Core Concepts Behind Modern AI Systems
Modern AI systems may look diverse on the surface, but under the hood they rely on a small set of recurring architectural and training ideas. This article distills foundational concepts—ranging from tokenization and decoding to RAG, diffusion models, and LoRA—that every ML engineer should understand to design, debug, and reason about real-world AI systems.