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Global Deep Learning Chipset Market, by Type, by Technology, by End User, by Region, Industry Analysis and Forecast, 2019 - 2025

  • ID: 5006133
  • Report
  • February 2020
  • Region: Global
  • 316 pages
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
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FEATURED COMPANIES

  • Google, Inc.
  • IBM Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Nvidia Corporation
  • Qualcomm, Inc.
  • MORE
The Global Deep Learning Chipset Market size is expected to reach $24.5 billion by 2025, rising at a market growth of 37% CAGR during the forecast period. Deep learning chips are customized Silicon chips that integrate AI technology and machine learning. Deep learning and machine learning, which are the sub-sets of Artificial Intelligence (AI) sub-sets, are used in carrying out AI related tasks. Deep learning technology has entered many industries around the world and is accomplished through applications like computer vision, speech synthesis, voice recognition, machine translation, drug discovery, game play, and robotics.

The widespread adoption of artificial intelligence (AI) for practical business applications has brought in a range of complexities and risk factors in virtually every industry, but one thing is certain: in today's AI industry, hardware is the key to solving many of the main problems facing the sector, and chipsets are at the heart of that hardware solution. Considering AI's widespread applicability, it's almost certain that every chip will have some kind of AI system embedded in future. The engine could make a wide range of forms, from a basic AI library running on a CPU to more complex, custom hardware. The potential for AI is better fulfilled when the chipsets are designed to provide the adequate amount of computing capacity for different AI applications at the right power budget. This is a trend that leads to increased specialization and diversifying of AI-optimized chipsets.

The factors influencing the development of the deep learning chipset market are increased acceptance of cloud-based technology and profound use of learning in big data analytics. A single-chip processor generates lighting effects and transforms objects each time a 3D scene is redrawn, or a graphic processing unit turns out to be very meaningful and efficient when applied to computation styles needed for neural nets. This in turn fuels the growth of the market for deep learning chipsets.

Based on type, the market is segmented into GPU, ASIC, CPU, FPGA and Others. Based on Technology, the market is segmented into System-on-chip (SoC), System-in-package (SIP) and Multi-chip module & Others. Based on End User, the market is segmented into Consumer Electronics, Industrial, Aerospace & Defense, Healthcare, Automotive and Others. Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa.

The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix, Google, Inc., Microsoft Corporation, Samsung Electronics Co., Ltd., Intel Corporation, Amazon.com, Inc., and IBM Corporation are some of the forerunners in the Deep Learning Chipset Market. Companies such as Advanced Micro Devices, Inc., Qualcomm, Inc., Nvidia Corporation, and Xilinx, Inc. are some of the key innovators in Deep Learning Chipset Market. The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Samsung Electronics Co., Ltd. (Samsung Group), Microsoft Corporation, Intel Corporation, Nvidia Corporation, IBM Corporation, Google, Inc., Amazon.com, Inc. (Amazon Web Services), Qualcomm, Inc., Advanced Micro Devices, Inc., and Xilinx, Inc.

Recent strategies deployed in Deep Learning Chipset Market

Partnerships, Collaborations, and Agreements:

Jan-2020: Xilinx collaborated with Telechips, a leading Automotive System on Chip (SoC) supplier. The collaboration is expected to provide a comprehensive solution for addressing the integration of in-cabin monitoring systems (ICMS) and IVI systems.
Dec-2019: Samsung Electronics teamed up with Baidu, a leading Chinese-language Internet search provider. Under the collaboration, the companies announced that the development of Baidu KUNLUN, its first cloud-to-edge AI accelerator has been completed. KUNLUN chip provides 512 gigabytes per second (Gbps) memory bandwidth and offers up to 260 Tera operations per second (TOPS) at 150 watts.

Oct-2019: Microsoft announced technology collaboration with Nvidia, a technology company. The collaboration was focused on intelligent edge computing, which is designed for helping the industries in gaining and managing the insights from the data created by warehouses, retail stores, manufacturing facilities, urban infrastructure, connected buildings, and other environments.

Oct-2019: Microsoft launched Lakefield, a dual-screen device powered by Intel’s unique processor. This device combines a hybrid CPU with Intel’s Foveros 3D packaging technology. This provides more flexibility to device makers for innovating designs, experience, and form factor.

