Edge AI Hardware Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028, Segmented By Device (Smartphones, Robots, Surveillance Cameras, Wearables, Smart Speakers, Automotive, Smart Mirrors, Others), By Power Consumption (Less Than 1W, 1-3W, 3-5W, 3-5W and More Than 10W), By Function (Training, Inference), By Processor (CPU, GPU, ASIC, and Others), By Vertical (Healthca
Published Date: November - 2024 | Publisher: MIR | No of Pages: 320 | Industry: ICT | Format: Report available in PDF / Excel Format
View Details Buy Now 2890 Download Sample Ask for Discount Request CustomizationEdge AI Hardware Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028, Segmented By Device (Smartphones, Robots, Surveillance Cameras, Wearables, Smart Speakers, Automotive, Smart Mirrors, Others), By Power Consumption (Less Than 1W, 1-3W, 3-5W, 3-5W and More Than 10W), By Function (Training, Inference), By Processor (CPU, GPU, ASIC, and Others), By Vertical (Healthca
The global Edge AI Hardware market is predicted to grow during the forecast period owing to the requirement for low latency and real-time data transmission processing on edge devices. Edge AI is the implementation of artificial intelligence (AI) in an edge computing environment. This implies that rather than at a centralised cloud computing facility or off-site data centre, AI computations are performed at the edge of a particular network, typically on the device where the data is created. In addition, edge AI hardware is a term used for artificial intelligence (AI) based robotics and gadgets that are processed and powered by a collection of tools and machinery. Companies are progressively using enabling edge AI hardware’s in their devices to manage the efficiency and enables customers to deploy solutions quickly with high processing capability and low-power consumption. Numerous innovations carried out in artificial intelligence, and machine learning technologies are expected to enhance the features of Edge AI Hardware. This, in turn, is expected to drive market growth during the forecast period.
Increasing Demand for Smart Homes and Smart Cities
The increasing demand for smart homes and smart cities is driving the growth of global edge AI hardware market during the forecast period. Many industrialists and builders across the countries are adopting advanced technologies to make their homes and the cities infrastructure smarter with the integration of artificial intelligence (AI). Smart cities all around the world are progressively using these AI technologies as they become increasingly widespread across several sectors. As smart cities spread, more individuals are getting interested in the concept of a smart house. As more people choose to live in cities, there will likely be a greater need for automated services in everyday life. The demand for smart homes is turning them from a luxury to an essential need. Edgehardware devices on behalf of Artificial Intelligence (AI) is helping the smart devices with additional benefits such as adaptation to user behavior using machine learning algorithms, low latency with real-time responses. Moreover, many developing nations have started implementing smart cities initiatives as a definition of future with the growth in urbanization. Incorporating AI into smart home products and smart cities can make devices more efficient, convenient, and personalised, leading to a better overall user experience. For instance, countries such as Singapore, Finland, Switzerland, and Norway and many more are among the top smart cities in the world in 2022. Furthermore, the government all around the world are leveraging cutting-edge technology to address the fundamental issues involved in assuring the security and safety of individuals. Thus, the increasing demand for smart homes and smart cities are driving the growth of global edge AI hardware market during the forecast period.
Requirement for Low Latency and Real-Time Data Transmission Processing on Edge Devices
The inference process for data-intensive deep learning on edge devices is accelerated by specialized hardware called AI accelerators. Specialized edge AI hardware enables the quick deep learning on-device that has become more and more significant due to the increasing need for real-time deep learning workloads. To get beyond the issues of high latency and security gaps, edge AI processes IoT-generated data at close range. The cloud receives a significant amount of data from an IoT device, which is then processed by machine learning (ML) models before being sent back to the IoT device. This procedure may cause a response time delay. Yet on-device AI limits data exchange, enabling a quicker reaction. The ability to store a significant amount of data on the cloud may also not be possible. Sending this data to the cloud is not necessary with edge AI since the devices themselves have the processing capability. Therefore, increasing Edge AI Hardware demands for low latency and real-time data transmission processing on edge devices are expected to grow the adoption of Edge AI Hardware in the global market.
