5 ms·

I was going to say "so you believe the LLM's don't have the capacity to understand" but then I realized that the precise language would be something like "the p

I was going to say "so you believe the LLM's don't have the capacity to understand" but then I realized that the precise language would be something like "the presence of photons in this human's retinas in patterns encoding statements about LLM's having understanding correlates to the activation of neuron signaling chains corresponding to, and emission of, muscle activations engaging keyboard switches, which produce patterns of 'no they don't' with high frequency." The critiques of mental state applied to the LLM's are increasingly applicable to us biologicals, and that's the philosophical abyss we're staring down.

xigency 1y ago
This only applies to people who understand how computers and computer programs work, because someone who doesn't externalize their thinking process would never ascribe human elements of consciousness to inanimate materials. Certainly many ancient people worshiped celestial objects or crafted idols by their own hands and ascribed to them powers greater than themselves. That doesn't really help in the long run compared to taking personal responsibility for one's own actions and motives, the best interests of their tribe or community, and taking initiative to understand the underlying cause of mysterious phenomena.
- deleted 1y ago
  [deleted]
mjburgess 1y ago
No it's not. He gave you modal conditions on "understanding", he said: predicting the syntax of valid programs, and their operational semantics, ie., the behaviour of the computer as it runs. I would go much further than this; but this is a de minimus criteria that the LLM already fails. What zealots eventually discover is that they can hold their "fanatical proposition" fixed in the face of all opposition to the contrary, by tearing down the whole edifice of science, knowledge, and reality itself. If you wish to assert, against any reasonable thought, that the sky is a pink dome you can do so -- first that our eyes are broken, and then, eventually that we live in some paranoid "philosophical abyss" carefully constructed to permit your paranoia. This abursidty is exhausting, and I'd wish one day to find fanatics who'd realise it quickly and abate it -- but alas, I have never. If you find yourself hollowing-out the meaning of words to the point of making no distinctions, denying reality to reality itself, and otherwise arriving at a "philosophical abyss" be aware that it is your cherished propositions which are the maddness and nothing else. Here: no, the LLM does not understand. Yes, we do. It is your job to begin from reasonable premises and abduce reasonable theories. If you do not, you will not.
- famouswaffles 1y ago
  >No it's not. He gave you modal conditions on "understanding", he said: predicting the syntax of valid programs, and their operational semantics, ie., the behaviour of the computer as it runs. LLMs are perfectly capable of predicting the behavior of programs. You don't have to take my word for it, you can test it yourself. So he gave modal conditions they already satisfy. Can I conclude they understand now ? >If you find yourself hollowing-out the meaning of words to the point of making no distinctions, denying reality to reality itself, and otherwise arriving at a "philosophical abyss" be aware that it is your cherished propositions which are the maddness and nothing else. The only people denying reality are those who insist that it is not 'real' understanding and yet cannot distinguish this 'real' from 'fake' property in any verifiable manner, the very definition of an invented property. Your argument boils down to 'I think it's so absurd so it cannot be so'. That's the best you can do ? Do you genuinely think that's a remotely convincing argument ?
  - kannanvijayan 1y ago
    LLMs are reasonably competent at surfacing the behaviour of simple programs when the behaviour of those programs is a relatively straightforward structural extension of enough of its training set that it's managed to correlate together. It's very clear that LLMs lack understanding when you use them for anything remotely sophisticated. I say this as someone who leverages them extensively on a daily basis - mostly for development. They're very powerful tools and I'm grateful for their existence and the force multiplier they represent. Try to get one to act as a storyteller and the limitations in understanding glare out. You try to goad some creativity and character out of it and it spits out generally insipid recombinations of obvious tropes. In programming, I use AI strictly as a auto-complete extension. Even in that limited context, the latest models make trivial mistakes in certain circumstances that reveal their lack of understanding. The ones that stand out are the circumstances where the local change to make is very obvious and simple, but the context of the code is something that the ML hasn't seen before. In those cases, I see them slapping together code that's semantically wrong in the local context, but pattern matches well against the outer context. It's very clear that the ML doesn't even have a SIMPLE understanding of the language semantics, despite having been trained on presumably multiple billions of lines of code from all sorts of different programming languages. If you train a human against half a dozen programming languages, you can readily expect by the end of that training that they will, all by themselves, simply through mastering the individual languages, have constructed their own internal generalized models of programming languages as a whole, and would become aware of some semantic generalities. And if I had asked that human to make that same small completion for me, they would have gotten it right. They would have understood that the language semantics are a stronger implicit context compared to the surrounding syntax. MLs just don't do that. They're very impressive tools, and they are a strong step forward toward some machine model of understanding (sophisticated pattern matching is likely a fundamental prerequisite for understanding), but ascribing understanding to them at this point is jumping the gun. They're not there yet.
shafyy 1y ago
Countering the argument that LLMs are just gloriefied probability machines and do not undertand or think with "how do you know humans are not the same" has been the biggest achievement of AI hypemen (and yes, it's mostly men). Of course, now you can say "how do you know that our brains are not just efficient computers that run LLMs", but I feel like the onus of proof lies on the makers of this claim, not on the other side. It is very likely that human intelligence is not just autocomplete on crack, given all we know about neuroscience so far.
- mlinhares 1y ago
  BuT iT CoUlD Be, cAn YoU PrOvE ThAT IT is NOt? I'm having a great experience using Cursor, but i don't feel like trying to overhype it, it just makes me tired to see all this hype. Its a great tool, makes me more productive, nothing beyond that.
  - shafyy 1y ago
    That's great for you. I'm not diminishing your experience or taking it away. I think we agree on the hype.
- BobbyTables2 1y ago
  I’ve come to realize AI works as well as it does because it was trained extensively on the same kinds of things people normally ask. So, it already has the benefit of vast amounts of human responses. Of course, ask it a PhD level question and it will confidently hallucinate more than Beavis & Butthead. It really is a damn glorified autocomplete, unfortunately very useful as a search engine replacement.
  - uh_uh 1y ago
    The LLM is a glorified autocomplete in as much as you are a glorified replicator. Yes, it was trained on autocomplete but that doesn't say much about what capabilities might emerge.
    - 1y ago

