Overview

Silicon, Power, and Intelligence Volume I: Foundations of Hardware-Aware AIArtificial intelligence is often portrayed as a triumph of algorithms. In reality, it is a triumph of physics. Every token generated by an AI model, every inference performed by a neural network, and every breakthrough in machine learning is ultimately governed by the movement of electrons through silicon, the flow of energy through hardware, and the relentless constraints imposed by memory, heat, and thermodynamics. In Foundations of Hardware-Aware AI, engineer and author Sanzaya Patel takes readers on a fascinating journey beneath the software stack to uncover the physical principles that make modern intelligence possible. Beginning with the economics of inference and the thermodynamic cost of information, this volume explores the hidden mechanisms that shape the performance of today's AI systems-from CMOS power dynamics and memory bottlenecks to dataflow architectures, AI accelerators, thermal management, and hardware security. Unlike traditional AI books that focus solely on models and algorithms, this volume presents a unified systems-level perspective that connects information theory, semiconductor physics, computer architecture, and artificial intelligence engineering into a single coherent framework. Inside, you will discover: Why moving data often consumes more energy than computation itself How the Memory Wall has become the defining challenge of modern AI Why GPUs, NPUs, and specialized accelerators are transforming inference How thermodynamics places fundamental limits on computation Why power, heat, latency, and intelligence are inseparably linked The engineering principles that will shape the future of edge and cloud AI Whether you are an engineer, researcher, student, architect, or technology enthusiast, this book provides the essential foundation needed to understand not only how artificial intelligence works, but why it works-and why its future depends on mastering the physical world beneath the code. Before there were models, there was silicon. Before there was intelligence, there was energy. The journey to understanding AI begins here.

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