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>“but GPT-3 isn’t actually intelligent!”. Everyone knows. Not sure that's true, or at least people vastly underestimate just how surface level these models are

>“but GPT-3 isn’t actually intelligent!”. Everyone knows. Not sure that's true, or at least people vastly underestimate just how surface level these models are. You left the most egregious example from the article out. "“A robin is a ____” it correctly answers “bird”. Unfortunately, if you insert the word not (“A robin is not a ___”) you get exactly the same thing. As AI ethics expert Timnit Gebru and her collaborators put it, these systems are “stochastic parrots” that do a decent job of mimicry but utterly lack the depth of understanding that general artificial intelligence will require." If openAI would state on its about page "we build APIs that do stochastic inferences on text and build editor tools" then I don't think anyone would argue anything. But if you withhold your models for 'safety reasons' to huge press fanfare and act like the singularity is around next year every time you make a bigger model it becomes a little ridiculous. People like Judea Pearl asking what the theoretical answer to the fundamental limitations of these data driven approaches is if you're starting a gigantic foundation is valid.

schleck8 5y ago
> As AI ethics expert Timnit Gebru and her collaborators put it, these systems are “stochastic parrots” that do a decent job of mimicry but utterly lack the depth of understanding that general artificial intelligence will require gpt 3 is the first publicly available iteration of large scale text transformers and it's decent for that. it doesn't have to be perfect
- tikhonj 5y ago
  It doesn't have to be perfect, sure, but it would have to be a lot better to be "a new foundation for AI"—exactly what the article (and presumably this discussion) is about.
- wongarsu 5y ago
  Surely you meant GPT2? We can argue about the definition of "large scale", but calling GPT3 "publicly available" is a stretch at best.
sooheon 5y ago
Humans are just "better" stochastic parrots.
- colordrops 5y ago
  Can a parrot have an complex and abstract goal and figure out the many steps to get to that goal?
  - mellavora 5y ago
    Real parrots (and many other birds), yes. Stochastic parrots, perhaps not.
  - sgt101 5y ago
    as the other commenter said - yes. But the thing is I think it's unlikely that the parrot associates language with the problem solving. Parrots with language capabilities and parrots without language don't seem to have different problem solving capabilities - parrots don't have a spoken/written culture. Humans that are prevented from getting a spoken culture (by isolation) exhibit much reduced problem solving - because the humans with a spoken culture have lots of tips from other humans.
- marricks 5y ago
  In all these cases if you asked a human for their initial gut response I imagine they’d make the same type of mistakes as GPT3, the difference is if you have someone a minute to think about it and review they wouldn’t.
  - CRConrad 5y ago
    "Should I kill myself?" "I think you should." Some sadists may of course have that "gut response" because they're sadists, but which human would respond that way by mistake?!?
- flunhat 5y ago
  An oft-repeated claim in these debates, usually presented without evidence. But it's not self-evident to me.
Iv 5y ago
GPT-3 is not trained to produce true statements. It is trained to output credible sentences that could be found on internet. It is a master bullshitter and will never say "I don't understand what you mean" if it can wriggle around. This is a great step towards a real AI. It is a sort of raw intuition. It now needs to learn to filter its intuition with rationality and epistemological techniques.
- CRConrad 5y ago
  It may be A something, but not I.
  - Iv 5y ago
    For as long as we make intelligent algorithms, people will continue moving the goalposts by changing the definitions of intelligence. We have an algorithm that can learn to outperform humans at any deterministic game and learn the rules by simply watching it. We have algorithms that outperform humans at image recognition and OCR. We have algorithm that draw images according to descriptions. We have algorithms that decipher languages just by looking at a corpus of text. But somehow, as soon as a computer can do it, it is not considered an intelligent task anymore. Kasparov or Champollion used to be considered very smart for what they did, but now apparently that's just considered dumb applied statistics.
Jack000 5y ago
I think it's a mistake to judge the performance of GPT-3 like this because it's not comparing apples to apples. What GPT-3 is doing is equivalent to me giving you a book in Chinese (without any further context, translation or grounding in the physical world) and then expecting you to produce articles in Chinese. This is plainly impossible for any human and it's amazing that it can do this at all. A human generates language while having knowledge of entire other modalities that GPT-3 lacks - vision, audio, proprioception and more. No, of course GPT-3 doesn't know what it's talking about, it's only ever seen tokens! What you should be asking is, what will happen when these modalities are incorporated, when it does know what it's talking about. Personally I suspect a massive number of white collar workers that mostly work with text are about to become obsolete.
- brabel 5y ago
