LLMs 101: Understanding the Technology Behind ChatGPT, Claude, and Gemini

Short summary

A beginner-friendly explainer covering what large language models are, how they are trained on trillions of tokens, and why they excel at text prediction but struggle with math, reasoning, and factual accuracy. It includes practical getting-started steps for developers using OpenAI APIs, local models via Ollama, and open-source alternatives like Llama and Mistral. The article also outlines current trends including multimodal models, longer context windows, and agentic capabilities.

• •LLMs are neural networks trained on trillions of tokens to predict the next word — not to reason or understand
• •They are good at text generation and code but bad at math, current events, and factual accuracy
• •Developers can start via OpenAI API, local models with Ollama, or open-source models like Llama and Mistral

Generated with AI, which can make mistakes.