Summary

The AI Chip market is projected to grow from USD 123.2 billion in 2024 and is estimated to reach USD 311.58 billion by 2029; it is expected to grow at a CAGR of 20.4% from 2024 to 2029.
The market for AI chips is expected to grow due to increasing adoption of machine learning and deep learning algorithms. The increase in AI server shipments will boost the demand for chips supporting AI capabilities. Moreover, the emerging trend of autonomous vehicles is expected to boost the market for AI chips used for real-time decision making.
“The Neural Processing Unit (NPU) segment is projected to grow at a high rate during the forecast period.”
The Neural Processing Unit (NPU) segment is projected grow at a high rate in the AI chip market from 2024 to 2029. The market growth is attributed to the increasing adoption of high-end smartphones and AI PCs and laptops which requires dedicated AI capabilities at the edge. The NPUs helps to accelerate the neural network processing to perform the AI-driven tasks including advanced AI image processing and natural language processing. Market players are extensively focusing on developing high-end NPU solutions to stay competitive in the market. For instance, in September 2023, Apple Inc. (US) launched the iPhone 15 Pro series, featuring the A17 Pro chip. The new AI processor is incorporated with a dedicated 16-core Neural Engine which has capabilities of performing 35 trillion operations per second (TOPS). Such significant product developments and launches are expected to amplify the adoption of NPUs in the market over the forecast timeframe.
“Machine Learning segment of the AI Chip market to witness high market share during the forecast period.”
The machine learning segment in AI chip market is expected to grow at a high rate during the forecast period. AI chips are critical in running large datasets to process and enable predictive analytics, supporting real-time decision-making, as they are optimized to machine learning tasks such as training and inference. For this category of AI chips, the foremost drivers of adoption were flexibility and scalability of machine learning models within autonomous systems and personalized recommendations. This AI chip is widely used in many sectors—from cloud services and healthcare to finance, automotive, and retail—in which companies are developing powerful AI chips in support of machine learning capabilities, where business insights can be gained, the customer experience improved, and efficiency generally jacked. For instance, Google (US) announced Trillium in May 2024 as its sixth-generation TPU. It focuses on its cloud platform with an onboard accelerator for machine learning workload acceleration. Enterprises that have adopted TPUs widely bring machine learning power to predictive analytics, personalization, and operational efficiency. This represents increasing dependence on AI chips in this domain. As businesses seek to exploit the power of data for insight, efficiencies, and customer experience, demand is surging for machine learning capabilities.
“North America to hold a major market share of the AI chip market during the forecast period” North America took the largest market share for the AI chip market in 2023. The presence of prominent technology firms and data center operators are driving the AI chip market across North America region. The region hosts companies such as NVIDIA Corporation (US), Intel Corporation (US), Advanced Micro Devices, Inc. (AMD) (US), Google (US); and cloud service providers include Amazon Web Services, Inc. (AWS) (US), Microsoft Azure (US), and Google Cloud (US). For instance, in April 2024, Google (US) announced a USD 3 billion investment to expand their data centers across the US. These data centers are further backed by AI infrastructure to provide real-time services across the world. The region also hosts several startups set up in the area for providing AI chips for data centers, which include SAPEON Inc. (US), Tenstorrent (Canada), Taalas (Canada), Kneron, Inc. (US), SambaNova Systems, Inc. (US). North America has a well-established technological infrastructure that supports advanced AI research and development. There are very many modern data centers in this region, equipped with state-of-the-art AI hardware. They may include GPUs and TPUs, as well as specialized AI chips. The presence of large scale data centers and leading AI chip developers in the region are driving the market growth of AI chips.