  > vision, audio, proprioception and more... what will happen when these modalities are incorporated First of all, there's no evidence that a token-based model, as you yourself call it, can be made to work on visual or sound data where you have more than one dimension to the data. Second, even if you manage to make it work, it needs to be able to relate the different senses somehow, and no training data is going to be able to give it information about how things relate, it will have to use heuristics to determine that and I can only see that failing spetacularly because much of the relations between what someone sees and how someone acts can take very large amounts of time or never materialize at all (e.g. studying maths VS actually using it to solve a real-world problem).
  - Jack000 5y ago
    hm.. have you seen DALL-E/CLIP? It's literally a language model applied to images and text. It's also the dumbest possible way to generate images (generating tokens one at a time, down and to the right) yet it works.
  - jeeceebees 5y ago
    There is a lot of evidence that these token-based models work with multi-modal data. In fact, several groups have proposed different multi-modal transformer architectures already (e.g. [1] or [2]), although I don't believe anyone has scaled them up much farther than 300M parameters yet. If these models are shown videos of butterflies flapping their wings with a text description of 'a butterfly flapping its wings,' why wouldn't you expect it to start to relate the information coming from multiple modalities? It's definitely a challenge to get enough high-quality data to feed a 100B parameter version of such a mutli-modal model, but there don't seem to be any theoretically insurmountable issues towards this "dumb" way of giving the models more intuition. [1] VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text, https://arxiv.org/abs/2104.11178 https://arxiv.org/abs/2104.11178 [2] Perceiver IO: A General Architecture for Structured Inputs & Outputs, https://arxiv.org/abs/2107.14795 https://arxiv.org/abs/2107.14795
exo-pla-net 5y ago
The robin example applies to BERT, not GPT-3. With GPT-3, here are a couple generations I got for "A robin is not a": A robin is not a bird of a thousand feathers. It is a bird of a thousand songs. – Lebanese Proverb A robin is not a bird of prey and cannot eat a pigeon. I've never seen a robin kill one of those.
- aaronharnly 5y ago
  I also get this little koan: A robin is not a bird. It is a robin.” “I know it is a robin,” answered the boy. “I am only telling you what it is. It is a robin.” “And what is a robin?” asked the old man. “A robin is a robin,” said the boy. “Then a robin is a robin?” said the old man. “It is,” said the boy. “And what is a robin?” asked the old man. “It is a robin,” said the boy. “Then a robin is a robin,” said the old man. “But if it is a robin, it is not a bird.”
nothis 5y ago
Recent advancements in AI made me wonder whether human intelligence is little more than a "stochastic parrot" with a large enough training set. If I dig down far enough, almost any knowledge could be learned and understood that way. You can write a math book using natural language. Even smart people occasionally make simple mistakes when doing math, isn't that just a "stochastic" error as well?
- Jensson 5y ago
  An AI isn't an individual, it should be compared to generations of experts working on a problem. If you could make an AI which works as a group of individuals with generations etc, it would still just be a single AI. And generations of experts basically don't make math mistakes, we have built our entire society on their works and it is extremely accurate Modern stochastic AI couldn't get that sort of accuracy, at some point it would need to determine that a result X is true and eliminate all other possibilities, humanity did that so for AI to have human like power it needs to be able to do the same. That is extremely important since it now means that we can start to properly analyse results depending on X and see that everything which depends on X being false can't happen so we can ignore those, this helps humanity drive progress.
- CRConrad 5y ago
  > Recent advancements in AI made me wonder whether human intelligence is little more than a "stochastic parrot" with a large enough training set. If I dig down far enough, almost any knowledge could be learned and understood that way. People don't get obviously counter-productive results like "I think you should" (kill yourself) from human intelligence, though. As long as this simple stochastic text-regurgitators do that, I think it's an insult to intelligence to call them "intelligence". Idunno, I think "intelligence" has (at least to me) very strong connotations of common sense. (Yeay, yeah, I know: Not so common at all, unfortunately, heh heh heh.) These models don't seem to have any of that at all.
- marcosdumay 5y ago
  There are some things that those "stochastic parrots" can not replicate. A famous one it the "not" problem ("a robin is not a ____", but more famously, it's googling for "shirt without strips") one comment sibling of yours talks about.
plutonorm 5y ago
But it is. By training on language it is forming structures within itself that are isomorphic to the structures that exist in the world, through the relationships between words. These models are the same models that we have in our heads. There are vast interlocking webs of relationships that define how we think about the world - these are encoded within the language we use, the models can pick out these structures and replicate them. It is no surprise at al that they are as capable as they are. What you are seeing is a baby intelligence that is getting things wrong through lack of experience and lack of different information modalities. It's trained only on words for God's sake! You are looking at a baby savant and deluding yourself into thinking there is no intelligence there. You are all in for a shock.

