Core Viewpoint - The AI application market is undergoing a silent cleansing, with a significant number of companies exiting the market due to high operational costs and lack of sustainable business models [4][5][18]. Group 1: Market Dynamics - Since the launch of ChatGPT until July 2024, 78,612 newly registered AI companies in China have disappeared, accounting for 8.9% of the total new registrations during the same period [5]. - The AI application industry is experiencing a bifurcation, where only products that understand long-term operations can survive through cycles [7]. - The rapid expansion of applications like Quark and Doubao contrasts sharply with the mass exit of companies, indicating a market correction as capital enthusiasm wanes [6][7]. Group 2: AI Entrepreneurship Trends - The AI entrepreneurship wave is driven by a mix of genuine demand and market anxiety, with many companies rushing to enter the AI space without a clear understanding of user needs [9][13]. - The cost of using large models has significantly decreased, with models like GPT-3.5-turbo costing only $0.002 per 1,000 tokens in 2023, a 90% reduction compared to previous versions [10]. - The proliferation of AI applications has led to a situation where almost anyone can leverage large models for entrepreneurship, but many lack the necessary technical maturity [11][13]. Group 3: Challenges Faced by AI Products - Many AI products are failing due to unclear business models and a lack of paying user bases, leading to a cycle of high technical investment and weak revenue generation [22][23]. - The high degree of product homogeneity in the AI space has resulted in a lack of core competitiveness, with many products relying on third-party APIs rather than developing unique technologies [25][27]. - The intense competition in the AI market, exacerbated by the entry of major tech giants, has squeezed the survival space for smaller players, leading to price wars and unsustainable growth strategies [32][33]. Group 4: Strategies for Long-term Viability - Successful AI applications need to cover a broad range of market demands and lower usage barriers, ensuring a wide user base [37]. - Rich product functionality is essential, as single-function applications often struggle to attract a large user market [37][38]. - Advanced technology and diverse data sources are critical for building core competitiveness, allowing applications to create unique user value and maintain relevance in a crowded market [40][41]. Conclusion - The exit of 80,000 AI application companies does not negate the value of AI but highlights the need for products that solve real problems and create tangible value [43]. - The future of AI belongs to those who focus on practical solutions rather than chasing trends [44].