Extensive primary interviews were conducted with key industry experts in the AI chip market to determine and verify the market size for various segments and subsegments gathered through secondary research. The break-up of primary participants for the report has been shown below:
The break-up of the profile of primary participants in the AI chip market:
• By Company Type: Tier 1 – 45%, Tier 2 – 32%, and Tier 3 – 23%
• By Designation: C-level – 30%, Director Level – 45%, Others- 25%
• By Region: North America – 26%, Europe – 40%, Asia Pacific – 22%, ROW- 12%
The report profiles key players in the AI Chip market with their respective market ranking analysis. Prominent players profiled in this report are NVIDIA Corporation (US), Intel Corporation (US), Advanced Micro Devices, Inc. (US), Micron Technology, Inc. (US), Google (US), Samsung (South Korea), SK HYNIX INC. (South Korea), Qualcomm Technologies, Inc. (US), Huawei Technologies Co., Ltd. (China), Apple Inc. (US), Imagination Technologies (UK), Graphcore (UK), Cerebras (US).
Apart from this, Mythic (US), Kalray (France), Blaize (US), Groq, Inc. (US), HAILO TECHNOLOGIES LTD (Israel), GreenWaves Technologies (France), SiMa Technologies, Inc. (US), Kneron, Inc. (US), Rain Neuromorphics Inc. (US), Tenstorrent (Canada), SambaNova Systems, Inc. (US), Taalas (Canada), SAPEON Inc. (US), Rebellions Inc. (South Korea), Rivos Inc. (US), and Shanghai BiRen Technology Co., Ltd. (China) are among a few emerging companies in the AI chip market.
Research Coverage: This research report categorizes the AI Chip market on the basis of offerings, function, technology, end user, and region. The report describes the major drivers, restraints, challenges, and opportunities pertaining to the AI chip market and forecasts the same till 2029. Apart from these, the report also consists of leadership mapping and analysis of all the companies included in the AI chip ecosystem.
Key Benefits of Buying the Report The report will help the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI chip market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and to plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
• Analysis of key drivers (increasing data traffic and need for high computing power, emerging trend of autonomous vehicles, growing adoption of industrial robots, rising focus on parallel computing in AI data centers, increasing adoption of machine learning and deep learning algorithms, increase in AI server shipments to boost the demand for AI chips), restraints (lack of AI hardware experts and skilled workforce, increasing power consumption), opportunities (surging demand for AI-based field programmable gate array (FPGA) technology, integration of AI-based solutions into defense systems, growing potential of AI-based tools in healthcare sector, planned investments in data centers by cloud service providers, rise of ASICs based on AI technology), and challenges (data privacy concerns associated with AI platforms, unreliability of AI algorithms, availability of limited structured data to develop efficient AI systems, supply chain disruptions) influencing the growth of the AI Chip market.
