📄 中文摘要
在学习大型语言模型（LLMs）时，'变压器'是最先接触到的术语，源自于论文《Attention Is All You Need》。然而，许多人在阅读相关内容时感到困惑，主要原因在于对'神经架构'这一流行术语的理解不足。为了更好地理解变压器的概念，掌握神经网络的基础知识至关重要。文章将神经网络的内容分为五个部分，分别是：神经网络的定义、神经网络的必要性、神经网络的工作原理、神经网络的优势及其应用等。通过这些基础知识的梳理，读者能够更清晰地理解变压器的工作机制。
神经网络：理解变压器的第一步
出处: Neural Networks: The First Step Toward Understanding Transformers
发布: 2026年3月16日
📄 English Summary
Neural Networks: The First Step Toward Understanding Transformers
The term 'Transformer' is often the first encountered when learning about large language models (LLMs), originating from the paper 'Attention Is All You Need.' However, many readers find the material confusing, largely due to a lack of understanding of the popular term 'neural architecture.' Grasping the foundational knowledge of neural networks is essential for comprehending Transformers. The content is divided into five sections: the definition of a neural network, the necessity of neural networks, how they function, their advantages, and their applications. By clarifying these foundational concepts, readers can gain a clearer understanding of the mechanisms behind Transformers.