Generative Modeling
The use of algorithms to generate new data samples that resemble a training dataset, often used in AI for creating realistic outputs.
The use of algorithms to generate new data samples that resemble a training dataset, often used in AI for creating realistic outputs.
An iterative design process that uses algorithms and computational tools to generate a wide range of design solutions based on defined constraints and goals.
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models.
A design approach that uses data, algorithms, and predictive analytics to anticipate user needs and behaviors, creating more personalized and effective experiences.
A search method that seeks to improve search accuracy by understanding the contextual meaning of terms in a query rather than just matching keywords.
A type of artificial intelligence capable of generating new content, such as text, images, and music, by learning from existing data.
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance.
An inference method used in AI and expert systems where reasoning starts from the goal and works backward to determine the necessary conditions.
An inference method used in AI and expert systems where reasoning starts from known facts and applies rules to derive new facts.