[tsimionescu]

Well, babies start picking out objects within weeks or months after birth. And many birds and mammals are much faster than that. That's not a huge amount of data to learn something so abstract from scratch, especially given the limited bandwidth of our data acquisition.

Furthermore, for other kinds of human knowledge, the learning process is very rarely based on data. After the acquisition of language, we generally seem to learn much more by analogy and deduction than by purely analyzing data. The difference is evident, since we can often pick up facts with a single datapoint, even in small children in kindergarten.

Also, getting back to your point on how we start AI - if you try to take a neural network and throw 3D sensor data at it, and immediately start using its outputs to modify the environment those sensors are sensing, I suspect you will not get any meaningful amount of learning. You probably need a very complex model and set of initial weights to have any chance of learning something like 3D objects and their basic physics (weight, speed and hwo those affect their predicted position). I would at least bet that you wouldn't get anywhere near, say, kitten accuracy in one month of training.

Related to 3D objects vs 2D, I completely agree.