Beginning in the late 2000s, the emergence of deep learning drove progress and research in image and video processing, text analysis, speech recognition, and other tasks. Since its founding, the field of machine learning has used statistical models, including generative models, to model and predict data. While not a top priority, one of the WGA's 2023 requests was 'regulations around the use of (generative) AI'. History Ī picketer at the 2023 Writers Guild of America strike.

However, there are also concerns about the potential misuse of generative AI, such as in creating fake news or deepfakes, which can be used to deceive or manipulate people. Investment in generative AI surged during the early 2020s, with large companies such as Microsoft, Google, and Baidu as well as numerous smaller firms developing generative AI models. Generative AI has potential applications across a wide range of industries, including art, writing, software development, product design, healthcare, finance, gaming, marketing, and fashion. Other generative AI models include artificial intelligence art systems such as Stable Diffusion, Midjourney, and DALL-E.

Notable generative AI systems include ChatGPT (and its variant Bing Chat), a chatbot built by OpenAI using their GPT-3 and GPT-4 foundational large language models, and Bard, a chatbot built by Google using their LaMDA foundation model. Generative AI models learn the patterns and structure of their input training data, and then generate new data that has similar characteristics. Generative artificial intelligence or generative AI is a type of artificial intelligence (AI) system capable of generating text, images, or other media in response to prompts. Not to be confused with Artificial general intelligence.

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