Recently, the Information Office of Wuhan Municipal People's Government held a press conference on several policy measures to promote the development of the artificial intelligence (AI) industry in Wuhan. The city announced the launch of an "AI+" initiative this year, aiming to promote large model applications across more than 20 industries.

This initiative, based on the Wuhan Municipal Policies for Promoting the Development of the Artificial Intelligence Industry, comprises ten key measures. These include supporting technological breakthroughs, enhancing computing power supply, and promoting model innovation, all aimed at accelerating the construction of a full AI industry chain ecosystem. The policies will be application-scenario driven, focusing on core elements such as computing power, models, data, and talent. Wuhan will allocate no less than 10 million yuan annually in computing power service subsidies to ease the burden on SMEs, and provide up to 20 million yuan in support for individual key technology projects.

Reports indicate that Wuhan's AI industry is projected to exceed 70 billion yuan in scale by 2024, with an average annual growth rate exceeding 30% in the past three years and over 1,000 companies. Furthermore, Wuhan has successfully deployed the world's first multi-modal large model with over 100 billion parameters, "Zidong Taichu" 3.0, and a domestic general-purpose large model R&D platform.

The press conference also highlighted policy focuses on key areas, including humanoid robots, intelligent connected vehicles, and dataset construction. For humanoid robots, Wuhan will promote the development of a full industrial chain for core components, striving for breakthroughs in cognitive, decision-making, and collaborative capabilities. For intelligent connected vehicles, Wuhan will promote the early mass production of intelligent driving models and collaborate with companies such as Huawei and Baidu. Furthermore, dataset construction will promote the classified development of public, enterprise, and personal data to build high-quality datasets.