The problem with natural language processing is that we are trying to learn it
(read: construct models of it) from utterances, things that are being said or
transcribed. And that is a big, huge problem because there is a lot more to
language than utterances. Hell, there is a lot more to language than language
itself.
There are things you cannot put into words, and yet you think them. There are
things that you can't put into words and yet you can make people around you
understand them. There are things you understand without even knowing you
understand them. But even before we go there- there are so many things that
people can make utterances about that are not possible to collect into example
sets and train models on.
How do you collect examples of whatever it is that makes people lie on the
beach to get a sun tan? How do you collect examples of imagination, dreams,
abstract thinking, all those things that your brain does that may be a
side-effect of self-aware intelligence or the whole point of self-aware
intelligence in the first place?
How do you collect a data set that's as big as the whole world you've
experienced in your however many years of life? And even if you could, what
machine has the processing power to train on that stuff, again and again,
until it gets it right?
Machine learning meaning is hopeless, folks. Fuggeddabout it. There's not
enough data in the whole world, there's no machine big enough to process it if
it existed. We 'll make some advances in text processing, sure, we'll automate
some useful stuff like translation (for languages close to each other) and
captioning (for photographs) and then we'll stall until the next big thing
comes about in a few generations from now.
That's what the current state of the art suggests.
I am a very bad example though, for one because English is just my second language. Sure there is thinking before words are learned. Language is a complicated problem to talk about, just like self awareness. Consciousness is a very nebulous term to me. Still, you'd have to prove that language is theoretically unfit. Any such logic might be incomplete if you suppose you cannot put it into words. A complete first order logic is expressible however, following Goedels completeness theorem.
There are things you cannot put into words, and yet you think them. There are things that you can't put into words and yet you can make people around you understand them. There are things you understand without even knowing you understand them. But even before we go there- there are so many things that people can make utterances about that are not possible to collect into example sets and train models on.
How do you collect examples of whatever it is that makes people lie on the beach to get a sun tan? How do you collect examples of imagination, dreams, abstract thinking, all those things that your brain does that may be a side-effect of self-aware intelligence or the whole point of self-aware intelligence in the first place?
How do you collect a data set that's as big as the whole world you've experienced in your however many years of life? And even if you could, what machine has the processing power to train on that stuff, again and again, until it gets it right?
Machine learning meaning is hopeless, folks. Fuggeddabout it. There's not enough data in the whole world, there's no machine big enough to process it if it existed. We 'll make some advances in text processing, sure, we'll automate some useful stuff like translation (for languages close to each other) and captioning (for photographs) and then we'll stall until the next big thing comes about in a few generations from now.
That's what the current state of the art suggests.