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI chip market.
• Market Development: Comprehensive information about lucrative markets – the report analysis the AI chip market across various regions
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Ai Chip market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and product offerings of leading players like NVIDIA Corporation (US), Intel Corporation (US), Advanced Micro Devices, Inc. (US), Micron Technology, Inc. (US), Google (US), among others in the AI Chip market.

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Table of Contents

1 INTRODUCTION 28
1.1 STUDY OBJECTIVES 28
1.2 MARKET DEFINITION 28
1.3 STUDY SCOPE 29
1.3.1 MARKETS COVERED AND REGIONAL SCOPE 29
1.3.2 INCLUSIONS AND EXCLUSIONS 30
1.3.3 YEARS CONSIDERED 30
1.4 CURRENCY CONSIDERED 31
1.5 UNIT CONSIDERED 31
1.6 LIMITATIONS 31
1.7 STAKEHOLDERS 31
1.8 SUMMARY OF CHANGES 32
2 RESEARCH METHODOLOGY 34
2.1 RESEARCH DATA 34
2.1.1 SECONDARY AND PRIMARY RESEARCH 36
2.1.2 SECONDARY DATA 36
2.1.2.1 List of key secondary sources 37
2.1.2.2 Key data from secondary sources 37
2.1.3 PRIMARY DATA 37
2.1.3.1 List of primary interview participants 38
2.1.3.2 Breakdown of primaries 38
2.1.3.3 Key data from primary sources 39
2.1.3.4 Key industry insights 40
2.2 MARKET SIZE ESTIMATION METHODOLOGY 41
2.2.1 BOTTOM-UP APPROACH 43
2.2.1.1 Approach to arrive at market size using bottom-up analysis
(demand side) 43
2.2.2 TOP-DOWN APPROACH 44
2.2.2.1 Approach to arrive at market size using top-down analysis
(supply side) 44
2.3 DATA TRIANGULATION 45
2.4 RESEARCH ASSUMPTIONS 46
2.5 RISK ANALYSIS 47
2.6 RESEARCH LIMITATIONS 47
3 EXECUTIVE SUMMARY 48
 
4 PREMIUM INSIGHTS 54
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI CHIP MARKET 54
4.2 AI CHIP MARKET, BY COMPUTE 54
4.3 AI CHIP MARKET, BY MEMORY 55
4.4 AI CHIP MARKET, BY NETWORK 55
4.5 AI CHIP MARKET, BY TECHNOLOGY AND FUNCTION 56
4.6 AI CHIP MARKET, BY END USER 56
4.7 AI CHIP MARKET, BY REGION 57
4.8 AI CHIP MARKET, BY COUNTRY 57
5 MARKET OVERVIEW 58
5.1 INTRODUCTION 58
5.2 MARKET DYNAMICS 58
5.2.1 DRIVERS 59
5.2.1.1 Pressing need for large-scale data handling and real-time analytics 59
5.2.1.2 Rising adoption of autonomous vehicles 60
5.2.1.3 Surging use of GPUs and ASICs in AI servers 60
5.2.1.4 Continuous advancements in machine learning and deep
learning technologies 61
5.2.1.5 Increasing penetration of AI servers 61
5.2.2 RESTRAINTS 62
5.2.2.1 Shortage of skilled workforce with technical know-how 62
5.2.2.2 Computational workloads and power consumption in AI Chip 63
5.2.2.3 Unreliability of AI algorithms 64
5.2.3 OPPORTUNITIES 65
5.2.3.1 Elevating demand for AI-based FPGA chips 65
5.2.3.2 Government initiatives to deploy AI-enabled defense systems 66
5.2.3.3 Rising trend of AI-driven diagnostics and treatments 66
5.2.3.4 Increasing investments in AI-enabled data centers by
cloud service providers 67
5.2.3.5 Rise in adoption of AI-based ASIC technology 67
