Artificial Intelligence (AI): A to Z Glossary
Artificial Intelligence (AI) and natural language (NL) technologies are vital for enterprise businesses but can be challenging to understand due to their complexity. However, these conversations should be accessible to everyone. To simplify the discussion, we’ve created a glossary of essential AI and NL terms.
This list provides key definitions to help you build and enhance your understanding of natural language and artificial intelligence technologies. With these terms, you’ll be better equipped to explore, adopt, and implement natural language processing (NLP) and natural language understanding (NLU) solutions within your organization.
- A/B Testing
- Accelerator
- Accuracy
- Actionable Intelligence
- Activation Function
- Active Learning (Active Learning Strategy)
- Adapter
- Agentic AI
- Agents
- AGI (Artificial General Intelligence)
- AI (Artificial Intelligence)
- AI Copilot
- AI Ethics
- AI Plugin
- AI Search
- Algorithm
- Alignment
- Anaphora
- Annotation
- Application Programming Interface (API)
- Area Under the Curve (AUC)
- ASI (Artificial Super Intelligence)
- Associative Memory
- Attention
- Auto-Classification
- Auto-Complete
- Backpropagation (Backpropagation Through Time)
- Batch
- Bayes’s Theorem
- Benchmarking
- BERT
- Bias (Inductive Bias, Confirmation Bias)
- Bias-Variance Tradeoff
- Big Data
- Boosting
- Bounding Box
- Cataphora
- Categorization
- Category
- Category Trees
- Central Processing Unit (CPU)
- Chain of Thought
- Chatbot
- ChatGPT
- Classification
- Classification
- Clustering
- Cognitive Computing
- Cognitive Map
- Cold-Start
- Collaborative Filtering
- Collective Learning
- Completions
- Composite AI
- Computational Linguistics
- Computational Semantics
- Compute
- Computer Vision
- Confidence Interval
- Content
- Content Enrichment
- Contrastive Language–Image Pretraining (CLIP)
- Contributor
- Controllability
- Controlled Vocabulary
- Conversational AI
- Convolutional Neural Networks
- Co-occurrence
- Corpus
- Cost of Large Language Models
- Cross-Validation (k-fold Cross-Validation, Leave-p-out Cross-Validation)
- Curse of Dimensionality
- Custom/Domain Language Model
- Data Augmentation
- Data Discovery
- Data Drift
- Data Extraction
- Data Ingestion
- Data Labelling
- Data Mining
- Data Scarcity
- Data Science
- Data (Structured Data, Unstructured Data, Data augmentation)
- Decision Tree
- Deep Blue
- Deep Learning
- Deterministic Model
- Did You Mean (DYM)
- Diffusion
- Dimensionality Reduction
- Disambiguation
- Discriminative Model
- Domain Knowledge
- Double Descent
- Edge Model
- Embedding
- Emergent Behavior
- Emotion AI
- End-to-End Learning
- Ensemble Methods
- Enterprise AI
- Entity
- Entropy
- Environmental, Social, and Governance (ESG)
- Epoch
- ETL (Entity Recognition, Extraction)
- Expert Systems
- Explainable AI/Explainability
- Extensibility
- Extraction
- Extractive Summarization
- False Negative
- False Positive
- Feature (Feature Selection, Feature Learning)
- Feature Learning
- Feed-Forward (Neural) Networks
- Few-Shot Learning
- Fine-Tuned Model
- Fine-Tuning
- Forward Propagation
- Foundation Model
- F-Score
- Garbage In, Garbage Out
- General Data Protection Regulation (GDPR)
- Generalized Model
- Generation
- Generative Adversarial Networks (GANs)
- Generative AI
- Generative Pre-Trained Transformer
- Generative Summarization
- Genetic Algorithm
- GPT-3
- GPT-4
- Gradient Descent
- Graphic Processing Unit (GPU)
- Grounding
- Ground Truth
- Guardrails
- Hallucination
- Hallucitation
- Hidden Layer
- Human-in-the-Loop
- Hybrid AI
- Hyperparameter
- ImageNet
- Image Recognition
- Inference Engine
