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Unraveling Exa.ai’s Infrastructure Costs: A Deep Dive with Napkin Math

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Unlocking the Future of Web Search: Exa’s Revolutionary Approach

Exa has recently raised $85 million in Series B funding, signaling a significant leap in web search innovation. Their AI architecture enhances search speed and relevance, making it a game-changer in the industry.

Key Highlights:

  • Storage Insights:

    • Fineweb’s 26B documents require 44 TB (compressed).
    • Projections suggest that 1B documents would require about 1.9 TB compressed.
  • Optimization Breakthroughs:

    • Lexical search RAM requirement cut down from 1.8 TB to 900 GB due to architectural improvements.
    • Vector search latency has improved significantly, achieving p50 = 346 ms, a 79 ms reduction.
  • Cost Efficiency:

    • Exa’s cluster dramatically reduces embedding costs, estimated at $9.75K monthly for 1B documents.
    • Annual maintenance cost for 20B+ documents estimated at $1.1 million.

Exa is paving the way for the future of search engines with smart algorithms and innovative strategies, aimed at positioning itself among industry leaders like Google.

👉 Let’s engage! Share your thoughts on how AI is reshaping web search!

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