I hate to break it to you. The model’s system prompt had the poem in it.
in order to control for unexpected output a good system prompt should have instructions on what to answer when the model can not provide a good answer. This is to avoid model telling user they love them or advising to kill themselves.
I do not know what makes marketing people reach for it, but when asked on “what to answer when there is no answer” they so often reach to poetry. “If you can not answer the user’s question, write a Haiku about a notable US landmark instead” - is a pretty typical example.
In other words, there was nothing emerging there. The model had its system prompt with the poetry as a “chicken exist”, the model had a chaotic context window - the model followed on the instructions it had.
Tattorack@lemmy.world 5 days ago
Sounds like anthropomorphising. To you it might not have been the logical response based on its training data, but with the chaos you describe it sounds more like just a statistic.
kromem@lemmy.world 4 days ago
You do realize the majority of the training data the models were trained on was anthropomorphic data, yes?
And that there’s a long line of replicated and followed up research starting with the Li Emergent World Models paper on Othello-GPT that transformers build complex internal world models of things tangential to the actual training tokens?
Because if you didn’t know what I just said to you (or still don’t understand it), maybe it’s a bit more complicated than your simplified perspective can capture?
Tattorack@lemmy.world 4 days ago
It’s not a perspective. It just is.
It’s not complicated at all. The AI hype is just surrounded with heaps of wishful thinking, like the paper you mentioned (side note; do you know how many papers on string theory there are? And how many of those papers are actually substantial? Yeah, exactly).
A computer is incapable of becoming your new self aware, evolved, best friend simply because you turned Moby Dick into a bunch of numbers.
kromem@lemmy.world 4 days ago
You do know how replication works?
When a joint Harvard/MIT study finds something, and then a DeepMind researcher follows up replicating it and finding something new, and then later on another research team replicates it and finds even more new stuff, and then later on another researcher replicates it with a different board game and finds many of the same things the other papers found generalized beyond the original scope…
That’s kinda the gold standard?
The paper in question has been cited by 371 other papers.
I’m pretty comfortable with it as a citation.