No, if we were we could figure out the genetic code, or how a neural net makes its decisions. But we can't because, among other things, we have a limited working memory of 7-12 objects.
Programmers know how it is to live at the edge of the capacity of the mind to grasp the big picture. We always reinvent the wheel in the quest to make our code more grasp-able and debuggable. Why? Because it's often more complex than can be handled by the brain.
An AGI would not have such limitations. Our limitations emerged as a tradeoff between energy expenditure and ability to solve novel tasks. If we had a larger brain, or more complicated brain, we would require more resources to train. But resources are limited, we need to be smart while being scrappy.
For the record I don't think there is any general intelligence on our planet. A general intelligence would need access to all kinds of possible environments and problems. There is no such thing.
There's also the no free lunch theorem - it might not apply directly here, but it gives us a nice philosophical intuition about why AGI is impossible.
> We have dubbed the associated results NFL theorems because they demonstrate that if an algorithm performs well on a certain class of problems then it necessarily pays for that with degraded performance on the set of all remaining problems. [1]
Another argument relies on the fact that words are imprecise tools in modelling reality. Language is itself a model and as all models, it's good at some tasks and bad at other tasks. There is no perfect language for all tasks. Even if we use language we are not automatically made 'generally intelligent'. We're specialised intelligences.
Programmers know how it is to live at the edge of the capacity of the mind to grasp the big picture. We always reinvent the wheel in the quest to make our code more grasp-able and debuggable. Why? Because it's often more complex than can be handled by the brain.
An AGI would not have such limitations. Our limitations emerged as a tradeoff between energy expenditure and ability to solve novel tasks. If we had a larger brain, or more complicated brain, we would require more resources to train. But resources are limited, we need to be smart while being scrappy.
For the record I don't think there is any general intelligence on our planet. A general intelligence would need access to all kinds of possible environments and problems. There is no such thing.
There's also the no free lunch theorem - it might not apply directly here, but it gives us a nice philosophical intuition about why AGI is impossible.
> We have dubbed the associated results NFL theorems because they demonstrate that if an algorithm performs well on a certain class of problems then it necessarily pays for that with degraded performance on the set of all remaining problems. [1]
[1] https://en.wikipedia.org/wiki/No_free_lunch_theorem
Another argument relies on the fact that words are imprecise tools in modelling reality. Language is itself a model and as all models, it's good at some tasks and bad at other tasks. There is no perfect language for all tasks. Even if we use language we are not automatically made 'generally intelligent'. We're specialised intelligences.