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Home / Glossary / Diffusion Models

What is Diffusion Models?

Diffusion models are generative AI models that learn to generate high-quality images and other data by gradually refining noise into meaningful structures. They have gained prominence in applications like AI art and video generation.

Related Glossaries

  • Support vector machine A Support Vector Machine (SVM) is a supervised learning algorithm used for classification and regression tasks. It identifies decision boundaries by maximizing the margin between data points, making it effective in text classification, image recognition, and anomaly detection.
  • Test data Test data refers to datasets used to evaluate the performance and accuracy of machine learning models. It is separate from training data and ensures that AI systems generalize well to new, unseen data.
  • Data collaboratives Data collaboratives are partnerships where organizations share data to drive social impact, innovation, and research. These collaborations enable secure, privacy-preserving data exchanges across industries such as healthcare, environmental research, and smart city initiatives.
  • Synthetic-first Data Layer Synthetic-first Data Layer refers to the operational layer designed to prioritize synthetic, reconstructed, or transformed data before exposing raw source data downstream. This approach increases usability while reducing dependence on direct source access.
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