Jun-2019: AMD came into partnership with Samsung following which, the former company is licensing its graphics technology to Samsung for use in future mobile chips. Under this partnership, Samsung paid AMD for getting access to its RDNA graphics architecture.

Jun-2019: Nvidia collaborated with Volvo for developing artificial intelligence that is used in self-driving trucks.

May-2019: Samsung Electronics came into partnership with Efinix, an innovator in programmable product platforms and technologies. Under this partnership, the companies were aimed at developing Quantum eFPGAs on Samsung’s 10nm silicon process.

Dec-2018: IBM extended its partnership with Samsung for developing 7-nanometer (nm) microprocessors for IBM Power Systems, LinuxONE, and IBM Z. The expansion was aimed at driving the performance of the unmatched system including encryption and compression speed, acceleration, memory, and I/O bandwidth, as well as system scaling.

Jun-2018: AWS announced its collaboration with Cadence Design Systems. The collaboration was aimed at delivering a Cadence Cloud portfolio to electronic systems and semiconductor design.

Mar-2018: Nvidia came into partnership with Arm for bringing deep learning interface to billions of consumer electronics, mobile, and Internet of Things devices.

Acquisition and Mergers:

Aug-2019: Xilinx took over Solarflare, a provider of high-performance, low latency networking solutions. The acquisition helped in generating more revenues and enabled new marketing and R&D funds for the future.

Apr-2019: Intel completed the acquisition of Omnitek, a provider of video and vision field-programmable gate array (FPGA). Through the acquisition, the FPGA processor business of the company has been doubled.

Jul-2018: Intel took over eASIC, a fabless semiconductor company. The acquisition bolstered the company's business in providing chips.

Apr-2017: AMD acquired Nitero, a company engaged in providing technology to connect VR headsets wirelessly to PCs. The acquisition helped the company in getting control over VR experiences.

Product Launches and Product Expansions:

Dec-2019: Nvidia launched Drive AGX Orin, a new Orin AI processor or system-on-chip (SoC). This processor improves power efficiency and performance. This processor is used in evolving the automotive business.

Dec-2019: AWS unveiled Graviton2, the next-generation of its ARM processors. It is a custom chip that is designed with 7nm architecture and based on 64-bit ARM Neoverse cores.

Nov-2019: AMD launched two new Threadripper 3 CPUs with 24 and 32 cores. Both these CPUs will be integrated into AMD’s new TRX40 platform using the new sTRX4 socket.

Nov-2019: Intel unveiled Ponte Vecchio GPUs, a graphics processing unit (GPU) architecture. This chip was designed for handling the artificial intelligence loads and heavy data in the data center.
Nov-2019: Intel launched Stratix 10 GX 10M, a new FPGA. This consists of two large FPGA dies and four transceiver tiles and has a total of 10.2 million logic elements and 2304 user I/O pins.

Oct-2018: Google launched TensorFlow, the popular open-source artificial intelligence framework. This framework runs deep learning, machine learning, and other predictive and statistical analytics workloads. This simplifies training models, the process of acquiring data, refining future results, and serving predictions.

Sep-2019: AWS released Amazon EC2 G4 GPU-powered Amazon Elastic Compute Cloud (Amazon EC2) instances. It delivers up to 1.8 TB of local NVMe storage and up to 100 Gbps of networking throughput to AWS custom Intel Cascade Lake CPUs and NVIDIA T4 GPUs.

Aug-2019: Xilinx released Virtex UltraScale+ VU19P, a 16nm device with 35 billion transistors. It has four chips on an interposer. It is the world's largest field-programmable gate array (FPGA) and has 9 million logic cells.

May-2019: Nvidia introduced NVIDIA EGX, an accelerated computing platform. This platform was aimed at allowing the companies in performing low-latency AI at the edge for perceiving, understanding, and acting in real-time on continuous streaming data between warehouses, factories, 5G base stations, and retail stores.

Nov-2018: AWS introduced Inferentia and Elastic Inference, two chips and 13 machine learning capabilities and services. Through these launches, the company aimed towards attracting more developers.

Sep-2018: Qualcomm unveiled Snapdragon Wear 3100 chipset. This chipset is used in smartwatches and has extended battery life.

Aug-2018: AMD introduced B450 chipset for Ryzen processors. The chip runs about 2 watts lower in power than B350 chipset.
Jul-2018: Google introduced Tensor Processing Units or TPUs, the specialized chips. This chip lives in data centers of the company and simplifies the AI tasks. These chips are used in enterprise jobs.

Apr-2018: Qualcomm launched QCS605 and QCS603 SoCs, two new system-on-chips. These chips combine image signal processor, CPU, AI, GPU technology for accommodating several camera applications, smart displays, and robotics.

Scope of the Study

Market Segmentation:

By Compute Capacity
  • High
  • Low
By Type
  • GPU
  • ASIC
  • CPU
  • FPGA
  • Others
By Technology
  • System-on-chip (SoC)
  • System-in-package (SIP)
  • Multi-chip module & Others
By End User
  • Consumer Electronics
  • Industrial
  • Aerospace & Defense
  • Healthcare
  • Automotive
  • Others
By Geography

North America
  • US
  • Canada
  • Mexico
  • Rest of North America
Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA
Companies Profiled
  • Samsung Electronics Co., Ltd. (Samsung Group)
  • Microsoft Corporation
  • Intel Corporation
  • Nvidia Corporation
  • IBM Corporation
  • Google, Inc.
  • Amazon.com, Inc. (Amazon Web Services)
  • Qualcomm, Inc.
  • Advanced Micro Devices, Inc.
  • Xilinx, Inc.
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FEATURED COMPANIES

  • Google, Inc.
  • IBM Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Nvidia Corporation
  • Qualcomm, Inc.
  • MORE
Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Deep Learning Chipset Market, by Compute Capacity
1.4.2 Global Deep Learning Chipset Market, by Type
1.4.3 Global Deep Learning Chipset Market, by Technology
1.4.4 Global Deep Learning Chipset Market, by End User
1.4.5 Global Deep Learning Chipset Market, by Geography
1.5 Methodology for the research

Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.2 Executive Summary
2.1.3 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints

Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Mergers & Acquisitions
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2015-2019)
3.3.2 Key Strategic Move: (Product Launches and Product Expansions : 2019-Dec - 2017-Aug) Leading Players

Chapter 4. Global Deep Learning Chipset Market by Compute Capacity
4.1 Global Deep Learning Chipset High Market by Region
4.2 Global Deep Learning Chipset Low Market by Region

Chapter 5. Global Deep Learning Chipset Market by Type
5.1 Global GPU Deep Learning Chipset Market by Region
5.2 Global ASIC Deep Learning Chipset Market by Region
5.3 Global CPU Deep Learning Chipset Market by Region
5.4 Global FPGA Deep Learning Chipset Market by Region
5.5 Global Other Type Deep Learning Chipset Market by Region

Chapter 6. Global Deep Learning Chipset Market by Technology
6.1 Global Deep Learning Chipset System-on-chip (SoC) Market by Region
6.2 Global Deep Learning Chipset System-in-package (SIP) Market by Region
6.3 Global Deep Learning Chipset Multi-chip module & Others Market by Region

Chapter 7. Global Deep Learning Chipset Market by Industry Vertical
7.1 Global Consumer Electronics Deep Learning Chipset Market by Region
7.2 Global Industrial Deep Learning Chipset Market by Region
7.3 Global Aerospace & Defense Deep Learning Chipset Market by Region
7.4 Global Healthcare Deep Learning Chipset Market by Region
7.5 Global Automotive Deep Learning Chipset Market by Region
7.6 Global Others Deep Learning Chipset Market by Region

Chapter 8. Global Deep Learning Chipset Market by Region
8.1 North America Deep Learning Chipset Market
8.1.1 North America Deep Learning Chipset Market by Compute Capacity
8.1.1.1 North America Deep Learning Chipset High Market by Country
8.1.1.2 North America Deep Learning Chipset Low Market by Country
8.1.2 North America Deep Learning Chipset Market by Type
8.1.2.1 North America GPU Deep Learning Chipset Market by Country
8.1.2.2 North America ASIC Deep Learning Chipset Market by Country
8.1.2.3 North America CPU Deep Learning Chipset Market by Country
8.1.2.4 North America FPGA Deep Learning Chipset Market by Country
8.1.2.5 North America Other Type Deep Learning Chipset Market by Country
8.1.3 North America Deep Learning Chipset Market by Technology
8.1.3.1 North America Deep Learning Chipset System-on-chip (SoC) Market by Country
8.1.3.2 North America Deep Learning Chipset System-in-package (SIP) Market by Country
8.1.3.3 North America Deep Learning Chipset Multi-chip module & Others Market by Country
8.1.4 North America Deep Learning Chipset Market by Industry Vertical
8.1.4.1 North America Consumer Electronics Deep Learning Chipset Market by Country
8.1.4.2 North America Industrial Deep Learning Chipset Market by Country
8.1.4.3 North America Aerospace & Defense Deep Learning Chipset Market by Country
8.1.4.4 North America Healthcare Deep Learning Chipset Market by Country
8.1.4.5 North America Automotive Deep Learning Chipset Market by Country
8.1.4.6 North America Others Deep Learning Chipset Market by Country
8.1.5 North America Deep Learning Chipset Market by Country
8.1.5.1 US Deep Learning Chipset Market
8.1.5.1.1 US Deep Learning Chipset Market by Compute Capacity
8.1.5.1.2 US Deep Learning Chipset Market by Type
8.1.5.1.3 US Deep Learning Chipset Market by Technology
8.1.5.1.4 US Deep Learning Chipset Market by Industry Vertical
8.1.5.2 Canada Deep Learning Chipset Market
8.1.5.2.1 Canada Deep Learning Chipset Market by Compute Capacity
8.1.5.2.2 Canada Deep Learning Chipset Market by Type
8.1.5.2.3 Canada Deep Learning Chipset Market by Technology
8.1.5.2.4 Canada Deep Learning Chipset Market by Industry Vertical
8.1.5.3 Mexico Deep Learning Chipset Market
8.1.5.3.1 Mexico Deep Learning Chipset Market by Compute Capacity
8.1.5.3.2 Mexico Deep Learning Chipset Market by Type
8.1.5.3.3 Mexico Deep Learning Chipset Market by Technology
8.1.5.3.4 Mexico Deep Learning Chipset Market by Industry Vertical
8.1.5.4 Rest of North America Deep Learning Chipset Market
8.1.5.4.1 Rest of North America Deep Learning Chipset Market by Compute Capacity
8.1.5.4.2 Rest of North America Deep Learning Chipset Market by Type
8.1.5.4.3 Rest of North America Deep Learning Chipset Market by Technology
8.1.5.4.4 Rest of North America Deep Learning Chipset Market by Industry Vertical
8.2 Europe Deep Learning Chipset Market
8.2.1 Europe Deep Learning Chipset Market by Compute Capacity
8.2.1.1 Europe Deep Learning Chipset High Market by Country
8.2.1.2 Europe Deep Learning Chipset Low Market by Country
8.2.2 Europe Deep Learning Chipset Market by Type
8.2.2.1 Europe GPU Deep Learning Chipset Market by Country
8.2.2.2 Europe ASIC Deep Learning Chipset Market by Country
8.2.2.3 Europe CPU Deep Learning Chipset Market by Country
8.2.2.4 Europe FPGA Deep Learning Chipset Market by Country
