AI Glossary

LLM Collection

The table below includes some of the most influential models, and the order is sorted by their release dates.

Model	Release Date	Developer	License	Description
GPT-4	2023	OpenAI	Custom	Successor to GPT-3, built on a similar architecture but with improvements.
GPT-3	June 2020	OpenAI	Custom	175 billion parameters, known for its versatility and capability.
Turing-NLG	February 2020	Microsoft	Custom	17 billion parameters, aimed at natural language understanding and generation.
GPT-2	February 2019	OpenAI	Modified MIT	Initially withheld from public release due to concerns over potential misuse.
BERT	October 2018	Google	Apache 2.0	Designed to understand the context of words in search queries.
Transformer XL	January 2019	Google/CMU	Apache 2.0	Extended Transformer model to handle longer sequences of text.
GPT	June 2018	OpenAI	Modified MIT	First Generative Pre-trained Transformer with 117M parameters.
ELMo	March 2018	Allen Institute	Apache 2.0	Deep contextualized word representations, allowing for rich word meanings.

Back to Glossary Home

Gradient Clipping Generative Adversarial Networks (GANs)Rule-Based AI AI Assistants AI Voice Agents Activation Functions Dall-E Prompt Engineering Text-to-Speech Models AI Agents Hyperparameters AI and Education AI and Medicine Chess bots Midjourney (Image Generation)DistilBERT Mistral XLNet Benchmarking Llama 2 Sentiment Analysis LLM Collection ChatGPT Mixture of Experts Latent Dirichlet Allocation (LDA)RoBERTa RLHF Multimodal AI Transformers Winnow Algorithm k-Shingles Flajolet-Martin Algorithm Batch Gradient Descent CURE Algorithm Online Gradient Descent Zero-shot Classification Models Curse of Dimensionality Backpropagation Dimensionality Reduction Multimodal Learning Gaussian Processes AI Voice Transfer Gated Recurrent Unit Prompt Chaining Approximate Dynamic Programming Adversarial Machine Learning Bayesian Machine Learning Deep Reinforcement Learning Speech-to-text models Grounding Feedforward Neural Network BERT Gradient Boosting Machines (GBMs)Retrieval-Augmented Generation (RAG)Perceptron Overfitting and Underfitting Machine Learning Large Language Model (LLM)Graphics Processing Unit (GPU)Diffusion Models Classification Tensor Processing Unit (TPU)Natural Language Processing (NLP)Google's Bard OpenAI Whisper Sequence Modeling Precision and Recall Semantic Kernel Fine Tuning in Deep Learning Gradient Scaling AlphaGo Zero Cognitive Map Keyphrase Extraction Multimodal AI Models and Modalities Hidden Markov Models (HMMs)AI Hardware Deep Learning Natural Language Generation (NLG)Natural Language Understanding (NLU)Tokenization Word Embeddings AI and Finance AlphaGo AI Recommendation Algorithms Binary Classification AI AI Generated Music Neuralink AI Video Generation OpenAI Sora Hooke-Jeeves Algorithm Mamba Central Processing Unit (CPU)Generative AI Representation Learning AI in Customer Service Conditional Variational Autoencoders Conversational AI Packages Models Fundamentals Datasets Techniques AI Lifecycle Management AI Literacy AI Monitoring AI Oversight AI Privacy AI Prototyping AI Regulation AI Resilience Machine Learning Bias Machine Learning Life Cycle Management Machine Translation MLOps Monte Carlo Learning Multi-task Learning Naive Bayes Classifier Machine Learning Neuron Pooling (Machine Learning)Principal Component Analysis Machine Learning Preprocessing Rectified Linear Unit (ReLU)Reproducibility in Machine Learning Restricted Boltzmann Machines Semi-Supervised Learning Supervised Learning Support Vector Machines (SVM)Topic Modeling Uncertainty in Machine Learning Vanishing and Exploding Gradients AI Interpretability Data Labeling Inference Engine Probabilistic Models in Machine Learning F1 Score in Machine Learning Expectation Maximization Beam Search Algorithm Embedding Layer Differential Privacy Data Poisoning Causal Inference Capsule Neural Network Attention Mechanisms Domain Adaptation Evolutionary Algorithms Contrastive Learning Explainable AI Affective AI Semantic Networks Data Augmentation Convolutional Neural Networks Cognitive Computing End-to-end Learning Prompt Tuning Double Descent Model Drift Neural Radiance Fields Regularization Natural Language Querying (NLQ)Foundation Models Forward Propagation F2 Score AI Ethics Transfer Learning AI Alignment Whisper v3 Whisper v2 Semi-structured data AI Hallucinations Emergent Behavior Matplotlib NumPy Scikit-learn SciPy Keras TensorFlow Seaborn Python Package PyTorch Natural Language Toolkit (NLTK)Pandas Ego 4D The Pile Common Crawl Datasets SQuAD Intelligent Document Processing Hyperparameter Tuning Markov Decision Process Graph Neural Networks Neural Architecture Search Ablation Knowledge Distillation Model Interpretability Out-of-Distribution Detection Recurrent Neural Networks Active Learning (Machine Learning)Imbalanced Data Loss Function Unsupervised Learning AI and Big Data AdaGrad Clustering Algorithms Parametric Neural Networks Acoustic Models Articulatory Synthesis Concatenative Synthesis Grapheme-to-Phoneme Conversion (G2P)Homograph Disambiguation Neural Text-to-Speech (NTTS)Voice Cloning Autoregressive Model Candidate Sampling Machine Learning in Algorithmic Trading Computational Creativity Context-Aware Computing AI Emotion Recognition Knowledge Representation and Reasoning Metacognitive Learning Models Synthetic Data for AI Training AI Speech Enhancement Counterfactual Explanations in AI Eco-friendly AI Feature Store for Machine Learning Generative Teaching Networks Human-centered AI Metaheuristic Algorithms Statistical Relational Learning Cognitive Architectures Computational Phenotyping Continuous Learning Systems Deepfake Detection One-Shot Learning Quantum Machine Learning Algorithms Self-healing AI Semantic Search Algorithms Artificial Super Intelligence AI Guardrails Limited Memory AI Chatbots Diffusion Hidden Layer Instruction Tuning Objective Function Pretraining Symbolic AI Auto Classification Composite AI Computational Linguistics Computational Semantics Data Drift Named Entity Recognition Few Shot Learning Multitask Prompt Tuning Part-of-Speech Tagging Random Forest Validation Data Set Test Data Set Neural Style Transfer Incremental Learning Bias-Variance Tradeoff Multi-Agent Systems Neuroevolution Spike Neural Networks Federated Learning Human-in-the-Loop AI Association Rule Learning Autoencoder Collaborative Filtering Data Scarcity Decision Tree Ensemble Learning Entropy in Machine Learning Corpus in NLP Confirmation Bias in Machine Learning Confidence Intervals in Machine Learning Cross Validation in Machine Learning Accuracy in Machine Learning Clustering in Machine Learning Boosting in Machine Learning Epoch in Machine Learning Feature Learning Feature Selection Genetic Algorithms in AI Ground Truth in Machine Learning Hybrid AI AI Detection Information Retrieval AI Robustness AI Safety AI Scalability AI Simulation AI Standards AI Steering AI Transparency Augmented Intelligence Decision Intelligence Ethical AI Human Augmentation with AI Image Recognition ImageNet Inductive Bias Learning Rate Learning To Rank Logits Applications

AI Glossary Categories

Categories

AlphabeticalAlphabetical

Alphabetical