7 ms·

I think there’s a huge assumption here that more LLM will lead to AGI. Nothing I’ve seen or learned about LLMs leads me to believe that LLMs are in fact a path

I think there’s a huge assumption here that more LLM will lead to AGI. Nothing I’ve seen or learned about LLMs leads me to believe that LLMs are in fact a pathway to AGI. LLMs trained on more data with more efficient algorithms will make for more interesting tools built with LLMs, but I don’t see this technology as a foundation for AGI. LLMs don’t “reason” in any sense of the word that I understand and I think the ability to reason is table stakes for AGI.

cortic 3y ago
If humans are basically evolved LLMs, which i think is likely; Reasoning will be an emergent property of LLMs within context with appropriate weights.
- enieslobby 3y ago
  Why do you think humans are basically evolved LLMs? Honest question, would love to read more about this viewpoint.
  - cortic 3y ago
    Look at a year old baby, there is no logic, no reasoning, no real consciousness, just basic algorithms and data input ports. It takes ten years of data sets before these emergent properties start to develop, and another ten years before anything of value can be output.
    - berniedurfee 3y ago
      I strongly disagree. Kids, even infants, show a remarkable degree of sophistication in relation to an LLM. I admit that humans don’t progress much behaviorally, outside of intellect, past our teen years; we’re very instinct driven. But still, I think even very young children have a spark that’s something far beyond rote token generation. I think it’s typical human hubris (and clever marketing) to believe that we can invent AGI in less than 100 years when it took nature millions of years to develop. Until we understand consciousness, we won’t be able to replicate it and we’re a very long way from that leap.
      - visarga 3y ago
        Humans are not very smart, individually, and over a single lifetime. We become smart as a species in tens of millennia of gathering experience and sharing it through language. What LLMs learn is exactly the diff between primitive humans and us. It's such a huge jump a human alone can't make it. If we were smarter we should have figured out the germ theory of disease sooner, as we were dying from infections. So don't praise the learning abilities of little children, without language and social support they would not develop very much. We develop not just by our DNA and direct experiences but also by assimilating past experiences through language. It's a huge cache of crystallized intelligence from the past, without which we would not rule this planet. That's also why I agree LLMs are stalling because we can't quickly scale a few more orders of magnitude the organic text inputs. So there must the a different way to learn, and that is by putting AI in contact with environments and letting it do its own actions and learn from its mistakes just like us. I believe humans are "just" contextual language and action models. We apply language to understand, reason and direct our actions. We are GPTs with better feedback from outside, and optimized for surviving in this environment. That explains why we need so few samples to learn, the hard work has been done by many previous generations, brains are fit for their own culture. So the path forward will imply creating synthetic data, and then somehow evaluating the good from the bad. This will be task specific. For coding, we can execute tests. For math, we can use theorem provers to validate. But for chemistry we need simulations or labs. For physics, we need the particle accelerator to get feedback. But for games - we can just use the score - that's super easy, and already led to super-human level players like AlphaZero. Each topic has its own slowness and cost. It will be a slow grind ahead. And it can't be any other way, AI and AGI are not magic. They must use the scientific method to make progress just like us.
        RandomLensman 3y ago
        Humans do more than just enhance predictive capabilities. It is also a very strong assumption that we are optimised for survival in many or all aspects (even unclear what that means). Some things could be totally incidental and not optimised. I find appeals to evolutionary optimisation very tricky and often fraught.
    - spzb 3y ago
      Have you ever met a baby? They're nothing like an LLM. For starters, they learn without using language. By one year old they've taught themselves to move around the physical world. They've started to learn cause and effect. They've learned where "they" end and "the rest of the world" begins. All an LLM has "learnt" is that some words are more likely to follow others.
      - visarga 3y ago
        Why not? We have multi-modal models as well. Not pure text.
    - timacles 3y ago
      This comment is just sad. What are you even talking about? Have you ever seen a 1 year old
  - lumost 3y ago
    An LLM is simply a model which given a sequence, predicts the rest of the sequence. You can accurately describe any AGI or reasoning problem as an open domain sequence modeling problem. It is not an unreasonable hypothesis that brains evolved to solve a similar sequence modeling problem.
    - RandomLensman 3y ago
      In the broader sense that is tricky as accurate prediction is not always the right metric (otherwise we'd still be using epicycles for the planets).
      - lumost 3y ago
        It depends on the goal, epicycles don't tell you about the nature of heavenly bodies - but they do let you keep an accurate calendar for a reasonable definition of accurate. I'm not sure whether I need deep understanding of intelligence to gain economic benefit from AI.
