5 related articles

A deep dive into Anthropic's Mathematical Framework for Transformer Circuits — covering QK/OV circuits, residual streams, and induction heads in mechanistic interpretability.
Deep DivesUnderstand Transformer through the lens of word continuation. Breaking down language generation into Embedding, Transformer Block, and Probability output modules for intuitive understanding.
Deep DivesAnalyzing 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.
Deep DivesDeep dive into Transformer architecture covering self-attention QKV mechanics, Encoder-Decoder structure, Flash Attention memory optimization, RoPE positional encoding, and GQA inference acceleration.
Deep DivesDeep dive into Agent core logic ReAct (Reasoning + Acting) execution flow, Transformer self-attention mechanism, and essential AI skills for frontend developers including prompt engineering, RAG, and Agent development.