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There is no artificial intelligence. There are only systems that are very good at generating text or images when given a text prompt. That's not intelligence, a

There is no artificial intelligence. There are only systems that are very good at generating text or images when given a text prompt. That's not intelligence, and it's misleading if not dangerous to call it that.

brookst 3y ago
It's just semantics. Some people use intelligence to mean sentience, others use it to mean directed problem solving / solution-finding.
- eynsham 3y ago
  Could you give an example of people who explicitly claim that sentience is equivalent to intelligence? I’d agree that some arguments trade on an equivocation between the two, but I don’t think their adherents intentionally do so.
  - brookst 3y ago
    The post I replied to seemed to make the conflation. Because “just guessing the next word” seems like a reasonable refutation to sentience, but not to intelligence. I agree that it’s not usually an intentional mixup. From what I’ve seen it’s mostly a lack of rigor in defining terms.
eynsham 3y ago
There are arguments for this position that are philosophically and scientifically respectable and to which I am inclined. But merely repeating this nostrum isn’t very constructive. Of course, I’m also repeating nostrums here, but I am not making any definitive claim here. 1. Intelligence is surely best characterised not bivalently; if, then, it’s a matter of degree, it is at least somewhat non-trivial to show that LLMs make no progress whatsoever on previous AI (soi-disantes). 2. It’s also unclear that intelligence is best characterised by a single factor. Perhaps that’s uncontroversial in the psychometric literature (I wouldn’t know), but even then, why would g be the right way of characterising intelligence in beings with quite different strengths and weaknesses? And, if ‘intelligence’ admits multiple precisifications, the claims that (a) some particular system displays intelligence simpliciter (perhaps a pragmatic notion) on one such precisification and (b) that some particular system displays some higher level of intelligence than before in that respect are yet weaker and more difficult to rebut. 3. It’s unclear whether ‘are’ is to be construed literally (i.e., indicatively) or as a much stronger claim, e.g., in the Fodorian or Lucasian vein, that some wide class of would-be AI simply can’t achieve intelligence due to some systematic limitation.
- SanderNL 3y ago
  I had a feeling you had something interesting to say, but I couldn’t make heads or tails of it. I am being serious. I just applied GPT4 to ELI5 your comment to me. I feel like I have crossed some threshold and I’m not sure if I am proud of it, but there it is. I am still not entirely sure what your main point is, but I learned about the Fodorian and Lucasian arguments which I don’t find particularly impressive, but then again, I need a language model to explain things to me. Interesting nonetheless. I did not know about “g” either. How did I survive for so long you may ask and it is indeed a miracle. Anyway, a nuanced understanding of intelligence seems reasonable and useful. The concept “nostrum” was also new to me as was the word “simpliciter”. In fact I asked GPT4 for a table of uncommon words and concepts in your post and it was quite substantial. All in all I rarely come across a post that makes me feel like an ape and sets me on a path of creativity and knowledge. Thank you for that. Edit: obligatory response in the proper style: “The manner in which this prose is articulated can be characterized as both prolix and imbued with a certain aesthetic appeal. One is left to ponder the origins of the author's stylistic inclinations. As for my own stance concerning the matter of artificial intelligence, it may be succinctly encapsulated as follows: "AI demonstrates utility, and as such, it possesses merit." This, regrettably, constitutes the extent of my intellectual engagement with the subject.”
  - eynsham 3y ago
    You’re right—the way I wrote the original comment isn’t particularly easy to parse. I’d been reading philosophy of language all day, and didn’t pause to edit. I’ll try to rephrase here; I don’t think the points are particularly complicated, so if the exposition here is still inadequate, that’s my fault. 1. On one view of intelligence, something is either intelligent or not. On another, some things are more intelligent than others, but there’s no clear cutoff between intelligent and non-intelligent things. On the first view, it seems quite plausible that actually existing ‘AI’ (e.g., GPT) doesn’t count as intelligent. On the second view, actually existing ‘AI’ seems to be at least somewhat intelligent: more so than most other software we’ve written. If the second view is right, it’s unhelpful in many cases to simply pronounce things intelligent and unintelligent. 2. By way of analogy, suppose I say that a walking route is quite hard. I might mean that it’s very long. Or I might mean that it’s hilly. Or I might mean that it’s very boggy. Each is a perfectly good reason to say that the route is hard. So a walk that’s merely quite hilly counts as hard, even if it’s fairly short and the ground is dry. We might say that attributions of intelligence are similar. If so, we can attribute intelligence to systems for many different individually respectable reasons. Perhaps a system is intelligent because it can respond to novel situations in some appropriate way. Perhaps it’s intelligent because it predicts a certain statistical parameter correctly. Perhaps it’s intelligent because it’s small but can correctly deal with a wide range of situations. If the analogy is right, it would be odd (perhaps wrong) to say that a system good at one of these just isn’t intelligent because it falls down on the other measures. If so, surely GPT counts as intelligent for at least one respectable reason or another. On the other hand, suppose I call someone tall. There’s only one way to be tall. Being fat, or having muscly arms, or