Issue #53 • Mar 12, 2026 Transfer Learning: Build Powerful AI Models Without Training From Scratch Learn how transfer learning lets you reuse pre-trained models to build AI faster, cheaper, and with far less data. Read issue
Issue #52 • Mar 06, 2026 Model Quantization: How a 70B Model Fits on Your Laptop Learn how quantization shrinks AI models by 2-4x with minimal quality loss, and why it matters for cost and deployment. Read issue
Issue #51 • Mar 03, 2026 Temperature & Sampling: Why Your AI Gives Different Answers Every Time Learn how temperature, top-p, and sampling settings control AI output randomness and when to use each. Read issue
Issue #50 • Feb 27, 2026 Tokens & Context Windows: Why ChatGPT Has Limits Tokens & Context Windows Explained Read issue
Issue #49 • Feb 18, 2026 Three Ways to Customize LLMs: Prompting, RAG, and Fine-Tuning Three approaches to customize LLMs: implementation guide with code examples. Read issue
Issue #48 • Feb 12, 2026 What is RAG? Building Production AI Without Training Models Production AI without model training: How RAG works with code examples. Read issue
Issue #47 • Feb 04, 2026 Embeddings & Vector Spaces: How AI Understands Meaning How AI turns words into meaning using vectors Read issue
Issue #46 • Jan 30, 2026 Transformers: The Architecture That Changed Everything The architecture behind ChatGPT, Claude, and every major AI breakthrough - explained simply. Read issue
Issue #45 • Jan 23, 2026 Attention Mechanisms: Teaching Neural Networks Where to Look Weighted embeddings and why attention replaced RNNs for modern AI. Read issue
Issue #44 • Jan 14, 2026 Recurrent Neural Networks: Processing Sequences and Time How RNNs process sequences through hidden state loops and LSTM gates. Read issue
Issue #43 • Jan 08, 2026 Convolutional Neural Networks: How AI Sees Images From edge detection to face recognition: How CNNs use sliding filters and parameter sharing to understand images with 1000x fewer parameters. Read issue
Issue #42 • Jan 06, 2026 AI in 2026: The 'Show Me the Money' Year Week 1 of 2026: ROI pressure, quantum bets, transformer plateau, and physical AI Read issue
Issue #41 • Dec 31, 2025 What Are Tensors? (And Why Modern AI Needs Them) The multi-dimensional data structures that power modern AI architectures. Read issue
Issue #40 • Dec 29, 2025 Training Neural Networks: The Complete Learning Loop The complete 7-step training loop: epochs, batches, overfitting, and when to stop. Read issue
Issue #39 • Dec 20, 2025 How Neural Networks Actually Learn (Gradient Descent) What gradient descent is, how it uses gradients to update weights, and why it's the optimization algorithm that makes neural network learning possible Read issue
