Assuming AI is aligned, I don’t see how self-replicating machines would be useful. I doubt there’ll be much pressure for that. If AI is malicious, self-replication hardly matters.
The real-world data is likely the real obstacle. With enough, I expect they’ll be able to compensate for manufacturing defects, and have regular maintenance. I assume they’ll be able to self-improve with more experience (and likely pooling experiences)
My speculation is that one day the AI might be able to engineer self replicating machines in a simulation, while it is still too shortsighted to realize that the machines will help humanity pause AI and thwart its chances of taking over the world.
This way self replicating machines may be useful even if the AI is misaligned.
I think uploading a lot of machines into the simulation, and performing manufacturing inside the simulation (in order to get data about manufacturing defects and wear and tear) will be very expensive. But it might be relatively far less expensive than manufacturing in the real world, which we do manage to afford.
We might only need to do this once.
Wear and tear might be estimated by running a simulation for a long time, and the training an AI to predict long term wear and tear using short term data.
Assuming AI is aligned, I don’t see how self-replicating machines would be useful. I doubt there’ll be much pressure for that. If AI is malicious, self-replication hardly matters.
The real-world data is likely the real obstacle. With enough, I expect they’ll be able to compensate for manufacturing defects, and have regular maintenance. I assume they’ll be able to self-improve with more experience (and likely pooling experiences)
It’s pure speculation though.
My speculation is that one day the AI might be able to engineer self replicating machines in a simulation, while it is still too shortsighted to realize that the machines will help humanity pause AI and thwart its chances of taking over the world.
This way self replicating machines may be useful even if the AI is misaligned.
I think uploading a lot of machines into the simulation, and performing manufacturing inside the simulation (in order to get data about manufacturing defects and wear and tear) will be very expensive. But it might be relatively far less expensive than manufacturing in the real world, which we do manage to afford.
We might only need to do this once.
Wear and tear might be estimated by running a simulation for a long time, and the training an AI to predict long term wear and tear using short term data.