[opium_tea]

I'm of the impression that concepts only have fundamental meaning to us because we can relate them to sensory input. For example, initially a child is taught what a boat is by seeing pictures, it eventually learns that boats, cars and bicycles share common characteristics and can be grouped together as vehicles. These common characteristics are all understood and identified by seeing, hearing, touching or smelling.

It would be impossible completely describe a concept such as "horse" to a person with no knowledge of animal physiology, without recourse to pointing at a a horse or impersonating a horse noise. Resorting to analogies with other concepts - "a horse is like a cow" - doesn't work because the person has no knowledge of the other concepts. This person could be a young child or an untrained computer, and they can be taught fundamental meanings of concepts by feeding them information in the form of sights, sounds, smells etc.

I haven't thought about this very deeply but these are the thoughts that always come into my mind when this topic comes up. Concepts have no meaning without relating them to sensory input. Humans learn by connecting the two. Why can the same not be applied to computers?

[Houshalter]

There is no question that additional data would be potentially useful to an AI. But it's a common fallacy that it's the only way to get "meaning". Data from a digital camera isn't fundamentally different than data from text. The only benefit is that visual data is far less compressed, more redundant. It's easier to find patterns in it. Natural language is a highly compressed description of things in the real world.

That said, it doesn't at all mean you can't learn anything meaningful from it. For example, you build a machine learning system to predict the missing words in a sentence. "A horse is similar to other farm animals like ____." Machines are getting better at this kind of thing, though still far from human level. Google's word2vec for example can take a word like "horse" and list the words that it is most similar to. You can subtract the representation for "man" from "king", add "woman" and it outputs "queen".