Accelerated Digital Transformation of Cities: AI Large Models Become the New Engine of Growth

Accelerated Digital Transformation of Cities: AI Large Models Become the New Engine of GrowthChongqing correspondent Xiao Xiao, 21st Century Business Herald On September 12, the National Big Data Administration held a meeting on the city's full-coverage digital transformation in Chongqing. At the meeting, industry experts summarized and released a list of scenarios for 97 cities, involving over 440 scenarios

Accelerated Digital Transformation of Cities: AI Large Models Become the New Engine of Growth

Chongqing correspondent Xiao Xiao, 21st Century Business Herald On September 12, the National Big Data Administration held a meeting on the city's full-coverage digital transformation in Chongqing. At the meeting, industry experts summarized and released a list of scenarios for 97 cities, involving over 440 scenarios. This meeting marks the entry of urban digital transformation into a new acceleration phase, with AI large models serving as a new technological engine that will bring new opportunities for urban digital development.

The investment proportion of the scenario list shows that the urban data foundation and digital economy have the highest investment proportion, accounting for over 80% of the total investment. The digital economy has become the focus of investment by social entities, and the investment proportion in the fields of digital public services and precise and refined governance is also relatively high.

Looking more specifically, urban digital scenario construction has been particularly prominent in driving technological innovation, especially in the fields of AI large models, low-altitude economy, blockchain, and embodied intelligence. Among them, 48% of the cities have proposed AI scenario needs. The connection scenarios between AI large models and digital cities mainly concentrate on areas such as industry-specific large models and data labeling.

How to provide development space for AI large models has become a significant issue for urban digital transformation. Taking Chongqing as an example, the city's "Chongqing Action Plan for High-Quality Development of the AI Industry Driven by Scenarios (2023-2025)", released in July last year, laid out four key scenarios for large models, encouraging the exploration of applications in specific industries such as transportation, healthcare, education, and agriculture. These scenarios are closely linked to urban digital governance and the digital economy. For instance, in the transportation industry, they are exploring smart charging, intelligent road network management, and intelligent multi-leg navigation.

It is noteworthy that cities across China, including Beijing, Shanghai, Shenzhen, Chengdu, Hangzhou, Wuxi, and Chongqing, have already issued new policies or policy drafts aimed at the era of AI large models. Local governments can provide support in the form of funding, data, computing power, and venues for the relevant scenarios they release. For example, many city representatives introduced the situation of their local computing power network scenarios at the meeting. The Beijing Municipal Bureau of Government Services and Data Management stated that Beijing has comprehensively built a "One Corridor, Four Poles" computing power infrastructure, currently generating over 2,000P of intelligent computing power supply capacity. Shenzhen has established a smart city computing power coordination and dispatch system, capable of real-time dispatching of computing power up to 13.5E, with an expected reach of 30E by the end of this year.

In recent years, cities like Beijing, Shanghai, Chongqing, and Changsha have all released scenario lists for urban digitization. The primary role of these lists is to clarify specific needs in smart city construction, provide application testing environments for new technologies, and attract and gather relevant industrial resources.

Experts attending the meeting concluded that urban digital transformation requires three key factors: first, using full-coverage scenario integration as a driving force; second, using full-process data interconnectivity as the core; and third, using full-chain data industry cultivation as the goal. By driving cross-departmental data interconnectivity through scenario lists, data technology, products, and services can be iterated during scenario practices, thereby promoting data industry development and fostering the growth of new forms of productivity.

In May of this year, the National Development and Reform Commission, the National Big Data Administration, the Ministry of Finance, and the Ministry of Natural Resources jointly issued the "Guiding Opinions on Deepening the Development of Smart Cities and Promoting City-wide Digital Transformation", clearly stating that by 2027, significant progress should be made in city-wide digital transformation across China, with the goal of achieving a comprehensive breakthrough by 2030.

The integration of AI large models will inject new vitality into urban digital transformation and create more possibilities for urban development. In the future, as technology continues to advance, we can expect urban digital transformation to become even more profound and efficient, bringing a more fulfilling life to people.