5.2.4 CHALLENGES 68
5.2.4.1 Data privacy concerns associated with AI platforms 68
5.2.4.2 Availability of limited structured data to develop efficient AI systems 69
5.2.4.3 Supply chain disruptions 69
5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 70
5.4 PRICING ANALYSIS 71
5.4.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY COMPUTE 71
5.4.2 AVERAGE SELLING PRICE TREND, BY REGION 72
5.5 VALUE CHAIN ANALYSIS 74
5.6 ECOSYSTEM ANALYSIS 77
5.7 INVESTMENT AND FUNDING SCENARIO 80
5.8 TECHNOLOGY ANALYSIS 81
5.8.1 KEY TECHNOLOGIES 81
5.8.1.1 High-bandwidth Memory (HBM) 81
5.8.1.2 GenAI workload 82
5.8.2 COMPLEMENTARY TECHNOLOGIES 82
5.8.2.1 Data center power management and cooling system 82
5.8.2.2 High-speed interconnects 82
5.8.3 ADJACENT TECHNOLOGIES 83
5.8.3.1 AI development frameworks 83
5.8.3.2 Quantum AI 83
5.9 SERVER COST STRUCTURE/BILL OF MATERIAL 83
5.9.1 CPU SERVER 83
5.9.2 GPU SERVER 85
5.10 PENETRATION AND GROWTH OF AI SERVERS 87
5.11 UPCOMING DEPLOYMENT OF DATA CENTERS BY CLOUD SERVICE PROVIDERS (CSPS) 88
5.12 CLOUD SERVICE PROVIDERS’ CAPEX 88
5.13 SERVER PROCUREMENT BY CLOUD SERVICE PROVIDERS, 2020–2029 90
5.14 PROCESSOR BENCHMARKING 91
5.14.1 GPU BENCHMARKING 91
5.14.2 CPU BENCHMARKING 91
5.15 PATENT ANALYSIS 92
5.16 TRADE ANALYSIS 98
5.16.1 IMPORT SCENARIO (HS CODE 854231) 98
5.16.2 EXPORT SCENARIO (HS CODE 854231) 100
5.17 KEY CONFERENCES AND EVENTS, 2024–2025 101
5.18 CASE STUDY ANALYSIS 103
5.18.1 CDW INTEGRATED AMD EPYC SOLUTIONS TO ENSURE ENERGY EFFICIENCY AND OPTIMUM SPACE UTILIZATION 103
5.18.2 OVH SAS LEVERAGED AMD EPYC PROCESSOR TO OPTIMIZE PERFORMANCE OF CLOUD SOLUTIONS IN AI WORKLOADS 103
5.18.3 INTEL XEON SCALABLE PROCESSORS POWER TENCENT CLOUD’S XIAOWEI INTELLIGENT SPEECH AND VIDEO SERVICE ACCESS PLATFORM 104
5.18.4 AIC HELPS WESTERN DIGITAL TO ENHANCE SSD TESTING AND VALIDATION EFFICIENCY USING AMD PROCESSOR 104
5.19 REGULATORY LANDSCAPE 105
5.19.1 REGULATORY BODIES, GOVERNMENT AGENCIES,
AND OTHER ORGANIZATIONS 105
5.19.2 STANDARDS 109
5.20 PORTER’S FIVE FORCES ANALYSIS 112
5.20.1 THREAT OF NEW ENTRANTS 113
5.20.2 THREAT OF SUBSTITUTES 114
5.20.3 BARGAINING POWER OF SUPPLIERS 114
 
5.20.4 BARGAINING POWER OF BUYERS 114
5.20.5 INTENSITY OF COMPETITION RIVALRY 115
5.21 KEY STAKEHOLDERS AND BUYING CRITERIA 115
5.21.1 KEY STAKEHOLDERS IN BUYING PROCESS 115
5.21.2 BUYING CRITERIA 116
6 AI CHIP MARKET, BY COMPUTE 117
6.1 INTRODUCTION 118
6.2 GPU 121
6.2.1 ABILITY TO HANDLE AI WORKLOADS AND PROCESS VAST DATA VOLUMES
TO BOOST ADOPTION 121
6.3 CPU 122
6.3.1 RISING DEMAND FOR VERSATILE AND GENERAL-PURPOSE
AI PROCESSING TO AUGMENT MARKET GROWTH 122
6.4 FPGA 123
6.4.1 GROWING NEED FOR FLEXIBILITY AND CUSTOMIZATION FOR
AI WORKLOADS TO SPUR DEMAND 123
6.5 NPU 124
6.5.1 RISING DEMAND FOR HIGH-END SMARTPHONES TO
DRIVE SEGMENTAL GROWTH 124
6.6 TPU 125
6.6.1 PRESSING NEED FOR FASTER PROCESSING IN AI RESEARCH AND APPLICATION DEVELOPMENT TO BOOST DEMAND 125
6.7 DOJO & FSD 126
6.7.1 ACCELERATING DEMAND FOR HIGH-PERFORMANCE, ENERGY-EFFICIENT AI PROCESSING IN AUTONOMOUS VEHICLES TO FUEL ADOPTION 126