- Information Retrieval
- Insight Engines
- Instruction-tuning
- Intelligence Amplification
- Intelligence Augmentation
- Intelligent Document Processing (IDP)
- Interpretability
- Keyphrase Extraction
- Knowledged Based AI
- Knowledge Engineering
- Knowledge Generation
- Knowledge Graph
- Knowledge Model
- K-Shot Learning
- LangOps (Language Operations)
- Language Data
- Large Language Model (LLM)
- Latency
- Latent Space
- Layer (Hidden Layer)
- Learning Rate
- Learning-to-Learn
- Learning-to-Rank
- Lemma
- Lexicon
- Limited Memory
- Linked Data
- Logit Function
- Long Short-Term Memory Networks
- Loss Function (or Cost Function)
- Low-Code
- Machine Learning
- Machine Learning Lifecycle Management
- Machine Translation
- Metacontext and Metaprompt
- Metadata
- Mixture of Experts
- Model
- Model Chaining
- Model Drift
- Model Parameter
- Monte Carlo
- Morphological Analysis
- Multi-hop Reasoning
- Multi-Modal Learning
- Multimodal Models and Modalities
- Multi-Task Learning
- Multitask Prompt Tuning (MPT)
- Naive Bayes
- Named Entity Recognition
- Natural Language Ambiguity
- Natural Language Generation (NLG)
- Natural Language Processing (NLP)
- Natural Language Query (NLQ)
- Natural Language Technology (NLT)
- Natural Language Understanding (NLU)
- Neural Network
- Neural Radiance Fields (NeRF)
- Neuron
- No-Code
- N-Shot Learning
- Objective Function
- Ontology
- OpenAI
- Optical Character Recognition
- Optimization
- Overfitting
- Parameter-Efficient Fine-tuning (PEFT)
- Parsing
- Part-of-Speech Tagging
- Pattern Recognition
- PEMT (Post-Edit Machine Translation)
- Personally Identifiable Information
- Plugins
- Pooling (Max Pooling)
- Post-processing
- Precision
- Prediction
- Predictive Analytics
- Pre-processing
- Prescriptive Analytics
- Pre-trained Model
- Pretraining
- Principal Component Analysis
- Prior
- Probabilistic Model
- Prompt
- Prompt Chaining
- Prompt Engineering
- Quantum Computing
- Question & Answer (Q&A)
- Random Forest
- Reasoning
- Recall
- Rectified Linear Unit
- Recurrent Neural Networks (RNN)
- Recursive Prompting
- Regression (Linear Regression, Logistic Regression)
- Regressor
- Regularization
- Reinforcement Learning
- Reinforcement Learning with Human Feedback (RLHF)
- Relations
- Reproducibility (crisis of)
- Responsible AI
- Restricted Boltzmann Machines
- Retrieval Augmented Generation (RAG)
- ROAI (Return on Artificial Intelligence)
- Rules-based Machine Translation (RBMT)
- SAO (Subject-Action-Object)
- Self-Supervised Learning
- Semantic Network
- Semantic Search
- Semi-Structured Data
- Semi-Supervised Learning
- Sentiment Analysis
- Sequence Modeling
- Similarity (and Correlation)
- Simple Knowledge Organization System (SKOS)
- Singularity
- Specialized Corpora
- Speech Analytics
- Speech Recognition
- Speech-to-Text
- Stable Diffusion
- Stacking
- Statistical Distribution
- Steerability
- Stochastic Parrot
- Strong AI
- Structured Data
- Summarization
- Supervised Learning
- Support Vector Machines (SVM)
- Symbolic AI
- Symbolic Methodology
- Syntax
- Synthetic Data
- Taxonomy
- Temperature
- TensorFlow
- Tensor Processing Unit (TPU)
- Testing (Testing Data)
- Test Set
- Text Analytics
- Text Summarization
- Text-to-Speech
- Thesauri
- Time Series (Time Series Data)
- Token
- Tokenization
- Topic Modeling
- Training Data
- Training Set
- Transfer Learning
- Transformer
- Treemap
- Triple or Triplet Relations
- Tunable
- Tuning
- Turing Test
- Uncertainty
- Underfitting
- Unstructured Data
- Unsupervised Learning
- Validation
- Vanishing/Exploding Gradients
- Variance
- Voice Processing
- Voice Recognition
- Windowing
- Zero Shot Extraction