having long legs but a short torso don’t count. So the analogy doesn’t apply to all concepts. Does it apply to intelligence? Initially, it might seem that it doesn’t: surely there are lots of ways to be intelligent. But I’ve heard that the psychometrics literature suggests that all these measures correlate to a great degree, and statistically can be predicted by a single-factor model (thus ‘g’). That might suggest that there really is only one way to be intelligent, and that appearances are misleading. I am not familiar with the psychometrics literature, so I wouldn’t know; maybe the single-factor model is wrong. But my point is this. Even if the single-factor model is right, it’s only been shown to be right about humans (so far): their statistical base has comprised humans. So maybe a multi-factor model of intelligence works better for would-be machine intelligence. For example, perhaps arithmetic ability in humans is predicted well by a single factor; maybe it’s even reducible to some single form of intelligence. But we can obviously separate arithmetic ability from e.g. analytic ability in computers, to an almost arbitrary extent, by making very good calculators. (And LLMs are often not very good at arithmetic, though I gather that’s being improved.) If that is so, intelligence is more like difficulty of a walking route than tallness. And so that’s another reason to avoid straightforward denial that would-be AI is or could be intelligent. 3. It’s quite plausible that no presently existing would-be AI should count as intelligent. But we don’t know whether that’s a general limitation or not. And if there are general limitations, how general are they? For example, maybe LLMs couldn’t be intelligent but some GOFAI type thing could be. Or maybe we simply need a new architecture. One argument we could read in Fodor is that neural networks have to implement a so-called language of thought to be meaningfully intelligent. That would be quite a general limitation, though arguably one we could overcome. (I’ve always been a bit confused by what Fodor really meant by a language of thought, and in particular what he required of mental representations, but I haven’t made a full study of him yet.) A much stronger argument from J.R. Lucas is broadly ‘anti-mechanism’, which would roughly include everything we can presently engineer or can be run on a Turing machine. This is very strong, and not many people agree in my experience. — The point of my comment is that these matters are complicated, and the comment above didn’t really address these complications. Sometimes nuance doesn’t add much or isn’t worth it. (I quite like Kieran’s ‘Fuck Nuance’ as a lesson for all theorising, not just sociology.) But sometimes it does matter. ‘[T]here is no artificial intelligence’ is hasty enough to require a response.
stemlord 3y ago
To me it's a tech colloquialism for a thing that uses a neural net in some capacity. I think its misleading to use it to describe other types of ML (i.e., SLAM robotics)
- robotresearcher 3y ago
  Classical SLAM by optimizing constraint graphs has little to do with ML. The optimization function is explicit, and there’s no training.
Closi 3y ago
> There is no artificial intelligence. There are only systems that are very good at generating text or images when given a text prompt. That's not intelligence, and it's misleading if not dangerous to call it that. Disagree - GPT4 definitely has a level of reasoning, can abstract problems, can apply knowledge in new and different ways, so it definitely meets some definitions of intelligence. What's your definition of intelligence that GPT4 wouldn't fulfill at some level? (Personally I believe it's possible to have intelligence without sentience/self-awareness)
- Diggsey 3y ago
  It's missing generality. It can't do basic maths, or even follow instructions. It can't make valid moves in a game. It can only do what it was trained to do: make a good guess at what word should come next. I don't mean to down-play how impressive models like GPT-4 are - they are very impressive and have great utility. The problem is we are talking about PR, and when you throw around words like "artificial intelligence" it misleads everyone who is not intimately familiar with the limitations of such models. > Personally I believe it's possible to have intelligence without sentience/self-awareness The general public doesn't make that distinction when you throw around terms like artificial intelligence. They hear artificial intelligence and imagine "thinking machines". No doubt people will say this is just moving the goalposts - that whatever these models achieve it will never be "AI", but that's demonstrably false. The concept of AI has existed in film and other media in the same form since forever, and it's pretty clear if you put those representations side by side with what we actually have today, that we are not even close yet. For some reason "advances in machine learning" just isn't hip enough to get funding, so "AI" gets thrown around instead.
  - Closi 3y ago
    > It can only do what it was trained to do: make a good guess at what word should come next. Disagree - GPT's mechanics are that it guesses what word/token should come next, however it is now displaying emergent capabilities which do show an agent which can generalize. Maybe not to 'AGI' levels, but it is starting to show little signs of it. > It can't do basic maths, or even follow instructions. It can't make valid moves in a game. It can do basic maths - better than most humans (but it cannot do maths better than a calculator). If I ask GPT4 to calculate 51 times 102 it will get the answer, despite most humans struggling with this task. It does this just via internal representation without any specific 'calculator' API call or functionality. It can follow instructions - if I tell it to take the sentence "abcd" and then tell it to follow the following steps: "1) swap b and c around, 2) reverse the string, 3) ignore step 1", it will output "dcba" and describe how it reached that output It can make valid game moves - Without being formally taught chess it will make valid chess moves most of the time (see: https://www.lesswrong.com/posts/xyjhFCSSXZsW6HDBb/a-chess-game-against-gpt-4 https://www.lesswrong.com/posts/xyjhFCSSXZsW6HDBb/a-chess-ga...). It made 29 valid moves before making invalid moves. Again, GPT4 has not been specifically trained to play chess, it just has picked up some chess rules and games while reading the internet and this has somehow formed some sort of internal representations for chess within it's model. I can also describe a new/novel game or puzzle to GPT4 and it can have a go at playing and solving it. What it can't do is learn at the moment, although learning isn't part of a lot of definitions of intelligence, which is why we have to define intelligence before you can say if it is/isn't intelligent.
