Artificial intelligence in the security industry's landing, promoting the further upgrading of security intelligence, but also brought the extension of the edge of the industry. With the deepening of the application of artificial intelligence in the field of security, this industry also attracts more and more AI enterprises, especially computer vision enterprises. As a natural algorithm manufacturer, their entry also opens up the security and AI enterprises in security Artificial intelligence era on the accumulation of genes and the contest.
Security video surveillance From the "human eye view" to the automatic analysis and identification of the machine structure and processing, thanks to the rapid development of artificial intelligence, cloud computing, big data and other technologies, including security in the area of the core of face recognition, vehicle character recognition , Behavior recognition and other applications brought together a large number of artificial intelligence algorithms, it is also in such an industrial technology structure, AI companies with leading edge algorithm advantages in the field of security accumulated a considerable influence, talking about artificial intelligence In the development of the industry market, the traditional security companies and AI companies play a role in the industry naturally become a topic that can not be detached.
Break the limitations of industrial role
From the business goals, security companies and AI companies have common place, are expected to be able to provide users with more intelligent and complete video solutions, and based on such a common goal, their focus falls on different aspects , Respectively, stood at both ends of the product and technology.
Traditional security companies focus more on business R & D equipment manufacturing, solutions and systems integration, AI companies are more focused on chip and algorithm technology research and development. Security AI from technology to products to solutions, the business between the two major industry roles is bound to gradually integrate. Algorithm vendors began to extend toward the product side, improve its own products and service system. The large security companies in order to optimize their smart security system application effect, not in the chip and algorithm is limited to people, to consolidate their market power of words, but also will set up its own team of artificial intelligence algorithms put more effort. The two sides fill shortcomings, it is more likely to shape the overall competitiveness of enterprises.
At present these trends have been reflected in the industry market. It is worth mentioning that in the current market environment, enterprises that have the dual resources of AI and security at the same time are more capable of breaking the limitations of industrial roles and are undoubtedly the lucky ones of the times. Of course, they also exist in the real world, and their future will certainly be hard-edged.
Fill short board integration development
However, the security industry is not like other manufacturing industries. It itself is a complex industry with multi-level, multi-regional and multi-sector opportunities. Although there are many opportunities, it is also dispersed. AI enterprises and traditional security companies in the era of smart security everlasting, need to fill short board, integration and development. AI companies want to enter the security market to do deep penetration, but also need to face two major problems:
First, the problem of industrial experience. Most AI companies start with artificial intelligence algorithms, focusing on the face recognition, behavior recognition, speech recognition and other technical areas, and security is just one of these applications can be cross-cutting technology. Most AI companies are involved in the field of security in the depth of learning wave (especially face recognition) that has arisen in recent years. Compared with the well-established security companies, the AI enterprise is undoubtedly the upstart in the industry. They do not have long-term experience in the security industry market, lack of in-depth understanding of security market conditions, including real user needs, product life cycle, channel system, solution capabilities and engineering systems, etc., not by virtue of technology or capital Can thoroughly understand.
Second, the problem of technology. The AI enterprise occupies a significant advantage in the chip and algorithm. However, the actual security project tests the capability of the enterprise solution. From hardware and software to the system, the algorithm is only one of the dimensions, and how to transform the high-quality algorithm into "productivity" Serve the actual application is the key.
In turn, the traditional security companies want to start in the AI algorithm and chip technology exploration, is also a difficult process. In the industrial chain, the development from upstream to downstream may also be "homeopathic", but it will be more difficult to expand upstream and downstream from upstream and downstream because there are two major impediments involved:
The first is a completely different business talent structure. Security products or integrated companies and algorithmic companies have very different talent composition, algorithmic company's team is generally composed of technology research and development personnel, such personnel training requires a strong professional environment, and the long training cycle. In the security products or integrated companies, even if the use of external means to quickly set up AI R & D team, this approach does not work quickly, or even fall into a research and development pit, after years of research and development to pay the high cost but in exchange for the product obsolete Or low competitiveness. In the final analysis, or because it involves the issue of corporate genes. Genes in a company depend largely on their founders / founding team, and if the founders / founding team do not have the ability to think, organize, coordinate, and make decision-making in algorithmic research and development, then it is hard for the underlying technical team to successfully To carry out work, leading to the successful commercialization of technology there is a big difficulty.
