Artificial intelligence, big data, and advanced algorithms are the three essential pillars driving modern technological progress. Today, many big data companies have evolved into AI-focused organizations, incorporating data visualization and analysis into their services. Haiyun Data, initially known for its data visualization capabilities, began exploring AI last year. In March of this year, it officially launched a lip-reading identification technology, and in August, it unveiled its comprehensive AI strategy. This significant transformation—whether driven by market trends or business necessity—will ultimately depend on whether big data and AI can effectively integrate into real-world applications, which will determine the success or failure of such efforts.
Haiyun Data has been deeply involved in public security, aiming to make the industry "intelligent" through the use of "smart brains." The company's AI-powered visual analysis has led to the development of a high-quality product called the "Smart Alert Brain."
On December 8th, Haiyun Data introduced a smart solution based on the MapEase 6.0 platform—the Smart Alert Brain. This product combines AI and data visualization technologies, focusing on enhancing the capabilities of public security operations. By integrating these modules with real-world security scenarios, it has developed over 200 industry-specific functions across 40 different segments.
So far, Haiyun Data has successfully deployed the Smart Alert Brain in more than one-third of provincial and municipal public security bureaus. After implementation, the time required for intelligence analysis has decreased by 70%, while operational efficiency has increased by 50%.
At the conference, Haiyun Data’s founder and CEO, Feng Yicun, demonstrated the upgraded "Smart Alert Brain." He used facial recognition to access the system and issued voice commands to a robot, achieving highly accurate results. During the demonstration, a police officer was present to assist in receiving, responding to, and executing orders.
Additionally, the Smart Alert Brain has predictive capabilities. For example, if individuals with a history of drug use tend to gather at night, the system can predict potential relapse risks. It can also analyze case clues, such as suspects' relationships and travel routes, helping to identify criminal networks and support law enforcement in solving multiple cases.
The system allows voice-controlled map zooming, video retrieval of accident scenes, and real-time display of nearby fire stations, hospitals, and police resources. This empowers senior commanders with quick decision-making and response capabilities, ensuring efficient handling of incidents.
According to Feng Yicun, the Smart Alert Brain integrates key elements like nearby police units, crime locations, surrounding areas, intelligence analysis, suspect paths, and key suspect files—all displayed on a single map. This enables real-time monitoring and instant decision-making for field personnel.
In all business scenarios, Haiyun aims to make command and intelligence centers fully intelligent, ensuring that all commands and information reach frontline officers instantly. This allows them to effectively execute police orders based on up-to-date intelligence.
Currently, Haiyun’s Tuyi platform has expanded into industries such as public safety, transportation, smart cities, and civil-military integration.
The road to AI productization is challenging. While many AI companies talk about cutting-edge technologies, few have successfully implemented them in specific, real-world applications. It's only when technology is embedded in practical products that its true value becomes evident. Haiyun has managed to implement AI within the deep-rooted public security sector, building mature products that reflect a more pragmatic approach.
Why is AI still struggling to become a product? The core of business innovation lies in productization. While the first half of the year focused on AI research, the second half is more about applying these technologies in real-world settings. Companies like Star AI have successfully transformed image recognition into various applications, especially in the security industry, where the demand for face recognition is high. Speech recognition firms are also exploring opportunities in the IoT space.
There's a growing debate on whether AI should be "industry + AI" or "AI + industry." These two approaches differ significantly. AI + industry is similar to how Ctrip transformed the travel industry, much like the Internet + industry. On the other hand, industry + AI means AI is an integral part of the industry itself, such as in autonomous driving.
Today, many companies are competing for market share. Giants dominate through portals and free tech platforms, while others leverage existing business models with AI integration. However, the level of technological maturity, product engineering, and commercial viability remain uncertain.
In the current AI era, there's a lot of competition, with BAT and emerging startups all vying for position. Recently, some AI companies faced criticism over their commercialization abilities. Whether it's easy or not, the next step in AI productization will determine who survives and thrives in this rapidly evolving landscape.
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