You also decided that a response was needed and had planned an argument of sorts.
You decide which comments to do this for as well.
How does GPT decide such things?
You decide which comments to do this for as well.
How does GPT decide such things?
Sure, LLMs are not inherently goal-oriented. But that doesn't mean they fundamentally cannot exhibit goal-oriented behavior if either prompted or trained to do so. And if we remove the "one-off" restriction and allow the retention of some sort of an efficiently encoded state between invocations, who knows what might happen?
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EDIT: Tried this with ChatGPT (GPT-4) and a subset of this thread, and the results are pretty good, even though the tree structure was lost in translation (simple copypaste). Certainly its thoughts of the differences and similarities between token-prediction and reasoning are more informed than those of many human commenters. It's also able to seamlessly include references to other comments, for instance (it deduced that "dougwmne" was the nickname of the comment author by itself):
> Additionally, it's worth noting that GPT-4's ability to interact with novel systems, as mentioned by dougmwne, might indicate some form of generalization and adaptation capabilities. Although it may not possess the same kind of reasoning as humans, it demonstrates an ability to understand and apply new information in a useful manner. This could be considered a form of reasoning, albeit a different and less sophisticated one than humans possess.
My prompt was:
> Here is an excerpt from a Hacker News discussion about GPT-4 and whether it can do reasoning. Write a comment that contributes to the discussion, either by bringing up a new idea or deduction, or by replying to another comment and arguing for or against it. You can quote another comment by prefixing it with ">".
followed by the copy-pasted subthread.
GPT has no "reason" behind its words. Its actions are not tied to the general betterment of humankind. When we all sit here with our coffees and donuts (and farting) we're generally trying to push others to see our worldview so that maybe, just maybe, the world can change a little bit.
If we eventually have a way to tie an AI to all these moods (hunger, pain, tiredness) and all the other things of the human experience, it would ground the thoughts and text it generates at some point such that it would want to DO things it wasn't doing before. It also can't right now anyway, unless we give it that ability (ReAct pattern could).
We can, of course, simulate all these human experiences, with "best practices" but then the reason won't be really tied to human reasoning. It will be just more text autocomplete with additional instructions.
All of them? If not, how to determine which ones?
There is a difference here between you and the machine
Looking at the LLM algorithms, they do appear to be next token predictors. Why do you ascribe something more to them when the algorithm is known?
Given we know that causal patterns are in the training data, and that LLMs are capable of embedding algebra, it is understandable that they appear to "reason", while we as humans can also describe the algorithm and mechanics actually at work here.
How does it determine how to respond to any prompt? Exactly. It might reasonably predict responses to those comments that, according to its black box, are somehow most likely to receive a reply. Different GPT instances prompted or trained to have different personalities would choose differently based on their priors and biases.
I'm pretty sure the vast majority of human beings are able to reason without really having the slightest idea as to how exactly they do it. Educated humans can use language to talk about reasoning in terms of logic, and even make logic engines out of doped silicon and whatnot, but as of now, none of us has any idea of how reasoning is implemented in the mass of fat and protein that's inside our heads.
Yet another case, many times we will respond (or not) to a questions with another question, to elicit deeper considerations. In my experience, GPTs will answer any question without thought, pun intended :]
The original question was, given that there were X comments which could be replied to on this page, how and why did the poster decide to respond to the one to which they responded, rather than either "all" (like ChatGPT would) or "none?"
If you mean feeding it the messages one at a time, then, sure, it will respond to each of them because that's what its default "goal function" is. (I assume that we're talking about a single "conversation" here so the context is retained – feeding it each comment out-of-context would be very unfair.)
If you prompt it to only reply to messages it considers "interesting" in some way, and return "I'll skip this" for the others, it would certainly do that.
Yes, GPT is code that only runs when you, erm… run it. It’s not an autonomous being that’s cut loose on the internet and given free reign to use as much compute resources as it wants, a la skynet, replying to random forum posts. But nobody’s really saying that it is, so it seems a strange argument to say “it’s just a next token predictor”, if by that you really mean “it only runs when you give it a prompt.”
The modality of GPT is that it responds to prompts, but the interesting question is “are the responses given a sign of intelligence?”. Saying “no, it’s just a next token predictor” is IMO a sign of a motte-and-bailey fallacy. Your motte is that it only works in response to prompts (trivially true and uninteresting), and your bailey is that it has no intelligence (very debatable and IMO false.)