I'm not talking about ChatGPT or anything like that, I'm just taking slight issue with your characterizing of our sources of knowledge. I think there are more sources than you laid out, as I explained.
Randomness is trivially addable. Additionally it's arguably not a source of source knowledge.
Its just a selection parameter. Which sources of knowledge do I use for composition and in what way do I compose it out of available compositions? The randomness parameter can influence these steps.
If you think there are other sources of knowledge, then what are they?
You're still thinking of selecting a random datum from a set of known datums. I'm talking about generating new datums randomly, datums that weren't known beforehand, like random mutations we see in genes.
The only way for randomness to work is to limit the set of available random "datums". This is done by composition pre-existing knowledge.
For example, if I have trillions of atoms randomly composed together with the objective to form a perfect cube, it will take eternity for a valid solution to arise.
If I have pre-existing cubes of atoms already pre-formed into cubic lego bricks and I have these components compose randomly, then it is far more likely that I get a cube.
LLMs, can do this with additional reinforcement training. chatGPT specifically is effective because it has this on top of the original GPT-3 model.
This is essentially random selection of known datums. It happens at the genetic level as well on a higher level.
The generation of raw novel datums in genes, however, is something that cannot happen in human brains. The mechanism for natural selection cannot exist within the brain itself, unless you're calling the trial by error process "natural selection." But again a human doesn't select a completely random strategy to "trial" he will select a strategy out of a known set. This is again, selecting a random datum.
Keep in mind, actual pure randomness generates useless noise 99.99999% of the time.