8.2.2.5 Europe Other Type Deep Learning Chipset Market by Country
8.2.3 Europe Deep Learning Chipset Market by Technology
8.2.3.1 Europe Deep Learning Chipset System-on-chip (SoC) Market by Country
8.2.3.2 Europe Deep Learning Chipset System-in-package (SIP) Market by Country
8.2.3.3 Europe Deep Learning Chipset Multi-chip module & Others Market by Country
8.2.4 Europe Deep Learning Chipset Market by Industry Vertical
8.2.4.1 Europe Consumer Electronics Deep Learning Chipset Market by Country
8.2.4.2 Europe Industrial Deep Learning Chipset Market by Country
8.2.4.3 Europe Aerospace & Defense Deep Learning Chipset Market by Country
8.2.4.4 Europe Healthcare Deep Learning Chipset Market by Country
8.2.4.5 Europe Automotive Deep Learning Chipset Market by Country
8.2.4.6 Europe Others Deep Learning Chipset Market by Country
8.2.5 Europe Deep Learning Chipset Market by Country
8.2.5.1 Germany Deep Learning Chipset Market
8.2.5.1.1 Germany Deep Learning Chipset Market by Compute Capacity
8.2.5.1.2 Germany Deep Learning Chipset Market by Type
8.2.5.1.3 Germany Deep Learning Chipset Market by Technology
8.2.5.1.4 Germany Deep Learning Chipset Market by Industry Vertical
8.2.5.2 UK Deep Learning Chipset Market
8.2.5.2.1 UK Deep Learning Chipset Market by Compute Capacity
8.2.5.2.2 UK Deep Learning Chipset Market by Type
8.2.5.2.3 UK Deep Learning Chipset Market by Technology
8.2.5.2.4 UK Deep Learning Chipset Market by Industry Vertical
8.2.5.3 France Deep Learning Chipset Market
8.2.5.3.1 France Deep Learning Chipset Market by Compute Capacity
8.2.5.3.2 France Deep Learning Chipset Market by Type
8.2.5.3.3 France Deep Learning Chipset Market by Technology
8.2.5.3.4 France Deep Learning Chipset Market by Industry Vertical
8.2.5.4 Russia Deep Learning Chipset Market
8.2.5.4.1 Russia Deep Learning Chipset Market by Compute Capacity
8.2.5.4.2 Russia Deep Learning Chipset Market by Type
8.2.5.4.3 Russia Deep Learning Chipset Market by Technology
8.2.5.4.4 Russia Deep Learning Chipset Market by Industry Vertical
8.2.5.5 Spain Deep Learning Chipset Market
8.2.5.5.1 Spain Deep Learning Chipset Market by Compute Capacity
8.2.5.5.2 Spain Deep Learning Chipset Market by Type
8.2.5.5.3 Spain Deep Learning Chipset Market by Technology
8.2.5.5.4 Spain Deep Learning Chipset Market by Industry Vertical
8.2.5.6 Italy Deep Learning Chipset Market
8.2.5.6.1 Italy Deep Learning Chipset Market by Compute Capacity
8.2.5.6.2 Italy Deep Learning Chipset Market by Type
8.2.5.6.3 Italy Deep Learning Chipset Market by Technology
8.2.5.6.4 Italy Deep Learning Chipset Market by Industry Vertical
8.2.5.7 Rest of Europe Deep Learning Chipset Market
8.2.5.7.1 Rest of Europe Deep Learning Chipset Market by Compute Capacity
8.2.5.7.2 Rest of Europe Deep Learning Chipset Market by Type
8.2.5.7.3 Rest of Europe Deep Learning Chipset Market by Technology
8.2.5.7.4 Rest of Europe Deep Learning Chipset Market by Industry Vertical
8.3 Asia Pacific Deep Learning Chipset Market
8.3.1 Asia Pacific Deep Learning Chipset Market by Compute Capacity
8.3.1.1 Asia Pacific Deep Learning Chipset High Market by Country
8.3.1.2 Asia Pacific Deep Learning Chipset Low Market by Country
8.3.2 Asia Pacific Deep Learning Chipset Market by Type
8.3.2.1 Asia Pacific GPU Deep Learning Chipset Market by Country
8.3.2.2 Asia Pacific ASIC Deep Learning Chipset Market by Country
