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Reproducible AI Requires Reproducible Randomness

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Pseudorandom number generators (PRNGs) constitute indispensable computational tools across multiple scientific domains, including Monte Carlo simulations, stochastic computing, and artificial intelligence (AI). The reproducibility of such applications critically depends on the ability of PRNG implementations to generate identical sequences across software environments when initialized from the same internal state. These algorithms enable the simulation of stochastic processes while providing deterministic and repeatable behaviour, thereby facilitating reproducible experiments. Modern PRNG impl

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Evidence & attribution

First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.