Look up any term in AI.

Ontologies

An ontology is a formal, machine-readable model of a domain — classes, properties and logical axioms a computer can reason over, not just a taxonomy of labels.

Bias in AI (Algorithmic Bias)

Why AI systems produce unfair outcomes: how bias enters through data and proxy labels, and why no model can satisfy every definition of fairness at once.

GPU Computing

Why a graphics chip runs AI: a GPU spends its transistors on arithmetic instead of on making one thread fast — and what that trade wins and costs.

Gradient Boosting

Each tree is fitted to the negative gradient of the loss, not to the residuals — a boosting round worked by hand, and what changes under log loss.

Quantum Computing (QC)

Quantum computing uses qubits — held in superposition and entangled — for exponential speedups on a narrow set of problems, not general computing.

Support Vector Machines (SVM)

A classifier that separates two classes with the widest possible margin, using support vectors and the kernel trick to handle non-linear data.