Digitalization and Increasing Adoption of Advanced Technologies Driving the Market Growth
The rising adoption of advanced technologies such as edge computing and artificial intelligence (AI) and growing digitalization are driving the growth of Edge AI Hardware market globally. As the technology is in developing stage with explicit future growth, more and more enterprises are integrating and adopting edge, AI enabled devices and solutions into their manufacturing and operation services. Edge AI hardware is helping businesses that are consistently using robots and other consumer electronics to process data in real-time and provide a seamless user experience. Moreover, artificial intelligence (AI) is becoming a key enabler to help automate and speed up the process by increasing efficiency and optimizing the performance and improving decision making. Therefore, increasing adoption of advanced technologies and growing digitalization is driving the demand of global edge AI hardware market.
Increase Usage of Smartphones to Propel Growth of Market
The increase in usage of smartphones in driving the demand of global edge AI hardware market. The lives of everyone are governed by smartphones and mobile gadgets. According to data on smartphone usage, two-thirds of the globe is now linked via smartphones and more than 7.33 billion people own mobile devices by 2023. Children begin receiving mobile devices at the age of 10. Nearly all children of generation Z owns a smartphone. The number of individuals utilizing the internet has increased as a result. The demand for cloud-based services and smart device users rises as a result. The edge AI hardware sector has greater options because of the usage of cloud-based services, which also leads to quicker installation times, easy and secure data transfers, rapid scaling demand increases, and cheaper infrastructure, energy, and facility costs.
Recent Advancements
- In Jan 23, 2023, Microsoft Corporation extended itspartnership with OpenAI and announced the investment of billions of dollars inthe form of Azure credits to jointly develop new technologies for the Azureplatforms. Moreover, Microsoft said it will further increase its investments inthe deployment of specialized supercomputing systems to accelerate OpenAI’s AIresearch while introducing new categories of digital experience.
- OnDec 08, 2022, Aetina Corporation, an edge AI solution provider to thegovernment entities, announced the launch of new ASIC-based edge AI systempowered by the programmable Blaize Pathfinder P1600 Embedded System on Module(SoM). The system offers dual ARM Cortex A53 processors, 16 GSP cores providing16 TOPS AI performance with low memory bandwidth and low latency benefits, makingit capable of accelerating neural network (NN) deployment and deep learning(DL) process.
- OnSep 20, 2022, NVIDIA Corporation, a pioneer in accelerated computing announcedthe launch of IGX Edge AI Computing Platform for safe, secure autonomous systems.The platform will aim to improve human-machine collaboration by being proactivesafety and advanced security to sensitive industries such as manufacturing,logistics and healthcare.
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Market Segmentation
Company Profiles
Qualcomm Technologies
| Attribute | Details |
| Base Year | 2022 |
| Historical Years | 2018 – 2021 |
| Estimated Year | 2023 |
| Forecast Period | 2024 – 2028 |
| Quantitative Units | Revenue in USD Billion and CAGR for 2018-2022 and 2023E-2028F |
| Report Coverage | Revenue forecast, company share, competitive landscape, growth factors, and trends |
| Segments Covered | By Device By Power Consumption By Function By Processor By Vertical By Region |
| Regional Scope | Asia-Pacific, North America, Europe, Middle East & Africa, and South America |
| Country Scope | China, Japan, India, Australia, South Korea, United States, Canada, Mexico, United Kingdom, Germany, France, Spain, Italy, Israel, Turkey, Saudi Arabia, UAE, Brazil, Argentina, Colombia |
| Key Companies Profiled | Qualcomm Technologies, Inc., Huawei Technologies Co. Ltd., Samsung Electronics Co. Ltd., MediaTek Inc., International Business Machines Corporation (IBM), Microsoft Corporation, NVIDIA Corporation, Google LLC (Alphabet Inc.), Apple Inc., Intel Corporation. |
| Customization Scope | 10% free report customization with purchase. Addition or alteration to country, regional & segment scope. |
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| Delivery Format | PDF and Excel through Email (We can also provide the editable version of the report in PPT/pdf format on special request) |
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