Latent Atlas

Latent Atlas is an offline guide to artificial intelligence and neural networks, designed to explain important concepts without heavy formulas or academic language. Explore a catalog covering fundamental architectures from simple perceptrons to transformers, diffusion models, and reinforcement learning systems. Each entry includes a short explanation, key facts, a sequence of training steps, and notes about limitations and common mistakes. Topics are organized by difficulty, making it easier to start with basic concepts and gradually move toward more advanced material. Use the comparison mode to place two approaches side by side and choose which one better fits a given task. Results from each comparison series are saved, allowing you to see which models and approaches were selected most often. Mark topics as read, rate them with emoji reactions, and pin important entries for quick access later. A weekly learning goal helps you maintain a steady pace and see how many topics you have explored. Badges unlock through actual activity, including reading entries, adding ratings, and completing comparison sessions. All content is fixed and fully available offline. Reading progress, ratings, pinned topics, comparison results, and achievements are stored locally on your device. No registration, accounts, cloud synchronization, or internet connection is required.