Learning the Essence of AI, Research and Notations# Contents Preface Intentions Let’s L.E.A.R.N! Demystifying the Buzzwords 1 Introduction 2 General Intelligence 2.1 Definition and Context 2.2 Evolutionary Aspect of Intelligence 2.2.1 Learning from Cognition 2.2.2 Dynamic and Adaptive Nature of Intelligence 2.2.3 Parallels with Human Intelligence and Ethical Implications 3 Natural Learning 3.1 Sensory Learning and Retention 3.2 Role of Memory in the Learning Process 3.3 Parallels Between Human and AI Learning 3.3.1 Learning in the Natural World 3.3.2 Instinct versus Learned Behavior 4 Distinctive Aspects of Intelligence and Learning 4.1 Intelligence as an Array of Cognitive Skills 4.2 Observations from Animal Kingdom 4.3 Translating Learning to AI Development 5 Artificial Intelligence 5.1 Current System and Future Prospects 5.1.1 Ethical Considerations and Societal Impact 5.1.2 Artificial Narrow Intelligence 5.1.3 The Quest for Artificial General Intelligence 5.2 Ethical Responsibilities in AI Development 6 Machine Learning 6.1 Understanding the Basics 6.1.1 The Learning Process in Machines 6.1.2 Historical Context and Evolution 6.2 Drawing Parallels with Human Learning 6.2.1 Chunk-Based Learning Approach 6.2.2 Importance of Data Diversity in Learning 6.2.3 Human Revision and Machine Learning Processing 6.2.4 Understanding Ground Truth and Loss 6.3 Challenges and Human Intervention in Machine Learning 6.3.1 Initial Exposure and Learning Curve 6.3.2 Impact of Data Quality on Learning Outcomes 6.3.3 Exploring Through Analogies Mathematics: The Universal Language 1 Introduction 2 Lexicon of Artificial Intelligence 2.1 Crafting the Vernacular of the Cosmos 2.2 From Symbols to Sentience 3 From Numbers to Neural Networks 3.1 The Fundamentals 3.2 Power of Algorithms and their Sustainability 4 Symphony of Numbers in Artificial Intelligence 4.1 Real Numbers 4.2 Complex Numbers 4.3 Rational Numbers 4.4 Irrational Numbers 4.5 Integers Sponsor Follow Connect