Machine Learning
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
A set of algorithms, modeled loosely after the human brain, designed to recognize patterns and perform complex tasks. Essential for developing advanced AI applications in various fields.
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.
Knowledge Organization System (KOS) refers to a structured framework for organizing, managing, and retrieving information within a specific domain or across multiple domains. Essential for improving information findability, enhancing semantic interoperability, and supporting effective knowledge management in digital environments.
Generative Pre-trained Transformer (GPT) is a type of AI model that uses deep learning to generate human-like text based on given input. This technology is essential for automating content creation and enhancing interactive experiences.
User-Centered Design (UCD) is an iterative design approach that focuses on understanding users' needs, preferences, and limitations throughout the design process. Crucial for creating products that are intuitive, efficient, and satisfying for the intended users.
A phenomenon where people are more likely to remember information when they are in the same state of consciousness as when they learned it. Important for understanding how context affects memory recall and designing experiences that facilitate better retention.
A time-boxed period in which Agile teams deliver incremental value in the form of working, tested software and systems. Essential for aligning teams, managing dependencies, and ensuring continuous delivery.