Expert System Architecture — components?
Knowledge base and inference engine
Knowledge Base — role?
Stores expert’s facts and rules
Inference Engine — function?
Applies logic to deduce decisions
NLP analysis levels — order?
Phonological, morphological, lexical, syntactic, semantic, pragmatic
Robotics — main components?
Sensors, actuators, control systems
Computer Vision — key techniques?
Filtering, feature extraction, object detection
VLSI testing — primary goal?
Fault detection and diagnosis
Sustainable AI — focus?
Minimize energy, environmental impact
Responsible AI — principles?
Fairness, transparency, accountability
Bias in AI — mitigation?
Identify, reduce, ensure fairness
Test your knowledge with 5 questions on Foundations of Intelligent Systems and Ethical AI.
1. How do the knowledge base and inference engine in expert systems architecture fundamentally differ from each other?
2. What is the primary purpose of analyzing language at different NLP levels such as phonological, morphological, lexical, syntactic, semantic, and pragmatic?
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