I get what you mean, but I believe it's more productive not lumping a neural network (inference model), with much of the "logic" coming from automated/self-training, into being "just a computer program". There's historical context & understanding of a "program" where a human actually designs & knows what IF-THEN-ELSE type of logic is executed... understanding it will do what it is 'programmed' to do. NN inference is modeled after (& named after) the human brain (weighted neurons) and there is both a lack of understanding all (most!) of the logic ('program') that is executing under-the-hood, as they say.
Note: I'm not at all saying that GPT 3.5/4 are sentient, but rather that it's missing a lot of the nuance, as well as complexity, of LLMs by referring to them as simply being "just a computer program".
I get what you mean, but I believe it's more productive not lumping a neural network (inference model), with much of the "logic" coming from automated/self-training, into being "just a computer program". There's historical context & understanding of a "program" where a human actually designs & knows what IF-THEN-ELSE type of logic is executed... understanding it will do what it is 'programmed' to do. NN inference is modeled after (& named after) the human brain (weighted neurons) and there is both a lack of understanding all (most!) of the logic ('program') that is executing under-the-hood, as they say.
Note: I'm not at all saying that GPT 3.5/4 are sentient, but rather that it's missing a lot of the nuance, as well as complexity, of LLMs by referring to them as simply being "just a computer program".