AI, machine learning, and computer science
Practical articles and interactive tools for builders learning how models work, how software systems behave, and how modern AI gets built.
Interactive tools
Nine playgrounds covering classification, clustering, neural networks, tensors, optimization, memory, sorting, and model architecture — plus a live directory of frontier models.
Build layers, train a small model, and inspect decisions.
Open toolSee how neighbors, distance, and class boundaries interact.
Open toolExperiment with centroids, inertia, and cluster movement.
Open toolExplore tensor shapes and operations with visual feedback.
Open toolStep through optimization on a loss surface.
Open toolTrace stack, heap, references, and runtime state changes.
Open toolStep through classic sorting algorithms bar-by-bar and compare their runtime behavior side by side.
Open toolLoad a trained model and inspect its architecture, layers, and predictions.
Open toolFilter and compare current frontier LLMs by capability, developer, and domain.
Browse directoryLatest articles
Read practical explainers, tutorials, and field notes on AI, software engineering, machine learning, and modern development.
Part 1 of a series on training a simulated Unitree Go1 quadruped with reinforcement learning. Everything here comes from runs on a single RTX 5060 (8 GB) with MuJoCo Playground, MJX/Warp and Brax PPO. We trained a four-legged robot to walk from scratch. Nobody told it how legs work. It got no motion capture, no […]
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Topic library
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Model concepts, applied ML workflows, and AI product notes.
Explore topicFrontend, backend, and architecture patterns for builders.
Explore topicCore algorithms, complexity, and problem-solving patterns.
Explore topicQueries, data modeling, and practical database techniques.
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Technical explainers and tutorials as they publish.
Notes when playgrounds, visualizers, and demos improve.
AI, ML, and systems topics with builder-level detail.