xigency 1y ago

This only applies to people who understand how computers and computer programs work, because someone who doesn't externalize their thinking process would never ascribe human elements of consciousness to inanimate materials. Certainly many ancient people worshiped celestial objects or crafted idols by their own hands and ascribed to them powers greater than themselves. That doesn't really help in the long run compared to taking personal responsibility for one's own actions and motives, the best interests of their tribe or community, and taking initiative to understand the underlying cause of mysterious phenomena.

deleted 1y ago
[deleted]

mjburgess 1y ago

No it's not. He gave you modal conditions on "understanding", he said: predicting the syntax of valid programs, and their operational semantics, ie., the behaviour of the computer as it runs. I would go much further than this; but this is a de minimus criteria that the LLM already fails. What zealots eventually discover is that they can hold their "fanatical proposition" fixed in the face of all opposition to the contrary, by tearing down the whole edifice of science, knowledge, and reality itself. If you wish to assert, against any reasonable thought, that the sky is a pink dome you can do so -- first that our eyes are broken, and then, eventually that we live in some paranoid "philosophical abyss" carefully constructed to permit your paranoia. This abursidty is exhausting, and I'd wish one day to find fanatics who'd realise it quickly and abate it -- but alas, I have never. If you find yourself hollowing-out the meaning of words to the point of making no distinctions, denying reality to reality itself, and otherwise arriving at a "philosophical abyss" be aware that it is your cherished propositions which are the maddness and nothing else. Here: no, the LLM does not understand. Yes, we do. It is your job to begin from reasonable premises and abduce reasonable theories. If you do not, you will not.