    - timacles 3y ago
      > It is not an unreasonable hypothesis that brains evolved to solve a similar sequence modeling problem. The real world is random, requires making decisions on incomplete information in situations that have never happened before. The real world is not a sequence of tokens. Consciousness requires instincts in order to prioritize the endless streams of information. One thing people dont want to accept about any AI is that humans always have to tell it WHAT to think about. Our base reptilian brains are the core driver behind all behavior. AI cannot learn that
      - hutzlibu 3y ago
        "Consciousness requires instincts in order to prioritize the endless streams of information. " What if "instinct" is also just (pretrained) model weight? The human brain is very complex and far from understood and definitely does NOT work like a LLM. But it likely shares some core concepts. Neuronal networks were inspired by brain synapses after all.
  - cortic 3y ago
    My first answer was a bit hasty, let me try again; We are clearly a product of our past experience (in LLMs this is called our datasets). If you go back to the beginning of our experiences, there is little identity, consciousness, or ability to reason. These things are learned indirectly, (in LLMs this is called an emergent property). We don't learn indiscriminately, evolved instinct, social pressure and culture guide and bias our data consumption (in LLMs this is called our weights). I can't think of any other way our minds could work, on some level they must function like a LLM, Language perhaps supplemented with general Data, but the principle being the same. Every new idea has been an abstraction or supposition of someones current dataset, which is why technological and general societal advancement has not been linear but closer to exponential.
    - Jensson 3y ago
      Genes encode a ton of behaviors, you can't just ignore that. Tabula rasa doesn't exist among humans. > If you go back to the beginning of our experiences, there is little identity, consciousness, or ability to reason. That is because babies brains aren't properly developed. There is nothing preventing a fully conscious being from being born, you see that among animals etc. A newborn foal is a fully functional animal for example. Genes encode the ability to move around, identify objects, follow other beings, collision avoidance etc.
      - cortic 3y ago
        >Genes encode a ton of behaviors, you can't just ignore that. I'm not ignoring that, I'm just saying that in LLMs we call these things weights. And i don't want to downplay the importance of weights, its probably a significant difference between us and other hominids. But even if you considered some behaviors to be more akin to the server or interface or preprocess in LLMs it still wouldn't detract from the fact that the vast majority of the things that make us autonomous logical sentient beings come about through a process that is very similar to the core workings of LLMs. I'm also not saying that all animal brains function like LLMs, though that's an interesting thought to consider.
- tgv 3y ago
  So you think we were originally trained on 300B tokens, those were then ingrained in our synapses, and then we evolved?
- lossolo 3y ago
  Reasoning and intelligence exists without language.
  - cortic 3y ago
    You know i assumed that was true until right now. But I can't think of a single example of reason and intelligence existing without any form of language. Even insects have rudimentary language, and in fact reasoning and intelligence seem to scale with the complexity of language, both by species and within species.
    - Jensson 3y ago
      Do slime mold have a language? Slime mold can learn and adapt to environments, so it is intelligent and can do rudimentary reasoning, but I doubt it communicates that information to other slime molds. It is a very different kind of life form though so many things that applies to other complex being doesn't apply to them. Being a large single cell means that they learn by changing its proteins and other internals, very hard for us humans to reason about and understand since it is so alien compared to just having nerve cells with physical connections.
      - cortic 3y ago
        Not sure i would say a slime mold has reason and intelligence .. Or if i would then so does a river. Also i think that how it changes its proteins could be considered a language, without stretching the definition of language any more than we have already stretched the definition of reason and intelligence.
        Jensson 3y ago
        Why is a slime mold a river but a human isn't? Slime mold can predict temperature changes in its environment and react before it happens, that isn't something a river could do. So your statement just seems to be your bias thinking that a slime mold couldn't possible do any reasoning. Cells are much smarter than most thinks. Edit: Anyway, apparently slime molds can communicate what they learn by sharing those proteins. So they do have a language, it is like a primitive version of how human bodies cells communicate. So your point still stands, reasoning seems to go hand in hand with communication. If you can reason then it is worth it to share those conclusions with your friends and family. They also taught slime molds to cross a bridge for food, and it learned to do it. Then they got the slime mold to tell other slime molds and now those also knew how to cross the bridge. It is pretty cool that slime molds can be that smart. https://asknature.org/strategy/brainless-slime-molds-both-learn-and-teach/ https://asknature.org/strategy/brainless-slime-molds-both-le...
