The Asia Pacific Edge AI Hardware Market should witness market growth of 18.1% CAGR during the forecast period (2022-2028).
Performing a huge amount of calculations in parallel as opposed to sequentially. Calculating low-precision numbers in a method that effectively implements AI algorithms while simultaneously reducing the number of transistors necessary for the same calculation. Increasing memory access speed by putting a complete AI algorithm on a single AI chip.
Using specifically constructed programming languages to translate AI computer code for execution on an AI chip. Diverse types of AI chips are beneficial for various applications. GPUs are typically employed for the initial construction and refinement of AI algorithms, a process known as "training." FPGAs are typically employed to apply AI-trained algorithms to real-world data inputs, a process commonly referred to as "inference." ASICs may be created for either training or inference.
Before investing in AI hardware, organizations need, of course, to be aware of how different types of hardware meet varying requirements. With the transition towards purpose-made chips, users don't want to spend much money on unnecessary specialist hardware. The first step in selecting AI hardware is to map out how interactions with customers and suppliers could be improved to impact business processes.
Both India and China have extremely robust manufacturing sectors, which both contribute a large amount to the overall GDP of their respective countries. The International Trade Administration estimates that the manufacturing industry in India contributed between 16 and 17% of the country's GDP in 2018, and it is anticipated to be one of the industries with the greatest rate of expansion. The manufacturing industry in India relied heavily on the commercial and industrial machinery sector as its primary support structure.
The China market dominated the Asia Pacific Edge AI Hardware Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $2,219.8 million by 2028. The Japan market is estimated to grow a CAGR of 17.3% during (2022-2028). Additionally, The India market would experience a CAGR of 18.8% during (2022-2028).
Based on Function, the market is segmented into Inference and Training. Based on Device Type, the market is segmented into Smartphones, Surveillance Cameras, Wearables, Robots, Smart Speakers & Smart Mirrors, Automotive and Edge Servers. Based on Component, the market is segmented into Processor, Memory and Sensor & Others. Based on Vertical, the market is segmented into Consumer Electronics, Smart Home, Automotive & Transportation, Government, Healthcare, Industrial, Aerospace & Defense, Construction and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.
The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include Apple, Inc., MediaTek, Inc., Qualcomm, Inc., Huawei Technologies Co., Ltd., Samsung Electronics Co., Ltd. (Samsung Group), Intel Corporation, Nvidia Corporation, IBM Corporation, Google LLC, and Microsoft Corporation.
Performing a huge amount of calculations in parallel as opposed to sequentially. Calculating low-precision numbers in a method that effectively implements AI algorithms while simultaneously reducing the number of transistors necessary for the same calculation. Increasing memory access speed by putting a complete AI algorithm on a single AI chip.
Using specifically constructed programming languages to translate AI computer code for execution on an AI chip. Diverse types of AI chips are beneficial for various applications. GPUs are typically employed for the initial construction and refinement of AI algorithms, a process known as "training." FPGAs are typically employed to apply AI-trained algorithms to real-world data inputs, a process commonly referred to as "inference." ASICs may be created for either training or inference.
Before investing in AI hardware, organizations need, of course, to be aware of how different types of hardware meet varying requirements. With the transition towards purpose-made chips, users don't want to spend much money on unnecessary specialist hardware. The first step in selecting AI hardware is to map out how interactions with customers and suppliers could be improved to impact business processes.
Both India and China have extremely robust manufacturing sectors, which both contribute a large amount to the overall GDP of their respective countries. The International Trade Administration estimates that the manufacturing industry in India contributed between 16 and 17% of the country's GDP in 2018, and it is anticipated to be one of the industries with the greatest rate of expansion. The manufacturing industry in India relied heavily on the commercial and industrial machinery sector as its primary support structure.
The China market dominated the Asia Pacific Edge AI Hardware Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $2,219.8 million by 2028. The Japan market is estimated to grow a CAGR of 17.3% during (2022-2028). Additionally, The India market would experience a CAGR of 18.8% during (2022-2028).
Based on Function, the market is segmented into Inference and Training. Based on Device Type, the market is segmented into Smartphones, Surveillance Cameras, Wearables, Robots, Smart Speakers & Smart Mirrors, Automotive and Edge Servers. Based on Component, the market is segmented into Processor, Memory and Sensor & Others. Based on Vertical, the market is segmented into Consumer Electronics, Smart Home, Automotive & Transportation, Government, Healthcare, Industrial, Aerospace & Defense, Construction and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.
The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include Apple, Inc., MediaTek, Inc., Qualcomm, Inc., Huawei Technologies Co., Ltd., Samsung Electronics Co., Ltd. (Samsung Group), Intel Corporation, Nvidia Corporation, IBM Corporation, Google LLC, and Microsoft Corporation.
Scope of the Study
By Function
- Inference
- Training
By Device Type
- Smartphones
- Surveillance Cameras
- Wearables
- Robots
- Smart Speakers & Smart Mirrors
- Automotive
- Edge Servers
By Component
- Processor
- Memory
- Sensor & Others
By Vertical
- Consumer Electronics
- Smart Home
- Automotive & Transportation
- Government
- Healthcare
- Industrial
- Aerospace & Defense
- Construction
- Others
By Country
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
Key Market Players
List of Companies Profiled in the Report:
- Apple, Inc.
- MediaTek, Inc.
- Qualcomm, Inc.
- Huawei Technologies Co., Ltd.
- Samsung Electronics Co., Ltd. (Samsung Group)
- Intel Corporation
- Nvidia Corporation
- IBM Corporation
- Google LLC
- Microsoft Corporation
Unique Offerings
- Exhaustive coverage
- The highest number of Market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
Chapter 3. Competition Analysis - Global
Chapter 4. Asia Pacific Edge AI Hardware Market by Function
Chapter 5. Asia Pacific Edge AI Hardware Market by Device Type
Chapter 6. Asia Pacific Edge AI Hardware Market by Component
Chapter 7. Asia Pacific Edge AI Hardware Market by Vertical
Chapter 8. Asia Pacific Edge AI Hardware Market by Country
Chapter 9. Company Profiles
Companies Mentioned
- Apple, Inc.
- MediaTek, Inc.
- Qualcomm, Inc.
- Huawei Technologies Co., Ltd.
- Samsung Electronics Co., Ltd. (Samsung Group)
- Intel Corporation
- Nvidia Corporation
- IBM Corporation
- Google LLC
- Microsoft Corporation
Methodology
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