Group 1 - The core focus is on the AI inference market, which is identified as a trillion-dollar opportunity, with a significant increase in remaining performance obligations (RPO) reaching $455 billion [1] - AI inference is characterized as a continuous demand that will be utilized across various scenarios, contrasting with the periodic and resource-intensive nature of AI training [1] - Qiniu Intelligent reported AI-related revenue of 184 million yuan, contributing 22.2% to total revenue, with a notable increase in AI users reaching 15,000 due to the availability of over 50 callable large models [1] Group 2 - Meeting AI inference demand requires reducing end-to-end latency and increasing throughput in production environments, with inference compute needs surpassing training requirements [2] - High-quality, accessible enterprise data is essential for providing actionable insights from inference models, making structured data assets a key resource for entering the "inference era" [2] - Qiniu Intelligent's past 14 years of experience in audio and video cloud services has equipped it with low-latency, high-throughput global real-time nodes and vast storage capabilities, positioning it favorably in the AI cloud service growth curve [2]

Group 1 - The core opportunity in the AI market lies in AI inference, which is expected to be a trillion-dollar market, as highlighted by Oracle founder Larry Ellison [1] - Oracle's remaining performance obligations (RPO) surged to $455 billion, indicating strong future revenue potential [1] - AI training is resource-intensive and cyclical, while AI inference represents a continuous demand for resources, driving sustained growth in AI cloud services [1] Group 2 - Qiniu Intelligent reported AI-related revenue of 184 million yuan, accounting for 22.2% of total revenue, with a user base exceeding 15,000 [2] - The company's AI revenue is primarily derived from AI inference services and computing resources, with over 50 callable large models available [2] - To meet AI inference demands, companies must reduce end-to-end latency and improve throughput under high request pressure, necessitating high-quality enterprise data [2] Group 3 - Qiniu Intelligent leverages its 14 years of experience in audio and video cloud services to enhance its AI cloud services, focusing on low latency and high throughput [3] - The company occupies a dual position in the value chain by providing upstream data and midstream computing infrastructure, leading to long-term revenue growth from inference computing [3] - The integration of private audio and video heterogeneous data into inference models is crucial for the company's growth in AI services [3]