It seems that you can “convince” LLMs of almost anything if you are insistent enough.
The first is a real LLM program which chooses text to append to a document, a dream-machine with no real convictions beyond continuing the themes of its training data. It lacks convictions, but can be somewhat steered by any words that somehow appear in the dream, with no regard for how the words got there.
The second there's a fictional character within the document that happens to be named after the real-world one. The character displays "convictions" through dialogue and stage-direction that incrementally fit with the story so far. In some cases it can be "convinced" of something when that fits its character, in other cases its characterization changes as the story drifts.
Albeit they'd be much more annoying for humans to use, because feelings.
I believe LLMs would be more useful if they actually had intelligence and principals and beliefs --- more like people.
Unfortunately, they don't.
Any output is the result of statistical processes. And statistical results can be coerced based on input. The output may sound good and proper but there is nothing absolute or guaranteed about the substance of it.
LLMs are basically bullshit artists. They don't hold concrete beliefs or opinions or feelings --- and they don't really "care".
https://www.inf.fu-berlin.de/inst/ag-ki/rojas_home/documents...
"However, we should be careful with the metaphors and paradigms commonly introduced when dealing with the nervous system. It seems to be a constant in the history of science that the brain has always been compared to the most complicated contemporary artifact produced by human industry [297]. In ancient times the brain was compared to a pneumatic machine, in the Renaissance to a clockwork, and at the end of the last century to the telephone network. There are some today who consider computers the paradigm par excellence of a nervous system. It is rather paradoxical that when John von Neumann wrote his classical description of future universal computers, he tried to choose terms that would describe computers in terms of brains, not brains in terms of computers."
But from our limited understanding, it is definitely not strictly digital and statistical in nature.
Nobody knows what the most useful level of approximation is.
The first step to achieving a "useful level of approximation" is to understand what you're attempting to approximate.
We're not there yet. For the most part, we're just flying blind and hoping for a fantastical result.
In other words, this could be a modern case of alchemy --- the desired result may not be achievable with the processes being employed. But we don't even know enough yet to discern if this is the case or not.
That said, I wouldn't be surprised if if the state of the art in AI is to our minds as a hot air balloon is to flying, with FSD and Optimus being the AI equivalent of E.P. Frost's steam powered ornithopters wowing tech demos but not actually solving real problems.
You are calculating the angular distance between signals just like Claude is. It's more of a question of degree than category.
How many of us take a Machiavellian approach to calculate the combined chance of getting caught and the punishment if we are, instead of just going with gut feelings based on our internalised model from a lifetime of experience? Some, but not most of us.
What we get from natural selection is instinct, which I think includes what smiles look like, but that's just a fast way to get feedback.
Assuming this statement is made in good faith and isn't just something tech bros say to troll people, what neuroscience textbooks describe the brain as a "statistical process" that you would recommend.
that's a nice bit of anthropomorphising humans, but it's not how humans work.
Only on HN.
Convince an entity require this entity to have axiological feelings. Then to convince it, you either have to persuade the entity that the demand fits its ethos, or lead it to operate against its own inner values, or to go through a major change of values.