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On the Google search Web site, the "AI responses may include mistakes." weak disclaimer small print is also hidden behind the "Show more" button. When OpenAI l

• loa_in_ 1y ago
  It's a memory augmentation/information retrieval tool with flexible input and output interface.
• stavros 1y ago
  I really don't understand the view that it's a "parlor trick that looks like AI". If it's not "a thing that can write code", but instead just looks like a thing that can write code (but can actually write code), it can write code. All the "no true Scotsman" stuff about what it's doing behind the scenes is irrelevant, because we have no idea what human brains are doing behind the scenes either.
  • keiferski 1y ago
    It matters if we are making a distinction between essence and output. On the output side, it functionally doesn’t really have a difference. At least in terms of more abstract things like writing code. Although I would argue that the output AI makes still doesn’t match the complexity and nuance of an individual human being, though, and may never do so, simply because the AI is simulating embodiment and existing in the world. It might need to simulate an Earth equivalent to truly simulate a human’s personal output. In the essence side, it’s much more of a clear distinction. We have numerous ways of determining if a thing is human or not - biology, for one. It would take some serious sci-fi until we get to the point where an android is indistinguishable from a human on the cellular level.
    • ben_w 1y ago
      > Although I would argue that the output AI makes still doesn’t match the complexity and nuance of an individual human being, though LLMs are very good at nuance. Better than any human I've seen — so much so, I find it to be a tell. > We have numerous ways of determining if a thing is human or not - biology, for one. I don't care if the intelligence is human, I care if it's (1) (a) intelligent, (b) educated, and (2) has the ability to suffer or not so I know if it should have moral subject rights. 1a is slowly improving but we're guessing and experimenting: not really engineering intelligence, just scaling up the guesses that work OK. 1b was always easy, libraries fit "education" in isolation from the "intelligent" part of 1a. LLMs are good enough combination of (a) and (b) to be interesting, potentially even an economic threat, depending on how long the time-horizon between failures gets. 2 is pre-paradigmatic, we don't have enough understanding of the problem to ask the correct question — even ignoring AI for the moment, the same problem faces animal welfare (and why would the answer be the same for each of chimps, dogs, ravens, lobsters, and bees?) and even within humans on topics such as abortion, terminal stage of neurodegenerative conditions such as Alzheimer's, etc.
  • ben_w 1y ago
    Although I broadly agree, I wouldn't go quite as far as where you say: > All the "no true Scotsman" stuff about what it's doing behind the scenes is irrelevant, because we have no idea what human brains are doing behind the scenes either. Computers and transistors have a massive speed advantage over biological brains and synapses — literally, not metaphorically, the same ratio as the speed difference between how far you walk in a day and continental drift, with your brain being continental draft — which means they have the possibility of reading the entire Internet in a few weeks to months to learn what they know, and not the few tens to hundreds of millenia it would take a human. Unfortunately, the method by which they acquire information and knowledge, is sufficiently inefficient that they actually need to read the entire Internet to reach the skill level of someone who has only just graduated. This means I'm quite happy to *simultaneously* call them extremely useful, even "artificial general intelligence", and yet also agree with anyone who calls them "very very stupid". If we actually knew how our brains did this inteligence thing, we could probably make AI genuinely smart as well as absurdly fast.
  • neilv 1y ago
    Historically, there's been some discussion about that: https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room
  • hnlmorg 1y ago
    Their point wasn’t that it’s not useful. It’s that it isn’t artificial intelligence like the masses consider the term. You wouldn’t say Intellisense isn’t useful but you also wouldn’t call it “AI”. And what LLMs are like is basically Intellisense on steroids (probably more like a cocktail of speed and acid, but you get my point)
    • stavros 1y ago
      If you'd call k-means AI but you wouldn't call LLMs AI, I'm so far off that reasoning that I don't think we can agree.
      • hnlmorg 1y ago
        I’m not arguing that LLMs are not AI. The problem is that “AI” itself is a nonsense term. It’s been around since forever and used to describe a whole plethora of different behaviours. My point is that to the average user of Gemini or ChatGPT, LLMs are like AGI. Whereas they’re actually more closer to intellisense or text-completions. And this is where the problem lies. People will read the output of LLMs and think it has read content on the topic (which is correct) and then deduced an answer (which is technically incorrect). It also doesn’t help that OpenAI keep using terms like “reasoning” which sounds a lot like general intelligence. But it’s actually just a bunch of scales based on words. AI doesn’t understand any of the core concepts it is reasoning about. So its reasoning is akin to asking a Hollywood script writer to throw a bunch of medical terms together for a new medical drama. Sure the words might be correct on their own, but that doesn’t mean the sentences are correct. And any subject matter expert who watches a drama that features their specialist subject will tell you that there’s more to understanding a subject than simply knowing the words.
        • stavros 1y ago
          Ah OK, I see what you mean, by "AI" you mean "AGI", not what we call ML. It makes sense that way.
          • 1y ago
  • otabdeveloper4 1y ago
    LLMs can't write code. They don't have capacity to understand logical or temporal relationships, which is the core competency of coding. They can form syntactically valid strings in a formal language, which isn't the same thing as coding.
    • stavros 1y ago
      Hmm, I guess I better throw away all this working code they wrote, then.
      • otabdeveloper4 1y ago
        See my second paragraph. "Working" (aka syntactically correct) code is not the significant and difficult part of coding.
        • stavros 1y ago
          I don't care if the code works because it was formed because of temporal understanding or if it works because an LLM predicted enough tokens correctly, I care that it works.
    • throw5425 1y ago
      You can rationalize it any way you want. I don't care what they capacity they have, or if they syntactically whatever, or any academic thing. In practice, they work. That's all it matters.
      • otabdeveloper4 1y ago
        > In practice, they work. Not really. You'll understand once you start trying to use the code they produce seriously.