AI Glossary: Letter "I"

Image Segmentation is a computer vision process of partitioning a digital image into multiple segments (sets of pixels), assigning a label to every pixel to outline exact boundaries of objects.

An Imbalanced Dataset is a training dataset where one class (or category) is significantly overrepresented compared to other classes, causing models to favor the majority class.

In-Context Learning (ICL) is the emergent ability of pre-trained Large Language Models to learn new tasks from examples provided in the prompt context without gradient updates.

Indirect Prompt Injection is a security exploit where an attacker embeds malicious instructions inside untrusted third-party data (like web pages, uploaded PDFs, or emails) that an AI agent is instructed to read. When the agent processes the document, the hidden prompt overrides the system instructions and hijacks the agent.

Induction Heads are a specialized two-head attention circuit mechanism in Transformer neural networks that implement in-context pattern copying. A Previous Token Head attends to prior occurrences of a token, while an Induction Head looks back to locate tokens that succeeded it in previous contexts, allowing models to replicate multi-step patterns and complete zero-shot copying.

Inductive Bias refers to the assumptions a machine learning algorithm uses to predict outputs for unseen inputs. It prioritizes specific solutions based on the structural design of the model.

Inference is the process of using a trained AI model to make predictions or generate text based on new inputs. During inference, data flows forward through the neural network to produce an output, without modifying the model's weights.

An Intelligent Agent is an autonomous entity that perceives its environment through inputs, makes rational decisions based on goals, and executes actions using tools to achieve outcomes.