Glossary
Graphics Processing Unit (GPU)
Fundamentals
Adversarial Machine LearningAI AgentsAI and EducationAI and MedicineAI AssistantsAI HardwareAI Voice TransferApproximate Dynamic ProgrammingBackpropagationBayesian Machine LearningCurse of DimensionalityData LabelingDeep LearningDeep Reinforcement LearningDimensionality ReductionF1 Score in Machine LearningFeedforward Neural NetworkFine Tuning in Deep LearningGated Recurrent UnitGenerative AILarge Language Model (LLM)Machine LearningMultimodal LearningNatural Language Generation (NLG)Natural Language Processing (NLP)Natural Language Understanding (NLU)Precision and RecallTransformersZero-shot Classification Models
Models
AlphaGo ZeroBERTChatGPTChess botsDall-EDiffusion ModelsDistilBERTGoogle's BardHidden Markov Models (HMMs)Inference EngineLarge Language Model (LLM)Llama 2LLM CollectionMidjourney (Image Generation)MistralOpenAI WhisperPerceptronProbabilistic Models in Machine LearningRoBERTaRule-Based AISpeech-to-text modelsText-to-Speech ModelsXLNet
Techniques
Activation FunctionsBatch Gradient DescentBeam Search AlgorithmBenchmarkingClassificationCURE AlgorithmExpectation MaximizationFlajolet-Martin AlgorithmGaussian ProcessesGenerative Adversarial Networks (GANs)Gradient Boosting Machines (GBMs)Gradient ClippingGradient ScalingGroundingHyperparametersk-ShinglesLatent Dirichlet Allocation (LDA)Mixture of ExpertsMultimodal AIOnline Gradient DescentOverfitting and UnderfittingPrompt ChainingPrompt EngineeringRetrieval-Augmented Generation (RAG)RLHFSentiment AnalysisSequence ModelingSemantic KernelTokenizationWinnow AlgorithmWord Embeddings
Last updated on September 28, 202314 min read
Graphics Processing Unit (GPU)

A Graphics Processing Unit (GPU) is a specialized electronic circuit designed to accelerate the processing of images and videos for display, and it's increasingly used for complex computations in various scientific and artificial intelligence applications.

Graphics Processing Units, commonly known as GPUs, have long been the workhorses behind the stunning visuals in video games and computer graphics. Initially designed to accelerate the creation of images for a screen, these specialized chips have found a new and critical role in a different domain: Artificial Intelligence (AI).

From their origins in simple arcade games to their current status as indispensable tools in AI research and applications, GPUs have seen a remarkable evolution. Their shift from primarily handling graphics to powering complex AI computations is a reflection of both technological progress and the ever-expanding boundaries of computing. As we delve into the world of GPUs, we’ll explore how a chip designed for visuals became a cornerstone in the rapidly advancing field of AI.

Historical Overview: The Evolution of GPUs

The Arcade Era

In the early days, the sights and sounds of arcades were the playgrounds for GPUs. These were simpler times, where the primary task was to render basic graphics for games like Pong and Space Invaders. The GPUs of this era weren’t the powerhouses we know today, but they laid the foundation, turning pixels into paddle tennis and alien invasions.