_Algernon_ 3y ago
It writes better texts than many adult humans, and outside of a persons area of expertise it probably performs better than an adult human as long as the problem can be described in text. It is overly optimistic, and does make mistakes, but it certainly shows intelligent behaviour.
- hilbertseries 3y ago
  It’s interesting that we view the fact that it makes mistakes as evidence it’s not intelligent. By this metric then, humans are also not intelligent.
  - ChatGTP 3y ago
    A rock doesn’t make mistakes, it’s awesome at being a rock.
  - glandium 3y ago
    What's interesting to me is how ChatGPT with GPT-4 can fail to follow your instructions randomly (for the same instructions, in the same session). That's these kind of behaviors that show it is, in fact, not intelligent, but that probabilities line up properly for the emergent behavior to look like it is.
    - gmerc 3y ago
      By that measure most humans are not intelligent … go 10 times to a restaurant and tell me the failure rate of getting precisely what you want :)
      - deleted 3y ago
        [deleted]
      - nullsense 3y ago
        If that restaurant is McDonald's or KFC then about 10% ~ 15%?
robotresearcher 3y ago
Two generations ago we were calling chess programs AI. Last generation it was face detection in images. Each generation makes a new clever thing, calls it AI for a while, puts it to good use and forgets about it for the next shiny thing called AI for real this time. Don’t get me wrong: the new large models are amazing, and will be useful. Not dissing them. Just observing the history of the term ‘AI’ in popular usage.
- AshamedCaptain 3y ago
  This is a irony I've noticed too. Some engineers tell me their managers are in a state of panic about how to "best make use of AI" (translated: how to ride the current hype wave to get nice PR points). The correct answer of course is "we already use AI and have been doing so since the 80s". Considering it is ridiculously impractical to use ChatGPT in many areas where 1980s AI techniques are in use (think metaheuristics, chess, etc.), I suspect this is rather common.
  - turtleyacht 3y ago
    It would be nice to have a table where, say, column A has "linear regression," and column B has something the business already uses that for. Sure, we can also associate supply chain and logistics bin packing, inventory forecasting, existing warehouse automation--including computer vision and such. But once you get to NLP, deep learning, and LLM, doesn't it kind of go off the rails?
  - ska 3y ago
    There is an old quote about this, I’m too lazy to find at the moment (from the 80s or 90s?). Gist was that we call the new thing AI until we really understand it, then we start calling it machine learning. Lather, rinse, repeat.
- CamperBob2 3y ago
  Two generations ago we were calling chess programs AI... I think this observation held up well until AlphaGo hit the scene. Then it started to sound a bit less insightful. At this point, it's just whistling past the proverbial graveyard.
School-Cotton 3y ago
> There are only systems that are very good at generating text or images when given a text prompt. How is that not intelligence?
elbigbad 3y ago
Words change over time. Plenty of words have changed meaning in my lifetime to become less formal than they once were. And I guarantee I used to be this pedantic about some of them, particularly around the usage of grammar and punctuation, and in some cases am still very stubbornly pedantic even though it’s clear the world has moved on and I’m the only one left on the hill. The phrase “artificial intelligence” is the same here. You may still die on this hill, but the world has moved on. AI has become overloaded to mean a wide variety of things and not just the “dangerous” generalized terminator robot you’re envisioning. One strategy to cope is to come up with a new word and define it as you’d like, being careful to not overload it.
akomtu 3y ago
Imo, it's time to define tiers of intelligence, and then say "GPT4 is a level 3 AI". We can start with observing animals and birds to define the basic level 1 intelligence: it's an ability to react to environment, but they cannot learn because they don't have much memory. Level 2 adds sub-conscious memory that enables learning basic tricks, but learning is very slow. That's monkeys. Level 3 adds conscious memory: the subject is aware of its existence and can use it to remember faces or learn complex behaviours. That's early humans. Level 4 would introduce the concept of thought: an imaginary object that can be manipulated to model reality. Level 5 is abstract thought: it's no longer limited to real things and can model abstract concepts that's never been seen by the subject.
- dragonwriter 3y ago
  > Imo, it’s time to define tiers of intelligence First, we would have to define the concept of intelligence.
- AnimalMuppet 3y ago
  Level 5 might be recursive - thinking about thinking. Or it might be observable thought - the ability to watch yourself think.
CamperBob2 3y ago
So when a LLM writes a credible epilogue to an existing novel [1], that's not "intelligent?" Sounds a bit like a god-of-the-gaps argument. 1: https://huggingface.co/mosaicml/mpt-7b-storywriter https://huggingface.co/mosaicml/mpt-7b-storywriter

