Deep Learning Chip Market Segmented by Top Manufacturers - AMD (Advanced Micro Devices), Google, Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx, Samsung

The report is a comprehensive exploration of global Deep Learning Chip market offering growth rates, size of the industry, competitive landscape information, factors to the contributing growth of the global Deep Learning Chip market and more.

Deep Learning Chip market is a new nomenclature for the artificial neural networks technology. This technology is a computer program, which is similar to a biological brain. The brain is made up of billions of cells known as neurons, which are connected with the help of pathways called synapses. New observations and experiences alter the strength of these synaptic connections. With these new collections of observations and experience, the strength of the connections results in the learning. Deep learning transforms these structures into a software with digital versions of neurons, synapses, and connection strengths. By feeding the experience and observations to an artificial neural network and adjusting the weights accordingly, a neural network learns complex functions similar to the biological brain.

The global deep learning chip market has witnessed significant growth over the years, owing to increase in efforts to make more human-like robots and rise in rate of deployments in the developing regions.

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The global deep learning chip market is segmented based on chip type, industry vertical, technology, and geography. On the basis of chip type, the market is categorized into graphics processing unit (GPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), central processing unit (CPU), and others. System-on-chip, system-in-package, multi-chip module, and others are the technologies considered. The various industry verticals are media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and others.

Geographically, the market is sub-segmented into North America, Europe, Asia-Pacific, and LAMEA.

The key players profiled in the report include AMD (Advanced Micro Devices), Google, Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx, Samsung.

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KEY BENEFITS FOR STAKEHOLDERS

This study comprises an analytical depiction of the global deep learning chip market with current trends and future estimations to depict the imminent investment pockets.

The overall market potential is determined to understand the profitable trends to gain a stronger coverage in the market.

The report presents information related to key drivers, restraints, and opportunities with a detailed impact analysis.

The current market is quantitatively analyzed from 2017 to 2025 to highlight the financial competency of the market.

Porter’s Five Forces analysis illustrates the potency of the buyers and suppliers.

BY CHIP TYPE

GPU

ASIC

FPGA

CPU

Others

BY TECHNOLOGY

System-on-chip (SoC)

System-in-package (SIP)

Multi-chip module

Others

BY INDUSTRY VERTICAL

Media & advertising

BFSI

IT & telecom

Retail

Healthcare

Automotive & transportation

Others

Table of content:

CHAPTER 1: INTRODUCTION

1.1. REPORT DESCRIPTION

1.2. KEY BENEFITS FOR STAKEHOLDERS

1.3. KEY MARKET SEGMENTS

1.4. RESEARCH METHODOLOGY

1.4.1. Primary research

1.4.2. Secondary research

1.4.3. Analyst tools and models

CHAPTER 2: EXECUTIVE SUMMARY

2.1. CXO PERSPECTIVE

CHAPTER 3: MARKET OVERVIEW

3.1. MARKET DEFINITION AND SCOPE

3.2. KEY FINDINGS

3.2.1. Top impacting factors

3.2.2. Top investment pockets

3.2.3. Top winning strategies

3.3. PORTERS FIVE FORCES ANALYSIS

3.3.1. Moderate-to-high bargaining power of suppliers

3.3.2. Moderate-to-high threat of new entrants

3.3.3. Low-to-Moderate threat of substitutes

3.3.4. High-to-moderate intensity of rivalry

3.3.5. High-to-moderate bargaining power of buyers

3.4. MARKET SHARE ANALYSIS (2017)

3.5. MARKET DYNAMICS

3.5.1. Drivers

3.5.1.1. Increase in demand for smart homes & smart cities

3.5.1.2. Rise in investments in AI startups

3.5.1.3. Emergence of quantum computing

3.5.1.4. Growth in number of AI applications

3.5.2. Restraints

3.5.2.1. Dearth of skilled workforce

3.5.3. Opportunities

3.5.3.1. Increased adoption of deep learning chips in the developing regions

3.5.3.2. Development of smarter robots

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