Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability
PositiveArtificial Intelligence
A recent study explores how Transformer models can effectively learn sequences generated by Permuted Congruential Generators (PCGs), which are more complex than traditional linear congruential generators. This research is significant as it demonstrates the capability of advanced AI models to tackle challenging tasks in random number generation, potentially enhancing their application in various fields such as cryptography and simulations.
— Curated by the World Pulse Now AI Editorial System


