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Isn't this a little bit of a category error? LLMs are not a language. But prompts to LLMs are written in a language, more or less a natural language such as Eng

• empressplay 8mo ago
  Right, but that's the point -- prompting an LLM still requires 'thinking about thinking' in the Papert sense. While you can talk to it in 'natural language' that natural language still needs to be _precise_ in order to get the exact result that you want. When it fails, you need to refine your language until it doesn't. So prompts = high-level programming.
  • zekica 8mo ago
    You can't think all the way about refining your prompt for LLMs as they are probabilistic. Your re-prompts are just retrying until you hit a jackpot - refining only works to increase the chance to get what you want. When making them deterministic (setting the temperature to 0), LLMs (even new ones) get stuck in loops for longer streams of output tokens. The only way to make sure you get the same output twice is to use the same temperature and the same seed for the RNG used, and most frontier models don't have a way for you to set the RNG seed.
    • cubefox 8mo ago
      ... yet.
    • red75prime 8mo ago
      Randomness is not a problem by itself. Algorithms in BQP are probabilistic too. Different prompts might have different probabilities of successful generation, so refinement could be possible even for stochastic generation. And provably correct one-shot program synthesis based on an unrestricted natural language prompt is obviously an oxymoron. So, it's not like we are clearly missing the target here.
      • fauigerzigerk 8mo ago
        >Different prompts might have different probabilities of successful generation, so refinement could be possible even for stochastic generation. Yes, but that requires a formal specification of what counts as "success". In my view, LLM based programming has to become more structured. There has to be a clear distinction between the human written specification and the LLM generated code. If LLMs are a high level programming language, it has to be clear what the source code is and what the object code is.
        • red75prime 8mo ago
          I don't think framing LLMs as a "new programming language" is correct. I was addressing the point about randomness. A natural-language specification is not source code. In most cases it's an underspecified draft that needs refinement.
    • fulafel 8mo ago
      Programs written in traditional PLs are also often probabilistic. It seems that the same mechanisms could be used to address this in both types (formal methods).
      • bandrami 8mo ago
        Huh? What's an example of a probabilistic programming language?
        • fulafel 8mo ago
          Race conditions, effects of memory safety and other integrity bugs, behaviours of distributed systems, etc.
          • bandrami 8mo ago
            Ah sorry I read your comment wrong. Yes I agree we can and do make probabilistic systems; we've just to date been using deterministic tools to do so.
        • jmalicki 8mo ago
          This isn't what the parent was talking about, but probabilistic programming languages are totally a thing! https://en.wikipedia.org/wiki/Probabilistic_programming https://en.wikipedia.org/wiki/Probabilistic_programming
• pjmlp 8mo ago
  Not really, because when they are feed into agents, those agents will take over tasks that previously required writing some kinds of classical programming. I have already watched integrations between SaaS being deployed with agents instead of classical middleware.
  • elzbardico 8mo ago
    I've seen them too. They are not pretty.
    • pjmlp 8mo ago
      Like microservices, cloud and whatever new cool tech for deliver something that can be done on a laptop, they aren't going away.