📄 中文摘要
大型语言模型（LLMs）在表面上看似神奇，用户输入一句话，AI便能生成代码、解释物理或撰写电子邮件。然而，在其背后，系统实际上在进行结构化的处理。理解文本的第一步是将句子拆分为更小的单位，称为标记（tokens）。例如，句子“I love artificial intelligence”可以被标记化为一个数组，便于AI进行后续的分析和处理。接下来，模型通过学习大量文本数据，掌握语言的结构和语义，从而生成连贯的输出。这一过程的核心构建块为现代AI模型的运作奠定了基础。
从文字到智能：大型语言模型的实际运作方式（无数学困扰）
📄 English Summary
From Words to Intelligence: How LLMs Actually Work (Without the Math Headache)
Large Language Models (LLMs) appear magical at first glance, allowing users to input a sentence and receive outputs such as code, physics explanations, or email drafts. However, beneath the surface, the system operates in a surprisingly structured manner. The first step in understanding text involves breaking it down into smaller units known as tokens. For instance, the sentence 'I love artificial intelligence' can be tokenized into an array, facilitating further analysis and processing by the AI. Subsequently, the model learns from vast amounts of text data, grasping the structure and semantics of language, which enables it to generate coherent outputs. This core building block lays the foundation for the operation of modern AI models.