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噪声感知计算重分配(Noise-aware Compute Redistriburion
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嚯!国产视频模型的物理水准超神了 | 实测MiniMax海螺02
量子位· 2025-06-19 06:25
Core Viewpoint - The article discusses the launch of the Hailuo 02 video generation model by MiniMax, which successfully addresses the challenges of generating gymnastics videos, showcasing significant advancements in AI-generated content quality and physical realism [2][4][12]. Group 1: Model Features and Performance - Hailuo 02 supports native 1080p resolution and can handle extremely complex physical scenes, outperforming previous models like Veo 3 [4][12]. - The model demonstrates strong physical performance, accurately reflecting real-world physics in generated videos, including reflections and complex movements [5][7]. - Users have reported that Hailuo 02 is superior to Veo 3, indicating a positive reception in the market [11][9]. Group 2: Technical Advancements - Hailuo 02's architecture utilizes Noise-aware Compute Redistribution (NCR), enhancing training and inference efficiency by 2.5 times, allowing for a threefold increase in parameter count and a fourfold increase in training data compared to its predecessor [77][79][82]. - The model's ability to generate videos with high fidelity and low cost positions it as a leader in the video generation field, reflecting the growing capabilities of domestic AI models [84][86]. Group 3: User Experience and Accessibility - New users can experience Hailuo 02 for free, with 500 complimentary points provided for video generation, making it accessible for a wider audience [12][14]. - The model includes pre-set prompts and guidance for users, addressing common challenges in writing prompts for video generation [71]. Group 4: Broader Implications and Future Outlook - MiniMax is expanding its technological capabilities across various modalities, including text, speech, and video, indicating a comprehensive approach to AI development [86][87]. - The ongoing advancements in AI models like Hailuo 02 exemplify the potential for domestic players to lead in the global AI landscape, particularly in video generation [84][88].