#大模型架构

3 related articles

2026年6月3日·2 min

The "Worse is Better" Philosophy of Large Model Design: Why Simple and Brutal Beats Refined and Complex

Analyzing the "worse is better" philosophy in large model architecture: why DeepSeek V4 dropped N-gram, why Transformer dominates AI, and three iron laws of simple, efficient model design.

DeepSeek V4 Deep Technical Breakdown: Million-Token Context and Extreme Cost Efficiency

Deep Dives

2026年6月2日·3 min

DeepSeek V4 Deep Technical Breakdown: Million-Token Context and Extreme Cost Efficiency

Deep analysis of DeepSeek V4's core architecture: Hybrid Compressed Attention, Manifold-Constrained Hyperconnection, and MUON optimizer—how they cut inference costs by 10x and enable million-token context processing.

Core Principles of the Transformer Architecture: A Deep Dive into Self-Attention Mechanisms and Engineering Optimizations

Deep Dives

2026年6月2日·4 min

Core Principles of the Transformer Architecture: A Deep Dive into Self-Attention Mechanisms and Engineering Optimizations

Deep dive into Transformer architecture covering self-attention QKV mechanics, Encoder-Decoder structure, Flash Attention memory optimization, RoPE positional encoding, and GQA inference acceleration.