whoami_nr 3y ago
Why next-token prediction is enough for AGI - Ilya Sutskever - https://www.youtube.com/watch?v=YEUclZdj_Sc https://www.youtube.com/watch?v=YEUclZdj_Sc
- bamboozled 3y ago
  Ilya can feel the AGI
- passion__desire 3y ago
  We need planning. Imagine doing planning like this "drone in a forest" in a different domain like "migrate this project from python to rust". https://youtu.be/m89bNn6RFoQ?t=71 https://youtu.be/m89bNn6RFoQ?t=71
- lewhoo 3y ago
  I really don't think there's an explanation there. All Sutskever says is the idea is to ask a LLM to be the smartest being on the planet and it magically happens.
lkbm 3y ago
I guess it's an "assumption", but it's an assumption that's directly challenged in the article: > But of course we don’t actually care directly about performance on next-token prediction. The models already have humans beat on this loss function. We want to find out whether these scaling curves on next-token prediction actually correspond to true progress towards generality. And: > Why is it impressive that a model trained on internet text full of random facts happens to have a lot of random facts memorized? And why does that in any way indicate intelligence or creativity? And: > So it’s not even worth asking yet whether scaling will continue to work - we don’t even seem to have evidence that scaling has worked so far.
- berniedurfee 3y ago
  The conclusion that AGI will happen in 2040 is what I’m arguing against. I think 4020 is maybe a better estimate. I don’t feel like we’re anywhere close given that we can’t even yet meaningfully define reasoning or consciousness… or as another commenter put it, what is it that differentiates us so significantly from other animals.
__MatrixMan__ 3y ago
We do have systems that reason. Prolog comes to mind. It's a niche tool, used in isolated cases by relatively few people. I think that the other candidates are similar: proof assistants, physics simulators, computational chemistry and biology workflows, CAD, etc. When we get to the point where LLMs are able to invoke these tools for a user, even if that user has no knowledge of them, and are able to translate the results of that reasoning back into the user's context... That'll start to smell like AGI. The other piece, I think, is going to be improved cataloging of human reasoning. If you can ask a question and get the answer that a specialist who died fifty years ago would've given you because that specialist was a heavy AI user and so their specialty was available for query... That'll also start to smell like AGI. The foundations have been there for 30 years, LLMs are the paint job, the door handles, and the windows.
- cchance 3y ago
  Ya i feel like this issue is people think an LLM will someday "wake up" no, LLM's will just be multimodal and developed to use tools, and a software ecosystem around it will end up using the LLM to reason how to execute, basically the LLM will be the internal monologue of whatever the AGI looks like.
  - __MatrixMan__ 3y ago
    Agreed. I think it's more likely that we'll reach a point where their complexity is so great that no single person can usefully reason about their outputs in relation to their structure. Not so much a them waking up as an us falling asleep.
- lossolo 3y ago
  > We do have systems that reason. Prolog comes to mind. It's a niche tool, used in isolated cases by relatively few people. I think that the other candidates are similar: proof assistants, physics simulators, computational chemistry and biology workflows, CAD, etc. I think OP meant other definition of reason, because by your definition calculator can also reason. These are tools created by humans, that help them to reason about stuff by offloading calculations for some of the tasks. They do not reason on their own and they can't extrapolate. They are expert systems. http://www.incompleteideas.net/IncIdeas/BitterLesson.html http://www.incompleteideas.net/IncIdeas/BitterLesson.html
ctoth 3y ago
> I think there’s a huge assumption here that more LLM will lead to AGI. I'm not sure you realize this, but that is literally what this article was written to explore! I feel like you just autocompleted what you believe about large language models in this thread, rather than engaging with the article. Engagement might look like "I hold the skeptic position because of X, Y, and Z, but I see that the other position has some really good, hard-to-answer points." Instead, we just got the first thing that came to your mind talking about AI. In fact, am I talking to a person?
- jeremyjh 3y ago
  I feel like an LLM would do a much better job than GP.
  - berniedurfee 3y ago
    Lol, at least then your comment wouldn’t have bothered me so much!
    - deleted 3y ago
      [deleted]
    - jeremyjh 3y ago
      I'm sorry I hurt your feelings, it wasn't my intention. For what its worth, I actually think there is a good chance that you are right - that there is something missing in LLMs that still won't be present in bigger LLMs. I mostly meant that an LLM would be more organized around the source material and address specific points. I actually asked ChatGPT 4 to do so, and it produced the sort of reasonable but unremarkable stuff I've come to expect from it.
      - berniedurfee 3y ago
        Ah, gotcha, no worries, thanks for the reply!
- berniedurfee 3y ago

