爱诗王长虎、谢旭璋：“不会创业” 的创始人，怎么做出用户量第一的 AI 视频产品

Core Viewpoint - The article discusses the rapid growth and innovative approach of Aishi Technology, particularly through its product PixVerse, which has gained significant traction in the AI video generation market, especially among younger users [4][6][10]. Group 1: Company Overview - Aishi Technology, founded by Wang Changhu and Xie Xuzhang, has over 60 million global users, with PixVerse achieving over 16 million monthly active users within just six months of launch [4][6]. - The company focuses on both model development and application, catering to both professional video creators and general consumers [4][10]. Group 2: Product Features and User Engagement - PixVerse allows users to create engaging videos easily by uploading photos and selecting templates, leading to viral content shared on platforms like TikTok and Instagram [4][5][6]. - The product has seen significant success, with a template that became popular on the US iOS download charts and videos created with PixVerse surpassing 1 billion views [6][10]. Group 3: Market Strategy and Competition - Aishi Technology aims to penetrate the Chinese market while also targeting global users, believing that the demand for video generation is universal [8][10]. - The company differentiates itself from competitors by leveraging its proprietary video models, which provide a unique user experience compared to existing products [10][11]. Group 4: Technological Advancements - Aishi has released multiple versions of its model, with V3 significantly improving user experience by reducing wait times for video generation to under 10 seconds [6][9][20]. - The company emphasizes the importance of continuous model improvement and user feedback in shaping product development [20][21]. Group 5: Industry Perspective - The video generation industry is still evolving, with Aishi Technology positioned to capitalize on the growing demand for content creation tools [10][22]. - The founders believe that video generation has been undervalued compared to large language models, presenting both a challenge and an opportunity for the company [24][25].