Try counting the number of your red retina cells that are firing while you look at a painting.
Don’t need to be exact as firing is statistical, just give us a good average.
Hard? You can’t count?
Computers count pixels no problem. So weird you can’t.
Dementia? Not an AGI? /h
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This is what is happening.
Here are the “Reasons”.
In your vision system, the raw information from individual retina signals is munged into a different representation before reaching a level where you have flexible processing.
Likewise, in LLMs, letters are munged into tokens before LLMs “see” them.
When they sometimes get that “simple” question right, it’s actually a bit of an amazing feat. Given how they are constructed.
—-
Now try counting R’s as you read at a normal rate, or listen to someone speak.
You can’t do that either, during normal processing.
When we add spelling to LLMs training examples, they will do it easily. Just as you learned to do it, only after special lessons, after you had already learned to listen and speak.
Spelling is its own special practiced skill, in humans and LLMs.
> Try counting the number of your red retina cells that are firing during while you look at a painting.
This analogy makes sense because everybody could count their red retina cells until a couple years ago when the new painting paradigm arose, and also counting red retinal cells is a good analogy for being able to see simple objects that have always been distinguishable.
It is fascinating how tapping the “Do Not Use LLMs For Computation If The Results Need To Be Reliably Better Than A Random Output” sign invites explanations of why that fact is actually Cool and Good
Ask anyone who has not specifically learned to spell, to count R’s while you speak.
You learned to listen and speak words before you could spell. Imagine if nobody had actually shown you written words?
Or they were speaking another dialect but expecting you to count R’s in standard English?
LLMs are not trained on words in the form of letters.
They process and generate the words in the form of tokens. Pre- and post-processing systems converts letters to tokens and the reverse, without their ability to access that processing.
Spelling, for both us and LLMs, requires specific training/lessons.
> It is fascinating how tapping the “Do Not Use LLMs For Computation If The Results Need To Be Reliably Better Than A Random Output” sign invites explanations of why that fact is actually Cool and Good
Also fascinating:
People who hallucinate/confabulate ridiculous straw man rationales for people they disagree with, unaware they are filling in gaps in their knowledge regarding other people’s actual reasoning and the actual subject at hand.
The analogy I use is that illiterate people obviously can't spell, but it doesn't say much about their ability on other tasks. General intelligence doesn't need to be able to spell, since that describes a fair number of actual humans.
(There are tasks that LLMs totally fail on that would be obvious to an illiterate human though)
Don’t need to be exact as firing is statistical, just give us a good average.
Hard? You can’t count?
Computers count pixels no problem. So weird you can’t.
Dementia? Not an AGI? /h
—-
This is what is happening.
Here are the “Reasons”.
In your vision system, the raw information from individual retina signals is munged into a different representation before reaching a level where you have flexible processing.
Likewise, in LLMs, letters are munged into tokens before LLMs “see” them.
When they sometimes get that “simple” question right, it’s actually a bit of an amazing feat. Given how they are constructed.
—-
Now try counting R’s as you read at a normal rate, or listen to someone speak.
You can’t do that either, during normal processing.
When we add spelling to LLMs training examples, they will do it easily. Just as you learned to do it, only after special lessons, after you had already learned to listen and speak.
Spelling is its own special practiced skill, in humans and LLMs.