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I think it's a incredibly important question to be able to explain how an AI creating novel work is different then a Human creating novel work. Why does this gr

I think it's a incredibly important question to be able to explain how an AI creating novel work is different then a Human creating novel work. Why does this grind your gears?

sillysaurusx 4y ago
I suspect it's the same reason it grinds my gears that it's called a "learning rate" instead of "step size" in ML. Not only is it less precise term, but it gives the wrong implications. Personally, I'm on the side of releasing training data. Let everybody train on everything. But it's always felt absurd to say that the ML models are "learning" things. But hey, none of us know how learning works anyway, right? So maybe it's not such a big distinction. As you say, none of us can pinpoint why a model isn't learning vs why we are.
- godelski 4y ago
  I think the problem with these words is that the vernacular has different meanings with the common lexicon. But this is quite true for any field. "Field" is even a good example of this as mathematicians use it in a drastically different way than I just used it now. This can make people think they understand technicals more than they do. But if you're making the argument that ML needs to learn more math and needs more rigor, then I'd defend that claim. It is a personal pet peeve of min (fuck man, how often I have to explain to my research group what a covariance matrix is and why it is essential to diffusion is absurd).
  - wnkrshm 4y ago
    A lot of what we see is cargo cult engineering and not fundamental research in ML. Most of it is applied research or engineering - there is a little bit of fundamental research that actually expands our own knowledge about how things work and what their limits are, while applied science keeps marching on (maybe towards funamentally impossible goals).
bonsaibilly 4y ago
To me it seems to imply a stunningly nihilistic point of view vis-a-vis human writing (or art, where it also gets repeated a lot here). It seems almost definitionally obvious that what an LLM does is not the same as what a human does – both on the basis that if all human writing were merely done via blending together other writing we had seen in the past, it would appear to be impossible for us to have developed written communication in the first place, and on the basis that when I write something, I mean something I am then attempting to communicate. An LLM never means to communicate anything, there is no there there; it simply reproduces the most likely tokens in response to a prompt. To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory.
- hprotagonist 4y ago
  see: http://www.jaronlanier.com/zombie.html http://www.jaronlanier.com/zombie.html It’s not said very much, but this style of dehumanization is really corrosive in a way that directly benefits the worst forms of human governments and structures, and this fact goes i think genuinely unrecognized too often in tech-land. if we really are p-zombies, then those people aren’t really suffering, right, so it’s fine …
- oneoff786 4y ago
  > To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory Let’s assume humans are not just evolved pattern machines for a second. A human can still do a completely non profound work of art following a prompt to draw X in the style of Y. And that’s ok. So why can a machine not do the same? Surely not everything a human does is intrinsically profound.
  - bonsaibilly 4y ago
    This is not just moving but fully inverting the goal posts. Nobody at any point was disputing that a machine can’t ape non-profound or rote or meaningless human output. The original discussion was precisely an objection to the attitude underlying "How is *GPT taking in data and producing an output different than a human learning a skill and making prose/code/art?" and the answer is right in your premise - not everything a human does is not profound. A human can intend to mean something with prose or art, even if not all prose or art means something — but any meaning we see in ChatGPT’s output is essentially pareidolia.
kube-system 4y ago
I'm not the parent commenter, but it grinds my gears because the answer is obvious. Humans value human creativity because of emotion, shared experience, and the value we place on each other as humans.
- MacsHeadroom 4y ago
  It's just as obvious to me that humans do not actually care where creative works they appreciate come from. Some of my favorite creative works came from some awful people and others came from algorithms. I don't care. It does not effect the works or the way in which the works effect me.
  - kube-system 4y ago
    Awful people are humans, with human experiences. All algorithms are made by humans and/or process human input. And besides, I never said creativity is a requirement for appreciation. I appreciate things in nature regardless of the fact they weren’t the result of creativity.
  - greysphere 4y ago
    The fashion industry and pretty much the concept and existence of luxury brands are counter to this claim.
AnimalMuppet 4y ago
Because the implied answer is "it isn't different". That grinds our gears (for various values of "our") because 1) it assumes an answer to what is, at best, an open question, and 2) we think it assumes the wrong answer. If asked in good faith (not assuming the answer), I can agree that it's an important question.
- intelVISA 4y ago
  ChatGPT can already replicate the bugs in an average shop, I would say it is becoming post-human if we remove its ability to generate nonsense.
discreteevent 4y ago
> Why does this grind your gears? For the same reason it ground Kurt Cobain's gears. "He knows all our pretty songs, and he likes to sing along. But he don't know what it means" I always thought that was a bit condescending but it applies perfectly to chatgpt.
robotresearcher 4y ago
> I think it's a incredibly important question Why do you think that? If we had an widely accepted answer, how would the world be different?
- rowanG077 4y ago
  Because we most likely could use that information to both gain greater insight into how humans learn and most importantly innovate. And also we can strive to create better AI based on the principles discovered.

