I look forward to how the brush face technology can be highlighted on the road of technology.

Face recognition technology is once again gaining widespread attention. Recently, in a middle school simulation exam in Beijing, students are required to "scan their faces" for verification. Since the introduction of Face ID on the iPhone X, this biometric authentication method has sparked a new wave of interest, with people becoming increasingly fascinated by the idea of "smart faces." However, face scanning technology is still in its early stages, and both its technical maturity and user experience remain under development. Despite these challenges, the road ahead for this technology remains promising, and we are eager to see how it will evolve and make a significant impact in the tech world. From checking the housing fund to attendance tracking and security checks, more daily activities are now being labeled as "face scanning." Even in public restrooms at Ritan Park in Beijing, toilet paper dispensers now require users to scan their faces. This trend reflects the growing integration of face recognition into everyday life, making it an essential part of modern convenience. When combined with government services, face recognition is expected to become a standard way to verify identity in the future. You may no longer need to go through extensive paperwork or provide multiple documents — just a quick facial scan could be enough. Chinese enthusiasm for face recognition is also evident in the funding landscape. Companies like Face++, a leading face recognition cloud service provider, and Shangtang Technology, which focuses on AI visual engines, have raised substantial funds. Face++ secured $100 million in Series C funding, while Shangtang raised $410 million in a B-round round, positioning them among the top AI "unicorns." The tipping point for commercial applications of face recognition seems to be approaching. While the iPhone X might not have fully realized its potential, it has certainly brought face recognition into the mainstream. There are three main algorithms used in face recognition: 1. **1:1 Recognition**: This is the most basic form, where a person's face is matched against a pre-stored image to confirm identity. It’s commonly used for mobile phone unlocking, online payments, and airport security checks. The accuracy is high, and the computational power needed is relatively low. 2. **1:N Recognition**: This involves matching a single face against a large database of images to identify who the person is. It’s widely used in law enforcement for suspect identification and missing persons searches. The challenge here is that the system must analyze dynamic video footage without the subject’s cooperation, making it more complex and less accurate than 1:1 recognition. 3. **N:N Recognition**: This is essentially performing multiple 1:N comparisons simultaneously, allowing systems to identify multiple individuals in a crowd. Despite its rapid growth, face recognition is still far from perfect. While China leads in practical applications, basic research is on par with the US and Europe. However, real-world implementation remains challenging due to factors like lighting, angles, and obstructions such as masks or glasses. Recent demonstrations have even shown that a 3D-printed face can trick some systems, highlighting vulnerabilities in current technology. For startups, the key to success lies not just in technology, but in understanding real-world scenarios. Many companies focus too much on technical superiority without considering practical use cases. Investors emphasize that data, application scenarios, and commercialization capabilities are just as important as algorithms. As big players enter the market, startups must find their niche by focusing on deep industry knowledge and specialized services. While giants have advantages in resources and scale, there are still opportunities in areas like entertainment and consumer services, where high accuracy isn’t always necessary. In the end, the future of face recognition depends not only on technological advancement, but also on how well it can integrate into our daily lives in a secure, convenient, and user-friendly way.

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