8 ms·

The only way to reduce hallucinations in both humans and LLMs is to increase their general intelligence and their knowledge of the world.

by p1esk 3y ago

FpUser 3y ago
You post amounts to: in order to be smarter I need to increase my smartness. Great insight.
- lazide 3y ago
  I think it's more subtly misleading - to be smarter, I need more knowledge. But knowledge != smart, knowledge == informed, or educated. And the problem is more - how can an LLM tell us it doesn't know something instead of just making up good sounding, but completely delusional answers. Which arguably isn't about being smart, and is only tangentially about less or more (external) knowledge really. It's about self-knowledge. Going down the first path is about knowing everything (in the form of facts, usually). Which hey, maybe? Going down the second path is about knowing oneself. Which hey, maybe? They are not the same.
  - p1esk 3y ago
    Hallucinations are an interesting problem - in both humans and statistical models. If we asked an average person 500 years ago how the universe works, they would have confidently told you the earth is flat and it rests on a giant turtle (or something like that). And that there are very specific creatures - angels and demons who meddle in human affairs. And a whole a lot more which has no grounding in reality. How did we manage to reduce that type of hallucination?
    - ottaborra 3y ago
      by taking steps to verify everything that was said
    - Anotheroneagain 3y ago
      The expression "Urbi et orbi" goes back longer than that. It's a modern myth that they didn't know the world was a sphere.
  - ebcode 3y ago
    >> And the problem is more - how can an LLM tell us it doesn't know something instead of just making up good sounding, but completely delusional answers. I think the mistake lies in the belief that the LLM "knows" things. As humans, we have a strong tendency to anthropomorphize. And so, when we see something behave in a certain way, we imagine that thing to be doing the same thing that we do when we behave that way. I'm writing, and the machine is also writing, but what I'm doing when I write is very different from what the machine does when it writes. So the mistake is to say, or think, "I think when I write, so the machine must also think when it writes." We probably need to address the usage of the word "hallucination", and maybe realize that the LLM is always hallucinating. Not: "When it's right, it's right, but when it's wrong, it's hallucinating." It's more like, "Sweet! Some of these hallucinations are on point!"
    - p1esk 3y ago
      I think when I write, so the machine must also think when it writes. What is it exactly you do when you “think”? And how is it different from what LLM does? Not saying it’s not different, just asking.
      - Jensson 3y ago
        There are probably many, but the most glaring one is that LLMs has to write a word every time it thinks, meaning it can't solve a problem before it starts to write down the solution. That is an undeniable limitation of current architectures, it means that the way the LLM answers your question also matches its thinking process, meaning that you have to trigger a specific style of response if you want it to be smart with its answer.
        p1esk 3y ago
        Ok, so how do humans solve a problem? Isn’t it also a sequential, step by step process, even if not expressed explicitly in words? What if instead of words a model would show you images to solve a problem? Would it change anything?
robrenaud 3y ago
A smart bullshit artist who loves the sound of their own voice is going to generate more hallucinations than a less smart, more humble, more self aware person. Making LLMs more knowledgeable is great (more data, bigger models, yay!), but there are other avenues of plausible attack as well. Enabling LLMs to know when they have veered off distribution might work. That is, the LLM doesn't have to know more of the world, it just has to know what it knows and stay there. A person who says "I don't know" is a lot more valuable than an overzealous one who spouts nonsense confidently. Encouraging an LLM to say that there is a disagreement about a topic rather than picking one lane is also a valuable way forward.
- p1esk 3y ago
  I agree with your points but they are orthogonal to mine. A smart person might be more likely to say “I don’t know” than a stupid person. Also, a smart bullshit artist in your example does not hallucinate - he knows what he’s doing.
renegade-otter 3y ago
It's statistical prediction. LLMs do not "understand" the world by definition. Ask an image generator to make "an image of a woman sitting on a bus and reading a book". Images will be either a horror show or at best full of weird details that do not match the real world - because it's not how any of this works. It's a glorified auto-complete that only works due to the massive amounts of data it is trained on. Throw in any complex interactions it has not seen in the training data and it's all over.
- deleted 3y ago
  [deleted]
- sshumaker 3y ago
  You’re being downvoted because this is a hot take that isn’t supported by evidence. I just tried exactly that with dalle-3 and it worked well. More to the point, it’s pretty clear LLMs do form a model of the world, that’s exactly how they reason about things. There was some good experiments on this a while back - check out the Othello experiment. https://thegradient.pub/othello/ https://thegradient.pub/othello/
  - godelski 3y ago
    It's a hot take, but it is supported by a ton of evidence.
- HDThoreaun 3y ago
  I think the situation is a lot more complicated than youre making it out to be. GPT4 for example can be very good at tasks it has not seen in the training data. The philosophy of mind is much more open ended and less understood than you seem to think.
  - godelski 3y ago
    > not seen in the training data Do you have some evidence for this?
  - renegade-otter 3y ago
Anotheroneagain 3y ago
Your understanding is distorted by dealing mostly with psychotic people. Iron poisoning (well within the supposed healthy levels) and lead deficiency cause schizophrenia; normal people look childlike or "not intelligent" to the affected.
- AlexeyBelov 3y ago
  Do you have a source for this? It seems like most of your comments mention the same things but nothing is substantiated.
  - Anotheroneagain 3y ago
    I don't think it's possible to summarize it with one source. Some are my own experiments. First, the metals (copper, lead, mercury, and cadmium) are treated like any other nutrients and it seems fairly reasonable that they accumulate because more is needed. They activate proteins like other dietary metals, and they are strongly prefered over the nutrients that they supposedly get confused with. Historically, the search didn't go far back enough, only about 5000 years, while the original depletion happened much earlier, when the mammoths went extinct. An extensive study claims that it was actually the cause. (DOI: 10.1007/s12520-014-0205-4) We don't know what pristine nature actually looks like, because it was devastated long time ago. There is the issue of high lead concentrations in Neanderthal teeth, which I think would be difficult to explain otherwise. Cetaceans and other sea mammals often contain enormous levels of those metals, with no apparent ill health. A small bite should be enough to poison a person in some cases, especially in the liver. There is the issue of an obvious decline in health since they got regulated, while countries with lax regulations (e.g. Japan) seem to be spared. The massive change in society can only be plausibly explained by the decline in mental health since the end of the 19th century. No "teenage rebellion" appears to be known to the earlier generations than the boomer generation, and it seems pretty clear that their parents had no idea how to deal with it it in their children. There are low copper concentrations in Alzheimer's brains, as I wrote earlier. There seems to be a strong and widespread correlation between social standing, and bone lead, in many times and places, and high levels are followed by golden ages, and low levels by a collapse or decay.