I think it's a incredibly important question to be able to explain how an AI creating novel work is different then a Human creating novel work. Why does this grind your gears?

sillysaurusx 4y ago

I suspect it's the same reason it grinds my gears that it's called a "learning rate" instead of "step size" in ML. Not only is it less precise term, but it gives the wrong implications. Personally, I'm on the side of releasing training data. Let everybody train on everything. But it's always felt absurd to say that the ML models are "learning" things. But hey, none of us know how learning works anyway, right? So maybe it's not such a big distinction. As you say, none of us can pinpoint why a model isn't learning vs why we are.

godelski 4y ago
I think the problem with these words is that the vernacular has different meanings with the common lexicon. But this is quite true for any field. "Field" is even a good example of this as mathematicians use it in a drastically different way than I just used it now. This can make people think they understand technicals more than they do. But if you're making the argument that ML needs to learn more math and needs more rigor, then I'd defend that claim. It is a personal pet peeve of min (fuck man, how often I have to explain to my research group what a covariance matrix is and why it is essential to diffusion is absurd).
- wnkrshm 4y ago
  A lot of what we see is cargo cult engineering and not fundamental research in ML. Most of it is applied research or engineering - there is a little bit of fundamental research that actually expands our own knowledge about how things work and what their limits are, while applied science keeps marching on (maybe towards funamentally impossible goals).

bonsaibilly 4y ago

To me it seems to imply a stunningly nihilistic point of view vis-a-vis human writing (or art, where it also gets repeated a lot here). It seems almost definitionally obvious that what an LLM does is not the same as what a human does – both on the basis that if all human writing were merely done via blending together other writing we had seen in the past, it would appear to be impossible for us to have developed written communication in the first place, and on the basis that when I write something, I mean something I am then attempting to communicate. An LLM never means to communicate anything, there is no there there; it simply reproduces the most likely tokens in response to a prompt. To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory.

hprotagonist 4y ago
see: http://www.jaronlanier.com/zombie.html http://www.jaronlanier.com/zombie.html It’s not said very much, but this style of dehumanization is really corrosive in a way that directly benefits the worst forms of human governments and structures, and this fact goes i think genuinely unrecognized too often in tech-land. if we really are p-zombies, then those people aren’t really suffering, right, so it’s fine …
oneoff786 4y ago
> To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory Let’s assume humans are not just evolved pattern machines for a second. A human can still do a completely non profound work of art following a prompt to draw X in the style of Y. And that’s ok. So why can a machine not do the same? Surely not everything a human does is intrinsically profound.
- bonsaibilly 4y ago
  This is not just moving but fully inverting the goal posts. Nobody at any point was disputing that a machine can’t ape non-profound or rote or meaningless human output. The original discussion was precisely an objection to the attitude underlying "How is *GPT taking in data and producing an output different than a human learning a skill and making prose/code/art?" and the answer is right in your premise - not everything a human does is not profound. A human can intend to mean something with prose or art, even if not all prose or art means something — but any meaning we see in ChatGPT’s output is essentially pareidolia.

kube-system 4y ago

I'm not the parent commenter, but it grinds my gears because the answer is obvious. Humans value human creativity because of emotion, shared experience, and the value we place on each other as humans.

MacsHeadroom 4y ago
It's just as obvious to me that humans do not actually care where creative works they appreciate come from. Some of my favorite creative works came from some awful people and others came from algorithms. I don't care. It does not effect the works or the way in which the works effect me.
- kube-system 4y ago
  Awful people are humans, with human experiences. All algorithms are made by humans and/or process human input. And besides, I never said creativity is a requirement for appreciation. I appreciate things in nature regardless of the fact they weren’t the result of creativity.
- greysphere 4y ago
  The fashion industry and pretty much the concept and existence of luxury brands are counter to this claim.

AnimalMuppet 4y ago

Because the implied answer is "it isn't different". That grinds our gears (for various values of "our") because 1) it assumes an answer to what is, at best, an open question, and 2) we think it assumes the wrong answer. If asked in good faith (not assuming the answer), I can agree that it's an important question.

intelVISA 4y ago
ChatGPT can already replicate the bugs in an average shop, I would say it is becoming post-human if we remove its ability to generate nonsense.

discreteevent 4y ago

> Why does this grind your gears? For the same reason it ground Kurt Cobain's gears. "He knows all our pretty songs, and he likes to sing along. But he don't know what it means" I always thought that was a bit condescending but it applies perfectly to chatgpt.

robotresearcher 4y ago

> I think it's a incredibly important question Why do you think that? If we had an widely accepted answer, how would the world be different?

rowanG077 4y ago
Because we most likely could use that information to both gain greater insight into how humans learn and most importantly innovate. And also we can strive to create better AI based on the principles discovered.