brookst 3y ago

It's just semantics. Some people use intelligence to mean sentience, others use it to mean directed problem solving / solution-finding.

eynsham 3y ago
Could you give an example of people who explicitly claim that sentience is equivalent to intelligence? I’d agree that some arguments trade on an equivocation between the two, but I don’t think their adherents intentionally do so.
- brookst 3y ago
  The post I replied to seemed to make the conflation. Because “just guessing the next word” seems like a reasonable refutation to sentience, but not to intelligence. I agree that it’s not usually an intentional mixup. From what I’ve seen it’s mostly a lack of rigor in defining terms.

eynsham 3y ago

There are arguments for this position that are philosophically and scientifically respectable and to which I am inclined. But merely repeating this nostrum isn’t very constructive. Of course, I’m also repeating nostrums here, but I am not making any definitive claim here. 1. Intelligence is surely best characterised not bivalently; if, then, it’s a matter of degree, it is at least somewhat non-trivial to show that LLMs make no progress whatsoever on previous AI (soi-disantes). 2. It’s also unclear that intelligence is best characterised by a single factor. Perhaps that’s uncontroversial in the psychometric literature (I wouldn’t know), but even then, why would g be the right way of characterising intelligence in beings with quite different strengths and weaknesses? And, if ‘intelligence’ admits multiple precisifications, the claims that (a) some particular system displays intelligence simpliciter (perhaps a pragmatic notion) on one such precisification and (b) that some particular system displays some higher level of intelligence than before in that respect are yet weaker and more difficult to rebut. 3. It’s unclear whether ‘are’ is to be construed literally (i.e., indicatively) or as a much stronger claim, e.g., in the Fodorian or Lucasian vein, that some wide class of would-be AI simply can’t achieve intelligence due to some systematic limitation.

