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> What a stupid future. Machines which make errors being “corrected” by machines which make errors in a death spiral. An unbelievable waste of figurative and li

> What a stupid future. Machines which make errors being “corrected” by machines which make errors in a death spiral. An unbelievable waste of figurative and literal energy. Humans are machines which make errors. Somehow, we got to the moon. The suggestion that errors just mindlessly compound and that there is no way around it, is what's stupid.

nuancebydefault 2y ago
Exactly my thought. Humans can correct humans. Machines can correct, or at least point to failures in the product of, machines.
reverius42 2y ago
To err is human. To err at scale is AI.
- danielmarkbruce 2y ago
  To err at scale isn't unique to AI. We don't say "no software, it can err at scale".
  - trod123 2y ago
    It is by will alone that I set my mind in motion. It is by the juice of Sapho that thoughts acquire speed, the lips become stained, the stains become a warning...
  - munk-a 2y ago
    CEOs embracing the marginal gains of LLMs by dumping billions into it are certainly great examples of humans erring at scale.
    - fuzztester 2y ago
      yep, nano mega.
- fuzztester 2y ago
  err, "hallucinate" is the euphemism you're looking for. ;)
  - arkh 2y ago
    I don't like the use of hallucinate. It implies that LLM have some kind of model of reality and some times get confused. They don't have any kind of model of anything, they cannot "hallucinate", they can only output wrong results.
    - fuzztester 2y ago
      yeah, i get you. it was a joke, though. that "hallucinate" term is a marketing gimmick to make it seem to the gullible that this "AI" (i.e. LLMs) can actually think, which is flat out BS. as many others have said here on hn, those who stand to benefit a lot from this are the ones promoting this bullcrap idea (that they (LLMs) are intelligent). greater fool theory. picks and shovels. etc. In detective or murder novels, the cliche is "look for the woman". https://en.m.wikipedia.org/wiki/Cherchez_la_femme https://en.m.wikipedia.org/wiki/Cherchez_la_femme in this case, "follow the money" is the translation, i.e. who really benefits (the investors and founders, the few), as opposed to who is grandly proclaimed to be the beneficiary (us, the many).
      - fuzztester 2y ago
        s/grand/grandiose/g from a search for grand vs grandiose: When it comes to bigness, there's grand and then there's grandiose. Both words can be used to describe something impressive in size, scope, or effect, but while grand may lend its noun a bit of dignity (i.e., “we had a grand time”), grandiose often implies a whiff of pretension. https://www.merriam-webster.com/dictionary/grandiose https://www.merriam-webster.com/dictionary/grandiose
    - fuzztester 2y ago
      >They don't have any kind of model of anything, they cannot "hallucinate", they can only output wrong results. it's even more fundamental than that. even if they had any model, they would not be able to think. thinking requires consciousness. only humans and some animals have it. maybe plants too. machines? no way, jose.
- cetu86 2y ago
  I fear that we'll see a lot of humans err at scale next Tuesday. Global warming is another example of human error at scale.
  - fuzztester 2y ago
    >next Tuesday. USA (s)election, I guess.
latexr 2y ago
> Humans are machines Even if we accept the premise (seeing humans as machines is literally dehumanising and a favourite argument of those who exploit them), not all machines are created equal. Would you use a bicycle to fill your taxes? > Somehow, we got to the moon Quite hand wavey. We didn’t get to the Moon by reading a bunch of text from the era then probabilistically joining word fragments, passing that around the same funnel a bunch of times, then blindly doing what came out, that’s for sure. > The suggestion that errors just mindlessly compound and that there is no way around it Is one that you made up, as that was not my argument.
- danielmarkbruce 2y ago
  LLMs are a lot better at a lot of things than a lot of humans. We got to the moon using a large number of systems to a) avoid errors where possible and b) build in redundancies. Even an LLM knows this and knew what the statement meant: https://chatgpt.com/share/6722e04f-0230-8002-8345-5d2eba2e7db6 https://chatgpt.com/share/6722e04f-0230-8002-8345-5d2eba2e7d... Putting "corrected" in quotes and saying "death spiral" implies error compounding. https://chatgpt.com/share/6722e19c-7f44-8002-8614-a560620b37e0 https://chatgpt.com/share/6722e19c-7f44-8002-8614-a560620b37... These LLMs seem so smart.
  - philipwhiuk 2y ago
    > LLMs are a lot better at a lot of things than a lot of humans. Sure, I'm really poor painter, Midjourney is better than me. Are they better than a human trained for that task, on that task? That's the real question. And I reckon the answer is currently no.
    - danielmarkbruce 2y ago
      The real question is can they do a good enough job quickly and cheaply to be valuable. ie, quick and cheap at some level of quality is often "better". Many people are using them in the real world because they can do in 1 minute what might take them hours. I personally save a couple hours a day using ChatGPT.
  - 2y ago
kelnos 2y ago
The difference is that when we humans learn from our errors, we learn how to make them less often. LLMs get their errors fed back into them and become more confident that their wrong code is right. I'm not saying that's completely unsolvable, but that does seem to be how it works today.
- danielmarkbruce 2y ago
  That isn't the way they work today. LLMs can easily find errors in outputs they themselves just produced. Start adding different prompts, different models and you get all kinds of ways to catch errors. Just like humans.
  - philipwhiuk 2y ago
    > LLMs can easily find errors in outputs they themselves just produced. No. LLMs can be told that there was an error and produce an alternative answer. In fact LLMs can be told there was an error when there wasn't one and produce an alternative answer.
    - danielmarkbruce 2y ago
      You don't use LLMs. https://chatgpt.com/share/6722e41d-6b20-8002-8cbb-3012cd9179dd https://chatgpt.com/share/6722e41d-6b20-8002-8cbb-3012cd9179...
      - cdchn 2y ago
        Do you believe that the LLM understands what it is saying and is applying the logic that you interprets from its response, or do you think its simply repeating similar patterns of words its seen associated with the question you presented it?
        danielmarkbruce 2y ago
        If you take the time to build an (S?)LM yourself, you'll realize it's neither of these. "Understands" is an ill-defined term, as is "applying logic". But a LLM is not "simply" doing anything. It's extremely complex and sophisticated. Once you go from tokens into high-dimensional embeddings... it seems these models (with enough training) figure out how all the concepts go together. I'd suggest reading the word2vec paper first, then think about how attention works. You'll come to the conclusion these things are likely to be able to beat humans at almost everything.
deleted 2y ago
[deleted]
goatlover 2y ago
Machines are intelligently designed for a purpose. Humans are born and grow up, have social lives, a moral status and are conscious, and are ultimately the product of a long line of mindless evolution that has no goals. Biology is not design. It's way messier.
openrisk 2y ago
> Humans are machines which make errors. Indeed, and one of the most interesting errors some human machines are making is hallucinating false analogies.
- danielmarkbruce 2y ago
  It wasn't an analogy.
deleted 2y ago
[deleted]

