Abstraction in AI
Abstraction in AI is the process of simplifying complexity by focusing on essential features and hiding irrelevant details, facilitating human-like perception, knowledge representation, reasoning, and learning. It’s extensively applied in problem-solving, theorem proving, spatial and temporal reasoning, and machine learning.
Areas of application
- Artificial Intelligence
- Natural Language Processing
- Machine Learning
- AI Safety
- Robotics
Example
For instance, a self-driving car using AI abstraction can focus on the essential features of a scene, such as the location of other cars, pedestrians, and road signs, while ignoring irrelevant details like the color of the buildings or the make of the passing cars.