In the context of that sentence though, it doesn’t make any sense. PCG is a PRNG, not a library for generating distributions. In fact, the PCG documentation use

In the context of that sentence though, it doesn’t make any sense. PCG is a PRNG, not a library for generating distributions. In fact, the PCG documentation uses the distributions from <random>: [1]. If people want to use PCG, that’s perfectly fine, it’s a great library. My point is, there’s nothing wrong with the PRNGs in <random>, they work great. Mersenne Twister is not state of the art anymore, but I guarantee you that unless you’re doing something truly insane, neither the throughput nor the statistical properties of MT is gonna be your bottleneck. [1]: https://www.pcg-random.org/using-pcg-cpp.html https://www.pcg-random.org/using-pcg-cpp.html