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.

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ScalabilityAI LiteracyMachine Learning BiasImage RecognitionAI ResilienceSynthetic Data for AI TrainingObjective FunctionData DriftSelf-healing AISpike Neural NetworksHuman-centered AIFederated LearningUncertainty in Machine LearningParametric Neural Networks Limited Memory AINaive Bayes ClassifierAI TransparencyHuman-in-the-Loop AIMachine Learning PreprocessingAI PrivacyMulti-Agent SystemsGenerative Teaching NetworksAI InterpretabilityAI RegulationHuman Augmentation with AIFeature Store for Machine LearningDecision IntelligenceChatbotsQuantum Machine Learning AlgorithmsComputational PhenotypingCounterfactual Explanations in AIContext-Aware ComputingInstruction TuningAI SimulationEthical AIAI OversightAI SafetySymbolic AIAI GuardrailsComposite AIGradient ClippingGenerative Adversarial Networks (GANs)Rule-Based AIAI AssistantsActivation FunctionsDall-EPrompt EngineeringHyperparametersAI and EducationChess botsMidjourney (Image Generation)DistilBERTMistralXLNetBenchmarkingLlama 2Sentiment AnalysisLLM CollectionChatGPTMixture of ExpertsLatent Dirichlet Allocation (LDA)RoBERTaRLHFMultimodal AITransformersWinnow Algorithmk-ShinglesFlajolet-Martin AlgorithmCURE AlgorithmOnline Gradient DescentZero-shot Classification ModelsCurse of DimensionalityBackpropagationDimensionality ReductionMultimodal LearningGaussian ProcessesAI Voice TransferGated Recurrent UnitPrompt ChainingApproximate Dynamic ProgrammingAdversarial Machine LearningDeep Reinforcement LearningSpeech-to-text modelsFeedforward Neural NetworkBERTGradient Boosting Machines (GBMs)Retrieval-Augmented Generation (RAG)PerceptronOverfitting and UnderfittingMachine LearningLarge Language Model (LLM)Graphics Processing Unit (GPU)Diffusion ModelsClassificationTensor Processing Unit (TPU)Natural Language Processing (NLP)Google's BardOpenAI WhisperSequence ModelingPrecision and RecallSemantic KernelFine Tuning in Deep LearningGradient ScalingAlphaGo ZeroCognitive MapKeyphrase ExtractionMultimodal AI Models and ModalitiesHidden Markov Models (HMMs)AI HardwareNatural Language Generation (NLG)Natural Language Understanding (NLU)TokenizationWord EmbeddingsAI and FinanceAlphaGoAI Recommendation AlgorithmsBinary Classification AIAI Generated MusicNeuralinkAI Video GenerationOpenAI SoraHooke-Jeeves AlgorithmMambaCentral Processing Unit (CPU)Generative AIRepresentation LearningAI in Customer ServiceConditional Variational AutoencodersConversational AIPackagesModelsFundamentalsDatasetsTechniquesAI Lifecycle ManagementAI MonitoringMachine TranslationMLOpsMonte Carlo LearningPrincipal Component AnalysisReproducibility in Machine LearningRestricted Boltzmann MachinesSupport Vector Machines (SVM)Topic ModelingVanishing and Exploding GradientsData LabelingF1 Score in Machine LearningExpectation MaximizationBeam Search AlgorithmEmbedding LayerDifferential PrivacyData PoisoningCausal InferenceCapsule Neural NetworkAttention MechanismsDomain AdaptationEvolutionary AlgorithmsContrastive LearningExplainable AIAffective AISemantic NetworksData AugmentationConvolutional Neural NetworksCognitive ComputingEnd-to-end LearningPrompt TuningModel DriftNeural Radiance FieldsRegularizationNatural Language Querying (NLQ)Foundation ModelsForward PropagationF2 ScoreAI EthicsTransfer LearningAI AlignmentWhisper v3Whisper v2Semi-structured dataAI HallucinationsMatplotlibNumPyScikit-learnSciPyKerasTensorFlowSeaborn Python PackagePyTorchNatural Language Toolkit (NLTK)PandasEgo 4DThe PileCommon Crawl DatasetsSQuADIntelligent Document ProcessingHyperparameter TuningMarkov Decision ProcessGraph Neural NetworksNeural Architecture SearchAblationModel InterpretabilityOut-of-Distribution DetectionRecurrent Neural NetworksActive Learning (Machine Learning)Imbalanced DataLoss FunctionUnsupervised LearningAdaGradAcoustic ModelsConcatenative SynthesisCandidate SamplingComputational CreativityAI Emotion RecognitionKnowledge Representation and ReasoningMetacognitive Learning Models AI Speech EnhancementEco-friendly 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