Evolution as both training run and algorithm designer

Evolution can be analogized two ways — as a training run producing humans as the end product, or as an algorithm designer producing a learning algorithm that runs over a human lifetime — and neither analogy is great, since the genome behaves very differently from a 100-trillion-parameter model and human lifetime learning is in many ways much better than gradient descent.