AI Breakthroughs (eBook, ePUB)
Theories and Concepts for Today
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The illustrations in this book are created by "Team Educohack".AI Breakthroughs: Theories and Concepts for Today is designed to guide readers through the essential scientific and technological principles that make artificial intelligence (AI) possible. We aim to enhance understanding of AI's development and its pervasive role in our lives.We explore two fundamental questions: Should AI replicate human performance through machines, or should it emulate the way humans think and act? This book discusses "classical AI" and machine learning (ML), the two main approaches to AI. While classical AI, d...
The illustrations in this book are created by "Team Educohack".
AI Breakthroughs: Theories and Concepts for Today is designed to guide readers through the essential scientific and technological principles that make artificial intelligence (AI) possible. We aim to enhance understanding of AI's development and its pervasive role in our lives.
We explore two fundamental questions: Should AI replicate human performance through machines, or should it emulate the way humans think and act? This book discusses "classical AI" and machine learning (ML), the two main approaches to AI. While classical AI, dating back to the 1960s, uses logic and representations to mimic human reasoning, ML, a newer method, focuses on manipulating numbers and statistical patterns to find answers.
Drawing insights from Daniel Kahneman's Behavioral Economics, we demonstrate that purely rational AI, operating solely on logical symbols, does not reflect human thought processes.
This book is crafted to support students, helping them grasp each concept in detail and ensuring they benefit from a thorough understanding of AI.
AI Breakthroughs: Theories and Concepts for Today is designed to guide readers through the essential scientific and technological principles that make artificial intelligence (AI) possible. We aim to enhance understanding of AI's development and its pervasive role in our lives.
We explore two fundamental questions: Should AI replicate human performance through machines, or should it emulate the way humans think and act? This book discusses "classical AI" and machine learning (ML), the two main approaches to AI. While classical AI, dating back to the 1960s, uses logic and representations to mimic human reasoning, ML, a newer method, focuses on manipulating numbers and statistical patterns to find answers.
Drawing insights from Daniel Kahneman's Behavioral Economics, we demonstrate that purely rational AI, operating solely on logical symbols, does not reflect human thought processes.
This book is crafted to support students, helping them grasp each concept in detail and ensuring they benefit from a thorough understanding of AI.
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