SanderNL 3y ago
I had a feeling you had something interesting to say, but I couldn’t make heads or tails of it. I am being serious. I just applied GPT4 to ELI5 your comment to me. I feel like I have crossed some threshold and I’m not sure if I am proud of it, but there it is. I am still not entirely sure what your main point is, but I learned about the Fodorian and Lucasian arguments which I don’t find particularly impressive, but then again, I need a language model to explain things to me. Interesting nonetheless. I did not know about “g” either. How did I survive for so long you may ask and it is indeed a miracle. Anyway, a nuanced understanding of intelligence seems reasonable and useful. The concept “nostrum” was also new to me as was the word “simpliciter”. In fact I asked GPT4 for a table of uncommon words and concepts in your post and it was quite substantial. All in all I rarely come across a post that makes me feel like an ape and sets me on a path of creativity and knowledge. Thank you for that. Edit: obligatory response in the proper style: “The manner in which this prose is articulated can be characterized as both prolix and imbued with a certain aesthetic appeal. One is left to ponder the origins of the author's stylistic inclinations. As for my own stance concerning the matter of artificial intelligence, it may be succinctly encapsulated as follows: "AI demonstrates utility, and as such, it possesses merit." This, regrettably, constitutes the extent of my intellectual engagement with the subject.”
- eynsham 3y ago
  You’re right—the way I wrote the original comment isn’t particularly easy to parse. I’d been reading philosophy of language all day, and didn’t pause to edit. I’ll try to rephrase here; I don’t think the points are particularly complicated, so if the exposition here is still inadequate, that’s my fault. 1. On one view of intelligence, something is either intelligent or not. On another, some things are more intelligent than others, but there’s no clear cutoff between intelligent and non-intelligent things. On the first view, it seems quite plausible that actually existing ‘AI’ (e.g., GPT) doesn’t count as intelligent. On the second view, actually existing ‘AI’ seems to be at least somewhat intelligent: more so than most other software we’ve written. If the second view is right, it’s unhelpful in many cases to simply pronounce things intelligent and unintelligent. 2. By way of analogy, suppose I say that a walking route is quite hard. I might mean that it’s very long. Or I might mean that it’s hilly. Or I might mean that it’s very boggy. Each is a perfectly good reason to say that the route is hard. So a walk that’s merely quite hilly counts as hard, even if it’s fairly short and the ground is dry. We might say that attributions of intelligence are similar. If so, we can attribute intelligence to systems for many different individually respectable reasons. Perhaps a system is intelligent because it can respond to novel situations in some appropriate way. Perhaps it’s intelligent because it predicts a certain statistical parameter correctly. Perhaps it’s intelligent because it’s small but can correctly deal with a wide range of situations. If the analogy is right, it would be odd (perhaps wrong) to say that a system good at one of these just isn’t intelligent because it falls down on the other measures. If so, surely GPT counts as intelligent for at least one respectable reason or another. On the other hand, suppose I call someone tall. There’s only one way to be tall. Being fat, or having muscly arms, or having long legs but a short torso don’t count. So the analogy doesn’t apply to all concepts. Does it apply to intelligence? Initially, it might seem that it doesn’t: surely there are lots of ways to be intelligent. But I’ve heard that the psychometrics literature suggests that all these measures correlate to a great degree, and statistically can be predicted by a single-factor model (thus ‘g’). That might suggest that there really is only one way to be intelligent, and that appearances are misleading. I am not familiar with the psychometrics literature, so I wouldn’t know; maybe the single-factor model is wrong. But my point is this. Even if the single-factor model is right, it’s only been shown to be right about humans (so far): their statistical base has comprised humans. So maybe a multi-factor model of intelligence works better for would-be machine intelligence. For example, perhaps arithmetic ability in humans is predicted well by a single factor; maybe it’s even reducible to some single form of intelligence. But we can obviously separate arithmetic ability from e.g. analytic ability in computers, to an almost arbitrary extent, by making very good calculators. (And LLMs are often not very good at arithmetic, though I gather that’s being improved.) If that is so, intelligence is more like difficulty of a walking route than tallness. And so that’s another reason to avoid straightforward denial that would-be AI is or could be intelligent. 3. It’s quite plausible that no presently existing would-be AI should count as intelligent. But we don’t know whether that’s a general limitation or not. And if there are general limitations, how general are they? For example, maybe LLMs couldn’t be intelligent but some GOFAI type thing could be. Or maybe we simply need a new architecture. One argument we could read in Fodor is that neural networks have to implement a so-called language of thought to be meaningfully intelligent. That would be quite a general limitation, though arguably one we could overcome. (I’ve always been a bit confused by what Fodor really meant by a language of thought, and in particular what he required of mental representations, but I haven’t made a full study of him yet.) A much stronger argument from J.R. Lucas is broadly ‘anti-mechanism’, which would roughly include everything we can presently engineer or can be run on a Turing machine. This is very strong, and not many people agree in my experience. — The point of my comment is that these matters are complicated, and the comment above didn’t really address these complications. Sometimes nuance doesn’t add much or isn’t worth it. (I quite like Kieran’s ‘Fuck Nuance’ as a lesson for all theorising, not just sociology.) But sometimes it does matter. ‘[T]here is no artificial intelligence’ is hasty enough to require a response.

