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I reiterate: > This is assuming by "deterministic," you mean the same thing I said about programming language implementations being "controllable, reproducible

I reiterate: > This is assuming by "deterministic," you mean the same thing I said about programming language implementations being "controllable, reproducible, and well-defined." If you mean it produces random but same results for the same inputs, then you haven't made any meaningful points. "Determinism" is a word that you brought up in response to my comment, which I charitably interpreted to mean the same thing I was originally talking about. Also, it's 100% correct to analyze things based on its fundamental properties. It's absurd to criticize people for assuming 2 + 2 = 4 because "continual progress" might make it 5 in the future.

soulofmischief 2y ago
What are these fundamental properties you speak of? 8 years ago this was all a pipe dream. Are you claiming to know what the next 8 years of transformer development will look like?
- soraminazuki 2y ago
  That LLMs are by definition models of human speech and have no cognitive capabilities. There is no sound logic behind what LLMs spit out, and will stay that way because it merely mimics its training data. No amount of vague future transformers will transform away how the underlying technology works. But let's say we have something more than an LLM, that still wouldn't make natural languages a good replacement for programming languages. This is because natural languages are, as the article mentions, imprecise. It just isn't a good tool. And no, transformers can't change how languages work. It can only "recontextualize," or as some people might call it, "hallucinate."
  - soulofmischief 2y ago
    Citation needed. Modern transformers are much, much more than just speech models. Precisely define "cognitive capabilities", and provide proof as to why neural models cannot ever mimic these cognitive capabilities. > But let's say we have something more than an LLM We do. Modern multi-modal transformers. > This is because natural languages are, as the article mentions, imprecise Two different programmers can take a well-enough defined spec and produce two separate code bases that may (but not must) differ in implementation, while still having the exact same interfaces and testable behavior. > And no, transformers can't change how languages work. It can only "recontextualize," or as some people might call it, "hallucinate." You don't understand recontextualization if you think it means hallucination. Or vice versa. Hallucination is about returning incorrect or false data. Recontextualization is akin to decompression, and can be lossy or "effectively" lossless (within a probabilistic framework; again, the interfaces and behavior just need to match)
    - soraminazuki 2y ago
      The burden of proof is on the one making extraordinary claims. There has been no indication from any credible source that LLMs are able to think for itself. Human brains are still a mystery. I don't know why you can so confidently claim that neural models can mimic what humanity knows so little about. > Two different programmers can take a well-enough defined spec and produce two separate code bases that may (but not must) differ in implementation, while still having the exact same interfaces and testable behavior. Imagine doing that without a rigid and concise way of expressing your intentions. Or trying again and again in vain to get the LLM produce the software that you want. Or debugging it. Software development will become chaotic and lot less fun in that hypothetical future.
      - soulofmischief 2y ago
        The burden of proof is not on the person telling you that a citation is needed when claiming that something is impossible. Vague phrases mean nothing. You need to prove that there are these fundamental limitations, and you have not done that. I have been careful to express that this is all theoretical and possible, you on the other hand are claiming it is impossible; a much stronger claim, which deserves a strong argument. > I don't know why you can so confidently claim that neural models can mimic what humanity knows so little about. I'm simply not ruling it out. But you're confidently claiming that it's flat out never going to happen. Do you see the difference?
        soraminazuki 2y ago
        You can't just make extraordinary claims [1][2], demand rigorous citation for those who question it, even going as far as to word lawyer the definition of cognition [3], and reverse the burden of proof. All the while providing no evidence beyond what essentially boils down to "anything and everything is possible." > Vague phrases mean nothing. Yep, you made my point. > Do you see the difference? Yes, I clearly state my reasons. I can confidently claim that LLMs are no replacements for programming languages for two reasons. 1. Programming languages are superior to natural languages for software development. Nothing on earth, not even transformers, can make up for the unavoidable lack of specificity in the hypothetical natural language programs without making things up because that's how logic works. 2. LLMs, as impressive as they may be, are fundamentally computerized parrots so you can't understand or control how they generate code unlike with compilers like GCC which provides all that through source code. This is just stating the obvious here, no surprises. [1]: https://news.ycombinator.com/item?id=43567653 https://news.ycombinator.com/item?id=43567653 [2]: https://news.ycombinator.com/item?id=43568699 https://news.ycombinator.com/item?id=43568699 [3]: https://news.ycombinator.com/item?id=43585498 https://news.ycombinator.com/item?id=43585498

soulofmischief 2y ago

What are these fundamental properties you speak of? 8 years ago this was all a pipe dream. Are you claiming to know what the next 8 years of transformer development will look like?

