Modern AI Chips: Architecture, Systems, and Frontiers

By: Thomas, Gareth Morgan

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:

Why the memory wall now matters more than raw arithmetic throughputWhy AI training and inference demand fundamentally different hardwareHow FP32, BF16, FP8, INT8, INT4, and FP4 change performance, accuracy, capacity, and costWhy HBM has become one of the most strategically important components in computingHow tensor cores, systolic arrays, dataflow processors, and SRAM-centric architectures actually workHow NVIDIA, AMD, Google, AWS, Groq, Cerebras, SambaNova, Taalas, and emerging Chinese GPU developers attack the same constraints differentlyWhy chiplets, silicon interposers, hybrid bonding, and multi-reticle packaging are replacing traditional monolithic scalingHow NVLink, Infinity Fabric, Ethernet, and other interconnect technologies determine cluster-level performanceWhy 1,000-watt-class accelerators are transforming data-centre power delivery and coolingHow compilers, operator fusion, runtimes, and software ecosystems determine whether theoretical performance becomes usable performanceWhy TOPS, FLOPS, tokens per second, latency, throughput, and vendor benchmarks can mislead even experienced buyersHow to evaluate an AI accelerator as a complete engineering system rather than a collection of headline specifications

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.

• Format: Paperback
• Language: English
• ISBN: B0HJZZF11N
• ISBN13: 9798174765405
• Release Date: September 2026
• Publisher: Independently Published
• Length: 458 Pages
• Weight: 2.32 lbs.
• Dimensions: 0.9" x 8.5" x 11.0"