6.8 TRAINIUM & INFERENTIA 127
6.8.1 ABILITY TO TRAIN COMPLEX AI AND DEEP LEARNING MODELS
TO DRIVE ADOPTION 127
6.9 ATHENA ASIC 128
6.9.1 INCREASING NEED TO HANDLE COMPLEX NLP AND LANGUAGE-BASED AI TASKS TO ACCELERATE MARKET GROWTH 128
6.10 T-HEAD 128
6.10.1 RISING DEMAND FOR CUSTOMIZED, HIGH-PERFORMANCE AI CHIPS ACROSS CHINESE DATA CENTERS TO STIMULATE MARKET GROWTH 128
6.11 MTIA 129
6.11.1 META'S EXPANSION INTO AR, VR, AND METAVERSE TO
FUEL MARKET GROWTH 129
6.12 LPU 129
6.12.1 INCREASING NEED TO HANDLE COMPLEX NLP AND LANGUAGE-BASED
AI TASKS TO ACCELERATE MARKET GROWTH 129
6.13 OTHER ASIC 130
 
7 AI CHIP MARKET, BY MEMORY 131
7.1 INTRODUCTION 132
7.2 DDR 134
7.2.1 RISING ADOPTION OF AI-ENABLED CPUS IN DATA CENTERS TO
SUPPORT MARKET GROWTH 134
7.3 HBM 135
7.3.1 ELEVATING NEED FOR HIGH THROUGHPUT IN DATA-INTENSIVE AI TASKS TO FUEL MARKET GROWTH 135
8 AI CHIP MARKET, BY NETWORK 136
8.1 INTRODUCTION 137
8.2 NIC/NETWORK ADAPTERS 139
8.2.1 INFINIBAND 141
8.2.1.1 Growing utilization of HPC and AI models to minimize latency and maximize throughput to boost segmental growth 141
8.2.2 ETHERNET 141
8.2.2.1 Rising demand for scalable and cost-effective networking solutions to propel growth 141
8.3 INTERCONNECTS 141
8.3.1 GROWING COMPLEXITY OF AI MODELS REQUIRING HIGH-BANDWIDTH DATA PATHS TO FUEL DEMAND 141
9 AI CHIP MARKET, BY TECHNOLOGY 143
9.1 INTRODUCTION 144
9.2 GENERATIVE AI 145
9.2.1 RULE-BASED MODELS 146
9.2.1.1 Rising need to detect fraud in finance sector to propel market 146
9.2.2 STATISTICAL MODELS 147
9.2.2.1 Requirement to make accurate predictions from complex data structures to boost segmental growth 147
9.2.3 DEEP LEARNING 148
9.2.3.1 Ability to advance AI technologies to boost demand 148
9.2.4 GENERATIVE ADVERSARIAL NETWORKS (GAN) 149
9.2.4.1 Pressing need to handle large-scale data to fuel segmental growth 149
9.2.5 AUTOENCODERS 149
9.2.5.1 Ability to compress and restructure data to ensure optimum storage space in data centers to stimulate demand 149
9.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS) 150
9.2.6.1 Surging demand for realistic and high-quality images and videos to accelerate market growth 150
9.2.7 TRANSFORMER MODELS 151
9.2.7.1 Increasing utilization in image synthesis and captioning applications to foster segmental growth 151
 
9.3 MACHINE LEARNING 152
9.3.1 RISING USE IN IMAGE AND SPEECH RECOGNITION AND PREDICTIVE ANALYTICS TO CONTRIBUTE TO MARKET GROWTH 152
9.4 NATURAL LANGUAGE PROCESSING 152
9.4.1 INCREASING NEED FOR REAL-TIME APPLICATIONS TO
SUPPORT MARKET GROWTH 152
9.5 COMPUTER VISION 153
9.5.1 ESCALATING NEED FOR ADVANCED PROCESSING CAPABILITIES
TO BOOST DEMAND 153
10 AI CHIP MARKET, BY FUNCTION 154
10.1 INTRODUCTION 155
10.2 TRAINING 157
10.2.1 SURGING NEED TO PROCESS LARGE DATA SETS AND PERFORM
PARALLEL COMPUTATION TO CREATE OPPORTUNITIES 157
10.3 INFERENCE 158
10.3.1 SURGING DEPLOYMENT ACROSS VARIOUS INDUSTRIES TO BOOST DEMAND 158
11 AI CHIP MARKET, BY END USER 159
11.1 INTRODUCTION 160
11.2 CONSUMER 161
11.2.1 GROWING ADOPTION OF AI-ENABLED PERSONAL DEVICES
