Sorry you’re getting downvoted, you’re correct. It’s not implausible to assume that generative AI systems may have some kind of umwelt, but it is highly implausible to expect that it would be anything resembling that of a human (or animal). I think people are getting hung up on it because they’re assuming a lack of understanding language implies a lack of any concious experience. Humans do lots of things without understanding how they might be understood by others.
To be clear, I don’t think these systems have experience, but it’s impossible to rule out until an actual robust theory of mind comes around.
Unless you want to call your predictive text on your keyboard a mind you really can’t call an LLM a mind. It is nothing more than a linear progression from that. Mathematically proven to not show any form of emergent behavior.
No such thing has been “mathematically proven.” The emergent behavior of ML models is their notable characteristic. The whole point is that their ability to do anything is emergent behavior.
I do not think that it is “linear” progression. ANN by definition is nonlinear. Neither I think anything is “mathematically proven”. If I am wrong, please provide a link.
Thank you. This paper though does not state that there are no emergent abilities. It only states that one can introduce a metric with respect to which the emergent ability behaves smoothly and not threshold-like. While interesting, it only suggests that things like intelligence are smooth functions, but so what? Some other metrics show exponential or threshold dependence and whether the metric is right depends only how one will use it. And there is no law that emerging properties have to be threshold like. Quite the opposite - nearly all examples in physics that I know, the emergence appears gradually.
Emergence is the whole being greater than the sum of its parts. That’s the original meaning of emergent properties, which is laid out in the first paragraph of the article. It’s the scholarly usage as well, and what the claims of observed emergence are using as the base of their claim.
The article very explicitly demonstrated that only about 10% of any of the measures for LLMs displayed any emergence and that illusory emergence was the result of overly rigid metrics. Swapping to edit distance as an approximately close metric causes the sharp spikes to disappear for obvious reasons: no longer having a sharp yes/no allows for linear progression to reappear. It was always there, merely masked by flawed statistics.
While it is not alive, whether it is a mind is not a clear cut. It can be called kind of a mind, a mind different of that of human.
What can’t be a kind of mind to you?
Sorry you’re getting downvoted, you’re correct. It’s not implausible to assume that generative AI systems may have some kind of umwelt, but it is highly implausible to expect that it would be anything resembling that of a human (or animal). I think people are getting hung up on it because they’re assuming a lack of understanding language implies a lack of any concious experience. Humans do lots of things without understanding how they might be understood by others.
To be clear, I don’t think these systems have experience, but it’s impossible to rule out until an actual robust theory of mind comes around.
Unless you want to call your predictive text on your keyboard a mind you really can’t call an LLM a mind. It is nothing more than a linear progression from that. Mathematically proven to not show any form of emergent behavior.
No such thing has been “mathematically proven.” The emergent behavior of ML models is their notable characteristic. The whole point is that their ability to do anything is emergent behavior.
Here’s a white paper explicitly proving:
https://arxiv.org/abs/2304.15004
The field changes fast, I understand it is hard to keep up
Sure, if you define “emergent abilities” just so. It’s obvious from context that this is not what I described.
Their paper uses industry standard definitions
Their paper uses terminology that makes sense in context. It’s not a definition of “emergent behavior.”
I do not think that it is “linear” progression. ANN by definition is nonlinear. Neither I think anything is “mathematically proven”. If I am wrong, please provide a link.
Sure thing: here’s a white paper explicitly proving:
https://arxiv.org/abs/2304.15004
Thank you. This paper though does not state that there are no emergent abilities. It only states that one can introduce a metric with respect to which the emergent ability behaves smoothly and not threshold-like. While interesting, it only suggests that things like intelligence are smooth functions, but so what? Some other metrics show exponential or threshold dependence and whether the metric is right depends only how one will use it. And there is no law that emerging properties have to be threshold like. Quite the opposite - nearly all examples in physics that I know, the emergence appears gradually.
It is obvious that you do not know what either “mathematical proof” or “emergence” mean. Unfortunately, you are misrepresenting the facts.
I don’t mean to criticize your religious (or philosophical) convictions. There is a reason people mostly try to keep faith and science separate.
Here’s a white paper explicitly proving:
No emergent properties (illusory due to bad measures)
Predictable linear progress with model size
https://arxiv.org/abs/2304.15004
The field changes fast, I understand it is hard to keep up
As I said, you do not understand what these 2 terms mean. As such, you are incapable of understanding that paper.
Perhaps your native language is Italian, so here are links to the .it Wikipedia.
https://it.wikipedia.org/wiki/Comportamento_emergente
https://it.wikipedia.org/wiki/Dimostrazione_matematica
Emergence is the whole being greater than the sum of its parts. That’s the original meaning of emergent properties, which is laid out in the first paragraph of the article. It’s the scholarly usage as well, and what the claims of observed emergence are using as the base of their claim.
The article very explicitly demonstrated that only about 10% of any of the measures for LLMs displayed any emergence and that illusory emergence was the result of overly rigid metrics. Swapping to edit distance as an approximately close metric causes the sharp spikes to disappear for obvious reasons: no longer having a sharp yes/no allows for linear progression to reappear. It was always there, merely masked by flawed statistics.
If you can’t be bothered to read here’s a very easy to understand video by one of the authors: https://www.youtube.com/watch?v=ypKwNrmuuPM
Good. Now do you understand how you have misrepresented the paper?