Dictionary

Type of artificial intelligence that has the ability to understand, learn, and apply knowledge across a wide range of tasks at a level comparable to human intelligence. Unlike narrow AI, which is designed for specific tasks (such as image recognition or language translation), AGI aims to perform any intellectual task that a human can do.

A form of communication between users and LLMs, often in a conversational format, where the LLM responds to user inputs in natural language.

An AI tool that can understand and execute code, allowing it to perform tasks such as data analysis, calculations, and more.

The range of text that an LLM can consider when generating a response. It defines how much previous conversation or text the model can “remember” at any given time.

A subset of machine learning involving neural networks with many layers. It is used for complex tasks like image and speech recognition.

A representation of data (like words or images) in a lower-dimensional space, often used to capture semantic meaning and relationships.

A machine learning approach where the model is trained with a very small amount of labeled data, often just a few examples.

The process of taking a pre-trained model and making small adjustments to adapt it to a specific task or dataset.

The ability of an AI to call and execute specific functions or tasks, often within a larger system or application.

Parts of an output where the model generates information that is not based on the input data or any real-world knowledge. This information output can include fabricated facts, incorrect details, or entirely fictional content that appears plausible but is not grounded in reality.

The data that is fed into an LLM (input) and the data that is produced by the system (output).

A type of AI model that is trained on vast amounts of text data to understand and generate human language.

A unit of communication in a chat or conversation, typically consisting of text sent by a user or generated by an LLM.

A field of AI focused on developing algorithms that allow computers to learn from and make predictions based on data.

A computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process information in layers.

The input or question given to an AI model to generate a response.

A technique that combines retrieval of relevant documents or information with generation of text to improve the quality and accuracy of responses.

A unit of text (such as a word or subword) that is processed by an LLM. 1 token is roughly equivalent to 4 characters.

The capability of an AI to invoke external tools or APIs to perform specific tasks or retrieve information.

The ability of an AI system to interpret and understand visual information from the world, such as images.

A machine learning approach where the model is able to make predictions on new, unseen classes without having been explicitly trained on those classes.