GPT is making boundaries around words because that is the pattern it is looking at.
If I feel the bumps in the fabric of my blanket, I will probably think the pattern of bumps at a certain scale is significant, but I won't have magically learned about threads or stitching!
Words are the most obvious pattern in written text. GPT models that pattern, but it does not recognize it as "words". It's just a pattern of tokens.
GPT models every pattern it can find. Most of these patterns are destined to fit the same boundaries as grammar rules: the example text was originally organized with grammar rules!
GPT can even recognize complex patterns like "it" substitution and question-answer dialogues, but it can never categorize them as such. It only knows "what" the pattern is: never "why".
The patterns that people use when writing have symbolic meaning. The subjective importance of each pattern is already known by the person writing.
Those patterns don't go anywhere. GPT's model is bound to find and replicate them.
Here's the problem: some patterns have ambiguous meaning. There is no semantic difference between a truth and a lie. Without interpreting the symbolic meaning and applying logic, there is no way to distinguish between the two: they are the same pattern.
GPT is making boundaries around words because that is the pattern it is looking at.
If I feel the bumps in the fabric of my blanket, I will probably think the pattern of bumps at a certain scale is significant, but I won't have magically learned about threads or stitching!
Words are the most obvious pattern in written text. GPT models that pattern, but it does not recognize it as "words". It's just a pattern of tokens.
GPT models every pattern it can find. Most of these patterns are destined to fit the same boundaries as grammar rules: the example text was originally organized with grammar rules!
GPT can even recognize complex patterns like "it" substitution and question-answer dialogues, but it can never categorize them as such. It only knows "what" the pattern is: never "why".
The patterns that people use when writing have symbolic meaning. The subjective importance of each pattern is already known by the person writing.
Those patterns don't go anywhere. GPT's model is bound to find and replicate them.
Here's the problem: some patterns have ambiguous meaning. There is no semantic difference between a truth and a lie. Without interpreting the symbolic meaning and applying logic, there is no way to distinguish between the two: they are the same pattern.