As the core technology of the new round of scientific and technological revolution, artificial intelligence is becoming an important driving force for scientific and technological innovation and economic development. Countries have raised artificial intelligence to the national strategic level and strengthened the top-level design and overall planning of artificial intelligence. The industry continues to explore the application of artificial intelligence in many fields and tap the potential of artificial intelligence technology. Driven by both policy and market, the artificial intelligence industry has entered a high-speed development stage, with the rapid release of technology dividends, the continuous emergence of research and development achievements, and the continuous expansion of application scenarios. Artificial intelligence continues to rise. A large number of artificial intelligence enterprises have emerged in the world, providing artificial intelligence products, services and solutions externally, and relying on artificial intelligence technology internally to drive the development of enterprises. According to the monitoring data of the data research center of the Chinese Academy of information and communications, by the end of July 2022, there were more than 23000 artificial intelligence enterprises in the world, and half of them were start-ups established in 2017 and later. From the development trend of artificial intelligence technology, the whole industry is in the early stage of development. From the perspective of capital market, the industry has entered the capital cashing period ahead of schedule. In 2021, more than 40 enterprises with artificial intelligence as their core business went public. The wave of listing in 2022 continues. The attention of capital to the artificial intelligence industry has not decreased, and the scale of artificial intelligence investment and financing has continued to expand. In 2021, the global AI venture capital reached US $27.4 billion, nearly doubling year-on-year. The proportion of financing amount of mature projects above round C has significantly increased. In the first half of 2022, the uncertainty of the global political and economic environment intensified. The scale of artificial intelligence financing decreased by 30% year-on-year, but remained high. Capital turned more to growth projects to seek opportunities. Medical treatment and transportation are still the most concerned vertical fields. Drug R & D, auxiliary diagnosis and treatment, health management and gene technology in the medical field are the main product R & D and capital investment directions. Domestic and foreign enterprises in various sub fields have recently been invested. The popularity of automatic driving in the transportation field has not decreased, and domestic enterprises have "blossomed". Didi woya, Zhijia technology, Yushi technology, Wenyuan Zhixing, Xiaoma Zhixing and other enterprises have recently received hundreds of millions of dollars of investment. A number of start-ups with strong technological innovation ability have also attracted attention, such as wayve and helm AI and other enterprises explore innovative models, and metropolis, intelligent robot and other enterprises are deeply engaged in key issues such as automatic driving imaging and 3D understanding. In terms of scientific research and innovation, the number of published papers on artificial intelligence and the number of patent applications worldwide are growing rapidly. From 2011 to the end of March 2022, the total number of artificial intelligence papers in the world reached 900000, the number of high-level papers exceeded 7000, the total number of patent applications reached 700000, and the total number of authorized papers reached 210000. From the research content, the research focus in the past two years includes the application of artificial intelligence in the COVID-19 epidemic, computer vision, the combination of artificial intelligence and ICT, optimization and prediction algorithms. The segmentation task algorithm model in the fields of computer vision and speech semantics has been further optimized. More than 100 or even thousands of model algorithms have been tested in the main tasks such as image classification, semantic segmentation, object recognition, question answering, language modeling and relationship extraction, and the SOT has been refreshed on several core data sets