cortic 3y ago

If humans are basically evolved LLMs, which i think is likely; Reasoning will be an emergent property of LLMs within context with appropriate weights.

enieslobby 3y ago
Why do you think humans are basically evolved LLMs? Honest question, would love to read more about this viewpoint.
- cortic 3y ago
  Look at a year old baby, there is no logic, no reasoning, no real consciousness, just basic algorithms and data input ports. It takes ten years of data sets before these emergent properties start to develop, and another ten years before anything of value can be output.
  - berniedurfee 3y ago
    I strongly disagree. Kids, even infants, show a remarkable degree of sophistication in relation to an LLM. I admit that humans don’t progress much behaviorally, outside of intellect, past our teen years; we’re very instinct driven. But still, I think even very young children have a spark that’s something far beyond rote token generation. I think it’s typical human hubris (and clever marketing) to believe that we can invent AGI in less than 100 years when it took nature millions of years to develop. Until we understand consciousness, we won’t be able to replicate it and we’re a very long way from that leap.
    - visarga 3y ago
      Humans are not very smart, individually, and over a single lifetime. We become smart as a species in tens of millennia of gathering experience and sharing it through language. What LLMs learn is exactly the diff between primitive humans and us. It's such a huge jump a human alone can't make it. If we were smarter we should have figured out the germ theory of disease sooner, as we were dying from infections. So don't praise the learning abilities of little children, without language and social support they would not develop very much. We develop not just by our DNA and direct experiences but also by assimilating past experiences through language. It's a huge cache of crystallized intelligence from the past, without which we would not rule this planet. That's also why I agree LLMs are stalling because we can't quickly scale a few more orders of magnitude the organic text inputs. So there must the a different way to learn, and that is by putting AI in contact with environments and letting it do its own actions and learn from its mistakes just like us. I believe humans are "just" contextual language and action models. We apply language to understand, reason and direct our actions. We are GPTs with better feedback from outside, and optimized for surviving in this environment. That explains why we need so few samples to learn, the hard work has been done by many previous generations, brains are fit for their own culture. So the path forward will imply creating synthetic data, and then somehow evaluating the good from the bad. This will be task specific. For coding, we can execute tests. For math, we can use theorem provers to validate. But for chemistry we need simulations or labs. For physics, we need the particle accelerator to get feedback. But for games - we can just use the score - that's super easy, and already led to super-human level players like AlphaZero. Each topic has its own slowness and cost. It will be a slow grind ahead. And it can't be any other way, AI and AGI are not magic. They must use the scientific method to make progress just like us.
      - RandomLensman 3y ago
        Humans do more than just enhance predictive capabilities. It is also a very strong assumption that we are optimised for survival in many or all aspects (even unclear what that means). Some things could be totally incidental and not optimised. I find appeals to evolutionary optimisation very tricky and often fraught.
  - spzb 3y ago
    Have you ever met a baby? They're nothing like an LLM. For starters, they learn without using language. By one year old they've taught themselves to move around the physical world. They've started to learn cause and effect. They've learned where "they" end and "the rest of the world" begins. All an LLM has "learnt" is that some words are more likely to follow others.
    - visarga 3y ago
      Why not? We have multi-modal models as well. Not pure text.
  - timacles 3y ago
    This comment is just sad. What are you even talking about? Have you ever seen a 1 year old
- lumost 3y ago
  An LLM is simply a model which given a sequence, predicts the rest of the sequence. You can accurately describe any AGI or reasoning problem as an open domain sequence modeling problem. It is not an unreasonable hypothesis that brains evolved to solve a similar sequence modeling problem.
  - RandomLensman 3y ago
    In the broader sense that is tricky as accurate prediction is not always the right metric (otherwise we'd still be using epicycles for the planets).
    - lumost 3y ago
      It depends on the goal, epicycles don't tell you about the nature of heavenly bodies - but they do let you keep an accurate calendar for a reasonable definition of accurate. I'm not sure whether I need deep understanding of intelligence to gain economic benefit from AI.
  - timacles 3y ago
