Glossary of AI Terms

Common terminology used in AI.

Glossary of AI Terms

Natural language processing (NLP) is a type of AI that allows machines to understand and interpret human language. It is used in applications such as virtual assistants, chatbots, and language translation.​ Neural networks are a type of AI that is modelled after the structure of the human brain. They are used in applications such as image recognition, natural language processing, and speech recognition.​

natural language processing neural networks

Artificial Intelligence is about creating machines that can think and act like humans, making them capable of understanding, learning, and making decisions on their own. ​

Artificial intelligence

A type of prompt engineering that does not provide any examples to the AI model, but only specifies the task and gives instructions. For example, the following prompt is a zero-shot prompt for generating a poem about love: "Write me a four-line rhyme about love".

zero-shot prompting

Hallucinations are a type of error that can occur in AI systems, where the system generates content that is not correct, but sounds correct. This can happen when the system is not properly trained or when it is exposed to biased or incomplete data.

hallucinations

Deep learning focuses on the development and training of deep neural networks to perform tasks that involve complex pattern recognition, problem solving and decision-making. ​

deep learning

A process in which a pre-trained machine learning model is adapted to a new task or data set.

transfer learning

Generative AI is a term for AI systems that generate various forms of novel output, including text, code, graphics, or audio. Generative AI uses deep learning techniques to recognise patterns in data and generate content based on these patterns.​ ​

generative ai

Fuzzy logic is a mathematical framework used in generative AI to handle uncertainty and imprecise reasoning in decision-making processes.

fuzzy logic

A technique of designing and providing inputs to a generative AI model, such as an LLM, to elicit a desired output. Prompt engineering can involve specifying the task, providing examples, giving instructions, adding constraints, and using keywords or symbols.

prompt engineering

Designed and trained for a specific task or a limited set of tasks.​ Examples include virtual assistants, image recognition, recommendation systems. ​

weak (narrow) ai

A large language model (LLM) is a type of AI that is trained on a large amount of text data and can generate new text that is similar in style and tone to the original data. It is used in applications such as language translation, text summarization, and content creation. ChatGPT, Google Bard and Bing AI are examples of a large language model.​

large language model

Machine learning is a type of AI that allows machines to learn from data and improve their performance over time. It is used in many applications, such as image recognition, natural language processing, and predictive analytics.​

Machine Learning