A visual mental model of how weights and tokens connect

A new open-source repository, "AI for Beginners Visual," offers simple diagrams and everyday analogies to explain core artificial intelligence concepts like tokens, embeddings, and neural networks to non-technical readers. The project, which covers 30 topics from training and inference to hallucination and fine-tuning, aims to bridge the gap between overly technical explanations and superficial overviews. Its creator is seeking GitHub stars to help more people discover the resource.

Simple visuals + everyday analogies that explain AI concepts to everyone — whether you write code or have never opened a terminal. If this helps you finally "get" AI — drop a ⭐. It helps more people find it. AI is everywhere, but most explanations are either too technical walls of math or too fluffy no real understanding . This repo sits in the middle. Every concept gets: - 🧒 An "Explain Like I'm 5" analogy — the one-liner you'll actually remember - 🖼️ A simple diagram — see the idea, don't just read it - 🔧 "How it actually works" — for when you're ready to go deeper - 🌍 A real-world example — where you've already seen it in action No PhD required. No prior coding needed. Just curiosity. | | Concept | One-liner | |---|---|---| | 1 | | 🔤 Token /behnia137/ai-for-beginners-visual/blob/main/concepts/token.md 📍 Embedding /behnia137/ai-for-beginners-visual/blob/main/concepts/embedding.md 🕸️ Neural Network /behnia137/ai-for-beginners-visual/blob/main/concepts/neural-network.md 🏋️ Training vs Inference /behnia137/ai-for-beginners-visual/blob/main/concepts/training-vs-inference.md 💬 Prompt /behnia137/ai-for-beginners-visual/blob/main/concepts/prompt.md 🪟 Context Window /behnia137/ai-for-beginners-visual/blob/main/concepts/context-window.md 🎯 Fine-tuning /behnia137/ai-for-beginners-visual/blob/main/concepts/fine-tuning.md 📖 RAG Retrieval-Augmented Generation /behnia137/ai-for-beginners-visual/blob/main/concepts/rag.md 🌀 Hallucination /behnia137/ai-for-beginners-visual/blob/main/concepts/hallucination.md | | Concept | One-liner | |---|---|---| | 11 | | 👀 Attention /behnia137/ai-for-beginners-visual/blob/main/concepts/attention.md 🌡️ Temperature /behnia137/ai-for-beginners-visual/blob/main/concepts/temperature.md 🔗 Chain of Thought /behnia137/ai-for-beginners-visual/blob/main/concepts/chain-of-thought.md | | Concept | One-liner | |---|---|---| | 15 | | ⚡ GPU /behnia137/ai-for-beginners-visual/blob/main/concepts/gpu.md 📏 Overfitting /behnia137/ai-for-beginners-visual/blob/main/concepts/overfitting.md 🎛️ Parameters / Weights /behnia137/ai-for-beginners-visual/blob/main/concepts/parameters-weights.md 🏛️ Foundation Model /behnia137/ai-for-beginners-visual/blob/main/concepts/foundation-model.md 🗜️ Quantization /behnia137/ai-for-beginners-visual/blob/main/concepts/quantization.md | | Concept | One-liner | |---|---|---| | 21 | | does things, not just chats. 🗄️ Vector Database /behnia137/ai-for-beginners-visual/blob/main/concepts/vector-database.md 🎨 Diffusion Model /behnia137/ai-for-beginners-visual/blob/main/concepts/diffusion-model.md 🎭 GAN /behnia137/ai-for-beginners-visual/blob/main/concepts/gan.md 🪪 System Prompt /behnia137/ai-for-beginners-visual/blob/main/concepts/system-prompt.md 🌈 Multimodal /behnia137/ai-for-beginners-visual/blob/main/concepts/multimodal.md 🛠️ Tool Calling /behnia137/ai-for-beginners-visual/blob/main/concepts/tool-calling.md | | Concept | One-liner | |---|---|---| | 28 | | 📅 Knowledge Cutoff /behnia137/ai-for-beginners-visual/blob/main/concepts/knowledge-cutoff.md 🕵️ Prompt Injection /behnia137/ai-for-beginners-visual/blob/main/concepts/prompt-injection.md 🧭 Alignment & Guardrails /behnia137/ai-for-beginners-visual/blob/main/concepts/alignment.md not to do. 🌅 AGI /behnia137/ai-for-beginners-visual/blob/main/concepts/agi.md php flowchart LR A 💬 Your Prompt -- B 🔤 Split into Tokens B -- C 📍 Turned into Embeddings C -- D 🕸️ Neural Network<br/ the LLM D -- E 🪟 Limited by<br/ Context Window D -- F 📝 Generates Answer F -.- |sometimes| G 🌀 Hallucination H 📚 Your Documents -- |RAG| D I 🎯 Fine-tuning -.- |specializes| D style A fill: dbeafe,stroke: 3b82f6 style D fill: fef3c7,stroke: f59e0b style F fill: dcfce7,stroke: 22c55e style G fill: fee2e2,stroke: ef4444 Read it in orderif you're brand new — each concept builds on the last.Jump aroundif you already know the basics. - Pick a concept from the table above -the-concepts . - Read the analogy. Look at the diagram. - Curious? Read "How it actually works." - Found it useful? Star the repo ⭐ and share it. Know a concept we're missing? Have a better analogy? We'd love your help. See CONTRIBUTING.md /behnia137/ai-for-beginners-visual/blob/main/CONTRIBUTING.md for the simple template — adding a concept takes about 10 minutes. Good first additions: Reinforcement Learning, Mixture of Experts MoE , MCP, Deepfake, Backpropagation, Loss Function, Zero-shot vs Few-shot, Speech-to-Text / Text-to-Speech, Open vs Closed Models, AI Ethics. MIT /behnia137/ai-for-beginners-visual/blob/main/LICENSE — free to use, share, remix, and teach with. Attribution appreciated. Made for curious humans. 🧠 If this made AI click for you, the best thank-you is a ⭐.