The fundamental difference lies in how patterns are formed in each case. For LLMs, all they know are the patterns they observe in "words" - that is the only "sense" they possess. But for humans, pattern recognition involves continuously ingesting and identifying patterns across our five primary senses—not just separately, but simultaneously.
For example, when an LLM describes something as "ball-shaped," it cannot feel the shape of a ball because it lacks another sense to associate with the word "ball-shaped." In contrast, humans have the sense of touch, allowing them to associate the word or sound pattern "ball" with the physical sensation of holding a ball.
One of the fundamental mechanisms by which brains operate. The bits we share with every other animal with a brain,
good luck teaching your dog to code.
being great at fetching your newspaper in the morning doesn't mean its going to wake up and write you an accounting software package at the end of the year.
Btw, I'm not saying it's just the number of parameters that matters.
It didn't, it's just very good at copying already existing code and tweeking it a bit.
>Did AI receive mentoring from an experienced senior
It doesnt even comprehend what an experienced senior is, all it cares about is how frequently certain patterns occurred in certain circumstances.
>Did the AI learn through hands-on coding or just by reading Stack Overflow?
it "learnt" by collecting a large database of existing code, most of which is very low quality open source proofs of concept, then spits out the bits that are probably related to a question.