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The Gaussian distribution (also known as the normal distribution) is the most fundamental and widely used probability model in statistics and data science. Its "bell curve" describes the distribution patterns of numerous natural phenomena and social data. This article, from the perspective of in-depth news reporting, systematically analyzes the basic principles, mathematical formulas, and classic applications of the Gaussian distribution...

This article, from a news reporting perspective, focuses on five key techniques used by AI platforms and enterprises in model compression and inference acceleration: quantization, pruning, knowledge distillation, lightweight architecture design, compilers, and hardware acceleration. The content covers mainstream methodologies...

Human-feedback-based reinforcement learning (RLHF) is poised to become an indispensable core technology for large-scale model training and intelligent upgrades in the AI field by 2025. This article comprehensively reviews the fundamental principles of RLHF, its differences from traditional RL, key training processes, and mainstream application tools, and delves into data bottlenecks, reward models, etc.

Transfer learning is transforming AI development. Newcomers can leverage it to save data resources, accelerate prototype iteration, and optimize model performance even with limited samples. This article details the fundamentals, mainstream methods, practical processes, and tools of transfer learning...