If there is meaning behind those words, please write something with multiple paragraphs.
I don't see any reason why there would be a limit, instability, or otherwise, any more or less than there is on biological evolution. I also don't see any reason why there wouldn't be a limit. We just have no idea at this point.
I do think a diversity of tasks is critical. An AGI should be able to not just complete human language but:
- Play a diversity of strategic games like chess or Starcraft
- Perform machine vision like Stable Diffusion
- Predict the output of Python programs (and vice-versa)
- Write (correct) mathematical proofs and arguments
- Control a robotic arm or airplane
... and so on.
We can train all of those independently -- and we could do so in a single network now -- but we're at the very early stages of architecture for how those things would integrate.
At some point, the best solution is a very sophisticated intelligence. How close deep learning in current -- and future -- architectures gets us to super-intelligence is an open question.
Let a neural network based agent act in an environment. Record its rewards. Update the neural network so that the best actions become a little more likely, and the worse actions become a little less likely. Thus, we have demonstrated a training step that improves the agent.
Now just run that training step in a loop forever and you'll improve each step and reach Godlike intelligence, right? Right? Well, no, there is instability in "pulling yourself up by the bootstraps", and while I expect to see more GTP improvements, I believe there may be limitations we don't know about yet.