4 ms·

>If ability to learn is limited to one modality, such as language, then that indicates a lack of generality. A good test for whether an AI system is in the same

>If ability to learn is limited to one modality, such as language, then that indicates a lack of generality. A good test for whether an AI system is in the same ballpark as a human in learning ability, aka intelligence, would be whether it can (at run-time) learn language itself, from a blank slate start, when running in a suitable environment. So a transformer ? Run-time? Seems like an arbitrary distinction to me. Because humans function in a certain way, every learning system no matter how capable must function in the same way to be 'truly' intelligent ?

HarHarVeryFunny 1mo ago
If a system wants to claim human-level intelligence, then yes. It's not a very high bar - even a rat has the basic ability to learn.
- famouswaffles 1mo ago
  The mechanism is irrelevant if the results are similar. No, it doesn't have to be implemented the same way as a human to qualify as a human-level intelligence. That would be silly.
  - HarHarVeryFunny 1mo ago
    How is text-based memorization going to let you learn non-linguistic skills, whether animal/human level or beyond (based on new data senses)? How is text-based memorization going to substitute for learning? The two are not the same. Perhaps this is more applicable to robotics than a text generator, but I also doubt an LLM could learn text-based skills like programming or math if it had not been pre-trained on them via SGD & RL, and had to instead rely on some poor-man's-learning context-based recall instead. What else can't it learn? How is the LLM intern, the "drop-in replacement remote worker" going to do on day #2? Instead of pretending that an LLM can be human-level, or super-human, or become generalist, why not just admit that this is not the final form of AI. An LLM is not an animal/human-like intelligence, it is something different - a language model, with it's own strengths and weaknesses. Despite all the AGI hype, an LLM seems to have more in common with a pre-trained single-purpose system like AlphaGo than a brain, but with the rubric/reward-based policy function baked into the weights. In another 10-20 years some new idea, hopefully more brain-like, will have superseded LLMs and they will indeed be labelled as "LLMs" as the AI/AGI label becomes attached to the new more brain-like creative intelligence. Perhaps it'll be sooner than 10-20 years, but I doubt it given the current 10-year fixation with LLMs which doesn't appear to be slowing down anytime soon. Perhaps Sutskever is working on something a bit different?
    - famouswaffles 1mo ago
      >How is text-based memorization going to let you learn non-linguistic skills I don't know. How is Astra a step change in computer use and spatial reasoning to the extent it can play games, paint good looking stuff with e.g canva and a whole number of other things ? >How is text-based memorization going to substitute for learning? The two are not the same. Of course if you call it something else then you can say it's not the same. >How is the LLM intern, the "drop-in replacement remote worker" going to do on day #2? Just fine I imagine ? ICL and the memory tools around a harness are pretty good. I'm not sure what sort of magic you're expecting from the human, but they're not getting any improvement in that time frame a frozen transformer can't match. >Instead of pretending that an LLM can be human-level, or super-human, or become generalist, why not just admit that this is not the final form of AI. It doesn't seem like I'm the one pretending here. >Despite all the AGI hype, an LLM seems to have more in common with a pre-trained single-purpose system like AlphaGo than a brain, but with the rubric/reward-based policy function baked into the weights. If you say so. >Perhaps it'll be sooner than 10-20 years, but I doubt it given the current 10-year fixation with LLMs which doesn't appear to be slowing down anytime soon. The architecture that keeps delivering results isn't slowing down ? You don't say. There's no shortage of people, even researchers, who for one reason or the other are convinced we are in need of some paradigm shift. But guess what? Talk is cheap. You beat the current paradigm or you don't.
      - HarHarVeryFunny 1mo ago
        > How is Astra a step change in computer use and spatial reasoning to the extent it can play games and paint good looking stuff with e.g canva ? Presumably because of pre-release training, because some alien outside of the model, armed with the reinforcement learning algorithm, came in and programmed its weights. > The architecture that keeps delivering results isn't slowing down ? You don't say Sure, nothing wrong with that, as long as you don't misrepresent the limitations of the approach. > There's no shortage of people, even researchers, who for one reason or the other are convinced we are in need of some paradigm shift. > But guess what? Talk is cheap. You beat the current paradigm or you don't. Do you seriously think that Meta never scaled JEPA ? The idea has not been taken very far, so what is there to scale? It's not a complete cognitive architecture. So far it's also been using a pre-trained transformer as the learning component, which makes it of limited interest. The animal intelligence approach, even in it's most fledgling form (that you would apparently dismiss), requires a complete agentic architecture, including new learning algorithms and generative behavior, before it can be compared to LLMs. We know that, done right, our brain architecture is more capable than an LLM, so even if any hypothetical attempts to reproduce it were not highly performant, we know that the idea itself is sound. You might compare with Uszkoreit's initial poor-performing implementation of his new language model architecture - should he have given up?