Another point, the algorithm is a field of deep technical research, the need for continuous investment, both sophisticated manpower, or research and development funding, and this continuous investment does not necessarily have a clear return, which is very much test business vision And patience. Especially for small and medium-sized security companies that do not have too much capital and resources, self-study algorithms require careful consideration. Of course, for large security companies, they will be much better because they have more abundant capital and human resources to support them. However, large companies are difficult to manage, they are often not focused on research and development, and they are inefficient and dragged down.
At present, some manufacturers in the industry will make some technical achievements in AI through continuous research and investment the day after tomorrow. However, in many cases, the effectiveness of such AIs is an external manifestation. In the long-term development perspective, the AI operations of these enterprises are more likely to emerge as a "mixture," and not purely that their core technologies have not yet taken root , There is not much technical output strength for practical applications and long-term competitiveness continue to endure. Due to the lack of innate AI genes, security companies since the algorithm of this road may go more difficult.
Win-win cooperation and stability
So, is not that security companies want to explore the field of AI opportunities must be slim? In actual fact, the traditional security vendors want to get the AI's "ticket" can still do some try, the most effective measure is Cooperation. For security and AI companies, relying on a single technology, product or market resources is very easy to follow. Find the right partners to achieve complementary advantages, but also to a win-win situation.
The win-win cooperation is based on the premise that both sides must know where their shortcomings. Differences in business models between different areas, and differences in the development of different enterprises within the same area of the ITW switch are all issues that need to be quantified during the process of selecting a partner.
The industry will continue to derive new opportunities for development in the process of meticulous operation. Only when all the advantages of gene, technology, experience, advantages of channels, etc., are integrated into comprehensive service capabilities based on user needs can the advantages be highlighted Its value, and this is the core value of security artificial intelligence in terms of users.
Security video surveillance From the "human eye view" to the automatic analysis and identification of the machine structure and processing, thanks to the rapid development of artificial intelligence, cloud computing, big data and other technologies, including security in the area of the core of face recognition, vehicle character recognition , Behavior recognition and other applications brought together a large number of artificial intelligence algorithms, it is also in such an industrial technology structure, AI companies with leading edge algorithm advantages in the field of security accumulated a considerable influence, talking about artificial intelligence In the development of the industry market, the traditional security companies and AI companies play a role in the industry naturally become a topic that can not be detached.
Break the limitations of industrial role
From the business goals, security companies and AI companies have common place, are expected to be able to provide users with more intelligent and complete video solutions, and based on such a common goal, their focus falls on different aspects , Respectively, stood at both ends of the product and technology.
Traditional security companies focus more on business R & D equipment manufacturing, solutions and systems integration, AI companies are more focused on chip and algorithm technology research and development. Security AI from technology to products to solutions, the business between the two major industry roles is bound to gradually integrate. Algorithm vendors began to extend toward the product side, improve its own products and service system. The large security companies in order to optimize their smart security system application effect, not in the chip and algorithm is limited to people, to consolidate their market power of words, but also will set up its own team of artificial intelligence algorithms put more effort. The two sides fill shortcomings, it is more likely to shape the overall competitiveness of enterprises.
At present these trends have been reflected in the industry market. It is worth mentioning that in the current market environment, enterprises that have the dual resources of AI and security at the same time are more capable of breaking the limitations of industrial roles and are undoubtedly the lucky ones of the times. Of course, they also exist in the real world, and their future will certainly be hard-edged.
