They are certainly still used for RL (and other cases where you don’t have a gradient), but even in those contexts there have been modern advancements that cause the preferred algorithms to diverge from old-school genetic algorithms. For instance, things like Particle Swarm Optimization and the Cross Entropy Method have their conceptual origins in the similar sampling regimes as MCMC approaches, but they’ve become their own entities at this point, outperforming genetic algorithms, and really being unique and broad enough to get their own categories.