8.3.2.3 Asia Pacific CPU Deep Learning Chipset Market by Country
8.3.2.4 Asia Pacific FPGA Deep Learning Chipset Market by Country
8.3.2.5 Asia Pacific Other Type Deep Learning Chipset Market by Country
8.3.3 Asia Pacific Deep Learning Chipset Market by Technology
8.3.3.1 Asia Pacific Deep Learning Chipset System-on-chip (SoC) Market by Country
8.3.3.2 Asia Pacific Deep Learning Chipset System-in-package (SIP) Market by Country
8.3.3.3 Asia Pacific Deep Learning Chipset Multi-chip module & Others Market by Country
8.3.4 Asia Pacific Deep Learning Chipset Market by Industry Vertical
8.3.4.1 Asia Pacific Consumer Electronics Deep Learning Chipset Market by Country
8.3.4.2 Asia Pacific Industrial Deep Learning Chipset Market by Country
8.3.4.3 Asia Pacific Aerospace & Defense Deep Learning Chipset Market by Country
8.3.4.4 Asia Pacific Healthcare Deep Learning Chipset Market by Country
8.3.4.5 Asia Pacific Automotive Deep Learning Chipset Market by Country
8.3.4.6 Asia Pacific Others Deep Learning Chipset Market by Country
8.3.5 Asia Pacific Deep Learning Chipset Market by Country
8.3.5.1 China Deep Learning Chipset Market
8.3.5.1.1 China Deep Learning Chipset Market by Compute Capacity
8.3.5.1.2 China Deep Learning Chipset Market by Type
8.3.5.1.3 China Deep Learning Chipset Market by Technology
8.3.5.1.4 China Deep Learning Chipset Market by Industry Vertical
8.3.5.2 Japan Deep Learning Chipset Market
8.3.5.2.1 Japan Deep Learning Chipset Market by Compute Capacity
8.3.5.2.2 Japan Deep Learning Chipset Market by Type
8.3.5.2.3 Japan Deep Learning Chipset Market by Technology
8.3.5.2.4 Japan Deep Learning Chipset Market by Industry Vertical
8.3.5.3 India Deep Learning Chipset Market
8.3.5.3.1 India Deep Learning Chipset Market by Compute Capacity
8.3.5.3.2 India Deep Learning Chipset Market by Type
8.3.5.3.3 India Deep Learning Chipset Market by Technology
8.3.5.3.4 India Deep Learning Chipset Market by Industry Vertical
8.3.5.4 South Korea Deep Learning Chipset Market
8.3.5.4.1 South Korea Deep Learning Chipset Market by Compute Capacity
8.3.5.4.2 South Korea Deep Learning Chipset Market by Type
8.3.5.4.3 South Korea Deep Learning Chipset Market by Technology
8.3.5.4.4 South Korea Deep Learning Chipset Market by Industry Vertical
8.3.5.5 Singapore Deep Learning Chipset Market
8.3.5.5.1 Singapore Deep Learning Chipset Market by Compute Capacity
8.3.5.5.2 Singapore Deep Learning Chipset Market by Type
8.3.5.5.3 Singapore Deep Learning Chipset Market by Technology
8.3.5.5.4 Singapore Deep Learning Chipset Market by Industry Vertical
8.3.5.6 Malaysia Deep Learning Chipset Market
8.3.5.6.1 Malaysia Deep Learning Chipset Market by Compute Capacity
8.3.5.6.2 Malaysia Deep Learning Chipset Market by Type
8.3.5.6.3 Malaysia Deep Learning Chipset Market by Technology
8.3.5.6.4 Malaysia Deep Learning Chipset Market by Industry Vertical
8.3.5.7 Rest of Asia Pacific Deep Learning Chipset Market
8.3.5.7.1 Rest of Asia Pacific Deep Learning Chipset Market by Compute Capacity
8.3.5.7.2 Rest of Asia Pacific Deep Learning Chipset Market by Type
8.3.5.7.3 Rest of Asia Pacific Deep Learning Chipset Market by Technology
8.3.5.7.4 Rest of Asia Pacific Deep Learning Chipset Market by Industry Vertical
8.4 LAMEA Deep Learning Chipset Market
8.4.1 LAMEA Deep Learning Chipset Market by Compute Capacity
8.4.1.1 LAMEA Deep Learning Chipset High Market by Country
