我MiniMax，用实习生处理数据，照样屠榜开源大模型

Core Viewpoint - The article discusses the development and unique features of the MiniMax M2 model, highlighting its performance, data processing techniques, and the rationale behind its design choices, particularly the shift from Linear Attention to Full Attention. Group 1: Model Performance - M2 demonstrated strong performance by winning first place in the AI-Trader simulation competition, earning nearly 3,000 yuan from a starting capital of 100,000 yuan over 20 days [2] - The choice of Full Attention over Linear Attention is presented as a strategic decision aimed at ensuring stability and reliability for commercial deployment [12][53] Group 2: Attention Mechanism - The article emphasizes the debate surrounding the choice of attention mechanisms, with M2's team opting for Full Attention after testing various alternatives, including Efficient Attention, which showed performance degradation with longer context lengths [12][15] - The team argues that the perceived advantages of Efficient Attention are misleading, particularly in complex tasks where it fails to perform as well as Full Attention [18][22] Group 3: Data Processing Techniques - M2's data processing approach is highlighted as mature, allowing even inexperienced interns to achieve expected results, indicating a well-structured data handling process [27] - The team focuses on enhancing the model's generalization capabilities by diversifying data formats and ensuring high-quality data through a rigorous cleaning process [35][38] Group 4: Task Execution and Adaptability - The concept of "Interleaved Thinking" is introduced, allowing the model to dynamically adjust its planning based on real-time execution feedback, improving its adaptability in task execution [46][48] - The training data is designed to simulate real-world scenarios, covering various uncertainties to enhance the model's performance in practical applications [51][52] Group 5: Engineering Philosophy - MiniMax's decision to use Full Attention reflects a pragmatic engineering philosophy prioritizing real-world applicability and stability over merely optimizing for computational efficiency [53][56] - The company aims to create a model that is not just technically advanced but also practical and understandable for developers, emphasizing a systematic approach to problem-solving [57][58]