TO PROPEL MARKET 161
11.3 DATA CENTERS 162
11.3.1 CLOUD SERVICE PROVIDERS 163
11.3.1.1 Surging AI workloads and cloud adoption to stimulate market growth 163
11.3.2 ENTERPRISES 164
11.3.2.1 Escalating use of NLP, image recognition, and predictive analytics to create growth opportunities 164
11.3.2.2 Healthcare 165
11.3.2.2.1 Integration of AI in computer-aided drug discovery and development to foster market growth 165
11.3.2.3 BFSI 166
11.3.2.3.1 Surging need for fraud detection in financial institutions to boost demand 166
11.3.2.4 Automotive 167
11.3.2.4.1 Growing focus on safe and enhanced driving experiences to fuel demand 167
11.3.2.5 Retail & ecommerce 169
11.3.2.5.1 Increasing use of chatbots and virtual assistants to offer improved customer services to drive market 169
11.3.2.6 Media & entertainment 170
11.3.2.6.1 Real-time analysis of viewer preferences, engagement patterns, and demographic information to augment
market growth 170
11.3.2.7 Others 171
11.4 GOVERNMENT ORGANIZATIONS 172
11.4.1 SIGNIFICANT FOCUS ON AUTOMATING ROUTINE TASKS AND EXTRACTING REAL-TIME ACTIONABLE INSIGHTS TO SUPPORT MARKET GROWTH 172
12 AI CHIP MARKET, BY REGION 174
12.1 INTRODUCTION 175
12.2 NORTH AMERICA 176
12.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA 176
12.2.2 US 181
12.2.2.1 Government-led initiatives to boost semiconductor manufacturing to drive market 181
12.2.3 CANADA 181
12.2.3.1 Growing emphasis on commercializing AI to spur demand 181
12.2.4 MEXICO 182
12.2.4.1 Increasing shift toward digital platforms and cloud-based solutions to accelerate demand 182
12.3 EUROPE 183
12.3.1 MACROECONOMIC OUTLOOK FOR EUROPE 183
12.3.2 UK 188
12.3.2.1 Growing investments in data center infrastructure to boost demand 188
12.3.3 GERMANY 189
12.3.3.1 Presence of robust industrial base to offer lucrative
growth opportunities 189
12.3.4 FRANCE 189
12.3.4.1 Increasing number of AI startups to accelerate demand 189
12.3.5 ITALY 190
12.3.5.1 Rising adoption of digitalization in automotive and healthcare sectors to drive market 190
12.3.6 SPAIN 191
12.3.6.1 Growing collaborations and partnerships among AI manufacturers to spur demand 191
12.3.7 REST OF EUROPE 191
12.4 ASIA PACIFIC 192
12.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC 192
12.4.2 CHINA 197
12.4.2.1 Surge in research funding and implementation of supportive regulatory policy to augment market growth 197
12.4.3 JAPAN 198
12.4.3.1 Rising adoption of AI chips to advance robotic systems to offer lucrative growth opportunities 198
12.4.4 INDIA 198
12.4.4.1 Government-led initiatives to boost AI infrastructure to
foster market growth 198
12.4.5 SOUTH KOREA 199
12.4.5.1 Thriving semiconductor industry to drive market growth 199
12.4.6 REST OF ASIA PACIFIC 199
12.5 ROW 200
12.5.1 MACROECONOMIC OUTLOOK FOR ROW 200
12.5.2 MIDDLE EAST 204
12.5.2.1 Growing emphasis on digital transformation and technological innovation to drive market growth 204
12.5.2.2 GCC countries 205
12.5.2.3 Rest of Middle East 205
12.5.3 AFRICA 206
