📄 中文摘要
在人工智能领域，序列数据的顺序不仅仅是细节，而是整个意义。语言和代码的例子表明，顺序的重要性。为了解决序列问题，人工智能经历了两个主要的架构时代：首先是递归神经网络（RNN），它们将句子视为类似于链表的结构，依赖于前后信息的传递。RNN在理解序列时存在一定的局限性，尤其是在长序列的情况下，导致信息遗失。变压器（Transformers）架构的出现，彻底改变了这一局面，通过自注意力机制，能够同时处理序列中的所有元素，从而提高了理解和生成的能力，成为当前AI领域的主流技术。
什么是变压器，它们为何主导人工智能领域？
出处: What are Transformers, Why do they Dominate the AI World?
发布: 2026年2月15日
📄 English Summary
What are Transformers, Why do they Dominate the AI World?
In the field of AI, the order of sequence data is not just a detail but the entire meaning. Examples from language and code illustrate the importance of order. To address sequence problems, AI has evolved through two major architectural eras: first, Recurrent Neural Networks (RNNs), which treat sentences like linked lists, relying on the passage of information from one element to the next. RNNs have limitations, especially with long sequences, leading to information loss. The emergence of Transformers has revolutionized this landscape by utilizing self-attention mechanisms, allowing the model to process all elements of a sequence simultaneously, thereby enhancing understanding and generation capabilities, making it the dominant technology in the AI field.