Generative AI refers to a category of artificial intelligence techniques that can create new data or content, such as images, text, music, or video. It involves using machine learning algorithms to model and learn patterns in data, and then using that knowledge to generate new examples that are similar in some way to the original data.
Generative AI techniques can be used for a wide range of applications, from creating realistic images and videos, to generating new music or text. Some common examples of generative AI models include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers.
One of the key advantages of generative AI is its ability to create new and unique content that would be difficult or impossible for humans to produce on their own. This has led to a range of innovative and exciting applications, including virtual assistants, personalized content recommendations, and even art and music creation.
Generative AI can often be confused with large language models. Although related, they are distinct concepts in artificial intelligence.
Generative AI is a category of machine learning techniques that involves creating new data or content based on patterns learned from existing data. On the other hand, large language models are a specific type of generative AI model that focuses on natural language processing.
- Large Language Model (LLM)
- Generative Adversarial Network (GAN)
- Deep Learning