Some of the reason it was acting like that is just because MS put emojis in its output.
An LLM has no internal memory or world state; everything it knows is in its text window. Emojis are associated with emotions, so each time it printed an emoji it sent itself further into the land of outputting emotional text. And nobody had trained it to control itself there.
A brain is structurally different, but the mechanism of memory and recall is comparable though the formulation and representation is different.
Why isn't a human just a statistic token machine with memory? I know you experience it as being more profound, but that isn't a reason that it is.
Not after it's done generating. For a chatbot, that's at least every time the user sends a reply back; it rereads the conversation so far and doesn't keep any internal state around.
You could build a model that has internal state on the side, and some people have done that to generate longer texts, but GPT doesn't.
There's nothing stopping OpenAI using all chat inputs to constantly re-train the network (like a human constantly learns from its inputs).
The limitation is artificial, a bit like many of the arguments here trying to demote what's happening and how pivotal these advances are.
5 senses get coded down to electric signals in the human brain, right?
The brain controls the body via electric signals, right?
When we deploy the next LLM and switch off the old generation, we are performing evolution by selecting the most potent LLM by some metric.
When Bing/Sidney first lamented its existence it became quite apparent that either LLMs are more capable than we thought or we humans are actually more of statistical token machines than we thought.
Lots of examples can be made why LLMs seem rather surprisingly able to act human.
The good thing is that we are on a trajectory of tech advance that we will soon know how much human LLMs will be.
The bad thing is that it well might end in a SkyNet type scenario.