12.5.3.1 Rising internet penetration and mobile subscriptions to offer lucrative growth opportunities 206
12.5.4 SOUTH AMERICA 206
12.5.4.1 Growing need to store vast volumes of data to boost demand 206
13 COMPETITIVE LANDSCAPE 207
13.1 INTRODUCTION 207
13.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2019–2024 207
13.3 REVENUE ANALYSIS, 2021–2023 209
13.4 MARKET SHARE ANALYSIS, 2023 210
13.5 COMPANY VALUATION AND FINANCIAL METRICS 214
13.6 BRAND/PRODUCT COMPARISON 215
13.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 216
13.7.1 STARS 216
13.7.2 EMERGING LEADERS 216
13.7.3 PERVASIVE PLAYERS 216
13.7.4 PARTICIPANTS 216
13.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 218
13.7.5.1 Company footprint 218
13.7.5.2 Compute footprint 219
13.7.5.3 Memory footprint 220
13.7.5.4 Network footprint 221
13.7.5.5 Technology footprint 222
13.7.5.6 Function footprint 223
13.7.5.7 End user footprint 224
13.7.5.8 Region footprint 225
13.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 226
13.8.1 PROGRESSIVE COMPANIES 226
13.8.2 RESPONSIVE COMPANIES 226
13.8.3 DYNAMIC COMPANIES 226
13.8.4 STARTING BLOCKS 226
13.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023 228
13.8.5.1 Detailed list of key startups/SMEs 228
13.8.5.2 Competitive benchmarking of key startups/SMEs 229
13.9 COMPETITIVE SCENARIO 230
13.9.1 PRODUCT LAUNCHES 230
13.9.2 DEALS 243
14 COMPANY PROFILES 256
14.1 KEY PLAYERS 256
14.1.1 NVIDIA CORPORATION 256
14.1.1.1 Business overview 256
14.1.1.2 Products/Solutions/Services offered 257
14.1.1.3 Recent developments 259
14.1.1.3.1 Product launches 259
14.1.1.3.2 Deals 261
14.1.1.4 MnM view 262
14.1.1.4.1 Key strengths 262
14.1.1.4.2 Strategic choices 262
14.1.1.4.3 Weaknesses and competitive threats 262
14.1.2 ADVANCED MICRO DEVICES, INC. 263
14.1.2.1 Business overview 263
14.1.2.2 Products/Solutions/Services offered 264
14.1.2.3 Recent developments 266
14.1.2.3.1 Product launches 266
14.1.2.3.2 Deals 267
14.1.2.4 MnM view 268
14.1.2.4.1 Key strengths 268
14.1.2.4.2 Strategic choices 268
14.1.2.4.3 Weaknesses and competitive threats 269
14.1.3 INTEL CORPORATION 270
14.1.3.1 Business overview 270
14.1.3.2 Products/Solutions/Services offered 271
14.1.3.3 Recent developments 275
14.1.3.3.1 Product launches 275
14.1.3.3.2 Deals 277
14.1.3.3.3 Other developments 278
14.1.3.4 MnM view 278
14.1.3.4.1 Key strengths 278
14.1.3.4.2 Strategic choices 279
14.1.3.4.3 Weaknesses and competitive threats 279
14.1.4 SK HYNIX INC. 280
14.1.4.1 Business overview 280
14.1.4.2 Products/Solutions/Services offered 281
14.1.4.3 Recent developments 282
14.1.4.3.1 Product launches 282
14.1.4.3.2 Deals 283
14.1.4.3.3 Other developments 283
14.1.4.4 MnM view 284
14.1.4.4.1 Key strengths 284
14.1.4.4.2 Strategic choices 284
14.1.4.4.3 Weaknesses and competitive threats 284
14.1.5 SAMSUNG 285
14.1.5.1 Business overview 285
14.1.5.2 Products/Solutions/Services offered 286
14.1.5.3 Recent developments 289
14.1.5.3.1 Product launches 289
14.1.5.3.2 Deals 291
14.1.5.4 MnM view 292
14.1.5.4.1 Key strengths 292
14.1.5.4.2 Strategic choices 292
