Global AI GPU Market Growth 2024-2030
Product Code:1081637
Published Date: Jun 20,2024
Pages: 100
Region: Global
Category: Electronics & Semiconductor
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Broadly speaking, AI chips refer to chips that run artificial intelligence algorithms. AI algorithms mainly include deep learning algorithms and machine learning algorithms. In a narrow sense, AI chips refer to chips specially designed to accelerate artificial intelligence algorithms. AI chips mainly include GPU, TPU, FPGA, ASIC, etc. GPU is a hardware component similar to CPU, but more professional. It can handle complex mathematical operations running in parallel more efficiently than a regular CPU. The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of the physical world. Its parallel processing capabilities, supported by thousands of computing cores, are essential to running deep learning algorithms. This form of AI, in which software writes itself by learning from large amounts of data, can serve as the brain of computers, robots and self-driving cars that can perceive and understand the world. Since artificial intelligence tasks often require a large number of computationally intensive operations such as matrix multiplication and convolution, these operations can be parallelized to speed up calculations. In contrast, CPUs have weak parallelism and their relatively small number of cores cannot handle this type of task efficiently. Therefore, in artificial intelligence tasks, using GPUs for calculations can significantly speed up calculations and improve calculation efficiency. Some of the most recent applications of GPU-powered deep learning include recommendation systems, which are AI algorithms trained to understand the preferences, previous decisions, and characteristics of people and products using data gathered about their interactions, large Language Models/NLP, which can recognize, summarize, translate, predict and generate text and other content based on knowledge gained from massive datasets. Generative AI, which uses algorithms that create new content, including audio, code, images, text, simulations, and videos, based on the data they have been trained on.
The global AI GPU market size is projected to grow from US$ 73340 million in 2024 to US$ 384730 million in 2030; it is expected to grow at a CAGR of 31.8% from 2024 to 2030.
LP Information, Inc. (LPI) ' newest research report, the “AI GPU Industry Forecast” looks at past sales and reviews total world AI GPU sales in 2023, providing a comprehensive analysis by region and market sector of projected AI GPU sales for 2024 through 2030. With AI GPU sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI GPU industry.
This Insight Report provides a comprehensive analysis of the global AI GPU landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyzes the strategies of leading global companies with a focus on AI GPU portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global AI GPU market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI GPU and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global AI GPU.
Global key players of AI GPU include NVIDIA, Intel, Shanghai Denglin, etc. The top three players hold a share over 99%. China is the largest market, and has a share about 68%, followed by America and Europe with share 24% and 4%, separately. In terms of product type, 32-80GB is the largest segment, occupied for a share of 73%. In terms of application, Machine Learning has a share about 82 percent.
This report presents a comprehensive overview, market shares, and growth opportunities of AI GPU market by product type, application, key manufacturers and key regions and countries.
Segmentation by Type:
≤16GB
32-80GB
Above 80GB
Segmentation by Application:
Machine Learning
Language Models/NLP
Computer Vision
Others
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analysing the company's coverage, product portfolio, its market penetration.
NVIDIA
AMD
Intel
Shanghai Denglin
Vastai Technologies
Shanghai Iluvatar
Metax Tech
Key Questions Addressed in this Report
What is the 10-year outlook for the global AI GPU market?
What factors are driving AI GPU market growth, globally and by region?
Which technologies are poised for the fastest growth by market and region?
How do AI GPU market opportunities vary by end market size?
How does AI GPU break out by Type, by Application?