Artificial Intelligence (AI) has become a game-changer in the world of technology, transforming how businesses operate and people interact with technology. edge AI is the next step in this transformation, enabling AI to be used in real-time applications without the need for cloud computing.
The edge AI hardware market has been on the rise and is expected to grow as the demand for AI-based applications increases. In this blog, we will explore the rise of edge AI hardware, its current status, trends in the market, recent developments by key players, and future prospects.
What has caused the rise of edge AI hardware?
The rise of edge AI hardware can be attributed to several factors. One of the main reasons is the increasing demand for AI-based applications in real time. With the emergence of the Internet of Things (IoT), there has been an increase in the number of connected devices. edge AI hardware enables these devices to perform complex computations locally without the need for cloud computing. This allows for real-time processing, reducing latency and increasing efficiency.
Another factor contributing to the rise of edge AI hardware is the need for data privacy and security. edge AI hardware enables data to be processed locally, reducing the need for data to be transmitted to the cloud for processing. This improves data privacy and reduces the risk of data breaches.
What is the current status and the actual purpose of edge AI hardware?
According to a report by Polaris Market Research, the global edge AI hardware market size is expected to reach USD 7,977.31 million by 2032, growing at a CAGR of 22.4% from 2023 to 2032. The actual purpose of edge AI hardware is to enable AI-based applications to be used in real-time without the need for cloud computing. edge AI hardware can be used in various applications, including autonomous vehicles, drones, surveillance systems, healthcare devices, and more.
Recent developments by Market key players in the industry
- In 2021, Qualcomm announced its Snapdragon 888 Plus processor, which features an integrated AI engine for edge AI applications.
- In 2020, Nvidia launched its Jetson Xavier NX platform, which is designed for edge AI applications and offering high-performance computing capabilities.
- In 2020, Intel announced its new Atom, Pentium, and Celeron processors, which feature integrated AI accelerators for edge AI applications.
- In 2020, Samsung announced its Exynos i S111 processor, designed for edge AI applications, offering enhanced security features.
What future does the market hold?
The future of the edge AI hardware market looks promising. With the increasing demand for AI-based applications, the market is expected to continue to grow. The development of new technologies, such as AI accelerators and edge computing platforms, is expected to drive the market’s growth.
In conclusion, the rise of edge AI hardware is transforming the way AI is used in real-time applications, enabling devices to perform complex computations locally, reducing latency, and improving efficiency.