The only way to reduce hallucinations in both humans and LLMs is to increase their general intelligence and their knowledge of the world.

by p1esk 3y ago

The only way to reduce hallucinations in both humans and LLMs is to increase their general intelligence and their knowledge of the world.

FpUser 3y ago

You post amounts to: in order to be smarter I need to increase my smartness. Great insight.

lazide 3y ago
I think it's more subtly misleading - to be smarter, I need more knowledge. But knowledge != smart, knowledge == informed, or educated. And the problem is more - how can an LLM tell us it doesn't know something instead of just making up good sounding, but completely delusional answers. Which arguably isn't about being smart, and is only tangentially about less or more (external) knowledge really. It's about self-knowledge. Going down the first path is about knowing everything (in the form of facts, usually). Which hey, maybe? Going down the second path is about knowing oneself. Which hey, maybe? They are not the same.
- p1esk 3y ago
  Hallucinations are an interesting problem - in both humans and statistical models. If we asked an average person 500 years ago how the universe works, they would have confidently told you the earth is flat and it rests on a giant turtle (or something like that). And that there are very specific creatures - angels and demons who meddle in human affairs. And a whole a lot more which has no grounding in reality. How did we manage to reduce that type of hallucination?
  - ottaborra 3y ago
    by taking steps to verify everything that was said
  - Anotheroneagain 3y ago
    The expression "Urbi et orbi" goes back longer than that. It's a modern myth that they didn't know the world was a sphere.
- ebcode 3y ago
  >> And the problem is more - how can an LLM tell us it doesn't know something instead of just making up good sounding, but completely delusional answers. I think the mistake lies in the belief that the LLM "knows" things. As humans, we have a strong tendency to anthropomorphize. And so, when we see something behave in a certain way, we imagine that thing to be doing the same thing that we do when we behave that way. I'm writing, and the machine is also writing, but what I'm doing when I write is very different from what the machine does when it writes. So the mistake is to say, or think, "I think when I write, so the machine must also think when it writes." We probably need to address the usage of the word "hallucination", and maybe realize that the LLM is always hallucinating. Not: "When it's right, it's right, but when it's wrong, it's hallucinating." It's more like, "Sweet! Some of these hallucinations are on point!"
  - p1esk 3y ago
    I think when I write, so the machine must also think when it writes. What is it exactly you do when you “think”? And how is it different from what LLM does? Not saying it’s not different, just asking.
    - Jensson 3y ago
      There are probably many, but the most glaring one is that LLMs has to write a word every time it thinks, meaning it can't solve a problem before it starts to write down the solution. That is an undeniable limitation of current architectures, it means that the way the LLM answers your question also matches its thinking process, meaning that you have to trigger a specific style of response if you want it to be smart with its answer.
      - p1esk 3y ago
        Ok, so how do humans solve a problem? Isn’t it also a sequential, step by step process, even if not expressed explicitly in words? What if instead of words a model would show you images to solve a problem? Would it change anything?

