Here you will find some AI terminology that may be useful to asist your understanding of AI
| Algorithm | An Algorithm is a set of instructions designed to perform a specific task. In machine learning, algorithms are used to parse data, learn from it, and then make decisions or predictions about new data. |
| Data Mining | Data Mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. |
| Generative AI | Generative AI is a subset of artificial intelligence that leverages machine learning techniques to generate content. It can create new content that is similar to the input data it has been trained on. Examples include creating images, writing text, and composing music. |
| Hallucinations | In the context of AI, hallucinations refer to the generation of information that isn't present in the input data. This can occur when AI models, such as language models, generate outputs that include false or misleading information. |
| Large Language Model (LLM) | A Large Language Model is a type of AI model designed to generate human-like text. It's trained on a large amount of text data and can generate sentences by predicting the likelihood of a word given the previous words used in the text. |
| Machine Learning (ML) | Machine Learning is a subset of AI, providing systems the ability to automatically learn and improve from experience without being explicitly programmed. |
| Neural Network | A Neural Network is a series of algorithms that seek to identify relationships in a data set via a process that mimics the way the human brain operates. |
