A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Game AI (Artificial Intelligence in Games): Game AI refers to the use of AI techniques to create intelligent behaviors and decision-making for non-player characters (NPCs) or opponents in video games, enhancing gameplay and realism.

GAN (Generative Adversarial Network): GANs are a type of neural network used in AI to generate data, such as images or text, by pitting two networks, a generator, and a discriminator, against each other in a training process.

Generalization: Generalization in AI refers to the ability of a trained model to perform well on unseen or new data, indicating its capacity to learn and apply learned patterns effectively.

Genetic Algorithm: Genetic algorithms are optimization techniques inspired by the process of natural selection, often used in AI for solving complex problems or finding optimal solutions.

Genetic Programming: Genetic Programming (GP) is an AI technique that evolves computer programs using principles from evolutionary algorithms. It’s used to automatically generate solutions for various problems by iteratively modifying and improving programs over generations.

GeoAI (Geospatial Artificial Intelligence): GeoAI involves the use of AI and machine learning to analyze geospatial data, such as maps, satellite imagery, and location-based information, for applications like urban planning and environmental monitoring.

Gesture recognition: Gesture recognition is the AI-powered technology that interprets human gestures, such as hand movements or facial expressions, often used in human-computer interaction and virtual reality.

GPT (Generative Pre-trained Transformer): GPT is a series of language models based on the Transformer architecture, widely used in natural language processing (NLP) tasks such as text generation, translation, and summarization.

GPU (Graphics Processing Unit): A GPU is a hardware component used in AI and deep learning to accelerate computational tasks, particularly neural network training, due to its parallel processing capabilities.

Graph Database: A graph database is a database management system that stores and queries data using graph structures, allowing for efficient representation and traversal of relationships between data points.

Graph Neural Network (GNN): GNNs are a class of neural networks designed to work with graph-structured data, making them suitable for tasks like social network analysis, recommendation systems, and molecular chemistry.

Grid Search: Grid search is a hyperparameter tuning technique in AI where a predefined set of hyperparameter combinations is systematically tested to find the best configuration for a model.

 

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