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- Apr 19, 2018 -

The Opportunities and Challenges of Safety Enterprises in the AI Times

In the “Global Artificial Intelligence Development Report (2016)”, it is clearly stated that in the future, artificial intelligence will take the lead in e-commerce retail, finance, health care, education, auto driving, personal assistants, and security. From the star-burst of the 2016 Beijing AMB to the embarrassing situation of the Shenzhen AMB in 2017, rapid industrial technology iterations will surely drive the industry towards a more open and integrated new ecology. The

Relevant data show that the Shenzhen AMB was affected by the wave of artificial intelligence, and the number of applicants has quadrupled from the forecast. It can even be said that the artificial intelligence will make the security new. However, returning to reality, companies still need to focus on the differences between concept and product landing. Blindly chasing the former will only become a part of the AI bubble. They will rationally view the changes in new technologies, and in addition to seeing opportunities, they must also promote high quality. Only by having a sustainable competitive product can we achieve true core competitiveness so as to obtain the expected profit. The

At present, security technologies that integrate artificial intelligence, big data, and cloud computing have been recognized by more and more users. Especially in the areas of safe cities and intelligent transportation, artificial intelligence can solve many urgent needs:

(1) According to statistics, in 2016, there were a total of 47 projects for Ping An City's 100 million projects, with a total market size of 10.92 billion. In the first half of 2017, there were 55 projects for Ping An City's over 100 million projects. The total amount of projects was 21.32 billion and the average project amount was 380 million yuan. After two years of exploration, security management around the regional crowd monitoring and case analysis system will surely be applied to the industrialization of more AI in 2018. From the second half of 2016, the proportion of functional software orders in government orders will increase rapidly. 2018 Year will usher in an outbreak;

(2) In 2016, the market size of the intelligent transportation industry reached 41.44 billion yuan, a year-on-year increase of 33.5%, and it is expected to maintain an increase of more than 20% in the next few years. Through artificial intelligence and big data, users can meet the needs of road traffic perception (vehicles, car park perception, etc.), vehicle identity identification, vehicle comparison, vehicle behavior analysis, and future driverless and car-assisted driving. The

First, deep learning requires a large amount of data samples to be trained. Theoretically collecting data can make machines omnipotent, but reality is not the case. The differences in the sample characteristics of various industries in different regions directly limit the sample collection is not unlimited, in addition to edge calculations, the study of how to improve learning ability in a limited sample is a problem that companies must face; Second, how to collect the security scene Combining data samples with actual combat is the real issue to be considered in security AI. If the technology is not integrated with actual combat, then the industry is essentially not improving;

Second, the breadth and depth of security AI development, the current data identified by the smart front-end is only shallow information, how the future will be derived in the breadth of more sub-domain products and how to complete the depth of information in the depth of knowledge, is Deep learning challenges in the security industry.