Core Viewpoint - The article emphasizes the challenges faced by AI companies in global expansion, particularly in infrastructure, talent, and business models, with a focus on the integration of high-quality large models and products for effective globalization [2][6]. Group 1: Development and Technical Route of Mureka Model - The Mureka model was initiated in 2020, leveraging existing music processing technologies and data accumulated from a music social product, Starmaker, which holds a significant market position overseas [7]. - The decision to enter the music generation field was based on the observation that the scale of music data is smaller compared to text and video data, leading to lower required investment and training resources [7]. - The company initially explored various technical routes for music generation, ultimately adopting the Diffusion Transformer (DIT) approach, which significantly improved the model's performance [9]. Group 2: Global Promotion Challenges and Non-Acquisition Growth - After developing the model, the company faced challenges in global promotion, particularly the reliance on user acquisition (UA) models, which are less effective in the AI startup landscape [11]. - Non-acquisition growth strategies include leveraging core technological breakthroughs for viral growth, SEO for user acquisition, and GEO optimization, which are essential for companies to explore beyond traditional UA methods [12][13]. Group 3: Product Judgement Standards and Market Opportunities - The article outlines two core judgments for the feasibility of To B products: they serve as "efficiency multipliers" and act as "workflow adhesives" to enhance automation [15]. - For To C products, the focus is on reducing production costs significantly, with AI music generation costing less than 0.1 RMB per song compared to traditional methods costing around 100,000 RMB [16]. - The article highlights the growing competitiveness of Chinese open-source large models, indicating that small and medium enterprises can leverage these models to build new ecosystems and tap into vast market opportunities [17].