5 ms·

Intelligence is a capability, not a level of knowledge, and in discussing AI vs human intelligence, or human vs dog, it is perhaps better to regard it as a spec

Intelligence is a capability, not a level of knowledge, and in discussing AI vs human intelligence, or human vs dog, it is perhaps better to regard it as a species-specific capability, not an individual-specific one. Was the genius or dumb person really born with different levels of learning ability, or were they just raised differently: nature vs nurture ? The "intelligence" of one species vs another comes down to differences in cognitive architecture, ultimately reflected in ability to learn and predict/infer. Intelligence, as a capability, not IQ test score, is best regarded as ability to learn from experience and use that learning to accurately predict future outcomes, ranging from passive observation, to the outcome of one's own actions, to the ability to reason. Comparing the intelligence (not knowledge) of different AI system to humans should therefore be assessed by comparing their ability to learn and use what they have learnt. An LLM is what it is - a language model, not a learning system. It's really an expert system of sorts, highly capable in terms of what it can infer based on the knowledge it encodes, but with very limited ability to learn. When you talk of comparing AI to a genius/professional/graduate/etc, you are really talking about comparing level of knowledge, comparing one expert system to another, which is fine and perhaps useful in some contexts, but it is not the same as comparing actual intelligence - learning ability, and especially so if you want to discuss general intelligence which is all about the ability to successfully take on any task (perhaps needing to learn it first), not just do well on some limited set of tasks you are already familiar with. 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.

famouswaffles 1mo ago
>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

famouswaffles 1mo ago

>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