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A-Z of Artificial Intelligence (AI) Terms
Artificial Intelligence (AI) Terms Glossary

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AI terminology

Browse the A-Z glossary of artificial intelligence (AI) terminology, complete with definitions, pronunciations and the meaning of each AI term broken down in layman's terms. Learn the terms, become a pro in conversation.
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S

  • Search Algorithm

    A procedure for locating specific data among a collection of data.

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R

  • Robotics

    Robotics is a branch of technology that deals with the design, construction, and operation of robots.

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Z

  • Zero-shot learning

    Zero-shot learning is a machine learning concept where a model can identify objects it hasn't been trained to recognise.

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B

  • Big Data

    Large volumes of structured, semi-structured, and unstructured data, analyzed to reveal patterns and insights.

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S

  • Speech-to-text

    Speech-to-text is a technology that converts spoken words into written text.

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B

  • Bias

    In AI, bias refers to a system's tendency to prioritize certain types of information or make predictions based on skewed data.

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R

  • Reasoning

    Reasoning is a subset of AI that involves drawing conclusions based on information or context.

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T

  • Text-to-speech

    Text-to-speech is a form of AI technology that translates written text into spoken words.

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N

  • No-code AI

    No-code AI is a form of Artificial Intelligence that doesn't require programming or coding skills.

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H

  • Hallucination

    In AI terms, hallucination refers to incorrect or imagined outputs produced by a neural network.

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G

  • Generative AI

    Generative AI is a subset of AI that creates new data from existing datasets.

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F

  • Fine-tuning

    Fine-tuning in AI involves adjusting parameters to optimize an already trained machine learning model.

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T

  • Text-to-image generator

    A Text-to-image generator is an AI tool that translates textual descriptions into corresponding visuals.

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P

  • Prompt

    In AI, a prompt is a request or instruction given to a system to generate a response.

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L

  • Large Language Model (LLM)

    LLMs are AI models trained on vast amounts of text data, empowering them with remarkable human-like language understanding abilities.

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D

  • Data Augmentation

    Data augmentation is a strategy used in machine learning to increase the diversity of data without collecting new instances.

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C

  • Chat GPT

    Chat GPT is an AI model developed to generate human-like text based on a given input.

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A

  • Automation

    Automation is the use of technology to control and operate tasks without human intervention.

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C

  • Computer Vision

    Computer vision is a field of AI that enables computers to interpret and understand visual data.

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R

  • Reinforcement Learning

    An aspect of AI where an agent learns to behave by receiving rewards or penalties for its actions.

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O

  • Open AI

    OpenAI refers to an artificial intelligence research organization, aiming to ensure that AGI's benefits are shared with all.

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A

  • AI Safety

    AI Safety refers to the study of ensuring artificial intelligence systems operate beneficially and harmlessly.

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A

  • Algorithm

    An algorithm is a defined set of step-by-step procedures for completing a task or solving a problem.

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C

  • Chatbot

    A chatbot is an AI-powered software designed to interact with humans in their natural languages.

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N

  • Natural Language Processing (NLP)

    NLP is an area of AI that helps computers understand, interpret, and use human language.

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N

  • Neural Networks

    Neural networks are interconnected layers of nodes modelling human brain in artificial intelligence.

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D

  • Deep Learning

    Deep Learning is a subset of AI that mimics the human brain in processing data for use in decision making.

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A

  • Artificial Intelligence (AI)

    Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems.

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M

  • Machine Learning (ML)

    A subset of AI that enables computers to learn from data and improve over time.

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A

  • Adapter

    In AI, an adapter is a method that allows models to understand and apply knowledge from different tasks.

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