superposition
4 free lessons tagged superposition across AI, Science. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Features, Directions, and Superposition
Why individual neurons are the wrong unit for understanding a neural network, and what the superposition hypothesis says is really going on inside the activations.
Qubits: superposition, measurement, and entanglement
What a qubit actually is, why measurement destroys superposition, how entanglement links qubits, and how the quantum circuit model turns these ingredients into computation.
Sparse autoencoders: reading the features hidden inside a neural network
Why neurons are polysemantic, how the superposition hypothesis explains it, and how sparse autoencoders use dictionary learning to pull a model's activations apart into monosemantic, steerable features, plus the failure modes and the top-k and gated fixes.
Superposition and the qubit
The mathematical object behind a qubit — a complex unit vector in a two-dimensional Hilbert space — and why measurement collapses superposition. The structural difference between a quantum state and a classical bit, expressed in math.