Once you understand that a chip is a manufactured circuit on silicon, the next question is obvious: why not just make one giant chip for AI?

In this episode, Satish explains how chiplets make modern AI chips possible: large-die limits, specialized silicon blocks, advanced packaging, high-bandwidth memory, fast die-to-die links, and the tradeoffs engineers manage when many pieces must behave like one machine.

This continues the foundation episode on what a computer chip is, and turns it into a practical mental model for modern AI accelerators.

In Simple Terms with Satish: daily technology explained simply, with enough technical depth for builders.

Production note: This episode uses authorized synthetic narration based on Satish's own voice. The topic, script, and final editorial approval are by Satish.

Sources:

• NVIDIA Blackwell architecture - https://www.nvidia.com/en-us/data-center/technologies/blackwell-architecture/
• AMD Instinct MI300X - https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html
• UCIe specifications - https://www.uciexpress.org/specifications
• UCIe - https://www.uciexpress.org/