Glossary

0-9

0-shot learning|1-shot learning|2-stage detector|3D convolution|4D data|5G + AI|6DoF pose estimation|7D representation|8-bit quantization|9-layer network

A

AGI / Artificial General Intelligence|Algorithm|Artificial Intelligence (AI)|Attention|Autoencoder

B

Backpropagation|Batch Normalization|BERT|Bias|Boosting

C

Chatbot|Classifier / Classification|Clustering|CNN / Convolutional Neural Network|Cross-Validation

D

Data Augmentation|Deep Learning|Deepfake|Deterministic Model|Discriminative Model

E

Embedding|Encoder|Ensemble Learning|Epoch|Explainable AI (XAI)

F

Feature Extraction|Fine-tuning|Forward Propagation|Foundation Model|Fusion / Multimodal Fusion

G

GAN / Generative Adversarial Network|Generative AI|Gradient Descent|Graph Neural Network (GNN)|Grounding

H

Hallucination|Heuristic|Hidden Layer|Hierarchical Model|Hyperparameter

I

Imbalanced Data|Instance / Sample|Instruction tuning|Intelligence Amplification / Augmentation|Interpretability

J

JAX|Jittering|Joint Embedding|JSONL / JSON-lines|Juxtaposition

K

K-means Clustering|K-Shot Learning|Kernel Trick|KL Divergence (Kullback–Leibler Divergence)|Knowledge Distillation

L

Large Language Model (LLM)|Latent Variable|Learning Rate|Loss Function|LSTM / Long Short-Term Memory

M

Machine Learning (ML)|Meta-learning|Model|Multi-head Attention|Multimodal / Multimodality

N

Neural Network|NLP / Natural Language Processing|NLU / Natural Language Understanding|Normalization|Novelty Detection / Anomaly Detection

O

Objective Function|One-hot Encoding|Online Learning|Optimizer|Overfitting

P

Parameter|Policy / Reinforcement Learning Policy|Pooling|Pretraining|Prompt

Q

Q-learning|Quality Estimation|Quantization|Query|Queue / Buffer

R

Regularization|Reinforcement Learning (RL)|Representation Learning|Retrieval Augmented Generation (RAG)|RNN / Recurrent Neural Network

S

Sampling|Self-Supervised Learning|Sequence Modeling|Softmax|Supervised Learning

T

Tokenizer|Training Data|Transfer Learning|Transformer|Tuning / Hyperparameter Tuning

U

U-Net|Uncertainty Estimation|Underfitting|Universal Approximation Theorem|Unsupervised Learning

V

Validation Set|Vanishing / Exploding Gradient|Variational Autoencoder (VAE)|Vector Embedding|Vision Transformer (ViT)

W

Weak Supervision|Weight Decay|Whitening / Whitening Transformation|Word Embedding|Workflow

X

X-axis / feature axis|XAI / Explainable AI|XLM|XLNet|XOR problem

Y

Y-axis / feature axis|Y-transform / YUV|YAGNI (You Aren't Gonna Need It)|Yield (model yield / throughput)|Yoga of AI

Z

Z-score Normalization|Zero-centric / Zero-bias initialization|Zero-gradient phenomenon|Zero-shot Learning / Zero-shot inference|Zygosity in augmentation