robrenaud 3y ago

A smart bullshit artist who loves the sound of their own voice is going to generate more hallucinations than a less smart, more humble, more self aware person. Making LLMs more knowledgeable is great (more data, bigger models, yay!), but there are other avenues of plausible attack as well. Enabling LLMs to know when they have veered off distribution might work. That is, the LLM doesn't have to know more of the world, it just has to know what it knows and stay there. A person who says "I don't know" is a lot more valuable than an overzealous one who spouts nonsense confidently. Encouraging an LLM to say that there is a disagreement about a topic rather than picking one lane is also a valuable way forward.

p1esk 3y ago
I agree with your points but they are orthogonal to mine. A smart person might be more likely to say “I don’t know” than a stupid person. Also, a smart bullshit artist in your example does not hallucinate - he knows what he’s doing.

renegade-otter 3y ago

It's statistical prediction. LLMs do not "understand" the world by definition. Ask an image generator to make "an image of a woman sitting on a bus and reading a book". Images will be either a horror show or at best full of weird details that do not match the real world - because it's not how any of this works. It's a glorified auto-complete that only works due to the massive amounts of data it is trained on. Throw in any complex interactions it has not seen in the training data and it's all over.

deleted 3y ago
[deleted]
sshumaker 3y ago
You’re being downvoted because this is a hot take that isn’t supported by evidence. I just tried exactly that with dalle-3 and it worked well. More to the point, it’s pretty clear LLMs do form a model of the world, that’s exactly how they reason about things. There was some good experiments on this a while back - check out the Othello experiment. https://thegradient.pub/othello/ https://thegradient.pub/othello/
- godelski 3y ago
  It's a hot take, but it is supported by a ton of evidence.
HDThoreaun 3y ago
I think the situation is a lot more complicated than youre making it out to be. GPT4 for example can be very good at tasks it has not seen in the training data. The philosophy of mind is much more open ended and less understood than you seem to think.
- godelski 3y ago
  > not seen in the training data Do you have some evidence for this?
- renegade-otter 3y ago

Anotheroneagain 3y ago

Your understanding is distorted by dealing mostly with psychotic people. Iron poisoning (well within the supposed healthy levels) and lead deficiency cause schizophrenia; normal people look childlike or "not intelligent" to the affected.

AlexeyBelov 3y ago
Do you have a source for this? It seems like most of your comments mention the same things but nothing is substantiated.
- Anotheroneagain 3y ago
  I don't think it's possible to summarize it with one source. Some are my own experiments. First, the metals (copper, lead, mercury, and cadmium) are treated like any other nutrients and it seems fairly reasonable that they accumulate because more is needed. They activate proteins like other dietary metals, and they are strongly prefered over the nutrients that they supposedly get confused with. Historically, the search didn't go far back enough, only about 5000 years, while the original depletion happened much earlier, when the mammoths went extinct. An extensive study claims that it was actually the cause. (DOI: 10.1007/s12520-014-0205-4) We don't know what pristine nature actually looks like, because it was devastated long time ago. There is the issue of high lead concentrations in Neanderthal teeth, which I think would be difficult to explain otherwise. Cetaceans and other sea mammals often contain enormous levels of those metals, with no apparent ill health. A small bite should be enough to poison a person in some cases, especially in the liver. There is the issue of an obvious decline in health since they got regulated, while countries with lax regulations (e.g. Japan) seem to be spared. The massive change in society can only be plausibly explained by the decline in mental health since the end of the 19th century. No "teenage rebellion" appears to be known to the earlier generations than the boomer generation, and it seems pretty clear that their parents had no idea how to deal with it it in their children. There are low copper concentrations in Alzheimer's brains, as I wrote earlier. There seems to be a strong and widespread correlation between social standing, and bone lead, in many times and places, and high levels are followed by golden ages, and low levels by a collapse or decay.