nuancebydefault 2y ago

Exactly my thought. Humans can correct humans. Machines can correct, or at least point to failures in the product of, machines.

reverius42 2y ago

To err is human. To err at scale is AI.

danielmarkbruce 2y ago
To err at scale isn't unique to AI. We don't say "no software, it can err at scale".
- trod123 2y ago
  It is by will alone that I set my mind in motion. It is by the juice of Sapho that thoughts acquire speed, the lips become stained, the stains become a warning...
- munk-a 2y ago
  CEOs embracing the marginal gains of LLMs by dumping billions into it are certainly great examples of humans erring at scale.
  - fuzztester 2y ago
    yep, nano mega.
fuzztester 2y ago
err, "hallucinate" is the euphemism you're looking for. ;)
- arkh 2y ago
  I don't like the use of hallucinate. It implies that LLM have some kind of model of reality and some times get confused. They don't have any kind of model of anything, they cannot "hallucinate", they can only output wrong results.
  - fuzztester 2y ago
    yeah, i get you. it was a joke, though. that "hallucinate" term is a marketing gimmick to make it seem to the gullible that this "AI" (i.e. LLMs) can actually think, which is flat out BS. as many others have said here on hn, those who stand to benefit a lot from this are the ones promoting this bullcrap idea (that they (LLMs) are intelligent). greater fool theory. picks and shovels. etc. In detective or murder novels, the cliche is "look for the woman". https://en.m.wikipedia.org/wiki/Cherchez_la_femme https://en.m.wikipedia.org/wiki/Cherchez_la_femme in this case, "follow the money" is the translation, i.e. who really benefits (the investors and founders, the few), as opposed to who is grandly proclaimed to be the beneficiary (us, the many).
    - fuzztester 2y ago
      s/grand/grandiose/g from a search for grand vs grandiose: When it comes to bigness, there's grand and then there's grandiose. Both words can be used to describe something impressive in size, scope, or effect, but while grand may lend its noun a bit of dignity (i.e., “we had a grand time”), grandiose often implies a whiff of pretension. https://www.merriam-webster.com/dictionary/grandiose https://www.merriam-webster.com/dictionary/grandiose
  - fuzztester 2y ago
    >They don't have any kind of model of anything, they cannot "hallucinate", they can only output wrong results. it's even more fundamental than that. even if they had any model, they would not be able to think. thinking requires consciousness. only humans and some animals have it. maybe plants too. machines? no way, jose.
cetu86 2y ago
I fear that we'll see a lot of humans err at scale next Tuesday. Global warming is another example of human error at scale.
- fuzztester 2y ago
  >next Tuesday. USA (s)election, I guess.

