This year's government work report proposes to vigorously promote the construction of a modern industrial system and accelerate the development of new quality productive forces. Among them, deepening the innovation and development of the digital economy ranks high. The report emphasizes "formulating policies to support the high-quality development of the digital economy, actively promoting digital industrialization and industrial digitization, and promoting deep integration of digital technology and the real economy", "deepening research and development applications such as big data and artificial intelligence, and carrying out" artificial intelligence+"actions". In the future, with the joint efforts of technology, policies, and industries, "artificial intelligence+" will accelerate the "blooming of a hundred flowers", injecting surging momentum into the accelerated cultivation and development of new productive forces. Developing new quality productive forces is an inherent requirement and important focus for promoting high-quality development. Currently, the digital economy has become an important force supporting the vigorous development of new quality productivity. Originating from rich application scenarios and massive data resources, China's digital economy has achieved rapid development. According to data from the China Academy of Information and Communications Technology, in 2022, the scale of China's digital economy reached 50.2 trillion yuan, a year-on-year increase of 10.3%, accounting for 41.5% of GDP. It is expected that the scale of China's digital economy will reach 56.1 trillion yuan by 2023. Artificial intelligence is an important engine for the development of the digital economy. In the just past year of 2023, innovative achievements in artificial intelligence in China have been constantly emerging, especially in the booming development of generative artificial intelligence (AIGC) represented by large models, and accelerating its deep integration with the real economy, empowering thousands of industries. Office, medical, education, finance, manufacturing and other areas have become active areas for the commercial application of artificial intelligence technology. From accelerating new drug research and development, accurately predicting weather, to shortening factory product delivery cycles and improving office efficiency; From single point applications and universal scenarios, to diversified applications and industry-specific scenarios, artificial intelligence is moving towards a new stage of comprehensive application. The widespread application of artificial intelligence has effectively promoted cost reduction, quality improvement, and efficiency enhancement in various industries. There are many examples that can be used as evidence. For example, the author noticed that in the agricultural field, the national agricultural industrialization leading enterprise, Tieqi Lishi, has built AI intelligent customer service based on DingTalk AI PaaS, achieving efficient technical and procurement consultation responses for farmers. They have also built 25 sets of business systems by calling DingTalk API interfaces, improving process efficiency by 30%, per capita income and order delivery rate by 20%, and product efficiency by 15%. For example, in the manufacturing industry, chip design company Aiwei Electronics has launched "AI Intelligent Customer Service", which enables uninterrupted intelligent answers 24/7, allowing technical experts to return to professional positions. In the consumer goods industry, the footwear and clothing brand Belle International has launched an AI assistant called "Product Digital Employee" to address the issue of discrepancies in the distribution of goods. By replacing real people with AI assistants, it not only frees up manpower but also improves business efficiency. In the deep integration with various industries, the capability boundaries of "artificial intelligence+" are constantly expanding. The application of artificial intelligence technology helps more and more enterprises achieve production automation, product innovation, and service intelligence, thereby continuously improving the overall competitiveness of the industry. Looking ahead to the future, the digital economy still has a very broad development space, and with the rapid iteration and maturity of large models, generative methods