■What Is Edge AI?
Edge AI is the technology of embedding AI into edge devices like IoT gadgets and smartphones, allowing them to process learning and inference locally without relying on the cloud.
In contrast, systems that perform AI learning and prediction on the cloud are referred to as Cloud AI.
With edge AI, data is processed locally without relying on network communication, enabling reduced transmission costs, improved data privacy, and real-time responsiveness. However, it comes with the challenge of limited inference processing power.
It is often used in combination with Cloud AI, depending on the case, to balance performance and capabilities.
One of the major benefits of Edge AI is its ability to perform real-time inference directly on the device—critical for applications where speed is essential.
Edge AI is commonly used in applications such as monitoring changes through sensors, control, safety management, and autonomous driving.
■The Background Behind the Growing Attention on Edge AI
In IoT, real-time data processing is required. Real-time capability is one of the key strengths of Edge AI, so with the increasing adoption of IoT, As a result, Edge AI has attracted increasing attention across industries.
Particularly in areas like autonomous driving, factory automation, and drone control, where real-time processing is critically important, Edge AI plays an essential role.
Additionally, advancements in both hardware and software, along with increased processing capabilities in edge devices, have lowered the barriers to deploying Edge AI, making it increasingly accessible and attractive to businesses.
While Edge AI technology, such as in autonomous driving, is still in development, technological advancements will continue to progress in the future.
■Souya’s Edge AI Development
While Edge AI offers many advantages, it also comes with limitations such as power consumption, performance, and device size constraints.
As such, the appropriate edge device depends on the operating environment and the specific processing tasks.
Moreover, AI models that work well on high-performance machines may not operate correctly on edge devices, or may experience slower processing speeds.
At Souya, we offer end-to-end support for Edge AI adoption—from selecting the optimal edge devices and designing efficient models to full system integration—ensuring tangible improvements to your operations.
If you are unsure whether Edge AI can solve your specific challenges, feel free to reach out to us. We will assess your needs and provide tailored solutions.
We tailor our recommendations based on your needs and use case, following a thorough consultation.
■Contact Us
For more information, please contact us through our inquiry form.