soraminazuki 2y ago
That LLMs are by definition models of human speech and have no cognitive capabilities. There is no sound logic behind what LLMs spit out, and will stay that way because it merely mimics its training data. No amount of vague future transformers will transform away how the underlying technology works. But let's say we have something more than an LLM, that still wouldn't make natural languages a good replacement for programming languages. This is because natural languages are, as the article mentions, imprecise. It just isn't a good tool. And no, transformers can't change how languages work. It can only "recontextualize," or as some people might call it, "hallucinate."
- soulofmischief 2y ago
  Citation needed. Modern transformers are much, much more than just speech models. Precisely define "cognitive capabilities", and provide proof as to why neural models cannot ever mimic these cognitive capabilities. > But let's say we have something more than an LLM We do. Modern multi-modal transformers. > This is because natural languages are, as the article mentions, imprecise Two different programmers can take a well-enough defined spec and produce two separate code bases that may (but not must) differ in implementation, while still having the exact same interfaces and testable behavior. > And no, transformers can't change how languages work. It can only "recontextualize," or as some people might call it, "hallucinate." You don't understand recontextualization if you think it means hallucination. Or vice versa. Hallucination is about returning incorrect or false data. Recontextualization is akin to decompression, and can be lossy or "effectively" lossless (within a probabilistic framework; again, the interfaces and behavior just need to match)
  - soraminazuki 2y ago
    The burden of proof is on the one making extraordinary claims. There has been no indication from any credible source that LLMs are able to think for itself. Human brains are still a mystery. I don't know why you can so confidently claim that neural models can mimic what humanity knows so little about. > Two different programmers can take a well-enough defined spec and produce two separate code bases that may (but not must) differ in implementation, while still having the exact same interfaces and testable behavior. Imagine doing that without a rigid and concise way of expressing your intentions. Or trying again and again in vain to get the LLM produce the software that you want. Or debugging it. Software development will become chaotic and lot less fun in that hypothetical future.
    - soulofmischief 2y ago
      The burden of proof is not on the person telling you that a citation is needed when claiming that something is impossible. Vague phrases mean nothing. You need to prove that there are these fundamental limitations, and you have not done that. I have been careful to express that this is all theoretical and possible, you on the other hand are claiming it is impossible; a much stronger claim, which deserves a strong argument. > I don't know why you can so confidently claim that neural models can mimic what humanity knows so little about. I'm simply not ruling it out. But you're confidently claiming that it's flat out never going to happen. Do you see the difference?
      - soraminazuki 2y ago
        You can't just make extraordinary claims [1][2], demand rigorous citation for those who question it, even going as far as to word lawyer the definition of cognition [3], and reverse the burden of proof. All the while providing no evidence beyond what essentially boils down to "anything and everything is possible." > Vague phrases mean nothing. Yep, you made my point. > Do you see the difference? Yes, I clearly state my reasons. I can confidently claim that LLMs are no replacements for programming languages for two reasons. 1. Programming languages are superior to natural languages for software development. Nothing on earth, not even transformers, can make up for the unavoidable lack of specificity in the hypothetical natural language programs without making things up because that's how logic works. 2. LLMs, as impressive as they may be, are fundamentally computerized parrots so you can't understand or control how they generate code unlike with compilers like GCC which provides all that through source code. This is just stating the obvious here, no surprises. [1]: https://news.ycombinator.com/item?id=43567653 https://news.ycombinator.com/item?id=43567653 [2]: https://news.ycombinator.com/item?id=43568699 https://news.ycombinator.com/item?id=43568699 [3]: https://news.ycombinator.com/item?id=43585498 https://news.ycombinator.com/item?id=43585498