Yang Fan, co-founder and vice president of Shang Tang Technology, is also a member of the EGO Beijing Branch. As the general manager of the Engineering Products Center at Shang Tang Technology, he has been instrumental in developing and delivering artificial intelligence solutions across the pan-security smart video, mobile internet, and financial industries. With over a decade of experience in computer vision algorithm development, product management, project leadership, R&D coordination, and team building, Yang Fan has played a key role in advancing the commercialization of AI technologies. In 2016 alone, the company secured hundreds of millions in product orders, marking a significant milestone. That same year, he was honored as “Outstanding Young Talent in Beijing†for his contributions to establishing Shang Tang as a leading AI company within just three years.
The following content is based on an interview with Mr. Yang Fan conducted by InfoQ.
“AI’s true value lies in its ability to integrate with various industries,†Yang Fan emphasizes. Having spent many years immersed in computer vision technology, he previously worked at Microsoft, where he focused on the incubation of new technologies such as face recognition, image object recognition, and portrait 3D reconstruction. Today, Shang Tang's core technologies still revolve around face recognition, intelligent monitoring, and image recognition. As a leader in this field, Yang Fan jokes that he has guided the hands of his researchers. Leading a team of over 200 engineers, he has helped develop AI solutions across multiple sectors, driving significant progress in the application of AI technologies.
Yang Fan believes that while AI itself is not new, it has seen a surge in recent years due to advancements in processing voice, images, and video, along with stronger technical capabilities. He argues that the success of AI depends heavily on real-world applications, which provide the necessary context for its development.
AI technology integrates various foundational technologies, and its application in different fields—such as healthcare, finance, security, logistics, and agriculture—requires tailored solutions. For example, AI in healthcare can be used for smart devices and diagnostics, while in finance, it enhances transaction security and enables precision marketing. The integration of AI and security supports intelligent surveillance and security robots. However, Yang Fan stresses that these concepts must be grounded in real scenarios, as only then can we truly understand their value.
There have been criticisms in the industry about some companies and developers lacking a deep understanding of how deep learning works. Yang Fan acknowledges that while some may not fully grasp the underlying principles, many teams—including Shang Tang—are investing in fundamental research. This basic research helps guide future development, but he emphasizes that both basic and applied research are essential. Enterprises must ultimately prove their value through tangible results.
Face recognition has sparked widespread interest, raising questions about the technology and the companies behind it. Shang Tang’s approach includes advanced face verification systems, which are being applied in areas like online account security, mobile payments, and personal authentication. These systems use live detection to ensure that the person interacting is genuine, not a photo or video. The company provides comprehensive solutions for both online and offline environments, especially in China, where the real-name system plays a crucial role in enhancing internet and public security.
Accuracy rates are often highlighted in the industry, but Yang Fan points out that they vary greatly depending on the scenario. A 99% accuracy rate may be sufficient for some applications, but in high-stakes environments like security, additional challenges arise from poor lighting, angles, and obstructions. He notes that while face recognition seems simple, the technical complexity in real-world applications is substantial.
To determine if an industry is worth pursuing with AI, Yang Fan suggests looking at five key factors: real demand, scalability, data loops, commercial viability, and innovation. Each of these elements contributes to the success of AI implementation in specific industries.
Finally, he highlights the importance of interdisciplinary talent. Combining technical expertise with industry knowledge is critical for successful AI deployment. As the AI landscape continues to evolve, the need for professionals who can bridge the gap between technology and business becomes even more vital. The journey of bringing AI to market is complex, but with the right strategy, talent, and vision, it remains a promising and impactful endeavor.
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