latexr 2y ago

> Humans are machines Even if we accept the premise (seeing humans as machines is literally dehumanising and a favourite argument of those who exploit them), not all machines are created equal. Would you use a bicycle to fill your taxes? > Somehow, we got to the moon Quite hand wavey. We didn’t get to the Moon by reading a bunch of text from the era then probabilistically joining word fragments, passing that around the same funnel a bunch of times, then blindly doing what came out, that’s for sure. > The suggestion that errors just mindlessly compound and that there is no way around it Is one that you made up, as that was not my argument.

danielmarkbruce 2y ago
LLMs are a lot better at a lot of things than a lot of humans. We got to the moon using a large number of systems to a) avoid errors where possible and b) build in redundancies. Even an LLM knows this and knew what the statement meant: https://chatgpt.com/share/6722e04f-0230-8002-8345-5d2eba2e7db6 https://chatgpt.com/share/6722e04f-0230-8002-8345-5d2eba2e7d... Putting "corrected" in quotes and saying "death spiral" implies error compounding. https://chatgpt.com/share/6722e19c-7f44-8002-8614-a560620b37e0 https://chatgpt.com/share/6722e19c-7f44-8002-8614-a560620b37... These LLMs seem so smart.
- philipwhiuk 2y ago
  > LLMs are a lot better at a lot of things than a lot of humans. Sure, I'm really poor painter, Midjourney is better than me. Are they better than a human trained for that task, on that task? That's the real question. And I reckon the answer is currently no.
  - danielmarkbruce 2y ago
    The real question is can they do a good enough job quickly and cheaply to be valuable. ie, quick and cheap at some level of quality is often "better". Many people are using them in the real world because they can do in 1 minute what might take them hours. I personally save a couple hours a day using ChatGPT.
- 2y ago

kelnos 2y ago

The difference is that when we humans learn from our errors, we learn how to make them less often. LLMs get their errors fed back into them and become more confident that their wrong code is right. I'm not saying that's completely unsolvable, but that does seem to be how it works today.

danielmarkbruce 2y ago
That isn't the way they work today. LLMs can easily find errors in outputs they themselves just produced. Start adding different prompts, different models and you get all kinds of ways to catch errors. Just like humans.
- philipwhiuk 2y ago
  > LLMs can easily find errors in outputs they themselves just produced. No. LLMs can be told that there was an error and produce an alternative answer. In fact LLMs can be told there was an error when there wasn't one and produce an alternative answer.
  - danielmarkbruce 2y ago
    You don't use LLMs. https://chatgpt.com/share/6722e41d-6b20-8002-8cbb-3012cd9179dd https://chatgpt.com/share/6722e41d-6b20-8002-8cbb-3012cd9179...
    - cdchn 2y ago
      Do you believe that the LLM understands what it is saying and is applying the logic that you interprets from its response, or do you think its simply repeating similar patterns of words its seen associated with the question you presented it?
      - danielmarkbruce 2y ago
        If you take the time to build an (S?)LM yourself, you'll realize it's neither of these. "Understands" is an ill-defined term, as is "applying logic". But a LLM is not "simply" doing anything. It's extremely complex and sophisticated. Once you go from tokens into high-dimensional embeddings... it seems these models (with enough training) figure out how all the concepts go together. I'd suggest reading the word2vec paper first, then think about how attention works. You'll come to the conclusion these things are likely to be able to beat humans at almost everything.

deleted 2y ago

[deleted]

goatlover 2y ago

Machines are intelligently designed for a purpose. Humans are born and grow up, have social lives, a moral status and are conscious, and are ultimately the product of a long line of mindless evolution that has no goals. Biology is not design. It's way messier.

openrisk 2y ago

> Humans are machines which make errors. Indeed, and one of the most interesting errors some human machines are making is hallucinating false analogies.

danielmarkbruce 2y ago
It wasn't an analogy.

deleted 2y ago

[deleted]