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千里科技(601777.SH)AI战略布局完成第一步,新品牌、新计划开启新阶段
Chongqing Qianli TechnologyChongqing Qianli Technology(SH:601777) 智通财经网·2025-09-28 13:42

Core Insights - The event "AI Chongqing Smart Driving Night" showcased the integration of AI in the automotive industry, emphasizing the potential of "AI+Car" in transforming the sector [1][3] - The company Qianli Technology announced its new brand name "AFARI" and logo, signaling its commitment to accelerate AI and international development [1][19] - Qianli Technology aims to establish itself as a world-class tech company by leveraging Chongqing's robust industrial chain and its own AI capabilities [3][5] Group 1: Event Highlights - The event featured discussions among industry leaders, including Qianli Technology's chairman and executives from major automotive companies, focusing on the future of AI in vehicles [3][5] - A live demonstration of Qianli's intelligent driving system was conducted in challenging urban environments, showcasing its capabilities in complex road conditions [1][12] - The event concluded with a spectacular drone show, illustrating the vision of AI's future impact on daily life [21] Group 2: Company Developments - Qianli Technology has completed its business layout in intelligent driving, intelligent cockpit, and smart mobility within a year, driven by AI technology [5][9] - The company is developing a comprehensive Robotaxi service, aiming to deploy over 1,000 vehicles in ten cities within 18 months [10][19] - The new brand "AFARI" symbolizes a vision of a future where AI enhances human life, with a focus on creating a unified operating system and intelligent assistants [19][18] Group 3: Technological Innovations - Qianli's intelligent driving system utilizes advanced AI models to redefine industry standards, achieving high safety and adaptability in real-world scenarios [5][14] - The integration of large models in smart cockpits is expected to significantly enhance user experience and customer value [7][9] - The company is committed to reducing reliance on traditional data models, focusing on a sustainable approach to AI development [16][19]