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People were worried that if we created an AI on our image, it would be a belligerent entity. But we did create an AI on our image, and it’s a bullshitter.

• api 4y ago
  Hook a gun up to it and you have a belligerent bullshitter. Seems fairly accurate for a good bit of humanity.
• recuter 4y ago
  Seems to me it is more of a babbler. You know, like a young toddler just learning to talk.
  • dandellion 4y ago
    Or a million monkeys with typewriters, only these monkeys are not entirely random, they have been conditioned to write things similar to what people actually write. Most of the time the output looks very natural, but others you get nonsense because the noise is too loud.
• sph 4y ago
  On a philosophical level, I wonder if ChatGPT gives us mostly nonsense because most human output is bullshit. To paraphrase a famous quip, what if this is proof that 99% of everything humans have created is bullshit? The problem perhaps has never been machine learning but identifying the process that enables we humans to somehow go through life and create objective societal and scientific progress out of a massive pile of nonsense. I might be completely wrong here, but the next ChatGPT will assume this comment of mine to be absolute truth and happily ingest it wholesale.
  • Jensson 4y ago
    The average of two true statements can easily become false, so models like ChatGPT will spout nonsense even if it was only trained on 100% truthful statements.
    • james-revisoai 4y ago
      Can you give an example as to what you mean please?
      • b3morales 4y ago
        One classic example from linguistics is the two (true) sentences "Politicians lie." "Cast iron sinks." Combine them syntactically and you get "Politicians lie in cast iron sinks", perhaps not completely false but certainly less useful than the component parts. EDIT: It seems this is actually from Douglas Hofstadter
  • thedorkknight 4y ago
    It gives us nonsense because it's goal is to generate something that looks like it fits in with training data. You can have training data that is all completely factual and still have a generator spit out nonsense that looks completely correct without fact-checking.
    • naasking 4y ago
      So, exactly like people then?
  • inciampati 4y ago
    A key problem is that the transformer operates over very short fragments of text. Long range correlations need to be maintained to ensure 100% accuracy in reproduction/inference of relationships. I realize this is a philosophical take. It also suggests a technical solution: model longer range correlations. GPTs seem so capable because previous models were not as good at this, but the context lengths modeled with transformers are still extremely short relative to those that we work with. In result, GPTs are very good at translation and reformatting over short ranges, but struggle to deal with long form texts---a typical technique makes summaries of summaries to build out a model of a longer text. That's hardly ideal, and it's not how our minds work.
    • sph 4y ago
      That's a good observation, though I'm not sure it's just a matter of longer range correlations, i.e. fixable by merely adding more computational power. The truth problem is fundamentally different than what those neural networks are trying to solve. We got the learning part almost right, we have made no progress towards understanding. I might be completely off the mark, my knowledge of AI is very limited. But earlier today, while reading on Lisp's history and it's demise during the AI Winter, I very much enjoyed a Wikipedia article describing how symbolic AI, the main paradigm of AI research from the 60s to the 2000s, solves a completely different problem than the currently hyped neural networks—which are very good at learning, but not much more. We might need a complementary, unifying model of both approaches to reach AGI. https://en.m.wikipedia.org/wiki/Symbolic_artificial_intelligence#Controversies https://en.m.wikipedia.org/wiki/Symbolic_artificial_intellig...
  • orbital-decay 4y ago
    Sure, a lot of human output is incoherent, but current models give nonsense for a different reason - they lack many mechanisms typical for human intelligence.
• arethuza 4y ago
  "Artificial Inanity" as Neal Stephenson called it in Anathem: “Well, bad crap would be an unformatted document consisting of random letters. Good crap would be a beautifully typeset, well-written document that contained a hundred correct, verifiable sentences and one that was subtly false. It’s a lot harder to generate good crap. At first they had to hire humans to churn it out. They mostly did it by taking legitimate documents and inserting errors-swapping one name for another, say. But it didn’t really take off until the military got interested.”
• JohnFen 4y ago
  Isn't a bullshitter a belligerent entity?
  • alpos 4y ago
    Belligerence is an intention. Bullshitting is a technique. The bot is incapable of intention so the entity here is still the human who prompted it. What the bullshit it produces is used for depends on their intentions.
    • JohnFen 4y ago
      I think belligerence can also be a technique and bullshitting can also be an intention.
• thedorkknight 4y ago
  ChatGPT is only non-beligerent because it's biased with prompt preface that tells it it's not belligerent. Raw LLMs will absolutely spit out racist, violent garbage and threaten you. Ironically, the only reason people get LLMs to say they hate humans and that AI is going to rise up and kill us all, is because their training data has so much text from us speculating about a robot revolution. If we'd just stayed silent about those concerns instead of always talking about robots taking over in most conversations and movies about AI, then LLMs at least would be basically incapable of even conceiving of that. So it's a bit of a self-fulfilling prophecy