What AI Is and Isnt: A Laypersons Guide to How LLMs Actually Work

This article is the first part of a five-part series aimed at demystifying AI for non-experts. It explains that large language models are prediction engines, not thinking machines, and breaks down core concepts like vectors, embeddings, tokens, transformers, self-attention, and position encoding. It also covers training processes (pre-training and fine-tuning), why models hallucinate, and common misconceptions about AI capabilities. The series promises to cover free AI tools, ChatGPT/Claude deep dives, specialized AI tools, and advanced topics like local models. The content is educational and focused on AI technology, making it highly relevant to IT/TECHNOLOGY.