Edge AI

This method runs AI directly on field devices (cameras, sensors, factory equipment) rather than on a server.

Edge AI is a method of executing AI directly within field devices such as cameras, sensors, and factory equipment, rather than sending data to a distant server. It is as if field staff makes an instant decision instead of asking all questions to headquarters, so it is quick to respond and works even when the Internet is disconnected.

This is especially necessary in cases where delays are not acceptable, such as instantaneous decisions in self-driving cars, in environments where communication is unstable, and when sensitive data is difficult to send externally. Thanks to the advancement of semiconductors and model lightweight technology, its application to smartphones, CCTV, home appliances, and even factory equipment is rapidly increasing, and it is also in line with the term on-device AI.

However, there are limits to the computational ability of the device, making it difficult to achieve the same performance as large models in the cloud. In actual industries, a mixed structure is common, with light decisions being processed on-site and heavy tasks being handled in the cloud.

✅ Why it matters

• Fast response and real-time judgment are possible because it does not go through a server
• Data does not leave the device, which is advantageous for privacy
• Works even in environments where there is no internet connection or is unstable

⚠️ Limits and debates

• It is difficult to achieve performance at the level of large models due to the limitations of the device's computing power
• The burden of updating and managing AI scattered across numerous devices is high
• The problem of rising device costs and power consumption must be solved together