Principles of Artificial Intelligence
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Introduction8 Topics|1 Quiz
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Core concepts of Artificial Intelligence15 Topics
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Learning (Machine Learning, Deep Learning, Reinforcement Learning)
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Reasoning (Logical Inference, Decision-Making, Planning Algorithms)
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Perception (Computer Vision, Speech Recognition, NLP)
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Knowledge Representation (Ontologies, Knowledge Graphs, Structured Data)
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Problem-Solving (Search Algorithms, Optimization Techniques)
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Natural Interaction (Human-Computer Interaction, Conversational AI, Virtual Assistants)
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Autonomy (Self-Learning Systems, Autonomous Agents, Robotics)
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Generalization (Transfer Learning, Few-Shot Learning, Zero-Shot Learning)
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Transparency & Explainability (Interpretable Models, Explainable AI, Trustworthiness)
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Fairness & Ethics (Bias Mitigation, Responsible AI, AI for Social Good)
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Robustness & Safety (Adversarial Robustness, Reliability, Fault Tolerance)
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Scalability (Distributed Computing, Cloud AI, Edge AI)
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Computational Efficiency (Hardware Acceleration, Model Compression, Energy-Efficient AI)
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Adaptability (Self-Improving Systems, Meta-Learning, Domain Adaptation)
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Emerging Principles and Considerations
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Learning (Machine Learning, Deep Learning, Reinforcement Learning)
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Important Questions on AI Principles14 Topics
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How do machines learn through different approaches in AI?
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What techniques enable AI to reason and make decisions?
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How do AI systems perceive and understand the world around them?
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How is knowledge represented in AI systems?
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What algorithms do AI systems use for problem-solving?
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How do AI systems interact with humans in a natural way?
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What makes an AI system autonomous?
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How do AI models generalize to new tasks or data?
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Why are transparency and explainability important in AI?
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How do we ensure AI is fair and used ethically?
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How can AI systems be made robust and safe from failure or attack?
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How do AI systems scale to handle very large data and many users?
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What techniques improve the computational efficiency of AI?
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How do AI systems adapt and self-improve when facing new conditions?
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How do machines learn through different approaches in AI?
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Glossary of Key AI Terms
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Recommended literature on Principles of AI
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References on Principles of AI
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Tools for Demonstrating AI Concepts11 Topics
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Machine Learning Basics – Google Teachable Machine
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Machine Learning Basics - ML Playground
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Deep Learning Fundamentals - Runway ML
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Deep Learning Fundamentals – Google Colab
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Natural Language Processing - Hugging Face Transformers Demo
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Reinforcement Learning - OpenAI Gymnasium
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Reinforcement Learning – SimpleGrid
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Generative AI - Image Processing and Computer Vision – DeepAI
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Image Processing and Computer Vision – YOLO
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General AI Demonstration Platforms - AI Experiments by Google
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General AI Demonstration Platforms - Kaggle Kernels
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Machine Learning Basics – Google Teachable Machine
Participants 15
Definition of Intelligence
Intelligence is the ability to acquire, understand, and apply knowledge and skills to solve problems, adapt to new situations, reason, and make decisions.
Key Aspects of Intelligence
- Learning – The ability to acquire and retain knowledge from experience.
- Reasoning & Problem-Solving – Applying logic and strategies to solve problems.
- Adaptability – Adjusting to new situations and environments.
- Memory – Storing and retrieving information when needed.
- Creativity – Generating novel ideas and solutions.
- Social Intelligence – Understanding and interacting with others.
- Self-Awareness – Recognizing one’s own thoughts and emotions (in humans and potentially in advanced AI).
Types of Intelligence
- Human Intelligence: Cognitive abilities in reasoning, learning, and problem-solving.
- Artificial Intelligence: Machine-based intelligence designed to mimic cognitive functions.
- Emotional Intelligence (EQ): The ability to understand and manage emotions.
- Multiple Intelligences (Howard Gardner’s Theory): Includes logical-mathematical, linguistic, spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal, and naturalistic intelligence.
Comparison: Human vs. Artificial Intelligence
Feature | Human Intelligence | Artificial Intelligence |
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Learning | Experience-based (general) | Data-driven (task-specific) |
Creativity | High, innovative thinking | Limited (emulates patterns) |
Adaptability | Quick generalization | Requires retraining |
Emotion & Self-Awareness | Yes | No (yet) |
Processing Speed | Slower (biological limits) | Faster (for computations) |
Definitions of Intelligence
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American Psychological Association (APA) Dictionary of Psychology: Defines intelligence as “the ability to derive information, learn from experience, adapt to the environment, understand, and correctly utilize thought and reason.” dictionary.apa.org
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Britannica: Describes human intelligence as “the mental quality that consists of the abilities to learn from experience, adapt to new situations, understand and handle abstract concepts, and use knowledge to manipulate one’s environment.” Encyclopædia Britannica
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Verywell Mind: Highlights that intelligence involves mental abilities such as logic, reasoning, problem-solving, and planning. verywellmind.com