailed deep learning processor market analysis based on competitive intensity and how the competition will take shape in coming years.

Key Segments Covered

Segments

Subsegments

 Type

  • GPU
  • ASIC
  • CPU
  • FPGA

 Technology

  • System-on-chip (SIC)
  • System-in-package (SIP)
  • Multi-chip Module
  • Others

 End User

  • Consumer Electronics
  • Healthcare
  • Automotive
  • Industrial
  • Others

 

Questions Answered in the Deep Learning Processor Market Research Report

  • Which are the leading players active in the deep learning processor market?
  • What are the current trends that will influence the market in the next few years?
  • What are the driving factors, restraints, and opportunities in the deep learning processor market?
  • What are the projections for the future that would help in taking further strategic steps?
 
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