Fill short board integration development
However, the security industry is not like other manufacturing industries. It itself is a complex industry with multi-level, multi-regional and multi-sector opportunities. Although there are many opportunities, it is also dispersed. AI enterprises and traditional security companies in the era of smart security everlasting, need to fill short board, integration and development. AI companies want to enter the security market to do deep penetration, but also need to face two major problems:
First, the problem of industrial experience. Most AI companies start with artificial intelligence algorithms, focusing on the face recognition, behavior recognition, speech recognition and other technical areas, and security is just one of these applications can be cross-cutting technology. Most AI companies are involved in the field of security in the depth of learning wave (especially face recognition) that has arisen in recent years. Compared with the well-established security companies, the AI enterprise is undoubtedly the upstart in the industry. They do not have long-term experience in the security industry market, lack of in-depth understanding of security market conditions, including real user needs, product life cycle, channel system, solution capabilities and engineering systems, etc., not by virtue of technology or capital Can thoroughly understand.
Second, the problem of technology. The AI enterprise occupies a significant advantage in the chip and algorithm. However, the actual security project tests the capability of the enterprise solution. From hardware and software to the system, the algorithm is only one of the dimensions, and how to transform the high-quality algorithm into "productivity" Serve the actual application is the key.
In turn, the traditional security companies want to start in the AI algorithm and chip technology exploration, is also a difficult process. In the industrial chain, the development from upstream to downstream may also be "homeopathic", but it will be more difficult to expand upstream and downstream from upstream and downstream because there are two major impediments involved:
The first is a completely different business talent structure. Security products or integrated companies and algorithmic companies have very different talent composition, algorithmic company's team is generally composed of technology research and development personnel, such personnel training requires a strong professional environment, and the long training cycle. In the security products or integrated companies, even if the use of external means to quickly set up AI R & D team, this approach does not work quickly, or even fall into a research and development pit, after years of research and development to pay the high cost but in exchange for the product obsolete Or low competitiveness. In the final analysis, or because it involves the issue of corporate genes. Genes in a company depend largely on their founders / founding team, and if the founders / founding team do not have the ability to think, organize, coordinate, and make decision-making in algorithmic research and development, then it is hard for the underlying technical team to successfully To carry out work, leading to the successful commercialization of technology there is a big difficulty.
Another point, the algorithm is a field of deep technical research, the need for continuous investment, both sophisticated manpower, or research and development funding, and this continuous investment does not necessarily have a clear return, which is very much test business vision And patience. Especially for small and medium-sized security companies that do not have too much capital and resources, self-study algorithms require careful consideration. Of course, for large security companies, they will be much better because they have more abundant capital and human resources to support them. However, large companies are difficult to manage, they are often not focused on research and development, and they are inefficient and dragged down.
At present, some manufacturers in the industry will make some technical achievements in AI through continuous research and investment the day after tomorrow. However, in many cases, the effectiveness of such AIs is an external manifestation. In the long-term development perspective, the AI operations of these enterprises are more likely to emerge as a "mixture," and not purely that their core technologies have not yet taken root , There is not much technical output strength for practical applications and long-term competitiveness continue to endure. Due to the lack of innate AI genes, security companies since the algorithm of this road may go more difficult.
Win-win cooperation and stability
So, is not that security companies want to explore the field of AI opportunities must be slim? In actual fact, the traditional security vendors want to get the AI's "ticket" can still do some try, the most effective measure is Cooperation. For security and AI companies, relying on a single technology, product or market resources is very easy to follow. Find the right partners to achieve complementary advantages, but also to a win-win situation.
The win-win cooperation is based on the premise that both sides must know where their shortcomings. Differences in business models between different areas, and differences in the development of different enterprises within the same area of the ITW switch are all issues that need to be quantified during the process of selecting a partner.
The industry will continue to derive new opportunities for development in the process of meticulous operation. Only when all the advantages of gene, technology, experience, advantages of channels, etc., are integrated into comprehensive service capabilities based on user needs can the advantages be highlighted Its value, and this is the core value of security artificial intelligence in terms of users.
In the absolute trend of security artificial intelligence, the future situation of the industry will have a great change in the continuous change of the market in the process, in addition to continuously consolidate their own business capabilities, companies should develop their own far-sighted pattern, to the death and Health courage, openness and win-win tolerance, so, to be stable and far!
