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Generative AI

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Generative AI
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Generative AI

Generative artificial intelligence (GenAI) is a subfield of artificial intelligence (AI) that uses generative models to generate text, images, videos, audio, software code or other forms of data. These models learn the underlying patterns and structures of their training data, and use them to generate new data in response to input, which often takes the form of natural language prompts. The prevalence of generative AI tools has increased significantly since the AI boom in the 2020s. This boom was made possible by improvements in deep neural networks, particularly large language models (LLMs), which are based on the transformer architecture. Generative AI applications include chatbots such as ChatGPT, Claude, Microsoft Copilot, DeepSeek, Doubao, Google Gemini, Grok, Kimi and Qwen; text-to-image models such as DALL-E, Firefly, Stable Diffusion, and Midjourney; and text-to-video models such as Veo, LTX and Sora. Companies in a variety of sectors have used generative AI, including those in software development, healthcare, finance, entertainment, customer service, sales and marketing, art, writing, and product design. Generative AI has been used for cybercrime, and to deceive and manipulate people through fake news and deepfakes. Generative AI models have been trained on copyrighted works without the rightholders' permission.

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Article table of contents 48 sections
1 History
1.1 Early history
1.2 Generative neural networks (since the late 2000s)
1.3 Generative AI adoption
2 Applications
2.1 Text and software code
2.2 Audio
2.3 Images
2.4 Video
2.5 Robotics
2.6 3D modeling
2.7 AI-assisted mathematical discovery
2.8 Materials science
2.9 Generative engine optimization
3 Software and hardware
3.1 Generative models and training techniques
3.1.1 Generative adversarial networks
3.1.2 Variational autoencoders
3.1.3 Transformers
4 Law and regulation
4.1 Copyright
4.1.1 Training with copyrighted content
4.1.2 Copyright of AI-generated content
5 Concerns
5.1 Societal impacts
5.1.1 Effects on mental health
5.1.2 Academic honesty
5.1.3 Fears over job losses
5.1.4 Use in journalism
5.2 Bias
Categories
2020s fads and trends2020s in computing2023 in computing2024 in computing2025 in computingArtificial neural networksDeep learningGenerative AIMachine learning
External references
Recent revisions
FrostSep 1, 2026 11:51 AM — Reverted edits by [[Special:Contributions/~2026-47625-33|~2026-47625-33]] ([[User talk:~2026-47625-…
~2026-47625-33Sep 1, 2026 11:50 AM — /* History */ 67890
Beatboxxx49Sep 1, 2026 9:13 AM — Expanded mental health section
AlenoachSep 1, 2026 5:31 AM — /* Generative neural networks (since the late 2000s) */ reintroduced two references, using cite con…
GrayfellAug 31, 2026 11:45 PM — /* Bias */ Fixing own error
GrayfellAug 31, 2026 11:44 PM — /* Bias */ Ref formatting
Contributors
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Templates used
AI artArtificial general intelligenceArtificial imaginationArtificial intelligence artArtificial intelligence in musicArtificial lifeChatbotComputational creativityDiffusion-based generative modelsDiffusion modelGenerative AI pornographyGenerative adversarial networkGenerative pre-trained transformerLarge language modelMusic and artificial intelligence
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Generative artificial intelligenceAI-generatedGenAIArtificial Generative IntelligenceArtificial generative intelligenceGenaiGen AIGen aiAI content creationArtificial intelligence content creationArtificial intelligence in content creationAI in content creationAI generatedAI GenerationAI generation
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Wikidata knowledge graph Q117246174

generative artificial intelligence

artificial intelligence model capable of generating content in response to a prompt

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Subclass of
artificial intelligence model, artificial intelligence, generative model
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