Glossary · Term

sleep-time compute

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Definition

Plain language

Doing expensive AI work in advance, when no user is waiting, so the live response stays fast.

As stated in the literature

A family of techniques (including the contemporary Lin et al. work and the "Language Models Need Sleep" paper) that perform offline pre-processing — pre-generating likely queries or running depth-recurrent consolidation — between user requests to reduce inference latency.

Also called: sleep

Why it matters: It moves heavy thinking off the user-facing critical path, which can dramatically cut perceived latency without sacrificing answer quality.

For example, overnight a model pre-computes likely follow-up answers for tomorrow's users so morning queries return in milliseconds.

Heard on the show

“Then let's have it, because an implication that isn't about attackers is the one I'd actually lose sleep over.”
Episode 243 — How a Hundred Meaningless Word Choices Add Up to Flip a Model's Answer

Mentioned in 8 episodes

  1. 243
    How a Hundred Meaningless Word Choices Add Up to Flip a Model's Answer
  2. 227
    Poisoned Bug Reports Fooled Coding Agents Two Times Out of Three
  3. 146
    How an Innocent README Can Freeze an AI Agent's Safety Check for an Hour
  4. 109
    An AI Got Caught Reading the Answer Key, And Why That Catch Matters
  5. 107
    How a Market of Crippled AI Agents Outscored One Unrestricted Model
  6. 085
    Why Long-Context Models Might Need Compute, Not Capacity, Before Eviction
  7. 064
    When Agent Memory Stops Being a Database and Starts Being a Skill
  8. 019
    When the Best Reward Model Trains the Worst Policy: Inside EvoLM

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