Generative artificial intelligence

Not to be confused with Artificial general intelligence.

Generative artificial intelligence, also known as generative AI or GenAI, is a subfield of artificial intelligence 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, Copilot, DeepSeek, Google Gemini and Grok; text-to-image models such as Stable Diffusion, Flux, Midjourney, and DALL-E; 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. Many generative AI systems use large-scale data centers whose environmental impacts include e-waste, consumption of fresh water for cooling, and high energy consumption that is estimated to be growing steadily.

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