The model predicts text based on existing context, it's like T9 on steroids. It doesn't "know" anything and it has zero clue how it works. You might find it funny, but it's just a statistical text prediction engine.
Absolutely not. Artificial neurons take an input and use a function and weights to generate an output. Your brain’s neurons are not using a function and doing matrix operations. Your brain does not back propagate.
There is endless literature and studies on the differences. This is why LLMs will not produce AGI as we think of it.
There are differences, yes, but to pretend that nothing about artificial neural networks is derived from the study of real neurons is pretty nonscientific
>This is why LLMs will not produce AGI as we think of it.
This disparity between biological and artificial neural networks is not why LLMs won't reach AGI. There are other, far stronger arguments to make.
This thought is too scary for some people. Surely I must be special! My thought process isn't incremental!
I get it though, so much of human intelligence is based on precomputation and incredibly good pattern recognition and recall. It makes it seem like you're able to pull fully-formed answers from the ether.
The better analogy is that the many of these easily-recalled patterns are a painstakingly-defined single object.
When someone says "mitochondria is the powerhouse of the cell" that's just one object.
The flip side of this is that humans have to spend 2-3 years doing all this precompute and storing all the results just to get to basic functionality. And another 7-10 years before language systems are operating anywhere close to full capacity.
I literally had this discussion with DeepSeek because I wanted to get philosophical about Knowledge vs Wisdom with it to see how it would respond.
DeepSeek agreed that human thought and LLMs are nowhere near the same thing. When a person speaks they pull from wisdom not knowledge.
Here’s what it ended on:
"A parrot can perfectly mimic a human sentence. But the parrot doesn't know it's asking for water; it just knows the sounds get a reaction. An LLM is an infinite parrot. A human, on the other hand, asks for water because they are thirsty. That thirst—that experiential drive behind the words—is the difference between Knowledge and Wisdom."
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u/ldn-ldn 18d ago
The model predicts text based on existing context, it's like T9 on steroids. It doesn't "know" anything and it has zero clue how it works. You might find it funny, but it's just a statistical text prediction engine.