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The AI race will not be decided by model size alone. It will be decided in silicon. Every major advance in artificial intelligence eventually collides with a physical limit: memory bandwidth, data movement, power consumption, heat, interconnect speed, manufacturing yield, or cost. That is why the most important question in AI hardware is not simply: How many operations can this chip perform? The real question is: How much useful computation can the complete system sustain when the model, memory, software, power, cooling, and communication demands are included? Modern AI Chips: Architecture, Systems, and Frontiers takes you inside the technologies determining the future of artificial intelligence-from numerical formats and tensor cores to HBM4, chiplets, wafer-scale processors, advanced packaging, data-centre interconnects, and edge AI. You will discover: This is not a superficial catalogue of processor announcements. It is a systems-level examination of the architecture, semiconductor technology, memory, packaging, networking, thermals, software, and economics behind modern AI computation. Whether you are an engineer, developer, technical investor, student, researcher, technology strategist, or serious industry observer, this book will give you the framework needed to look beyond marketing claims and identify where genuine hardware advantage resides. Understand the machines beneath the models-and the physical limits shaping the next generation of artificial intelligence.
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