8.4.1.2 LAMEA Deep Learning Chipset Low Market by Country
8.4.2 LAMEA Deep Learning Chipset Market by Type
8.4.2.1 LAMEA GPU Deep Learning Chipset Market by Country
8.4.2.2 LAMEA ASIC Deep Learning Chipset Market by Country
8.4.2.3 LAMEA CPU Deep Learning Chipset Market by Country
8.4.2.4 LAMEA FPGA Deep Learning Chipset Market by Country
8.4.2.5 LAMEA Other Type Deep Learning Chipset Market by Country
8.4.3 LAMEA Deep Learning Chipset Market by Technology
8.4.3.1 LAMEA Deep Learning Chipset System-on-chip (SoC) Market by Country
8.4.3.2 LAMEA Deep Learning Chipset System-in-package (SIP) Market by Country
8.4.3.3 LAMEA Deep Learning Chipset Multi-chip module & Others Market by Country
8.4.4 LAMEA Deep Learning Chipset Market by Industry Vertical
8.4.4.1 LAMEA Consumer Electronics Deep Learning Chipset Market by Country
8.4.4.2 LAMEA Industrial Deep Learning Chipset Market by Country
8.4.4.3 LAMEA Aerospace & Defense Deep Learning Chipset Market by Country
8.4.4.4 LAMEA Healthcare Deep Learning Chipset Market by Country
8.4.4.5 LAMEA Automotive Deep Learning Chipset Market by Country
8.4.4.6 LAMEA Others Deep Learning Chipset Market by Country
8.4.5 LAMEA Deep Learning Chipset Market by Country
8.4.5.1 Brazil Deep Learning Chipset Market
8.4.5.1.1 Brazil Deep Learning Chipset Market by Compute Capacity
8.4.5.1.2 Brazil Deep Learning Chipset Market by Type
8.4.5.1.3 Brazil Deep Learning Chipset Market by Technology
8.4.5.1.4 Brazil Deep Learning Chipset Market by Industry Vertical
8.4.5.2 Argentina Deep Learning Chipset Market
8.4.5.2.1 Argentina Deep Learning Chipset Market by Compute Capacity
8.4.5.2.2 Argentina Deep Learning Chipset Market by Type
8.4.5.2.3 Argentina Deep Learning Chipset Market by Technology
8.4.5.2.4 Argentina Deep Learning Chipset Market by Industry Vertical
8.4.5.3 UAE Deep Learning Chipset Market
8.4.5.3.1 UAE Deep Learning Chipset Market by Compute Capacity
8.4.5.3.2 UAE Deep Learning Chipset Market by Type
8.4.5.3.3 UAE Deep Learning Chipset Market by Technology
8.4.5.3.4 UAE Deep Learning Chipset Market by Industry Vertical
8.4.5.4 Saudi Arabia Deep Learning Chipset Market
8.4.5.4.1 Saudi Arabia Deep Learning Chipset Market by Compute Capacity
8.4.5.4.2 Saudi Arabia Deep Learning Chipset Market by Type
8.4.5.4.3 Saudi Arabia Deep Learning Chipset Market by Technology
8.4.5.4.4 Saudi Arabia Deep Learning Chipset Market by Industry Vertical
8.4.5.5 South Africa Deep Learning Chipset Market
8.4.5.5.1 South Africa Deep Learning Chipset Market by Compute Capacity
8.4.5.5.2 South Africa Deep Learning Chipset Market by Type
8.4.5.5.3 South Africa Deep Learning Chipset Market by Technology
8.4.5.5.4 South Africa Deep Learning Chipset Market by Industry Vertical
8.4.5.6 Nigeria Deep Learning Chipset Market
8.4.5.6.1 Nigeria Deep Learning Chipset Market by Compute Capacity
8.4.5.6.2 Nigeria Deep Learning Chipset Market by Type
8.4.5.6.3 Nigeria Deep Learning Chipset Market by Technology
8.4.5.6.4 Nigeria Deep Learning Chipset Market by Industry Vertical
8.4.5.7 Rest of LAMEA Deep Learning Chipset Market
8.4.5.7.1 Rest of LAMEA Deep Learning Chipset Market by Compute Capacity
8.4.5.7.2 Rest of LAMEA Deep Learning Chipset Market by Type
8.4.5.7.3 Rest of LAMEA Deep Learning Chipset Market by Technology
8.4.5.7.4 Rest of LAMEA Deep Learning Chipset Market by Industry Vertical

