napkin-math

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#napkin-math

@ycombinator: In 2001, @JeffDean and Sanjay Ghemawat did the math and realized Google’s entire search index would fit in RAM — then s…

X AI KOLs Timeline ↗ · 2026-07-30 Cached

At Startup School 2026, Google's Chief Scientist Jeff Dean recounts the napkin math that led to Google's search index fitting in RAM and the TPU development, discussing inference hardware specialization and how startups can still compete.

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#napkin-math

@GergelyOrosz: That @Sirupsen measured, published then memorized about 3x these numbers on networking+latency "basics" is only surpris…

X AI KOLs Following ↗ · 2026-07-21 Cached

Gergely Orosz praises Sirupsen for his deep understanding of networking and latency basics, referencing an interview where Sirupsen used napkin math to build a 10x cheaper or faster product.

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#napkin-math

@GergelyOrosz: More engineers should do this kind of napkin math and ask: “what is the *theoretical* limit of throughput for this syst…

X AI KOLs Following ↗ · 2026-06-30 Cached

The tweet highlights a fireside chat at AIE Worlds Fair where Simon Eskildsen emphasizes the value of napkin math for estimating theoretical system throughput limits and understanding why actual performance differs.

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#napkin-math

Inference cost at scale with napkin math (13 minute read)

TLDR AI ↗ · 2026-06-15 Cached

A technical walkthrough that shows how to estimate the cost of serving AI models at scale using simple napkin math, covering GPU bandwidth, matrix multiplication, token pricing, and user capacity.

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#napkin-math

The third wave of American philanthropy (23 minute read)

TLDR AI ↗ · 2026-05-20 Cached

A napkin math analysis reveals that philanthropic capital from OpenAI and Anthropic could add $37B-$100B per year to US giving, drastically increasing available funds and highlighting a gap in operational capacity to spend it effectively.

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