Glossary of AI Terms
A
Activation Functions
Mathematical equations that determine the output of a neural network.
API (Application Programming Interface)
A set of protocols and tools for building software applications, often used to interact with AI mode...
Artificial Intelligence
The simulation of human intelligence in machines.
Attention Mechanism
A technique that allows neural networks to focus on specific parts of the input when performing a ta...
B
C
Classification
A supervised learning task where the output variable is a category.
Clustering
An unsupervised learning task that involves grouping similar data points together.
Completion
The output generated by an AI model in response to a given prompt or input.
Computational Linguistics
An interdisciplinary field concerned with the computational modeling of natural language.
Computer Vision
A field of artificial intelligence that trains computers to interpret and understand visual informat...
Context
The surrounding information that gives meaning to a piece of text or data in AI models.
Context Length
The maximum amount of context an AI model can consider when processing or generating text.
Context Window
The range of surrounding tokens that a model considers when processing or generating text.
Contextual Embedding
A type of word embedding that captures the context-dependent meaning of words.
Convolutional Neural Networks
A class of deep neural networks, most commonly applied to analyzing visual imagery.
D
Data Augmentation
Techniques used to increase the amount of training data by applying transformations to existing data...
Dataset
A collection of data used for machine learning tasks, typically consisting of input-output pairs.
Deep Learning
A subset of machine learning based on artificial neural networks.
Digital Signal Processing
The manipulation of digital signals to improve their quality or extract useful information.
Dimensionality Reduction
The process of reducing the number of random variables under consideration in a dataset.
Distributional Semantics
A theory and method for quantifying and categorizing semantic similarities between linguistic items ...
E
F
Fine-tuning
The process of further training a pre-trained model on a specific task or dataset.
Fourier Transform
A mathematical transform that decomposes a function of time into its constituent frequencies.
Frequency Penalty
A parameter that reduces the likelihood of repetition in generated text by penalizing frequently use...
Functions
In the context of AI models, predefined tasks or operations that the model can perform.
G
Generative Adversarial Networks
A class of machine learning frameworks where two neural networks contest with each other in a game.
Generative Models
Machine learning models that can generate new data instances.
GPT (Generative Pre-trained Transformer)
A type of large language model based on the transformer architecture, capable of generating human-li...
GRU (Gated Recurrent Unit)
A type of recurrent neural network that is similar to LSTM but with a simpler architecture.
L
Language Models
AI models designed to understand, generate, or manipulate human language.
Large Language Models
Artificial intelligence models trained on vast amounts of text data to understand and generate human...
Long-range Dependency
The ability of a model to capture and utilize information from distant parts of the input sequence.
LSTM (Long Short-Term Memory)
A type of recurrent neural network capable of learning long-term dependencies.
M
N
P
Policy Gradients
A type of reinforcement learning method that directly optimizes the policy without using a value fun...
Presence Penalty
A parameter that reduces the likelihood of repetition by penalizing new tokens that appear in the ex...
Prompt
An input or instruction given to an AI model to elicit a specific response or behavior.
Prompt Engineering
The practice of designing and optimizing prompts to effectively communicate with AI models.
R
Recurrent Neural Networks
A class of neural networks where connections between nodes form a directed graph along a temporal se...
Regression
A supervised learning task where the output variable is a continuous value.
Reinforcement Learning
A type of machine learning where an agent learns to make decisions by interacting with an environmen...
S
Semantic Similarity
A measure of the degree to which two concepts or texts are related in meaning.
Semantic Understanding
The ability of an AI system to comprehend the meaning and context of language beyond just processing...
Sequence Modeling
The task of predicting or generating sequences of data points.
Sequence-to-Sequence Models
Neural network models that transform an input sequence into an output sequence.
Supervised Learning
A type of machine learning where the algorithm learns from labeled training data.
T
Temperature
A parameter in language models that controls the randomness of the output.
Text Mining
The process of deriving high-quality information from text.
Token
A unit of text or code in natural language processing and machine learning models.
Tokenization
The process of breaking down text into smaller units called tokens.
Top P (Nucleus Sampling)
A text generation method that samples from the smallest possible set of words whose cumulative proba...
Training Data
The dataset used to teach a machine learning model to perform a specific task.
Transfer Learning
A machine learning method where a model developed for a task is reused as the starting point for a m...
Transformer
A deep learning model architecture that relies entirely on attention mechanisms to draw global depen...
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