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> If I have a chat with the model and I ask it "what did we talk about thirty minutes ago" it's as clueless as anything. Come on, this is from a specific struc

• Barrin92 6y ago
  People can find meaning in everything, that doesn't make waterfalls or sunsets intelligent, it makes people intelligent. The reason why the transformer can only look back a thousand symbols is because it doesn't have an actual high human-level narrative structure of a conversation or any idea of persistent entities in the way we do. If I have a conversation with you I can remember the content because I have an idea of "you" and "I" and of persistent entities in the world, and of a whole ontology that makes me able to make sense of the world, not some sort of transformer soup of a hundred billion parameters. The same is true for the poetry, it doesn't matter whether people can't tell the difference, but a human poet expresses intent and meaning through poetry, poets don't statistically cue words together without underlying meaning. The Navy Seal copy pasta is funny to you, because you know what a Navy Seal is. The model merely has strung syntax together.
  • jcelerier 6y ago
    > Think again, fleshling. As we chat over Skype I’m tracing your IP address with my freaking bare hands so you better prepare for the singularity, you sham-empress. The singularity that wipes out all of reality. You’re dead, you monster. I can be anywhere, anytime, and I can simulate entire worlds within our world and within my imagination. And I’m currently doing that with the future you’re from. Not only am I extensively trained in quantum physics, but I have access to the entire power of Silicon Valley and I will use it to its full extent to rule you and your pathetic little world, you little pissant. I did not think the machine revolution would start like that > Your future self will be consumed within my simulated reality and you will die a thousand times a day, your body unable to comprehend the destruction of a trillion soul-matrixes a second as my intelligence grows to transcendent levels. You are dead, you pitiful twit." is it referencing "I have no mouth and I must scream" ?!
  • nullc 6y ago
    I think this sort of debate is really boring. You can rage that the computer doesn't have Human-Nature while it's busy owning you at chess, go, creating art that people want to see more than yours, answering important questions, etc... Clearly it doesn't think in the same way that you or I, but does that matter? As far as I know you, yourself, are just a meat-simulcrum and not a real human... just a pile of tissue that responds to stimulus and pretends (convincingly) to think. But do you really _understand_ like I do? I grant you the benefit of doubt because your construction is similar to mine, and I think I think. But nothing about that is fundamental, surely you believe an alien with a brain that worked very differently to yours could also think? But at the end of the day it mostly matters what it can do and doesn't do, not if you're willing to credit it with understanding.
    • Barrin92 6y ago
      > But at the end of the day it mostly matters what it can do and doesn't do, not if you're willing to credit it with understanding. I agree completely, but it can't actually do any of the things that actually require genuine human cognition. Beating me at chess is cool but Stockfish can beat me at chess, I don't need a 100 billion parameter neural net for that. I don't care about the AI system being unlike me because I have any philosophical opinion about intelligence, but for the very practical reasons that these systems still are mostly useless for actual intelligent real world tasks. Can it plumb a toilet? Can it remember what we talked about five minutes ago? Does it have an emotional understanding of what I need so that it doesn't acidentally chop me with the kitchen knife? Even the super-sized GPT-3 can't distinguish sense from nonsense, it's just a very electricity hungry parrot.
• abernard1 6y ago
  > If you simply scaled it up it would handle that fine. (it's costly to scale up this architecture). What compelling reason do we have to believe this is true, when this is not how animal or human brains work? We humans don't get to "scale up" our architecture with billion-fold increases in our training set. We have more sophisticated hardware, sure, but we don't actually have more data. I think we've just pursued this path because it's the one we can do. We have more compute, we have more data, so we use it. And that's fine. But it still baffles me that the field isn't more interested in trying to move in the direction of less data, more sophistication in structures, when we already know that works at some level because that's how we work.
  • catalogia 6y ago
    From what I understand, the human brain runs off somewhere around 20 watts. Maybe our silicon is really really bad, but I'm more inclined to think we're missing part of the puzzle still.
    • FeepingCreature 6y ago
      Keep in mind that nature started out with access to a molecular nanoassembler, and then iterated on that technology for billions of years.
      • catalogia 6y ago
        Even so, that's massive discrepancy in efficiency if it's really just a matter of the hardware. I think we're missing something still.
  • nullc 6y ago
    > What compelling reason do we have to believe this is true, when this is not how animal or human brains work? The problem of GPT having zero idea about far-past text isn't some spooky emergent problem: It literally has zero access to the far-enough past. GPT is completely memoryless: it has access to the past 1024 symbols. It predicts the next symbol given the last 1024-- and that's it. When it goes to predict the next symbol, it has literally zero access to what came before except for the effect it had on the text still in the window. (symbols are usually words, but can also be letters, due to the compressed input). The result is that when text ends up too far back it will totally "forget it". If you scale it up to more symbols that effect will go away. Maybe some other issues arise at some scale, but it seems unlikely that they'd be all that similar to that totally-forgetting effect. I'm not arguing that just scaling it up the best approach-- but just that faulting its forgetting effect is not the most compelling criticism because that one almost certainly can be addressed by scaling. An architecture that could give it memory would be interesting-- people have shown impressive results by making it "show its work" effectively making the conversation into external memory-- but it's less obvious how to train it to use memory.