famouswaffles 1y ago
>No it's not. He gave you modal conditions on "understanding", he said: predicting the syntax of valid programs, and their operational semantics, ie., the behaviour of the computer as it runs. LLMs are perfectly capable of predicting the behavior of programs. You don't have to take my word for it, you can test it yourself. So he gave modal conditions they already satisfy. Can I conclude they understand now ? >If you find yourself hollowing-out the meaning of words to the point of making no distinctions, denying reality to reality itself, and otherwise arriving at a "philosophical abyss" be aware that it is your cherished propositions which are the maddness and nothing else. The only people denying reality are those who insist that it is not 'real' understanding and yet cannot distinguish this 'real' from 'fake' property in any verifiable manner, the very definition of an invented property. Your argument boils down to 'I think it's so absurd so it cannot be so'. That's the best you can do ? Do you genuinely think that's a remotely convincing argument ?
- kannanvijayan 1y ago
  LLMs are reasonably competent at surfacing the behaviour of simple programs when the behaviour of those programs is a relatively straightforward structural extension of enough of its training set that it's managed to correlate together. It's very clear that LLMs lack understanding when you use them for anything remotely sophisticated. I say this as someone who leverages them extensively on a daily basis - mostly for development. They're very powerful tools and I'm grateful for their existence and the force multiplier they represent. Try to get one to act as a storyteller and the limitations in understanding glare out. You try to goad some creativity and character out of it and it spits out generally insipid recombinations of obvious tropes. In programming, I use AI strictly as a auto-complete extension. Even in that limited context, the latest models make trivial mistakes in certain circumstances that reveal their lack of understanding. The ones that stand out are the circumstances where the local change to make is very obvious and simple, but the context of the code is something that the ML hasn't seen before. In those cases, I see them slapping together code that's semantically wrong in the local context, but pattern matches well against the outer context. It's very clear that the ML doesn't even have a SIMPLE understanding of the language semantics, despite having been trained on presumably multiple billions of lines of code from all sorts of different programming languages. If you train a human against half a dozen programming languages, you can readily expect by the end of that training that they will, all by themselves, simply through mastering the individual languages, have constructed their own internal generalized models of programming languages as a whole, and would become aware of some semantic generalities. And if I had asked that human to make that same small completion for me, they would have gotten it right. They would have understood that the language semantics are a stronger implicit context compared to the surrounding syntax. MLs just don't do that. They're very impressive tools, and they are a strong step forward toward some machine model of understanding (sophisticated pattern matching is likely a fundamental prerequisite for understanding), but ascribing understanding to them at this point is jumping the gun. They're not there yet.

shafyy 1y ago

Countering the argument that LLMs are just gloriefied probability machines and do not undertand or think with "how do you know humans are not the same" has been the biggest achievement of AI hypemen (and yes, it's mostly men). Of course, now you can say "how do you know that our brains are not just efficient computers that run LLMs", but I feel like the onus of proof lies on the makers of this claim, not on the other side. It is very likely that human intelligence is not just autocomplete on crack, given all we know about neuroscience so far.

mlinhares 1y ago
BuT iT CoUlD Be, cAn YoU PrOvE ThAT IT is NOt? I'm having a great experience using Cursor, but i don't feel like trying to overhype it, it just makes me tired to see all this hype. Its a great tool, makes me more productive, nothing beyond that.
- shafyy 1y ago
  That's great for you. I'm not diminishing your experience or taking it away. I think we agree on the hype.
BobbyTables2 1y ago
I’ve come to realize AI works as well as it does because it was trained extensively on the same kinds of things people normally ask. So, it already has the benefit of vast amounts of human responses. Of course, ask it a PhD level question and it will confidently hallucinate more than Beavis & Butthead. It really is a damn glorified autocomplete, unfortunately very useful as a search engine replacement.
- uh_uh 1y ago
  The LLM is a glorified autocomplete in as much as you are a glorified replicator. Yes, it was trained on autocomplete but that doesn't say much about what capabilities might emerge.
  - 1y ago