Evolution Strategies is a type of black-box optimization algorithm that can be used to optimize deep learning models without knowing their precise analytic form. Unlike stochastic gradient descent, which requires access to the model's gradients, Evolution Strategies only needs function evaluations to find optimal parameters. This makes it useful for scenarios where the model's internal workings are not well understood or cannot be modified. --- Why it matters: Evolution Strategies is relevant to AI researchers because it provides an alternative optimization method that can work with complex models without requiring detailed knowledge of their inner workings, potentially leading to more robust and adaptable systems. Source: https://lilianweng.github.io/posts/2019-09-05-evolution-strategies/