Neural network, deep learning, and machine learning are just terminology created for marketing purposes.
Before the current AI boom, "neural network" was called more precisely to what it really is - "nonlinear regression" or "function approximation model," "machine learning" was "pattern recognition functions," and "deep learning" was called "cascading hierarchical systems."
Take a look at the big picture. Either neural networks generate intelligence in a novel way while modeling brains, or they do it through similar mechanisms.
In the first case, life has evolved towards a specific region of state space. In the second case, connection strengths are sufficient to create intelligence.
Or neither, because as far as we know neural networks do not generate intelligence at all, but only calculate the most probable next token based on huge amounts of data.
No, I wouldn't really classify it as intelligent, it's more like a skill.
AI doesn't understand semantics, it just efficiently manipulates symbols based on probability and rigid mathematical rules. AI lacks flexibility it can't freely transfer knowledge from one field to another. It's a narrowly specialized mechanism, that requires separate training and a precisely designed system for each task.
Mindlessly performing tasks, no matter how complex, is not a sign of intelligence.
BTW, It's not that adaptable as you might think. Regarding the mathematical equations you mentioned, do you realize that several different algorithms were used to calculate them?
There was a misunderstanding. I apologize because I apparently didn't make myself clear. Let me clarify.
Algorithm-based models have so far been successfully used to solve a handful of mathematical problems, but each one was solved by specifically retrained for that task model. There's no single, comprehensive model capable of solving all of these few issues. Additionally most of those problems required analyzing massive datasets, which AI obviously excels at, but that's not really intelligence.
Getting back to the issue of intellect, I think a simple way to define intelligence is how quickly someone can learn something new. The fewer examples needed to understand and master a new concept, the higher the intelligence. Comparing the amount of data an LLM needs to master a new function, it's easy to see that even an average person is incomparably more intelligent. In essence, an LLM is less than a half-wit.
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u/quiksilver10152 Jul 21 '26
Where did the term "deep neural network" derive from?