Click above toJoin the Computer Vision Alliance for more insights For academic sharing only, does not represent the stance of this public account, contact for removal if infringing Reprinted from: Machine Heart Recommended AI Doctor’s Notes Series Zhuhua Zhou’s “Machine Learning” hand-pushed notes have officially been open-sourced! Printable version with PDF download link attached CNN … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered promptly! From | Zhihu Author | JayLou Link | https://zhuanlan.zhihu.com/p/53682800 Editor | Deep Learning Matters public account This article is for academic sharing only. If there is any infringement, please contact us to delete it. This article summarizes the attention mechanism in natural language … Read more
Programmers transitioning to AI are following this account👇👇👇 1. Difference Between Attention Mechanism and Self-Attention Mechanism The difference between Attention mechanism and Self-Attention mechanism The traditional Attention mechanism occurs between the elements of the Target and all elements in the Source. In simple terms, the calculation of weights in the Attention mechanism requires participation from … Read more
The Attention mechanism is a technique in deep learning, particularly widely used in Natural Language Processing (NLP) and computer vision. Its core idea is to mimic the human attention mechanism, where humans focus on certain key parts of information while ignoring less important information. In machine learning models, this can help the model better capture … Read more
Introduction This sharing focuses on the implementation path and development prospects of multimodal RAG. The core topics cover five aspects: 1. Multimodal RAG based on semantic extraction 2. Multimodal RAG based on VLM 3. How to scale multimodal RAG based on VLM 4. Choice of technical routes 5. Q&A session Speaker｜Jin Hai Infiniflow Co-founder Editor｜Wang … Read more
1. What is Mixture of Experts (MoE)? In the field of deep learning, the improvement of model performance often relies on scaling up, but the demand for computational resources increases sharply. Maximizing model performance within a limited computational budget has become an important research direction. The Mixture of Experts (MoE) introduces sparse computation and dynamic … Read more
Comparison table Aspect MiniMax-01 DeepSeek-V3 Model Architecture Based on linear attention mechanism, using a hybrid architecture (Hybrid-Lightning), and integrating MoE architecture. Based on Transformer architecture, using MLA and DeepSeekMoE architectures, and introducing auxiliary loss-independent load balancing strategies. Parameter Scale 456 billion total parameters, 45.9 billion active parameters. 671 billion total parameters, 37 billion active parameters. … 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
This article focuses on explaining MLA (Multi-Head Latent Attention). Note: During my learning process, I usually encounter some knowledge blind spots or inaccuracies, and I recursively learn some extended contexts. This article also interprets the background of MLH’s proposal, the problems it aims to solve, and the final effects step by step along with some … Read more