stemlord 3y ago

To me it's a tech colloquialism for a thing that uses a neural net in some capacity. I think its misleading to use it to describe other types of ML (i.e., SLAM robotics)

robotresearcher 3y ago
Classical SLAM by optimizing constraint graphs has little to do with ML. The optimization function is explicit, and there’s no training.

Closi 3y ago

> There is no artificial intelligence. There are only systems that are very good at generating text or images when given a text prompt. That's not intelligence, and it's misleading if not dangerous to call it that. Disagree - GPT4 definitely has a level of reasoning, can abstract problems, can apply knowledge in new and different ways, so it definitely meets some definitions of intelligence. What's your definition of intelligence that GPT4 wouldn't fulfill at some level? (Personally I believe it's possible to have intelligence without sentience/self-awareness)

Diggsey 3y ago
It's missing generality. It can't do basic maths, or even follow instructions. It can't make valid moves in a game. It can only do what it was trained to do: make a good guess at what word should come next. I don't mean to down-play how impressive models like GPT-4 are - they are very impressive and have great utility. The problem is we are talking about PR, and when you throw around words like "artificial intelligence" it misleads everyone who is not intimately familiar with the limitations of such models. > Personally I believe it's possible to have intelligence without sentience/self-awareness The general public doesn't make that distinction when you throw around terms like artificial intelligence. They hear artificial intelligence and imagine "thinking machines". No doubt people will say this is just moving the goalposts - that whatever these models achieve it will never be "AI", but that's demonstrably false. The concept of AI has existed in film and other media in the same form since forever, and it's pretty clear if you put those representations side by side with what we actually have today, that we are not even close yet. For some reason "advances in machine learning" just isn't hip enough to get funding, so "AI" gets thrown around instead.
- Closi 3y ago
  > It can only do what it was trained to do: make a good guess at what word should come next. Disagree - GPT's mechanics are that it guesses what word/token should come next, however it is now displaying emergent capabilities which do show an agent which can generalize. Maybe not to 'AGI' levels, but it is starting to show little signs of it. > It can't do basic maths, or even follow instructions. It can't make valid moves in a game. It can do basic maths - better than most humans (but it cannot do maths better than a calculator). If I ask GPT4 to calculate 51 times 102 it will get the answer, despite most humans struggling with this task. It does this just via internal representation without any specific 'calculator' API call or functionality. It can follow instructions - if I tell it to take the sentence "abcd" and then tell it to follow the following steps: "1) swap b and c around, 2) reverse the string, 3) ignore step 1", it will output "dcba" and describe how it reached that output It can make valid game moves - Without being formally taught chess it will make valid chess moves most of the time (see: https://www.lesswrong.com/posts/xyjhFCSSXZsW6HDBb/a-chess-game-against-gpt-4 https://www.lesswrong.com/posts/xyjhFCSSXZsW6HDBb/a-chess-ga...). It made 29 valid moves before making invalid moves. Again, GPT4 has not been specifically trained to play chess, it just has picked up some chess rules and games while reading the internet and this has somehow formed some sort of internal representations for chess within it's model. I can also describe a new/novel game or puzzle to GPT4 and it can have a go at playing and solving it. What it can't do is learn at the moment, although learning isn't part of a lot of definitions of intelligence, which is why we have to define intelligence before you can say if it is/isn't intelligent.

