Machine Learning Chip Market by Top Players – AMD (Advanced Micro Devices), Google, Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx, Samsung

Machine Learning Chip Market by Chip Type (GPU, ASIC, FPGA, CPU, and Others), Technology (System-on-chip, System-in-package, Multi-chip module, and Others), and Industry Vertical (Media & Advertising, BFSI, IT & Telecom, Retail, Healthcare, Automotive & Transportation, and Others) - Global Opportunity Analysis and Industry Forecast, 2018-2025

Machine learning is derived from the field of artificial intelligence (AI), which uses algorithm to find out natural patterns in data for the development of computers. This data is used to take better decisions and make predictions in applications, such as stock trading, medicals, machine load forecasting, and others. For instance, many media sites depend on machine learning technology for the best recommendations of songs and movies from millions of options. Furthermore, retail industries also use this technology to predict purchasing behavior of their customers. The machine learning technology is widely adopted for the applications, such as image processing, face detections, motion & object detections, and others. In addition, it can also be implemented in computation biology for tumor detection and DNA sequencing. Furthermore, machine learning can be used for prediction of maintenance in automotive, manufacturing, and aerospace industries.

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The machine learning chip market has witnessed significant growth over the years, owing to increase in big data in various fields and rise in rate of deployments in the developing regions.

The global machine learning chip market is segmented based on chip type, industry vertical, technology, and geography. Based on 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. Based on technology, the market is segmented as system-on-chip, system-in-package, multi-chip module, and others. Based on industry vertical, it is divided into media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and others.

Based on region, the market is analyzed across 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.

KEY BENEFITS FOR STAKEHOLDERS

This study comprises an analytical depiction of the global machine 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 strong foothold 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.
Porters five forces analysis illustrates the potency of the buyers and suppliers.
KEY MARKET SEGMENTS

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
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Table of Content:

CHAPTER 1: INTRODUCTION

1.1. REPORT DESCRIPTION

1.2. KEY MARKET SEGMENTS

1.3. RESEARCH METHODOLOGY

1.3.1. Primary research

1.3.2. Secondary research

1.3.3. 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. Emergence of quantum computing

3.5.1.2 Growth in number of machine learning applications

3.5.1.3 Trending Artificial Intelligence (AI)

3.5.2. Restraints

3.5.2.1 Dearth of skilled workforce

3.5.2.2 AI Phobia

3.5.3. Opportunities

3.5.3.1 Increase in demand for smart homes & smart cities

3.5.3.2 Increase in efforts to make more human-like robots

3.5.3.3 Popularity of IoT across the globe

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