Miscellaneous

A large collection of text used to compile data and train machine learning models.

Measures and practices that protect personal or sensitive data from misuse or disclosure.

An interdisciplinary field that uses scientific methods to extract knowledge from data.

A collection of data specifically prepared and structured for training or testing AI models.

The process of making an AI model available for use in real-world applications or systems.

A framework for assessing and guiding the ethical development and deployment of AI systems.

A centralized repository of information that AI can use to provide answers or context.

A tag or annotation applied to data that indicates the correct output for supervised learning.

A document that provides information about a machine learning model’s purpose and performance.

An AI research lab focused on developing and promoting friendly AI for the benefit of humanity.

A high-level programming language known for clear, readable syntax and widely used in AI development.

An isolated testing environment for untested code and experiments that does not affect production.

A predefined message or prompt in a conversational AI system that guides user interactions.

A dataset kept separate from training data and used to evaluate a machine learning model after training.

A dataset of examples used to train a machine learning model to learn patterns and behaviors.

Data kept separate from the training dataset and used to tune model parameters and help prevent overfitting.

A specialized database that stores and retrieves vector representations of data for similarity search.

Diligent, reliable work that is often repetitive or requires substantial effort.