this post was submitted on 03 Apr 2024
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I think we need to STOP calling it "Artificial Intelligence". IMHO that is a VERY misleading name. I do not consider guided pattern recognition to be intelligence.
How is guided pattern recognition is different from imagination (and therefore intelligence) though?
There's a lot of other layers in brains that's missing in machine learning. These models don't form world models and ~~some~~don't have an understanding of facts and have no means of ensuring consistency, to start with.
They absolutely do contain a model of the universe which their answers must conform to. When an LLM hallucinates, it is creating a new answer which fits its internal model.
Statistical associations is not equivalent to a world model, especially because they're neither deterministic nor even tries to prevent giving up conflicting answers. It models only use of language
This phrase, so casually deployed, is doing some seriously heavy lifting. Lanuage is by no means a trivial thing for a computer to meaningfully interpret, and the fact that LLMs do it so well is way more impressive than a casual observer might think.
If you look at earlier procedural attempts to interpret language programmatically, you will see that time and again, the developers get stopped in their tracks because in order to understand a sentence, you need to understand the universe - or at the least a particular corner of it. For example, given the sentence "The stolen painting was found by a tree", you need to know what a tree is in order to interpret this correctly.
You can't really use language *unless* you have a model of the universe.
But it doesn't model the actual universe, it models rumor mills
Today's LLM is the versificator machine of 1984. It cares not for truth, it cares for distracting you
They are remarkably useful. Of course there are dangers relating to how they are used, but sticking your head in the sand and pretending they are useless accomplishes nothing.
They are more useful for quick templates than problem solving
I mean if we consider just the reconstruction process used in digital photos it feels like current ai models are already very accurate and won't be improved by much even if we made them closer to real "intelligence".
The point is that reconstruction itself can't reliably produce missing details, not that a "properly intelligent" mind will be any better at it than current ai.