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.
Software agents that can perform tasks or services for an individual based on verbal commands.
A problem-solving process that includes logical reasoning, pattern recognition, abstraction, and algorithmic thinking.
A structured framework for product design that stands for Comprehend the situation, Identify the customer, Report customer needs, Cut through prioritization, List solutions, Evaluate trade-offs, and Summarize recommendations.
A brainstorming technique where participants draw their ideas instead of writing them down.
The practice of designing and implementing processes, systems, or business solutions in a way that ensures their long-term viability, efficiency, and maintainability.
A cognitive bias where group members tend to discuss information that everyone already knows rather than sharing unique information, leading to less effective decision-making.
Jobs-To-Be-Done (JTBD) is a framework that focuses on understanding the tasks users are trying to accomplish with a product, emphasizing their goals and motivations over product features.
Garbage In-Garbage Out (GIGO) is a principle stating that the quality of output is determined by the quality of the input, especially in computing and data processing.