Your son and daughter will continue to learn new things as they grow up, a LLM cannot learn new things on its own. Sure, they can repeat things back to you that are within the context window (and even then, a context window isn’t really inherent to a LLM - its just a window of prior information being fed back to them with each request/response, or “turn” as I believe is the term) and what is in the context window can even influence their responses. But in order for a LLM to “learn” something, it needs to be retrained with that information included in the dataset.
Whereas if your kids were to say, touch a sharp object that caused them even slight discomfort, they would eventually learn to stop doing that because they’ll know what the outcome is after repetition. You could argue that this looks similar to the training process of a LLM, but the difference is that a LLM cannot do this on its own (and I would not consider wiring up a LLM via an MCP to a script that can trigger a re-train + reload to be it doing it on its own volition). At least, not in our current day. If anything, I think this is more of a “smoking gun” than the argument of “LLMs are just guessing the next best letter/word in a given sequence”.
Don’t get me wrong, I’m not someone who completely hates LLMs / “modern day AI” (though I do hate a lot of the ways it is used, and agree with a lot of the moral problems behind it), I find the tech to be intriguing but it’s a (“very fancy”) simulation. It is designed to imitate sentience and other human-like behavior. That, along with human nature’s tendency to anthropomorphize things around us (which is really the biggest part of this IMO), is why it tends to be very convincing at times.
That is my take on it, at least. I’m not a psychologist/psychiatrist or philosopher.
Your son and daughter will continue to learn new things as they grow up, a LLM cannot learn new things on its own. Sure, they can repeat things back to you that are within the context window (and even then, a context window isn’t really inherent to a LLM - its just a window of prior information being fed back to them with each request/response, or “turn” as I believe is the term) and what is in the context window can even influence their responses. But in order for a LLM to “learn” something, it needs to be retrained with that information included in the dataset.
Whereas if your kids were to say, touch a sharp object that caused them even slight discomfort, they would eventually learn to stop doing that because they’ll know what the outcome is after repetition. You could argue that this looks similar to the training process of a LLM, but the difference is that a LLM cannot do this on its own (and I would not consider wiring up a LLM via an MCP to a script that can trigger a re-train + reload to be it doing it on its own volition). At least, not in our current day. If anything, I think this is more of a “smoking gun” than the argument of “LLMs are just guessing the next best letter/word in a given sequence”.
Don’t get me wrong, I’m not someone who completely hates LLMs / “modern day AI” (though I do hate a lot of the ways it is used, and agree with a lot of the moral problems behind it), I find the tech to be intriguing but it’s a (“very fancy”) simulation. It is designed to imitate sentience and other human-like behavior. That, along with human nature’s tendency to anthropomorphize things around us (which is really the biggest part of this IMO), is why it tends to be very convincing at times.
That is my take on it, at least. I’m not a psychologist/psychiatrist or philosopher.