A rat can do something else that a neural net can't - it is a self replicator. Our neural nets don't have self replication or a huge, complex environment and timescale to evolve in. Self replication creates an internal goal for agents: survival. This drives learning. Instead, we just train agents with human-made rewards signals. Even a simple environment, like the Go board, when used for training many generations of agents in self-play, easily leads to super-human intelligence. We don't have the equivalent simulator for the real world environment or care to let loose billions of self replicating AI agents in the real world.