Generative AI definition
Generative AI is a type of artificial intelligence that can create new content, including imagery, text, and audio data. It uses machine learning (ML) algorithms to analyze large data sets and creates new content based on the learned patterns. This type of artificial intelligence can be used in various applications, such as text generation, video and image production, and music composition.
See also: artificial intelligence
How generative AI works
- Generative AI uses machine learning algorithms to analyze the relationships and patterns in large information datasets. It then uses this knowledge to create new content.
- The first step is training the generative AI model using a large dataset of examples. This information may include text, images, music, or video.
- The model learns the patterns and relationships within the dataset (e.g., which words follow others, which colors appear together, etc.)
- The generative AI model then generates new content using the learned patterns. The new content resembles the training material.
Generative AI examples
- Text generation. Generative AI can be trained using large datasets of text, such as books, blogs, and social media content. It uses this knowledge to generate new text that resembles the original.
- Video creation. Generative AI can generate new videos based on the training material for use in television or virtual reality video games.
- Speech synthesis. Generative AI can create new speech resembling the training data. This technology can be used for voice assistants, text-to-speech conversion, and even synthetic voiceovers for films and TV shows.
Examples of generative AI tools
- ChatGPT: a language generation tool developed by OpenAI and capable of generating human-like responses to various prompts and questions.
- StyleGAN: generates high-quality images that resemble the training data.
- Magenta: an open-source project by Google that can generate music and art.
