AI Dictionary

A

Algorithm

A set of rules or processes followed by AI to solve problems or make decisions

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Artificial Intelligence (AI)

The broad field of creating systems that simulate human intelligence

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B

Backpropagation

A key algorithm for training neural networks by adjusting weights based on errors

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Bias

Systematic errors in AI models often due to skewed data or design choices

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C

Chatbot

An AI system designed to simulate human conversation

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Convolutional Neural Network (CNN)

A type of neural network commonly used for image recognition

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D

Data

The raw information used to train and operate AI systems

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Deep Learning

A subset of machine learning using multi-layered neural networks

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E

Ethics

Moral principles guiding the development and use of AI

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Expert System

An AI program that mimics human expertise in specific domains

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F

Feature Engineering

The process of selecting and transforming data for better AI performance

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Fuzzy Logic

A reasoning approach in AI that handles uncertainty and imprecise data

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G

Generative AI

AI that creates new content like text images or music

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Gradient Descent

An optimization technique to minimize errors in machine learning models

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H

Heuristic

A practical problem-solving approach in AI often based on experience

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Hyperparameter

Settings tuned before training an AI model to control its behavior

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I

Inference

The process of making predictions or decisions using a trained AI model

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Intelligence

The ability of AI to perform tasks requiring reasoning learning or perception

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J

Joint Probability

A statistical concept used in AI to model relationships between variables

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Jupyter Notebook

A tool widely used for developing and testing AI code interactively

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K

K-Means

A popular clustering algorithm in machine learning

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Knowledge Representation

How AI stores and organizes information to reason about the world

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L

Large Language Model (LLM)

AI models trained on vast text data for natural language tasks

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Learning Rate

A hyperparameter controlling how much an AI model adjusts during training

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M

Machine Learning (ML)

A subset of AI where systems learn from data without explicit programming

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Model

A mathematical representation of a system or process in AI

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N

Natural Language Processing (NLP)

AI techniques for understanding and generating human language

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Neural Network

A computational model inspired by the human brain central to deep learning

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O

Optimization

The process of improving an AI model's performance or efficiency

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Overfitting

When an AI model learns training data too well failing to generalize to new data

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P

Pattern Recognition

AI's ability to identify trends or structures in data

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Prediction

The output of an AI model based on input data

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Q

Q-Learning

A reinforcement learning algorithm for decision-making

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Quantization

Reducing the precision of numbers in AI models to improve efficiency

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R

Recurrent Neural Network (RNN)

A neural network designed for sequential data like time series or text

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Reinforcement Learning

A type of ML where agents learn by trial and error to maximize rewards

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S

Singularity

A hypothetical future point where AI surpasses human intelligence

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Supervised Learning

ML where the model is trained on labeled data

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T

Training

The process of teaching an AI model using data

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Transformer

A neural network architecture pivotal in modern NLP and generative AI

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U

Underfitting

Underfitting happens when a machine learning model is too simple, meaning it fails to learn the important patterns in the data.

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Unsupervised Learning

ML where the model finds patterns in unlabeled data

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V

Validation

Testing an AI model on a separate dataset to evaluate its performance

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Vector

A mathematical representation of data (e.g. words or features) in AI models

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W

Weak AI

AI designed for specific tasks as opposed to general intelligence

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Weights

Parameters in a neural network adjusted during training to improve accuracy

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X

XAI (Explainable AI)

Techniques to make AI decision-making transparent and understandable

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XOR Problem

A classic test of a neural network's ability to learn non-linear patterns

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Y

Yield

In AI often refers to the output or performance gain from a model or process

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YOLO (You Only Look Once)

A real-time object detection algorithm in computer vision

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Z

Z-Score

A statistical measure used in AI for data normalization or anomaly detection

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Zero-Shot Learning

AI's ability to perform tasks without prior specific training examples

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