Fine, you win, I misunderstood.

It’s not a competition, but I genuinely respect you for saying you misunderstood.

Once an LLM is trained, it is static and unchanging until you re-train it with new data and update the model.

Absolutely! I honestly think this is the main thing (or at least one of the main things) that prevent human-level intelligence or even sentience in LLM’s.

Think about how our minds work. From the moment we’re born (really, it’s way before that) our brains are bombarded with input and feedback from every sense. It takes a person many months of that to start recognizing things. That’s also why babies sleep so much, their brains are kinda “training” and growing fast. Organizing all the data into memories.

Side bar: this is actually what dreams are. Dreams are emotions, thoughts, ideas, or whatever concept a neuron or group of neurons are associated with getting triggered. When we dream it’s our brain taking the days inputs and building new connections. The neural connections in our brains are very much like weights and feed-forward process of neural activation is near identical to how artificial neural networks function. They aren’t called “artificial neural networks” for no reason.

Here’s a useful graphic that shows things that make up “intelligence”

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A very basic definition of intelligence is “the ability to solve problems or make decisions”.

I think the term is just often misused in common parlance so often that people start applying in a scientific setting incorrectly. Kinda how people used to call an entire computer the CPU, which like the word intelligence everyone understands what’s being said, but it’s factually wrong.

Same thing today when people say “I bought a new GPU” when they should say “I bought a new video card” as the GPU is just a component.