AIXI-tl is very inefficient. Practical AIs will not be like that, and they will not be limited to one rigid goal like that.

Your second claim doesn't follow from the first. Practical AIs will of course be different. But the basic structure of AIXI, reinforcement learning, is agnostic to the model used. It just requires some algorithm to do learning/prediction. As prediction algorithms get better and better, they will still suffer the same problems as AIXI. Unless you are proposing some totally different model of AI than reinforcement learning, that somehow doesn't suffer from these problems.

And even if you find my theory of intelligence unconvincing, one that implies that evolution is intelligent is even less convincing, since it does not respect what people actually mean by the word.

Now we are debating definitions, which is not productive.

Evolution is not typically thought of as intelligent because it's not an agent. It doesn't exist in an environment, make observations, and adjust it's model of the world, etc. I accept that evolution is not an agent. But that doesn't matter.

There is only one problem that we really care about. Optimization. This is the only thing that really matters. The advantage humans have in this world is our ability to solve problems and develop technology. The risk and benefit of superintelligent AI comes entirely from its potential to solve problems and engineer technologies better than humans.

And that's exactly what evolution does. It's an algorithm that can solve problems and design very sophisticated and efficient machines. It does the thing we care about, despite not being an agent. Whether it meets the definition of "intelligence" or not, is really irrelevant. All that matters is if it's an algorithm that can solve the types of problems we care about. There is no reason that solving problems or designing machines should require an algorithm to be an agent.