schleck8 5y ago

> As AI ethics expert Timnit Gebru and her collaborators put it, these systems are “stochastic parrots” that do a decent job of mimicry but utterly lack the depth of understanding that general artificial intelligence will require gpt 3 is the first publicly available iteration of large scale text transformers and it's decent for that. it doesn't have to be perfect

tikhonj 5y ago
It doesn't have to be perfect, sure, but it would have to be a lot better to be "a new foundation for AI"—exactly what the article (and presumably this discussion) is about.
wongarsu 5y ago
Surely you meant GPT2? We can argue about the definition of "large scale", but calling GPT3 "publicly available" is a stretch at best.

sooheon 5y ago

Humans are just "better" stochastic parrots.

colordrops 5y ago
Can a parrot have an complex and abstract goal and figure out the many steps to get to that goal?
- mellavora 5y ago
  Real parrots (and many other birds), yes. Stochastic parrots, perhaps not.
- sgt101 5y ago
  as the other commenter said - yes. But the thing is I think it's unlikely that the parrot associates language with the problem solving. Parrots with language capabilities and parrots without language don't seem to have different problem solving capabilities - parrots don't have a spoken/written culture. Humans that are prevented from getting a spoken culture (by isolation) exhibit much reduced problem solving - because the humans with a spoken culture have lots of tips from other humans.
marricks 5y ago
In all these cases if you asked a human for their initial gut response I imagine they’d make the same type of mistakes as GPT3, the difference is if you have someone a minute to think about it and review they wouldn’t.
- CRConrad 5y ago
  "Should I kill myself?" "I think you should." Some sadists may of course have that "gut response" because they're sadists, but which human would respond that way by mistake?!?
flunhat 5y ago
An oft-repeated claim in these debates, usually presented without evidence. But it's not self-evident to me.

Iv 5y ago

GPT-3 is not trained to produce true statements. It is trained to output credible sentences that could be found on internet. It is a master bullshitter and will never say "I don't understand what you mean" if it can wriggle around. This is a great step towards a real AI. It is a sort of raw intuition. It now needs to learn to filter its intuition with rationality and epistemological techniques.

CRConrad 5y ago
It may be A something, but not I.
- Iv 5y ago
  For as long as we make intelligent algorithms, people will continue moving the goalposts by changing the definitions of intelligence. We have an algorithm that can learn to outperform humans at any deterministic game and learn the rules by simply watching it. We have algorithms that outperform humans at image recognition and OCR. We have algorithm that draw images according to descriptions. We have algorithms that decipher languages just by looking at a corpus of text. But somehow, as soon as a computer can do it, it is not considered an intelligent task anymore. Kasparov or Champollion used to be considered very smart for what they did, but now apparently that's just considered dumb applied statistics.

Jack000 5y ago

I think it's a mistake to judge the performance of GPT-3 like this because it's not comparing apples to apples. What GPT-3 is doing is equivalent to me giving you a book in Chinese (without any further context, translation or grounding in the physical world) and then expecting you to produce articles in Chinese. This is plainly impossible for any human and it's amazing that it can do this at all. A human generates language while having knowledge of entire other modalities that GPT-3 lacks - vision, audio, proprioception and more. No, of course GPT-3 doesn't know what it's talking about, it's only ever seen tokens! What you should be asking is, what will happen when these modalities are incorporated, when it does know what it's talking about. Personally I suspect a massive number of white collar workers that mostly work with text are about to become obsolete.

