2023 marks a year of explosive growth for large language models in artificial intelligence, with several concepts and English abbreviations emerging this year, leading to confusion and even bewilderment.
-
LLM: Large Language Model, refers to models designed to understand and generate human language. LLMs are characterized by their massive scale, containing hundreds of billions of parameters, capable of capturing complex language patterns, including syntax, semantics, and some context information, thereby generating coherent and meaningful text. Examples of typical large language models include ChatGPT, GPT-4, BERT, and Wenxin Yiyan.
-
GPT: Generative Pre-training Transformer, a large-scale natural language generation model developed by OpenAI based on the Transformer architecture.
-
AIGC: Artificial Intelligence Generated Content, refers to content generated using AI technology, such as AI writing articles, creating art, or even making videos.
-
AGI: Artificial General Intelligence, aims to create a system that can think, learn, and perform various tasks like a human, becoming an all-powerful “super brain” that may surpass humans in any field in the future.
In addition to these concepts, if you wish to delve deeper into the details and advancements of these technologies, I recommend reading the following books.
01 “ChatGPT Driven Software Development”
“ChatGPT Driven Software Development” Innovations and Practices of AI in the Full Software Development Process
Recommendation:Written by Chinese IT leader Chen Bin, this book details the application of ChatGPT throughout the software development process, significantly enhancing development efficiency and shaping engineers’ competitive advantages in the AI era.
02 “ChatGPT Principles and Practice”
“ChatGPT Principles and Practice” Algorithms, Technologies, and Privatization of Large Language Models
Recommendation:Written by senior AI experts from BAT and large model technology experts, including MOSS system lead Qiu Xipeng and many others, this book systematically organizes and deeply analyzes the core technologies, algorithm implementations, working principles, and training methods of ChatGPT, providing abundant code and annotations.
03 “Neural Networks and Deep Learning”
“Neural Networks and Deep Learning” Set
Recommendation:Rated 9.5 on Douban! A masterpiece by Professor Qiu Xipeng from Fudan University, recommended by Zhou Zhihua and Li Hang! This is the officially published version of the highly praised deep learning lecture notes. It systematically organizes the knowledge system of deep learning, explaining the principles, models, and methods of deep learning from simple to complex. This book is more suitable for Chinese readers. “Neural Networks and Deep Learning: Cases and Practices” is a companion case to Professor Qiu Xipeng’s “Neural Networks and Deep Learning,” deeply integrated with the original book, interpreting the theoretical content from a practical perspective. A joint effort by Professor Qiu Xipeng from Fudan University and the Baidu PaddlePaddle R&D team.
04 “AIGC Reshaping Education”
“AIGC Reshaping Education: AI Large Models Driven Educational Reform and Practice”
-
Recommendation:Leading guide for education and learning actions in the ChatGPT era, greatly assisting teachers, parents, and students to stay ahead in future competitions, written by Liu Wenyong, General Manager of College Student Business at Gaotu Education Technology Group.
Recommended by multiple educators and entrepreneurs.Includes accompanying video explanations, continuously updated with cutting-edge knowledge in the AIGC field.
05 “Artificial General Intelligence”
“Artificial General Intelligence: Origins and Future”
Recommendation:A must-read book on artificial intelligence.Since at least the 1950s, there has been extensive promotion that a machine capable of matching the full range and level of human intelligence would soon be created.Now, we have successfully created machines that can solve specific problems with accuracy that meets or even exceeds that of humans, but we still cannot achieve general intelligence.This book aims to discuss what efforts are still needed to achieve not only specialized intelligence but also general intelligence.
If you are interested in intelligence, want to learn more about how to build autonomous machines, or are concerned that these machines may one day dominate the world in a manner referred to as the “technological singularity,” please read this book.
Recent Live Broadcasts Welcome to Schedule
Source: IT Reading Rankings
Editor: Li Yuhan
Reviewer: Li Shuanglei
Statement: If there are copyright issues with the videos, images, or text used in this article, please inform us immediately, and we will confirm copyright based on the proof materials you provide and pay remuneration according to national standards or delete the content immediately!
