Generative Artificial Intelligence
Generative AI is a subfield of artificial intelligence that uses machine-learning models to produce new content such as text, images, video, audio, or code in response to user prompts. Emerging from early foundations like Markov chains (1906) and Harold Cohen’s AARON (1970s), the field advanced significantly with deep learning breakthroughs including variational autoencoders, GANs (2014-2019), and the Transformer architecture (2017). The AI boom began in 2020 with models like DALL-E and Midjourney, and accelerated with ChatGPT’s 2022 release, bringing generative AI to mainstream adoption.
Authoritative Definitions
Generative Artificial Intelligence (Generative AI or GenAI) is most commonly and authoritatively defined as:
" A subfield of artificial intelligence that uses machine-learning–based generative models to learn the underlying patterns and structures of a training dataset, and then produces entirely new content—text, images, video, audio or other data—in response to user input (often natural-language prompts). “1
A concise variant from Merriam-Webster similarly reads:
" Artificial intelligence that is capable of generating new content (such as images or text) in response to a submitted prompt by learning from a large reference database of examples. “2