Does is rely on true meanings of words, particularly? Why not on concepts? Individually, “vibrations of air” and “auditory experiences” can be coherent.
If it extrapolates coherently, then it’s a single concept, otherwise it’s a mixture :)
This may actually be doable, even at present level of technology. You gather a huge text corpus, find the contexts where the word “sound” appears, do the clustering using some word co-occurence metric. The result is a list of different meanings of “sound”, and a mapping from each mention to the specific meaning. You can also do this simultaneously for many words together, then it is a global optimization problem.
Of course, AGI would be able to do this at a deeper level than this trivial syntactic one.
Does is rely on true meanings of words, particularly? Why not on concepts? Individually, “vibrations of air” and “auditory experiences” can be coherent.
What’s the general algorithm you can use to determine if something like “sound” is a “word” or a “concept”?
If it extrapolates coherently, then it’s a single concept, otherwise it’s a mixture :)
This may actually be doable, even at present level of technology. You gather a huge text corpus, find the contexts where the word “sound” appears, do the clustering using some word co-occurence metric. The result is a list of different meanings of “sound”, and a mapping from each mention to the specific meaning. You can also do this simultaneously for many words together, then it is a global optimization problem.
Of course, AGI would be able to do this at a deeper level than this trivial syntactic one.