brabel 5y ago
> vision, audio, proprioception and more... what will happen when these modalities are incorporated First of all, there's no evidence that a token-based model, as you yourself call it, can be made to work on visual or sound data where you have more than one dimension to the data. Second, even if you manage to make it work, it needs to be able to relate the different senses somehow, and no training data is going to be able to give it information about how things relate, it will have to use heuristics to determine that and I can only see that failing spetacularly because much of the relations between what someone sees and how someone acts can take very large amounts of time or never materialize at all (e.g. studying maths VS actually using it to solve a real-world problem).
- Jack000 5y ago
  hm.. have you seen DALL-E/CLIP? It's literally a language model applied to images and text. It's also the dumbest possible way to generate images (generating tokens one at a time, down and to the right) yet it works.
- jeeceebees 5y ago
  There is a lot of evidence that these token-based models work with multi-modal data. In fact, several groups have proposed different multi-modal transformer architectures already (e.g. [1] or [2]), although I don't believe anyone has scaled them up much farther than 300M parameters yet. If these models are shown videos of butterflies flapping their wings with a text description of 'a butterfly flapping its wings,' why wouldn't you expect it to start to relate the information coming from multiple modalities? It's definitely a challenge to get enough high-quality data to feed a 100B parameter version of such a mutli-modal model, but there don't seem to be any theoretically insurmountable issues towards this "dumb" way of giving the models more intuition. [1] VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text, https://arxiv.org/abs/2104.11178 https://arxiv.org/abs/2104.11178 [2] Perceiver IO: A General Architecture for Structured Inputs & Outputs, https://arxiv.org/abs/2107.14795 https://arxiv.org/abs/2107.14795

exo-pla-net 5y ago

The robin example applies to BERT, not GPT-3. With GPT-3, here are a couple generations I got for "A robin is not a": A robin is not a bird of a thousand feathers. It is a bird of a thousand songs. – Lebanese Proverb A robin is not a bird of prey and cannot eat a pigeon. I've never seen a robin kill one of those.

aaronharnly 5y ago
I also get this little koan: A robin is not a bird. It is a robin.” “I know it is a robin,” answered the boy. “I am only telling you what it is. It is a robin.” “And what is a robin?” asked the old man. “A robin is a robin,” said the boy. “Then a robin is a robin?” said the old man. “It is,” said the boy. “And what is a robin?” asked the old man. “It is a robin,” said the boy. “Then a robin is a robin,” said the old man. “But if it is a robin, it is not a bird.”

nothis 5y ago

Recent advancements in AI made me wonder whether human intelligence is little more than a "stochastic parrot" with a large enough training set. If I dig down far enough, almost any knowledge could be learned and understood that way. You can write a math book using natural language. Even smart people occasionally make simple mistakes when doing math, isn't that just a "stochastic" error as well?

Jensson 5y ago
An AI isn't an individual, it should be compared to generations of experts working on a problem. If you could make an AI which works as a group of individuals with generations etc, it would still just be a single AI. And generations of experts basically don't make math mistakes, we have built our entire society on their works and it is extremely accurate Modern stochastic AI couldn't get that sort of accuracy, at some point it would need to determine that a result X is true and eliminate all other possibilities, humanity did that so for AI to have human like power it needs to be able to do the same. That is extremely important since it now means that we can start to properly analyse results depending on X and see that everything which depends on X being false can't happen so we can ignore those, this helps humanity drive progress.
CRConrad 5y ago
> Recent advancements in AI made me wonder whether human intelligence is little more than a "stochastic parrot" with a large enough training set. If I dig down far enough, almost any knowledge could be learned and understood that way. People don't get obviously counter-productive results like "I think you should" (kill yourself) from human intelligence, though. As long as this simple stochastic text-regurgitators do that, I think it's an insult to intelligence to call them "intelligence". Idunno, I think "intelligence" has (at least to me) very strong connotations of common sense. (Yeay, yeah, I know: Not so common at all, unfortunately, heh heh heh.) These models don't seem to have any of that at all.
marcosdumay 5y ago
There are some things that those "stochastic parrots" can not replicate. A famous one it the "not" problem ("a robin is not a ____", but more famously, it's googling for "shirt without strips") one comment sibling of yours talks about.

plutonorm 5y ago

But it is. By training on language it is forming structures within itself that are isomorphic to the structures that exist in the world, through the relationships between words. These models are the same models that we have in our heads. There are vast interlocking webs of relationships that define how we think about the world - these are encoded within the language we use, the models can pick out these structures and replicate them. It is no surprise at al that they are as capable as they are. What you are seeing is a baby intelligence that is getting things wrong through lack of experience and lack of different information modalities. It's trained only on words for God's sake! You are looking at a baby savant and deluding yourself into thinking there is no intelligence there. You are all in for a shock.