Semantic Encoding
The process of encoding sensory input that has particular meaning or can be applied to a context, enabling deeper processing and memory retention.
The process of encoding sensory input that has particular meaning or can be applied to a context, enabling deeper processing and memory retention.
A theory that suggests the depth of processing (shallow to deep) affects how well information is remembered.
A type of model architecture primarily used in natural language processing tasks, known for its efficiency and scalability.
An AI model that has been pre-trained on a large dataset and can be fine-tuned for specific tasks.
A cognitive approach that involves meaningful analysis of information, leading to better understanding and retention.
User-Centered Design (UCD) is an iterative design approach that focuses on understanding users' needs, preferences, and limitations throughout the design process.
Natural Language Processing (NLP) is a field of AI focused on the interaction between computers and humans using natural language.
A mode of thinking, derived from Dual Process Theory, that is fast, automatic, and intuitive, often relying on heuristics and immediate impressions.
A component in neural networks that allows the model to focus on specific parts of the input, improving performance.