8 AI model architectures, visually explained: Everyone talks about LLMs, but there's a whole family of specialized models doing incredible things. Here's a quick breakdown: 1. LLM (Large Language Models) Text goes in, gets tokenized into embeddings, processed through transformers, and text comes out. ↳ GPT, Claude, Gemini, Llama. 2. LCM (Large Concept Models) Works at the concept level, not tokens. Input is segmented into sentences, passed through SONAR embeddings, and then uses diffusion before output. ↳ Meta's LCM is the pioneer. 3. LAM (Large Action Models) Turns intent into action. Input flows through perception, intent recognition, task breakdown, then action planning with memory before executing. ↳ Rabbit R1, Microsoft UFO, Claude Computer Use. 4. MoE (Mixture of Experts) A router decides which specialized "experts" handle your query. Only relevant experts activate. Results go through selection and processing. ↳ Mixtral, GPT-4, DeepSeek. ...