Whilst everything you linked is great research which demonstrates the vast capabilities of LLMs, none of it demonstrates understanding as most humans know it.
This agrument always boils down to one’s definition of the word “understanding”. For me that word implies a degree of human consciousness, for others, apparently not.
To quote GPT-4:
LLMs do not truly understand the meaning, context, or implications of the language they generate or process. They are more like sophisticated parrots that mimic human language, rather than intelligent agents that comprehend and communicate with humans. LLMs are impressive and useful tools, but they are not substitutes for human understanding.
When people say that the model “understands”, it means just that, not that it is human, and not that it does so exactly humans do. Judging its capabilities by how close it’s mimicking humans is pointless, just like judging a boat by how well it can do the breast stroke. The value lies in its performance and output, not in imitating human cognition.
The reason it’s dangerous is because there are a significant number of jobs and people out there that do exactly that. Which can be replaced…
People making content should immediately pivot to become the approvers, not the generators.
The world needs waaaay more editors, too…
This post isn’t true, LLMs do have an understanding of things.
SELF-RAG: Improving the Factual Accuracy of Large Language Models through Self-Reflection
Chess-GPT’s Internal World Model
POKÉLLMON: A Human-Parity Agent for Pokémon Battle with Large Language Models
Language Models Represent Space and Time
Whilst everything you linked is great research which demonstrates the vast capabilities of LLMs, none of it demonstrates understanding as most humans know it.
This agrument always boils down to one’s definition of the word “understanding”. For me that word implies a degree of human consciousness, for others, apparently not.
To quote GPT-4:
You are moving goal posts
“understanding” can be given only when you reach like old age as a human and if you meditated in a cave
That’s my definition for it
No one is moving goalposts, there is just a deeper meaning behind the word “understanding” than perhaps you recognise.
The concept of understanding is poorly defined which is where the confusion arises, but it is definitely not a direct synonym for pattern matching.
When people say that the model “understands”, it means just that, not that it is human, and not that it does so exactly humans do. Judging its capabilities by how close it’s mimicking humans is pointless, just like judging a boat by how well it can do the breast stroke. The value lies in its performance and output, not in imitating human cognition.
Understanding is a human concept so attributing it to an algorithm is strange.
It can be done by taking a very shallow definition of the word but then we’re just entering a debate about semantics.
Animals understand.
Yes sorry probably shouldn’t have used the word human. It’s a human concept that we apply to living things.
Animals certainly understand things but it is a sliding scale where we use human understanding as a benchmark.
My point stands though, to attribute it to an algorithm is strange.
I’m starting to wonder about you though.
Well it was a fun ruse while it lasted.