Almost a good take. Except that AI doesn't exist on this planet, and you're likely talking about LLMs.
this post was submitted on 20 Apr 2024
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This is such a half brained response. Yes "actual" AI in the form of simulated neurons is pretty far off, but it's fairly obvious when people say they AI they mean LLMs and other advanced forms of computing. There's other forms of AI besides LLMs anyways, like image analyzers
The only thing half-brained is the morons who advertise any contemporary software as "AI". The "other forms" you mention are machine learning systems.
AI contains the word "intelligence", which implies understanding. A bunch of electrons manipulating a bazillion switches following some trial-and-error set of rules until the desired output is found is NOT that. That you would think the term AI is even remotely applicable to any of those examples shows how bad the brain rot is that is caused by the overabundant misuse of the term.
What do you call the human brain then, if not billions of “switches” as you call them that translate inputs (senses) into an output (intelligence/consciousness/efferent neural actions)?
It’s the result of billions of years of evolutionary trial and error to create a working structure of what we would call a neural net, which is trained on data (sensory experience) as the human matures.
Even early nervous systems were basic classification systems. Food, not food. Predator, not predator. The inputs were basic olfactory sense (or a more primitive chemosense probably) and outputs were basic motor functions (turn towards or away from signal).
The complexity of these organic neural networks (nervous systems) increased over time and we eventually got what we have today: human intelligence. Although there are arguably different types of intelligence, as it evolved among many different phylogenetic lines. Dolphins, elephants, dogs, and octopuses have all been demonstrated to have some form of intelligence. But given the information in the previous paragraph, one can say that they are all just more and more advanced pattern recognition systems, trained by natural selection.
The question is: where do you draw the line? If an organism with a photosensitive patch of cells on top of its head darts in a random direction when it detects sudden darkness (perhaps indicating a predator flying/swimming overhead, though not necessarily with 100% certainty), would you call that intelligence? What about a rabbit, who is instinctively programmed by natural selection to run when something near it moves? What about when it differentiates between something smaller or bigger than itself?
What about you? How will you react when you see a bear in front of you? Or when you’re in your house alone and you hear something that you shouldn’t? Will your evolutionary pattern recognition activate only then and put you in fight-or-flight? Or is everything you think and do a form of pattern recognition, a bunch of electrons manipulating a hundred billion switches to convert some input into a favorable output for you, the organism? Are you intelligent? Or just the product of a 4-billion year old organic learning system?
Modern LLMs are somewhere in between those primitive classification systems and the intelligence of humans today. They can perform word associations in a semantic higher dimensional space, encoding individual words as vectors and enabling the model to attribute a sort of meaning between two words. Comparing the encoding vectors in different ways gets you another word vector, yielding what could be called an association, or a scalar (like Euclidean or angular distance) which might encode closeness in meaning.
Now if intelligence requires understanding as you say, what degree of understanding of its environment (ecosystem for organisms, text for LLM. Different types of intelligence, paragraph 4) does an entity need for you to designate it as intelligent? What associations need it make? Categorizations of danger, not danger and food, not food? What is the difference between that and the Pavlovian responses of a dog? And what makes humans different, aside from a more complex neural structure that allows us to integrate orders of magnitude more information more efficiently?
Where do you draw the line?