Overview
A computational approach where problems are defined as a set of variables, domains, and constraints that must all be simultaneously satisfied.
More in Artificial Intelligence
Few-Shot Learning
Prompting & InteractionA machine learning approach where models learn to perform tasks from only a small number of labelled examples, often achieved through in-context learning in large language models.
Recall
Evaluation & MetricsThe ratio of true positive predictions to all actual positive instances, measuring completeness of positive identification.
Confusion Matrix
Evaluation & MetricsA table used to evaluate classification model performance by comparing predicted classifications against actual classifications.
Tensor Processing Unit
Models & ArchitectureGoogle's custom-designed application-specific integrated circuit for accelerating machine learning workloads.
AUC Score
Evaluation & MetricsArea Under the ROC Curve, a single metric summarising a classifier's ability to distinguish between classes.
AI Inference
Training & InferenceThe process of using a trained AI model to make predictions or decisions on new, unseen data.
ROC Curve
Evaluation & MetricsA graphical plot illustrating the diagnostic ability of a binary classifier as its discrimination threshold is varied.
Ontology
Foundations & TheoryA formal representation of knowledge as a set of concepts, categories, and relationships within a specific domain.