Miscellaneous

Referring to diligent, hard work, often of a nature that is repetitive or requires a high level of effort and reliability.

A specialized database for storing and retrieving vector representations of data, facilitating similarity searches.

Data set aside from the training dataset to tune model parameters and prevent overfitting, ensuring the model's generalizability.

The dataset used specifically for training a machine learning model, containing examples for learning patterns and behaviors.

A dataset used to evaluate the performance of a machine learning model after training, separate from training data.

Predefined messages or prompts used in conversational AI systems to guide user interactions.

A testing environment that isolates untested code changes and experimentation without affecting the production environment.

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

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

A comprehensive document providing essential information about a machine learning model's purpose and performance.

A tag or annotation applied to a piece of data, indicating the correct output for supervised learning.

A centralized repository of information, used in AI to provide answers or contextual information.

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

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

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

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

Measures and practices to ensure that personal or sensitive data is not misused or disclosed.

A large collection of texts used for compiling data and training machine learning models.