First of all, security practitioners have never felt as profoundly as AI can use today. Although Antelope Cloud is a platform manufacturer, it has been interested in AI and AI dedicated processor modules (chips or boards). Because there was no in-depth study in the past, Zhang Jin had been engaged in research and development for eight years from 2004 to 2012, and he was almost desperate. Because traditional technology can not achieve face recognition, license plate recognition, behavior analysis and target detection. Today, due to deep learning, the security industry has become a very important place for artificial intelligence.
Secondly, today's security industry has never been as eager to learn to run low-cost, low-power modules. Because the security chain is very long, the height, angle, light, processed functions, working environment, etc. of the camera are not solved by the CPU alone. Therefore, the security industry is very eager to have different solutions for different scenarios and environments.
For example, Antelope Yunxiang and Shenjian Technology Co., Ltd. cooperate with community/community solutions. Because the biggest opportunity for security comes from the "Snow Project" - a project jointly issued by the 9 ministries and commissions of the country, achieving 16 words: global coverage, network-wide sharing, full-time availability, and full control. It can be understood that the cameras of all of China are all connected. At present, there are few smart cameras with high requirements. This imposes high requirements on network technology conditions. Therefore, based on current network conditions, it is unlikely that all video signals will be processed in the cloud. Some smart devices may be placed at the front end, such as cameras or cell rooms. in. For example, in a residential area, many communities have security rooms. Intelligentization can make face recognition for people entering and leaving the community. They are residents or couriers, and can also identify license plates. If there is no low-power device, it is unlikely to be implemented.
So today's dedicated processing modules for different scenarios are very promising. For example, the FPGA-based solution from Shenjian Technology and the further dedicated chip solution (launched in the first half of next year) are very good solutions.
Third, security has become a huge place for AI. The security practitioners felt very bitter because there was a Huawei Haikang before, and there was a wave of startup companies, which was very difficult to get caught in the middle. The security industry has Huawei (Huawei Cloud) and Ali (City Network) strong entry, followed by many startups, such as Shang Tang, contempt, horizon, etc., traditional manufacturers are very embarrassed. How to treat artificial intelligence and security? In fact, the security industry chain is far from the finale, and it is now a halfway point. At this time, there will be a very obvious phenomenon: scenes. In the past, the security industry chain was differentiated according to categories, cameras, software, applications, etc. Today, many scenarios may be divided more and more finely. There are more vendors and scenarios, such as doing urban surveillance, such as Ali’s big city network, not going to be a community. Some do electricity; some do buildings. In these subdivision scenarios, the functional aspects of AI are unlikely to have a common AI in three or five years, that is, a set of face recognition algorithms can be applied in any scenario.
Sun Jian, the chief scientist of contempt, pointed out that deep learning is still far from reaching the solution. At this time, the development of the algorithm is a road. In this scenario, the different processing modules and product forms are very promising. So at present we can't judge what the security industry can do in the future, but today we can see many AI algorithm startups doing AI accelerators, AI-specific ASICs, AI-specific modules, Haikang doing AI's full-product solutions, etc. Everyone has a certain chance.
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