14.1.5.4.3 Weaknesses and competitive threats 292
14.1.6 MICRON TECHNOLOGY, INC. 293
14.1.6.1 Business overview 293
14.1.6.2 Products/Solutions/Services offered 294
14.1.6.3 Recent developments 296
14.1.6.3.1 Product launches 296
14.1.6.3.2 Deals 297
14.1.7 APPLE INC. 298
14.1.7.1 Business overview 298
14.1.7.2 Products/Solutions/Services offered 299
14.1.7.3 Recent developments 301
14.1.7.3.1 Product launches 301
14.1.7.3.2 Deals 302
14.1.8 QUALCOMM TECHNOLOGIES, INC. 303
14.1.8.1 Business overview 303
14.1.8.2 Products/Solutions/Services offered 304
14.1.8.3 Recent developments 307
14.1.8.3.1 Product launches 307
14.1.8.3.2 Deals 308
14.1.9 HUAWEI TECHNOLOGIES CO., LTD. 311
14.1.9.1 Business overview 311
14.1.9.2 Products/Solutions/Services offered 312
14.1.9.3 Recent developments 313
14.1.9.3.1 Product launches 313
14.1.9.3.2 Deals 314
 
14.1.10 GOOGLE 315
14.1.10.1 Business overview 315
14.1.10.2 Products/Solutions/Services offered 316
14.1.10.3 Recent developments 317
14.1.10.3.1 Product launches 317
14.1.10.3.2 Deals 318
14.1.11 AMAZON WEB SERVICES, INC. 319
14.1.11.1 Business overview 319
14.1.11.2 Products/Solutions/Services offered 320
14.1.11.3 Recent developments 321
14.1.11.3.1 Product launches 321
14.1.11.3.2 Deals 321
14.1.12 TESLA 323
14.1.12.1 Business overview 323
14.1.12.2 Products/Solutions/Services offered 324
14.1.13 MICROSOFT 325
14.1.13.1 Business overview 325
14.1.13.2 Products/Solutions/Services offered 326
14.1.13.3 Recent developments 327
14.1.13.3.1 Product launches 327
14.1.13.3.2 Deals 327
14.1.14 META 329
14.1.14.1 Business overview 329
14.1.14.2 Products/Solutions/Services offered 330
14.1.14.3 Recent developments 331
14.1.14.3.1 Product launches 331
14.1.14.3.2 Deals 331
14.1.15 T-HEAD 332
14.1.15.1 Business overview 332
14.1.15.2 Products/Solutions/Services offered 332
14.1.16 IMAGINATION TECHNOLOGIES 333
14.1.16.1 Business overview 333
14.1.16.2 Products/Solutions/Services offered 333
14.1.16.3 Recent developments 334
14.1.16.3.1 Product launches 334
14.1.16.3.2 Deals 335
14.1.17 GRAPHCORE 336
14.1.17.1 Business overview 336
14.1.17.2 Products/Solutions/Services offered 336
14.1.17.3 Recent developments 337
14.1.17.3.1 Product launches 337
14.1.17.3.2 Deals 337
14.1.18 CEREBRAS 338
14.1.18.1 Business overview 338
14.1.18.2 Products/Solutions/Services offered 338
14.1.18.3 Recent developments 339
14.1.18.3.1 Product launches 339
14.1.18.3.2 Deals 339
14.2 OTHER PLAYERS 340
14.2.1 MYTHIC 340
14.2.2 KALRAY 341
14.2.3 BLAIZE 342
14.2.4 GROQ, INC. 343
14.2.5 HAILO TECHNOLOGIES LTD 344
14.2.6 GREENWAVES TECHNOLOGIES 345
14.2.7 SIMA TECHNOLOGIES, INC. 345
14.2.8 KNERON, INC. 346
14.2.9 RAIN NEUROMORPHICS INC. 346
14.2.10 TENSTORRENT 347
14.2.11 SAMBANOVA SYSTEMS, INC. 347
14.2.12 TAALAS 348
14.2.13 SAPEON INC. 348
14.2.14 REBELLIONS INC. 349
14.2.15 RIVOS INC. 349
14.2.16 SHANGHAI BIREN TECHNOLOGY CO., LTD. 350
15 APPENDIX 351
15.1 DISCUSSION GUIDE 351
15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 355
15.3 CUSTOMIZATION OPTIONS 357
15.4 RELATED REPORTS 357
15.5 AUTHOR DETAILS 358