    > It is not an unreasonable hypothesis that brains evolved to solve a similar sequence modeling problem. The real world is random, requires making decisions on incomplete information in situations that have never happened before. The real world is not a sequence of tokens. Consciousness requires instincts in order to prioritize the endless streams of information. One thing people dont want to accept about any AI is that humans always have to tell it WHAT to think about. Our base reptilian brains are the core driver behind all behavior. AI cannot learn that
    - hutzlibu 3y ago
      "Consciousness requires instincts in order to prioritize the endless streams of information. " What if "instinct" is also just (pretrained) model weight? The human brain is very complex and far from understood and definitely does NOT work like a LLM. But it likely shares some core concepts. Neuronal networks were inspired by brain synapses after all.
- cortic 3y ago
  My first answer was a bit hasty, let me try again; We are clearly a product of our past experience (in LLMs this is called our datasets). If you go back to the beginning of our experiences, there is little identity, consciousness, or ability to reason. These things are learned indirectly, (in LLMs this is called an emergent property). We don't learn indiscriminately, evolved instinct, social pressure and culture guide and bias our data consumption (in LLMs this is called our weights). I can't think of any other way our minds could work, on some level they must function like a LLM, Language perhaps supplemented with general Data, but the principle being the same. Every new idea has been an abstraction or supposition of someones current dataset, which is why technological and general societal advancement has not been linear but closer to exponential.
  - Jensson 3y ago
    Genes encode a ton of behaviors, you can't just ignore that. Tabula rasa doesn't exist among humans. > If you go back to the beginning of our experiences, there is little identity, consciousness, or ability to reason. That is because babies brains aren't properly developed. There is nothing preventing a fully conscious being from being born, you see that among animals etc. A newborn foal is a fully functional animal for example. Genes encode the ability to move around, identify objects, follow other beings, collision avoidance etc.
    - cortic 3y ago
      >Genes encode a ton of behaviors, you can't just ignore that. I'm not ignoring that, I'm just saying that in LLMs we call these things weights. And i don't want to downplay the importance of weights, its probably a significant difference between us and other hominids. But even if you considered some behaviors to be more akin to the server or interface or preprocess in LLMs it still wouldn't detract from the fact that the vast majority of the things that make us autonomous logical sentient beings come about through a process that is very similar to the core workings of LLMs. I'm also not saying that all animal brains function like LLMs, though that's an interesting thought to consider.
tgv 3y ago
So you think we were originally trained on 300B tokens, those were then ingrained in our synapses, and then we evolved?
lossolo 3y ago
Reasoning and intelligence exists without language.
- cortic 3y ago
  You know i assumed that was true until right now. But I can't think of a single example of reason and intelligence existing without any form of language. Even insects have rudimentary language, and in fact reasoning and intelligence seem to scale with the complexity of language, both by species and within species.
  - Jensson 3y ago
    Do slime mold have a language? Slime mold can learn and adapt to environments, so it is intelligent and can do rudimentary reasoning, but I doubt it communicates that information to other slime molds. It is a very different kind of life form though so many things that applies to other complex being doesn't apply to them. Being a large single cell means that they learn by changing its proteins and other internals, very hard for us humans to reason about and understand since it is so alien compared to just having nerve cells with physical connections.
    - cortic 3y ago
      Not sure i would say a slime mold has reason and intelligence .. Or if i would then so does a river. Also i think that how it changes its proteins could be considered a language, without stretching the definition of language any more than we have already stretched the definition of reason and intelligence.
      - Jensson 3y ago
        Why is a slime mold a river but a human isn't? Slime mold can predict temperature changes in its environment and react before it happens, that isn't something a river could do. So your statement just seems to be your bias thinking that a slime mold couldn't possible do any reasoning. Cells are much smarter than most thinks. Edit: Anyway, apparently slime molds can communicate what they learn by sharing those proteins. So they do have a language, it is like a primitive version of how human bodies cells communicate. So your point still stands, reasoning seems to go hand in hand with communication. If you can reason then it is worth it to share those conclusions with your friends and family. They also taught slime molds to cross a bridge for food, and it learned to do it. Then they got the slime mold to tell other slime molds and now those also knew how to cross the bridge. It is pretty cool that slime molds can be that smart. https://asknature.org/strategy/brainless-slime-molds-both-learn-and-teach/ https://asknature.org/strategy/brainless-slime-molds-both-le...

