Manuscript OpenAI@2026-10-07 · OpenAI.tex · remark · 6a931f8f
Remark: 140-05. Replacing Gaussian observations in memory-constrained inference
Manuscript map · lines 5135–5144
OpenAI@2026-10-07#rem:oai-p-140-05
Authors: OpenAI. Family 140.
Title: Replacing Gaussian observations in memory-constrained inference.
Abstract: Replacing the Gaussian rows used to select a finite message by independent rows increases the remaining conditional information by at most $Cd$, for a uniform spherical signal, message entropy at most d2, and the specified row dimensions proportional to d. As an application, we prove that learners with $M=o(d{}2)$ persistent bits need $T={}Omega(d{}log(1/{}epsilon))$ exact observations to attain uniform-sphere angular success at least 3/5, for $0{}lt {}epsilon{}le1/10$ and a deterministic finite horizon.
This abstract is a catalogue record. It is not a verification and not a premise. It does not close O.1. O.1 stays NOT_CLOSED. No quantum coefficient is admitted. No compilation is asserted.
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