AI Model vs AI App: What Is the Difference?
An AI model is the engine; an AI app is the car you drive. The distinction decides who bills you, whose privacy policy applies, who handles support,…
EXPLORE THE TOPIC
AI Fundamentals
Core concepts, limitations, and output evaluation for beginners.
16 published articlesAI Hardware Explained: RAM, VRAM, Quantization, and Model Size
Running a local language model is mostly a memory-planning problem. This guide explains how parameter count, quantization, VRAM, RAM, context length, and runtime overhead determine whether a…
How Large Language Models Work: Tokens, Context, Training, and Inference
Large language models are next-token predictors, and almost every practical constraint they have follows from four ideas: how text becomes tokens, how the context window limits what…
RAG vs Fine-Tuning: How to Choose an Approach for Your Project
Start with retrieval augmented generation (RAG) when your project must answer questions from documents that change and cite sources. Choose fine-tuning when the model needs to match…