whoami_nr 3y ago

Why next-token prediction is enough for AGI - Ilya Sutskever - https://www.youtube.com/watch?v=YEUclZdj_Sc https://www.youtube.com/watch?v=YEUclZdj_Sc

bamboozled 3y ago
Ilya can feel the AGI
passion__desire 3y ago
We need planning. Imagine doing planning like this "drone in a forest" in a different domain like "migrate this project from python to rust". https://youtu.be/m89bNn6RFoQ?t=71 https://youtu.be/m89bNn6RFoQ?t=71
lewhoo 3y ago
I really don't think there's an explanation there. All Sutskever says is the idea is to ask a LLM to be the smartest being on the planet and it magically happens.

lkbm 3y ago

I guess it's an "assumption", but it's an assumption that's directly challenged in the article: > But of course we don’t actually care directly about performance on next-token prediction. The models already have humans beat on this loss function. We want to find out whether these scaling curves on next-token prediction actually correspond to true progress towards generality. And: > Why is it impressive that a model trained on internet text full of random facts happens to have a lot of random facts memorized? And why does that in any way indicate intelligence or creativity? And: > So it’s not even worth asking yet whether scaling will continue to work - we don’t even seem to have evidence that scaling has worked so far.

berniedurfee 3y ago
The conclusion that AGI will happen in 2040 is what I’m arguing against. I think 4020 is maybe a better estimate. I don’t feel like we’re anywhere close given that we can’t even yet meaningfully define reasoning or consciousness… or as another commenter put it, what is it that differentiates us so significantly from other animals.

__MatrixMan__ 3y ago

We do have systems that reason. Prolog comes to mind. It's a niche tool, used in isolated cases by relatively few people. I think that the other candidates are similar: proof assistants, physics simulators, computational chemistry and biology workflows, CAD, etc. When we get to the point where LLMs are able to invoke these tools for a user, even if that user has no knowledge of them, and are able to translate the results of that reasoning back into the user's context... That'll start to smell like AGI. The other piece, I think, is going to be improved cataloging of human reasoning. If you can ask a question and get the answer that a specialist who died fifty years ago would've given you because that specialist was a heavy AI user and so their specialty was available for query... That'll also start to smell like AGI. The foundations have been there for 30 years, LLMs are the paint job, the door handles, and the windows.

cchance 3y ago
Ya i feel like this issue is people think an LLM will someday "wake up" no, LLM's will just be multimodal and developed to use tools, and a software ecosystem around it will end up using the LLM to reason how to execute, basically the LLM will be the internal monologue of whatever the AGI looks like.
- __MatrixMan__ 3y ago
  Agreed. I think it's more likely that we'll reach a point where their complexity is so great that no single person can usefully reason about their outputs in relation to their structure. Not so much a them waking up as an us falling asleep.
lossolo 3y ago
> We do have systems that reason. Prolog comes to mind. It's a niche tool, used in isolated cases by relatively few people. I think that the other candidates are similar: proof assistants, physics simulators, computational chemistry and biology workflows, CAD, etc. I think OP meant other definition of reason, because by your definition calculator can also reason. These are tools created by humans, that help them to reason about stuff by offloading calculations for some of the tasks. They do not reason on their own and they can't extrapolate. They are expert systems. http://www.incompleteideas.net/IncIdeas/BitterLesson.html http://www.incompleteideas.net/IncIdeas/BitterLesson.html

ctoth 3y ago

> I think there’s a huge assumption here that more LLM will lead to AGI. I'm not sure you realize this, but that is literally what this article was written to explore! I feel like you just autocompleted what you believe about large language models in this thread, rather than engaging with the article. Engagement might look like "I hold the skeptic position because of X, Y, and Z, but I see that the other position has some really good, hard-to-answer points." Instead, we just got the first thing that came to your mind talking about AI. In fact, am I talking to a person?

jeremyjh 3y ago
I feel like an LLM would do a much better job than GP.
- berniedurfee 3y ago
  Lol, at least then your comment wouldn’t have bothered me so much!
  - deleted 3y ago
    [deleted]
  - jeremyjh 3y ago
    I'm sorry I hurt your feelings, it wasn't my intention. For what its worth, I actually think there is a good chance that you are right - that there is something missing in LLMs that still won't be present in bigger LLMs. I mostly meant that an LLM would be more organized around the source material and address specific points. I actually asked ChatGPT 4 to do so, and it produced the sort of reasonable but unremarkable stuff I've come to expect from it.
    - berniedurfee 3y ago
      Ah, gotcha, no worries, thanks for the reply!
berniedurfee 3y ago