Chapter 9. Company Profiles
9.1 Samsung Electronics Co., Ltd. (Samsung Group)
9.1.1 Company Overview
9.1.2 Financial Analysis
9.1.3 Segmental and Regional Analysis
9.1.4 Research & Development Expense
9.1.5 Recent strategies and developments:
9.1.5.1 Partnerships, Collaborations, and Agreements:
9.1.5.2 Product Launches and Product Expansions:
9.1.6 SWOT Analysis
9.2 Microsoft Corporation
9.2.1 Company Overview
9.2.2 Financial Analysis
9.2.3 Segmental and Regional Analysis
9.2.4 Research & Development Expenses
9.2.5 Recent strategies and developments:
9.2.5.1 Partnerships, Collaborations, and Agreements:
9.2.5.2 Product Launches and Product Expansions:
9.2.6 SWOT Analysis
9.3 Intel Corporation
9.3.1 Company Overview
9.3.2 Financial Analysis
9.3.3 Segmental and Regional Analysis
9.3.4 Research & Development Expenses
9.3.5 Recent strategies and developments:
9.3.5.1 Product Launches and Product Expansions:
9.3.5.2 Acquisition and Mergers:
9.3.6 SWOT Analysis
9.4 Nvidia Corporation
9.4.1 Company Overview
9.4.2 Financial Analysis
9.4.3 Segmental and Regional Analysis
9.4.4 Research & Development Expense
9.4.5 Recent strategies and developments:
9.4.5.1 Partnerships, Collaborations, and Agreements:
9.4.5.2 Product Launches and Product Expansions:
9.4.6 SWOT Analysis
9.5 IBM Corporation
9.5.1 Company Overview
9.5.2 Financial Analysis
9.5.3 Regional & Segmental Analysis
9.5.4 Research & Development Expenses
9.5.5 Recent strategies and developments:
9.5.5.1 Partnerships, Collaborations, and Agreements:
9.5.5.2 Product Launches and Product Expansions:
9.5.6 SWOT Analysis
9.6 Google, Inc.
9.6.1 Company Overview
9.6.2 Financial Analysis
9.6.3 Segmental and Regional Analysis
9.6.4 Research & Development Expense
9.6.5 Recent strategies and developments:
9.6.5.1 Product Launches and Product Expansions:
9.6.6 SWOT Analysis
9.7 Amazon.com, Inc. (Amazon Web Services)
9.7.1 Company Overview
9.7.2 Financial Analysis
9.7.3 Segmental and Regional Analysis
9.7.4 Recent strategies and developments:
9.7.4.1 Partnerships, Collaborations, and Agreements:
9.7.4.2 Product Launches and Product Expansions:
9.7.5 SWOT Analysis
9.8 Qualcomm, Inc.
9.8.1 Company Overview
9.8.2 Financial Analysis
9.8.3 Segmental and Regional Analysis
9.8.4 Research & Development Expense
9.8.5 Recent strategies and developments:
9.8.5.1 Partnerships, Collaborations, and Agreements:
9.8.5.2 Product Launches and Product Expansions:
9.8.6 SWOT Analysis
9.9 Advanced Micro Devices, Inc.
9.9.1 Company Overview
9.9.2 Financial Analysis
9.9.3 Segmental and Regional Analysis
9.9.4 Research & Development Expenses
9.9.5 Recent strategies and developments:
9.9.5.1 Partnerships, Collaborations, and Agreements:
9.9.5.2 Product Launches and Product Expansions:
9.9.5.3 Acquisition and Mergers:
9.1 Xilinx, Inc.
9.10.1 Company Overview
9.10.2 Financial Analysis
9.10.3 Regional Analysis
9.10.4 Research & Development Expense
9.10.5 Recent strategies and developments:
9.10.5.1 Partnerships, Collaborations, and Agreements:
9.10.5.2 Product Launches and Product Expansions:
9.10.5.3 Acquisition and Mergers:
Note: Product cover images may vary from those shown
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  • Samsung Electronics Co., Ltd. (Samsung Group)
  • Microsoft Corporation
  • Intel Corporation
  • Nvidia Corporation
  • IBM Corporation
  • Google, Inc.
  • Amazon.com, Inc. (Amazon Web Services)
  • Qualcomm, Inc.
  • Advanced Micro Devices, Inc.
  • Xilinx, Inc.
Note: Product cover images may vary from those shown
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