
Global Deep Learning Chipset Competitive Landscape Professional Research Report 2024
Description
Research Summary
A deep learning chipset, also known as an AI (Artificial Intelligence) chipset or neural network processor, is a specialized hardware component designed to accelerate the execution of deep learning algorithms and artificial neural networks. Deep learning chipsets are engineered to handle the complex mathematical calculations and large-scale data processing required for training and inference in deep learning models. These chipsets are optimized to perform operations like matrix multiplications, convolutions, and activation functions with high efficiency, speed, and parallel processing capabilities. They are commonly used in various AI applications, such as computer vision, natural language processing, speech recognition, and autonomous vehicles. Deep learning chipsets enable faster and more power-efficient execution of AI tasks, reducing the reliance on general-purpose processors and enhancing the performance of AI-powered devices and applications. The development of specialized hardware for deep learning has been a crucial factor in the advancement and widespread adoption of artificial intelligence technologies across diverse industries.
According to DIResearch's in-depth investigation and research, the global Deep Learning Chipset market size will reach XX US$ Million in 2024, and is expected to reach XX US$ Million in 2030, with a CAGR of XX% (2025-2030). Among them, the China market has changed rapidly in the past few years. The market size in 2024 will be XX US$ Million, accounting for approximately XX% of the world. It is expected to reach XX US$ Million in 2030, and the global share will reach XX%.
The major global manufacturers of Deep Learning Chipset include NVIDIA, Intel, IBM, Qualcomm, CEVA, KnuEdge, AMD, Xilinx, ARM, Google, Graphcore, TeraDeep, Wave Computing, BrainChip etc. The global players competition landscape in this report is divided into three tiers. The first tiers is the global leading enterprise, which occupies a major market share, is in a leading position in the industry, has strong competitiveness and influence, and has a large revenue scale; the second tiers has a certain share and popularity in the market, actively follows the industry leaders in product, service or technological innovation, and has a medium revenue scale; the third tiers has a smaller share in the market, has a lower brand awareness, mainly focuses on the local market, and has a relatively small revenue scale.
This report studies the market size, price trends and future development prospects of Deep Learning Chipset. Focus on analysing the market share, product portfolio, prices, sales volume, revenue and gross profit margin of global major manufacturers, as well as the market status and trends of different product types and applications in the global Deep Learning Chipset market. The report data covers historical data from 2019 to 2023, based year in 2024 and forecast data from 2025 to 2030.
The regions and countries in the report include North America, Europe, China, APAC (excl. China), Latin America and Middle East and Africa, covering the Deep Learning Chipset market conditions and future development trends of key regions and countries, combined with industry-related policies and the latest technological developments, analyze the development characteristics of Deep Learning Chipset industries in various regions and countries, help companies understand the development characteristics of each region, help companies formulate business strategies, and achieve the ultimate goal of the company's global development strategy.
The data sources of this report mainly include the National Bureau of Statistics, customs databases, industry associations, corporate financial reports, third-party databases, etc. Among them, macroeconomic data mainly comes from the National Bureau of Statistics, International Economic Research Organization; industry statistical data mainly come from industry associations; company data mainly comes from interviews, public information collection, third-party reliable databases, and price data mainly comes from various markets monitoring database.
Global Key Manufacturers of Deep Learning Chipset Include:
NVIDIA
Intel
IBM
Qualcomm
CEVA
KnuEdge
AMD
Xilinx
ARM
Google
Graphcore
TeraDeep
Wave Computing
BrainChip
Deep Learning Chipset Product Segment Include:
Graphics Processing Units (GPUs)
Central Processing Units (CPUs)
Application Specific Integrated Circuits (ASICs)
Field Programmable Gate Arrays (FPGAs)
Others
Deep Learning Chipset Product Application Include:
Consumer
Aerospace, Military & Defense
Automotive
Industrial
Medical
Others
Chapter Scope
Chapter 1: Product Research Range, Product Types and Applications, Market Overview, Market Situation and Trends
Chapter 2: Global Deep Learning Chipset Industry PESTEL Analysis
Chapter 3: Global Deep Learning Chipset Industry Porter’s Five Forces Analysis
Chapter 4: Global Deep Learning Chipset Major Regional Market Size (Revenue, Sales, Price) and Forecast Analysis
Chapter 5: Global Deep Learning Chipset Market Size and Forecast by Type and Application Analysis
Chapter 6: North America Deep Learning Chipset Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 7: Europe Deep Learning Chipset Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 8: China Deep Learning Chipset Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 9: APAC (Excl. China) Deep Learning Chipset Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 10: Latin America Deep Learning Chipset Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 11: Middle East and Africa Deep Learning Chipset Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 12: Global Deep Learning Chipset Competitive Analysis of Key Manufacturers (Sales, Revenue, Market Share, Price, Regional Distribution and Industry Concentration)
Chapter 13: Key Company Profiles (Product Portfolio, Sales, Revenue, Price and Gross Margin)
Chapter 14: Industrial Chain Analysis, Include Raw Material Suppliers, Distributors and Customers
Chapter 15: Research Findings and Conclusion
Chapter 16: Methodology and Data Sources
Table of Contents
170 Pages
Pricing
Currency Rates
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