How Large Language Models Work — From Transformers to Conversational AI

Short summary

Large Language Models work by predicting the next token in a sequence using Transformer architecture with attention mechanisms that identify relevant context. Encoder models excel at understanding input while decoder models generate output step-by-step; real-world conversational AI systems wrap additional components like safety filters, retrieval systems, and memory management around this core LLM engine.

• •LLMs predict next tokens iteratively using Transformer attention mechanisms
• •Encoder models understand input; decoder models generate output; encoder-decoder models do both
• •Conversational AI products add safety filters, retrieval systems, memory, and tool use around the core LLM

Generated with AI, which can make mistakes.