In recent years, artificial intelligence has made significant leaps, primarily due to large language models (LLMs). LLMs are very good at understanding and generating human-like text, leading to the creation of various new tools, such as advanced chatbots and AI writers. Although LLMs excel at generating fluent, human-like text, they sometimes struggle with factual accuracy. … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and enterprise researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reposted … Read more
Detailed Explanation of RAG 2.0 Architecture The so-called RAG, short for Retrieval-Augmented Generation, combines retrieval and generation technologies to enhance the effectiveness of text generation tasks. Its working principle combines the advantages of retrieval models and generation models to address some challenges and issues in text generation. RAG 2.0, on the other hand, is an … Read more
Introduction Many product managers and engineers familiar with RAG often complain, “It only takes a week to produce a demo with RAG, but it takes at least six months to reach a production-level standard!” This is a realistic issue for the current industrial implementation of RAG. The RAG framework is very simple and understandable, and … Read more
Beginner’s Guide: The Easiest Claude Assistant Tutorial! Today, I want to discuss the Claude AI assistant with everyone, helping you thoroughly understand what Claude really is. When it comes to knowing and effectively using Claude, I have summarized a 3+2 model, which consists of 3 foundational understandings and 2 advanced applications. This model is based … Read more
Author: Jacob, Code Intelligent Copilot & High-Performance Distributed Machine Learning SystemOriginal: https://zhuanlan.zhihu.com/p/18653363414>>Join the Qingke AI Technology Group to exchange the latest AI technologies with young researchers/developers Recommended Reading Interpretation of MiniMax-01 Technical Report Interpretation of DeepSeek-V3 Technical Report Comparison of MiniMax-01 and DeepSeek-V3 Aspect MiniMax-01 DeepSeek-V3 Model Architecture Based on linear attention mechanism, using hybrid … Read more
In the vast universe of software development, every small defect can potentially trigger a system failure. Therefore, accurately locating defects and predicting potential issues during the software testing phase is crucial for ensuring software quality. In recent years, the introduction of AI agents has provided new solutions to this challenge. This article will delve into … Read more
The wave of artificial intelligence is surging, and AI Agents are like the intelligent helmsmen of the future, guiding the course of technological innovation. They are no longer simple lines of code but intelligent entities capable of autonomous learning, decision-making, and task execution. They exhibit intelligence that surpasses conventional norms in perception, decision-making, and execution, … Read more
Personal Opinion: The commercial hype around intelligent agents is currently rampant, but there are very few “killer applications” that have landed successfully. I believe the main reason is that the application direction of intelligent agents has gone astray. Large language models are probabilistic models, and applying a single intelligent agent in a scenario with high … Read more
“If models can be trained, can intelligent agents be trained too?” The answer is, yes! Crew.ai provides training methods for intelligent agents. Through training, the decision-making and problem-solving capabilities of the agents can be enhanced. The core training method is autonomous learning and iterative training, this method emphasizes the agent’s continuous learning and optimization of … Read more