HarHarVeryFunny 1mo ago

If a system wants to claim human-level intelligence, then yes. It's not a very high bar - even a rat has the basic ability to learn.

famouswaffles 1mo ago
The mechanism is irrelevant if the results are similar. No, it doesn't have to be implemented the same way as a human to qualify as a human-level intelligence. That would be silly.
- HarHarVeryFunny 1mo ago
  How is text-based memorization going to let you learn non-linguistic skills, whether animal/human level or beyond (based on new data senses)? How is text-based memorization going to substitute for learning? The two are not the same. Perhaps this is more applicable to robotics than a text generator, but I also doubt an LLM could learn text-based skills like programming or math if it had not been pre-trained on them via SGD & RL, and had to instead rely on some poor-man's-learning context-based recall instead. What else can't it learn? How is the LLM intern, the "drop-in replacement remote worker" going to do on day #2? Instead of pretending that an LLM can be human-level, or super-human, or become generalist, why not just admit that this is not the final form of AI. An LLM is not an animal/human-like intelligence, it is something different - a language model, with it's own strengths and weaknesses. Despite all the AGI hype, an LLM seems to have more in common with a pre-trained single-purpose system like AlphaGo than a brain, but with the rubric/reward-based policy function baked into the weights. In another 10-20 years some new idea, hopefully more brain-like, will have superseded LLMs and they will indeed be labelled as "LLMs" as the AI/AGI label becomes attached to the new more brain-like creative intelligence. Perhaps it'll be sooner than 10-20 years, but I doubt it given the current 10-year fixation with LLMs which doesn't appear to be slowing down anytime soon. Perhaps Sutskever is working on something a bit different?
  - famouswaffles 1mo ago
    >How is text-based memorization going to let you learn non-linguistic skills I don't know. How is Astra a step change in computer use and spatial reasoning to the extent it can play games, paint good looking stuff with e.g canva and a whole number of other things ? >How is text-based memorization going to substitute for learning? The two are not the same. Of course if you call it something else then you can say it's not the same. >How is the LLM intern, the "drop-in replacement remote worker" going to do on day #2? Just fine I imagine ? ICL and the memory tools around a harness are pretty good. I'm not sure what sort of magic you're expecting from the human, but they're not getting any improvement in that time frame a frozen transformer can't match. >Instead of pretending that an LLM can be human-level, or super-human, or become generalist, why not just admit that this is not the final form of AI. It doesn't seem like I'm the one pretending here. >Despite all the AGI hype, an LLM seems to have more in common with a pre-trained single-purpose system like AlphaGo than a brain, but with the rubric/reward-based policy function baked into the weights. If you say so. >Perhaps it'll be sooner than 10-20 years, but I doubt it given the current 10-year fixation with LLMs which doesn't appear to be slowing down anytime soon. The architecture that keeps delivering results isn't slowing down ? You don't say. There's no shortage of people, even researchers, who for one reason or the other are convinced we are in need of some paradigm shift. But guess what? Talk is cheap. You beat the current paradigm or you don't.
    - HarHarVeryFunny 1mo ago
      > How is Astra a step change in computer use and spatial reasoning to the extent it can play games and paint good looking stuff with e.g canva ? Presumably because of pre-release training, because some alien outside of the model, armed with the reinforcement learning algorithm, came in and programmed its weights. > The architecture that keeps delivering results isn't slowing down ? You don't say Sure, nothing wrong with that, as long as you don't misrepresent the limitations of the approach. > There's no shortage of people, even researchers, who for one reason or the other are convinced we are in need of some paradigm shift. > But guess what? Talk is cheap. You beat the current paradigm or you don't. Do you seriously think that Meta never scaled JEPA ? The idea has not been taken very far, so what is there to scale? It's not a complete cognitive architecture. So far it's also been using a pre-trained transformer as the learning component, which makes it of limited interest. The animal intelligence approach, even in it's most fledgling form (that you would apparently dismiss), requires a complete agentic architecture, including new learning algorithms and generative behavior, before it can be compared to LLMs. We know that, done right, our brain architecture is more capable than an LLM, so even if any hypothetical attempts to reproduce it were not highly performant, we know that the idea itself is sound. You might compare with Uszkoreit's initial poor-performing implementation of his new language model architecture - should he have given up?