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New AI chips are announced with bold claims and big numbers. This checklist helps curious readers ask the right questions and keep the claims in context.
Computers use several kinds of memory, each with a different job. Here is how SRAM, DRAM and flash differ and where each fits in AI hardware.
In the late 1950s, two engineers independently figured out how to build a whole circuit on one piece of material. Here is how the integrated circuit...
The graphics processor was built to render games, not to train neural networks. Here is how the GPU evolved into the engine of modern AI.
Processors speak different instruction set languages. Here is what x86, Arm and RISC-V are, how they differ and where each shows up in AI infrastructure.
Chip factories are built around cleanrooms with air far purer than any ordinary room. Here is why cleanliness matters and how these spaces work.
Behind every chatbot reply and image recognition result is a vast amount of matrix multiplication. Here is what that math is and why chips are built...
AI chips juggle several number formats with cryptic names. Here is what the formats mean, why lower precision is popular and how each one is used.
AI clusters grow in two directions: by making tightly linked groups of chips larger, and by connecting more of those groups together. Here is the difference.
AI chip announcements arrive packed with numbers. This question-and-answer guide explains the most common specifications and what each one tells you.
Some ideas about AI hardware get repeated so often they sound true. Here are common myths about AI chips, paired with what is actually going on.
Every AI chip is built from billions of transistors. Here is what a transistor does, how it works in simple terms and why it is so...
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