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Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is artificial intelligence capable of generating text, images, videos, or other data using generative models, [2] often in response to prompts.
Generative models. Illustration: Ludwig Pettersson. This post describes four projects that share a common theme of enhancing or using generative models, a branch of unsupervised learning techniques in machine learning.
Generative AI models can generate unique works of art and design, or assist in graphic design. Applications include dynamic generation of environments, characters or avatars, and special effects for virtual simulations and video games.
Generative AI is based on a foundation models. Foundation models are huge models (billions of parameters), pre-trained on giant datasets (GB or TB of data), and capable of performing an...
Generative AI is a type of AI (such as ChatGPT) that can generate new forms of creative content, such as audio, code, images, text, simulations and videos.
Generative AI can be thought of as a machine-learning model that is trained to create new data, rather than making a prediction about a specific dataset. A generative AI system is one that learns to generate more objects that look like the data it was trained on.
Generative AI models can create graphs that show new chemical compounds and molecules that aid in drug discovery, create realistic images for virtual or augmented reality, produce 3D models for video games, design logos, enhance or edit existing images, and more.
What is a generative AI model? Generative AI models are a subset of artificial intelligence systems that specialize in creating new, original content that mirrors the characteristics of their training data.
Generative AI can be thought of as a machine-learning model that is trained to create new data, rather than making a prediction about a specific dataset. A generative AI system is one that learns to generate more objects that look like the data it was trained on.
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