If it were that easy, it wouldn't be semi-general, now would it?
In any case, I don't see why adding computing power would be much different than adding time. In fact, I'd expect adding time would be better. Anything you can do with two processers in parallel you can do with one in twice the time by doing one thread after the other. The reverse isn't true.
Twice the time, and twice the space. In any case, it does not work very well like this for brains, where you for some unknown reason fail at remembering more than ~7 objects in short term memory. Cut it to 3, and you may not be able to think many thoughts; add some small tweaks, and you may be as smart as Einstein.
Are there any essays anywhere that go in depth about scenarios where AIs become somewhat recursive/general in that they can write functioning code to solve diverse problems, but the AI reflection problem remains unsolved and thus limits the depth of recursion attainable by the AIs? Let's provisionally call such general but reflection-limited AIs semi-general AIs, or SGAIs. SGAIs might be of roughly smart-animal-level intelligence, e.g. have rudimentary communication/negotiation abilities and some level of ability to formulate narrowish plans of the sort that don't leave them susceptible to Pascalian self-destruction or wireheading or the like.
At first blush, this scenario strikes me as Bad; AIs could take over all computers connected to the internet, totally messing stuff up as their goals/subgoals mutate and adapt to circumvent wireheading selection pressures, without being able to reach general intelligence. AIs might or might not cooperate with humans in such a scenario. I imagine any detailed existing literature on this subject would focus on computer security and intelligent computer "viruses"; does such literature exist, anywhere?
I have various questions about this scenario, including: