1.Origin Transformers are an important deep learning architecture that originated in the fields of computer science and artificial intelligence. They have achieved remarkable success in natural language processing and other sequential data tasks. The history and evolution of this architecture are worth exploring. The story of Transformers began in 2017, when Vaswani et al. first … Read more
Click on the above “Beginner Learning Visuals” to select “Star” or “Pin” Important content delivered promptly Author: Wang Bo Kings, Sophia Overview of the Content of This Article: Wang Bo Kings’ Recent Learning Notes on Transformer Recommended AI Doctor Notes Series Weekly Zhi Hua’s “Machine Learning” Handwritten Notes Officially Open Source! Printable version with PDF … Read more
Author: Wang Chen, Who Asks Questions@Zhihu (Authorized) Source: https://www.zhihu.com/question/362131975/answer/3058958207 Editor: Jishi Platform Why Summarize Transformers Through Eighteen Questions? There are two reasons: First, the Transformer is the fourth major feature extractor after MLP, RNN, and CNN, also known as the fourth foundational model; the recently popular chatGPT is also built on the Transformer, highlighting its … Read more
Transformer is a model that utilizes the attention mechanism to improve the training speed of models. For more information about the attention mechanism, you can refer to this article (https://zhuanlan.zhihu.com/p/52119092). The transformer can be said to be a deep learning model that is entirely based on the self-attention mechanism, as it is suitable for parallel … Read more
Is there anyone who still doesn’t understand how the Transformer works in 2024?Come and try this interactive tool. In 2017, Google introduced the Transformer in the paper “Attention is All You Need,” which became a major breakthrough in deep learning. The paper has been cited nearly 130,000 times, and all models in the subsequent GPT … Read more
Click on the above “Beginner’s Visual Learning” to select “Add to Favorites” or “Pin” Essential content delivered immediately Source: Python Data Science This article is about 7200 words long and is recommended to read in 14 minutes. In this article, we will explore the Transformer model and understand how it works. 1. Introduction Google’s BERT … Read more
Introduction The transformer is a framework that cannot be overlooked in the field of NLP and even deep learning as a whole. Most large language models (LLMs) are trained using it to generate models, so the transformer is a framework that every robot developer or artificial intelligence developer cannot bypass. This article will gradually unveil … Read more
This article will cover theessence of Transformer, the principles of Transformer, and improvements in Transformer architecture in three aspects to help you understand Transformer. 1. Essence of Transformer Transformer Architecture: It mainly consists of four parts: input section (input-output embeddings and position encoding), multi-layer encoder, multi-layer decoder, and output section (output linear layer and Softmax). … Read more
Abstract: This article analyzes the characteristics of ChatGPT from aspects such as application models, application feedback, application scope, and application ecology. It discusses the impact of ChatGPT on economic and social development in terms of promoting high-quality economic growth and forcing the transformation and upgrading of the labor structure. It also provides insights for the … Read more
Source: Chen Wei Talks on Chips, This article will introduce the characteristics, functions, technical architecture, limitations, industrial applications, investment opportunities, and future of ChatGPT. Author: Dr. Chen Wei, the author previously served as the chief scientist of a Huawei-affiliated natural language processing (NLP) company. Integrated storage/computing/GPU architecture and AI expert, senior title. Expert in the … Read more