The Neural Evolution of AI
From Neurons to Networks and Beyond
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Beschreibung
The author tells the untold story behind artificial intelligence. From early discoveries about how neurons communicate to today’s powerful neural networks, deep learning and generative AI systems, this book traces how ideas from neuroscience shaped the machines that now shape our world. Written in clear, accessible language, it reveals how concepts such as learning, perception, and memory were first observed in biology and later translated into algorithms. More importantly, it shows how modern AI is now influencing the way scientists think about the brain, intelligence, and even what it means to be human. Based on realistic research rather than hype, the book is meant for anyone curious about where artificial intelligence truly came from—and what its growing role means for our future.
The book is written to serve both upper-level undergraduate and postgraduate students seeking conceptual grounding in AI beyond technical manuals, and academics and researchers in AI, neuroscience, philosophy, ethics, and social science, examining the origins, meaning, and societal implications of intelligent systems. The book should benefit students, researchers, engineers, and social scientists by providing historical grounding, conceptual clarity, and a framework for understanding AI as part of a longer scientific tradition. It builds on foundational neuroscience and AI research while contributing a novel interdisciplinary approach.
The author tells the untold story behind artificial intelligence. From early discoveries about how neurons communicate to today’s powerful neural networks, deep learning and generative AI systems, this book traces how ideas from neuroscience shaped the machines that now shape our world. Written in clear, accessible language, it reveals how concepts such as learning, perception, and memory were first observed in biology and later translated into algorithms. More importantly, it shows how modern AI is now influencing the way scientists think about the brain, intelligence, and even what it means to be human. Based on realistic research rather than hype, the book is meant for anyone curious about where artificial intelligence truly came from—and what its growing role means for our future.
The book is written to serve both upper-level undergraduate and postgraduate students seeking conceptual grounding in AI beyond technical manuals, and academics and researchers in AI, neuroscience, philosophy, ethics, and social science, examining the origins, meaning, and societal implications of intelligent systems. The book should benefit students, researchers, engineers, and social scientists by providing historical grounding, conceptual clarity, and a framework for understanding AI as part of a longer scientific tradition. It builds on foundational neuroscience and AI research while contributing a novel interdisciplinary approach.
In easy language, reveals how learning, perception or memory were observed in biology and translated into algorithms Explains how modern AI grew directly from neuroscience, tracing early brain research to Deep Learning and Generative AI Is aimed at students, academics and researchers in AI, neuroscience, philosophy, ethics, and social science
Autor*in
Anwaar Ulhaq
Themen in »The Neural Evolution of AI«
Neural AI Neuromorphic Computing Generative Adversarial Networks Deep Learning Perceptron Quantum Computing Agentic AI Diffusion Model Neuron XOR Problem AlphaGo Convolutional Neural Networks Backpropagation Transformer Autoencoder