AI glossary - AI terminology you need to know

This AI glossary compiles the most common terms you need to know before you start your AI journey. Whether you’re just starting your your career in artificial intelligence or already working on the same, this comprehensive A-Z AI glossary is specifically designed to help you understand the key concepts and cut through jargon.

  • AI ethicsAI ethics make sure you create and use AI in a responsible way. They promote fairness, privacy, accountability, and help society while avoiding harm and bias.
  • AI GuardrailsAI guardrails are protocols that make sure AI systems operate within ethical, legal‌ and technical boundaries, promoting safety and fairness‌. Learn more.
  • AI HallucinationAI hallucination refers to the generation of false or misleading information by a larger language model (LLM). This often occurs due to insufficient training data.
  • AI promptAI prompts are questions, statements or commands provided by humans to a large language model, triggering relevant responses.
  • Artificial General IntelligenceArtificial general intelligence refers to a hypothetical AI that understands, learns‌ and applies knowledge at a level equal to or beyond human capabilities.
  • Artificial IntelligenceArtificial Intelligence (AI) is the technology that allows machines to mimic human intelligence. They can learn from experiences and perform human-like tasks.
  • Artificial SuperintelligenceArtificial Superintelligence is advanced Artificial Intelligence that surpasses human intelligence in all aspects, including problem-solving and creativity.
  • Big DataBig data refers to huge amounts of complex data that grow exponentially over time and can't be handled by conventional data management systems. ‌
  • Computer VisionComputer Vision is like a human sight, which facilitates the technology that enables computers to interpret and understand visual data from images and video.‌
  • Conversational AIConversational AI refers to a form of Artificial Intelligence that enables natural and seamless interactions between humans and machines through conversation.
  • Deep Learning (DL)Deep Learning (DL) is a type of Machine Learning that trains computers to learn how to make decisions independently, using large amounts of data and complex algorithms.
  • Deepfake technologyDeepfakes are AI-generated media that convincingly replaces one person's likeness with another. While, it can also spread misinformation and violate privacy.
  • Frontier AIFrontier AI is an advanced, innovative technology that pushes the current boundaries of the most advanced AI models.
  • Generative AIGenerative AI refers to a form of AI that enables you to create original content automatically, like images, text, videos and music in a matter of seconds.
  • Generative Pre-trained Transformer (GPT)A generative Pre-trained Transformer (GPT) is an AI model developed by Open AI that processes and generates text based on human inputs.
  • Image RecognitionImage Recognition technology is a Computer Vision task that involves identifying and categorising the main content or subject of an entire image. Learn more.
  • Knowledge graphA knowledge graph is a structured representation of data in the form of a network, illustrating the relationships and connections between various entities.
  • Large Language Model (LLM)A large language model (LLM) is a type of Artificial Intelligence system designed to generate human language. It can generate text, images and content.
  • Machine Learning (ML)Machine Learning (ML) is a subset of Artificial Intelligence (AI) that involves training algorithms to learn from and make decisions based on data. Learn more.
  • Neural networkAI neural networks are computer systems inspired by the human brain, using interconnected nodes to process data, recognise patterns‌ and make decisions.
  • Reinforcement LearningReinforcement Learning is a Machine Learning technique where an agent learns to make decisions through trial and error, based on rewards to achieve an outcome.
  • Responsible AIResponsible AI ensures ethical and fair use of AI technologies, prioritising safety, accountability and privacy. It ensures that AI doesn't perpetuate biases.
  • Semi-supervised learningSemi-supervised learning is a Machine Learning method where a model learns from labelled and unlabelled data to make predictions on new, unseen data. ‌
  • Supervised learningSupervised learning is a Machine Learning method where a model learns from labelled data to make predictions on new, unseen data. Read on to learn more.
  • TransformersTransformers in Artificial Intelligence are a type of model that can handle long data more effectively and figure out which part of the input is most important.
  • Unsupervised learningUnsupervised Learning is a Machine Learning method where a model learns from unlabelled data to make predictions on new, unseen data. ‌