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Equation 31 · Part 3 · OpenAI Model Systems from First Principles: Weights, Post-Training, and Inference Compute

Symbol θ

s=f(θ, e, P, H, S, t),s = f(\theta,\ e,\ \mathcal{P},\ \mathcal{H},\ \mathcal{S},\ t),
θ\theta

What this part means

the weights.

Its job in the formula

θ is an input to the expression that computes the quantity on the left.

Where the article explains it

with weights θ\theta , reasoning effort e , prompt and decoding configuration P\mathcal{P} , evaluation harness H\mathcal{H} , serving stack S\mathcal{S} , and date t .

The passage around this formula

Collect the moving parts and the measurement problem becomes plain. An observed score s is produced by s=f(θ, e, P, H, S, t)s = f(\theta,\ e,\ \mathcal{P},\ \mathcal{H},\ \mathcal{S},\ t). with weights θ\theta , reasoning effort e , prompt and decoding configuration P\mathcal{P} , evaluation harness H\mathcal{H} , serving stack S\mathcal{S} , and date t . A published number fixes s and usually reports only part of θ\theta and t . The system is underdetermined : many configurations produce the same score, and the same configuration produces different scores on different dates.

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Learn the underlying idea

A variable is a named place for a value. Its letter is a local label: x can mean position in one formula and a data point in another.

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