_Algernon_ 3y ago

It writes better texts than many adult humans, and outside of a persons area of expertise it probably performs better than an adult human as long as the problem can be described in text. It is overly optimistic, and does make mistakes, but it certainly shows intelligent behaviour.

hilbertseries 3y ago
It’s interesting that we view the fact that it makes mistakes as evidence it’s not intelligent. By this metric then, humans are also not intelligent.
- ChatGTP 3y ago
  A rock doesn’t make mistakes, it’s awesome at being a rock.
- glandium 3y ago
  What's interesting to me is how ChatGPT with GPT-4 can fail to follow your instructions randomly (for the same instructions, in the same session). That's these kind of behaviors that show it is, in fact, not intelligent, but that probabilities line up properly for the emergent behavior to look like it is.
  - gmerc 3y ago
    By that measure most humans are not intelligent … go 10 times to a restaurant and tell me the failure rate of getting precisely what you want :)
    - deleted 3y ago
      [deleted]
    - nullsense 3y ago
      If that restaurant is McDonald's or KFC then about 10% ~ 15%?

robotresearcher 3y ago

Two generations ago we were calling chess programs AI. Last generation it was face detection in images. Each generation makes a new clever thing, calls it AI for a while, puts it to good use and forgets about it for the next shiny thing called AI for real this time. Don’t get me wrong: the new large models are amazing, and will be useful. Not dissing them. Just observing the history of the term ‘AI’ in popular usage.

AshamedCaptain 3y ago
This is a irony I've noticed too. Some engineers tell me their managers are in a state of panic about how to "best make use of AI" (translated: how to ride the current hype wave to get nice PR points). The correct answer of course is "we already use AI and have been doing so since the 80s". Considering it is ridiculously impractical to use ChatGPT in many areas where 1980s AI techniques are in use (think metaheuristics, chess, etc.), I suspect this is rather common.
- turtleyacht 3y ago
  It would be nice to have a table where, say, column A has "linear regression," and column B has something the business already uses that for. Sure, we can also associate supply chain and logistics bin packing, inventory forecasting, existing warehouse automation--including computer vision and such. But once you get to NLP, deep learning, and LLM, doesn't it kind of go off the rails?
- ska 3y ago
  There is an old quote about this, I’m too lazy to find at the moment (from the 80s or 90s?). Gist was that we call the new thing AI until we really understand it, then we start calling it machine learning. Lather, rinse, repeat.
CamperBob2 3y ago
Two generations ago we were calling chess programs AI... I think this observation held up well until AlphaGo hit the scene. Then it started to sound a bit less insightful. At this point, it's just whistling past the proverbial graveyard.

School-Cotton 3y ago

> There are only systems that are very good at generating text or images when given a text prompt. How is that not intelligence?

elbigbad 3y ago

Words change over time. Plenty of words have changed meaning in my lifetime to become less formal than they once were. And I guarantee I used to be this pedantic about some of them, particularly around the usage of grammar and punctuation, and in some cases am still very stubbornly pedantic even though it’s clear the world has moved on and I’m the only one left on the hill. The phrase “artificial intelligence” is the same here. You may still die on this hill, but the world has moved on. AI has become overloaded to mean a wide variety of things and not just the “dangerous” generalized terminator robot you’re envisioning. One strategy to cope is to come up with a new word and define it as you’d like, being careful to not overload it.

akomtu 3y ago

Imo, it's time to define tiers of intelligence, and then say "GPT4 is a level 3 AI". We can start with observing animals and birds to define the basic level 1 intelligence: it's an ability to react to environment, but they cannot learn because they don't have much memory. Level 2 adds sub-conscious memory that enables learning basic tricks, but learning is very slow. That's monkeys. Level 3 adds conscious memory: the subject is aware of its existence and can use it to remember faces or learn complex behaviours. That's early humans. Level 4 would introduce the concept of thought: an imaginary object that can be manipulated to model reality. Level 5 is abstract thought: it's no longer limited to real things and can model abstract concepts that's never been seen by the subject.

dragonwriter 3y ago
> Imo, it’s time to define tiers of intelligence First, we would have to define the concept of intelligence.
AnimalMuppet 3y ago
Level 5 might be recursive - thinking about thinking. Or it might be observable thought - the ability to watch yourself think.

CamperBob2 3y ago

So when a LLM writes a credible epilogue to an existing novel [1], that's not "intelligent?" Sounds a bit like a god-of-the-gaps argument. 1: https://huggingface.co/mosaicml/mpt-7b-storywriter https://huggingface.co/mosaicml/mpt-7b-storywriter