Source: Machine Heart This article contains 3744 words, and is recommended for a reading time of 8 minutes. Through this article, we will explain how to build models for natural language, audio, and other sequential data. Since Andrew Ng released the deeplearning.ai courses, many learners have completed all the specialized courses and meticulously created course … Read more
Today, let’s continue to introduce a “wheel”. In this era of information explosion, data is no longer a scarce resource; it is everywhere, like air. However, data itself does not equal wisdom. We are like boats floating in an ocean, surrounded by endless waters, and only by mastering the compass that guides our direction can … Read more
Selected from GitHub Author: Jay Alammar Contributors: Wang Zijia, Geek AI If you are a natural language processing practitioner, you must have heard of the recently popular BERT model.This article is a detailed tutorial on using a simplified version of the BERT model—DisTillBERT to complete the sentiment classification task of sentences, making it an invaluable … Read more
Large language models (LLMs) have revolutionized the field of artificial intelligence (AI) by enabling human-like text generation and natural language understanding. However, their reliance on static training data limits their responsiveness to dynamic real-time queries, resulting in outdated or inaccurate outputs. Retrieval-Augmented Generation (RAG) serves as a solution by integrating real-time data retrieval to enhance … Read more
In the field of artificial intelligence, large language models (LLMs) have achieved significant accomplishments. However, due to their reliance on static training data, they often struggle to respond effectively to dynamic real-time queries. Retrieval-Augmented Generation (RAG) technology has emerged, bringing new hope to address this issue. Agentic RAG further breaks through the limitations of traditional … Read more
Introduction This article delves into the essence, applications, and writing techniques of prompts. By defining prompts as expressions and discovering their potential as a “universal language” for communication with existing entities, the author shares numerous unique insights. Through the quadrant method, the key points for writing prompts in different situations are elaborated. Additionally, it introduces … Read more
Guide by Ali Mei Prompt engineering does not require complex programming knowledge; anyone can use prompt engineering to become an AI master. This article only discusses prompt engineering and does not cover model training or other content. It only discusses text generation and does not involve image-related fields. Background In this rapidly changing technological era, … Read more
Hello everyone, I am your tech blogger. Today, I want to share with you a new product that may revolutionize the programming world—Trae, a free AI programming and learning tool launched by ByteDance. If you are a developer or have a strong interest in programming, then join me to explore the charm of Trae. 1. … Read more
With the rapid development of artificial intelligence technology, AI aggregation tools have gradually become essential tools for various industries to improve efficiency and enhance intelligent services. AI aggregation tools can integrate multiple AI applications, providing users with one-stop intelligent services. So, what AI aggregation tools are available? In this article, we will compare several common … Read more
Since Tomas Mikolov from Google proposed Word2Vec in “Efficient Estimation of Word Representation in Vector Space”, it has become a fundamental component of deep learning in natural language processing. The basic idea of Word2Vec is to represent each word in natural language as a short vector with a unified meaning and dimension. As for what … Read more