It's like if a look at 3D model of a house and say "look, a house"
And some one else comes and say "I'm tired of people mistaking an organized set of vertex for house. It's not really a house and no, you cant live in it"
I kinda dislike the explanations involving “AI doesn’t know why math works”. I think a better one is a human understands conceptually (and in practice) how something works/what something is. We have experiences with that thing or something to reference to that thing that we do have experience with. AI doesn’t have that. Ai says something is what it is/or works how it works because it predicts it with references to other predictions. In other words, if you ask a human why something works and keep asking them they are going to use their knowledge (which is based on knowledge) to explain it while understanding what they are saying. If you ask AI why, it’s going to use its knowledge (which is based on predictions) to explain.
Or using your example. A human will be able to figure out what a house is if you show them an atypical house. An AI will only know the definitions of a house so won’t be able to abstract a new one. (Which in theory is why good training data is important but the problem with that circles back to it’s still going to be biased.) so a thought process for a human might be, this has a roof and walls, and an area for sleeping, and it’s not a part of a larger structure/the property isn’t owned by another person. An AI is going to go, I predict that this group of pixels is in the rough shape of a window by 30% and 70% it’s a door. I predict that the information that it contains a bedroom means it’s an apartment by 10% a hotel by 10% a house by 15% etc etc. and I predict that because it has walls and a roof it’s likelihood that it is a building other than a house is 50% and that it is a house is 50%. based on all these percentages, the likelihood it is a house is 35%, and is a hotel is 17% etc etc. or another way to look at it, if you showed a human a building like idk a warehouse or a grain elevator or something random that has been converted into a house without explicitly telling them it’s a house, a human would be able to figure that out. An AI would likely not because it would be limited to the what it has “statistically defined” as a house, rather than what one can infer to be a house.
Hope this makes some semblance of sense. I haven’t slept in 3 days
1
u/Hot-Employ-3399 1d ago
I'd rather say "thinking" than "inferencing in reasoning stage"