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Sure, there are problems that remain. But how can we say there are "so many" of them? We've seen large leaps in capabilities from architectures based on transfo

Sure, there are problems that remain. But how can we say there are "so many" of them? We've seen large leaps in capabilities from architectures based on transformers. We've yet to see the limit of transformers as the scaling curves haven't plateaued. It seems to me that we don't know if we're two innovations or two thousand away from AGI. What we do know is that progress has been faster than anyone would have predicted 10 years ago.

whimsicalism 5y ago
Look, I'm actually a massive optimist on this topic and think we can get very far with large language models. Memory I think will actually not be that difficult to solve, optimizing for long series of actions will be a hard one though, as will making an AI that can reason in a representationally invariant and transferrable way (ie. something that can reason just as well about data in the form of images as text). I'm not saying we're not seeing continuous improvements on performance on benchmarks from scaling up - we absolutely are. But "the end of the benchmarks" is not AGI - even if we have a tool AI/oracle AI that can perform at a superhuman level on benchmark tasks (which I think is absolutely doable within the current paradigm), we do not have a general AI.
- FeepingCreature 5y ago
  Hooking up transformers into an agent AI does not seem like a daunting task given the ability to generate snippets of reasoning on demand.
astrange 5y ago
The thing we’re progressing towards isn’t AGI, if by that you mean is conscious and sentient. I’m not sure this is actually possible, ie I don’t think we know “general intelligence” exists. The existence of your mind is a trick your brain plays on itself after all. You don’t exist independently of your body.
- FeepingCreature 5y ago
  AGI is AI that is as good as humans on all skills. It has nothing to do with consciousness or sentience.
  - visarga 5y ago
    I think reaching AGI has to do with the 4 E's: embodied, enacted, embedded and extended. These models have no embodiment, no complex external environment, and there is no goal to attain other than language games. But they could be embodied, and some experiments have shown for example how a LM can guide an agent in a 3D virtual home to accomplish tasks. (*) Maybe AIs can be educated like children after they reach a certain threshold, by giving them robotic bodies and immersing them in the human society which is the most complex environment for intelligence. (*) Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents - https://arxiv.org/pdf/2201.07207.pdf https://arxiv.org/pdf/2201.07207.pdf
    - sullyj3 5y ago
      Here's an example of an extended language model operating in a real world environment: https://www.youtube.com/watch?v=ysFav0b472w https://www.youtube.com/watch?v=ysFav0b472w
    - FeepingCreature 5y ago
      They have a complex external environment just as much as we do: the physical world generates their inputs. Just because their inputs are prefiltered through human language doesn't mean they're not exposed to its full complexity just as much as we are, after having it prefiltered through our eyeball and optic nerve. And predicting human statements implicitly requires modeling agents with goals - see the joke explanations.
      - visarga 5y ago
        But LM's can't do causal interventions to separate correlation from causation unless they have access to the real environment. Would a scientist that can't run experiments be able to advance the field by just reading past papers? Even babies need to try causality laws by letting objects fall and observing what happens, we learn by interacting with our environment.

whimsicalism 5y ago

Look, I'm actually a massive optimist on this topic and think we can get very far with large language models. Memory I think will actually not be that difficult to solve, optimizing for long series of actions will be a hard one though, as will making an AI that can reason in a representationally invariant and transferrable way (ie. something that can reason just as well about data in the form of images as text). I'm not saying we're not seeing continuous improvements on performance on benchmarks from scaling up - we absolutely are. But "the end of the benchmarks" is not AGI - even if we have a tool AI/oracle AI that can perform at a superhuman level on benchmark tasks (which I think is absolutely doable within the current paradigm), we do not have a general AI.

FeepingCreature 5y ago
Hooking up transformers into an agent AI does not seem like a daunting task given the ability to generate snippets of reasoning on demand.

astrange 5y ago

The thing we’re progressing towards isn’t AGI, if by that you mean is conscious and sentient. I’m not sure this is actually possible, ie I don’t think we know “general intelligence” exists. The existence of your mind is a trick your brain plays on itself after all. You don’t exist independently of your body.

FeepingCreature 5y ago
AGI is AI that is as good as humans on all skills. It has nothing to do with consciousness or sentience.
- visarga 5y ago
  I think reaching AGI has to do with the 4 E's: embodied, enacted, embedded and extended. These models have no embodiment, no complex external environment, and there is no goal to attain other than language games. But they could be embodied, and some experiments have shown for example how a LM can guide an agent in a 3D virtual home to accomplish tasks. (*) Maybe AIs can be educated like children after they reach a certain threshold, by giving them robotic bodies and immersing them in the human society which is the most complex environment for intelligence. (*) Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents - https://arxiv.org/pdf/2201.07207.pdf https://arxiv.org/pdf/2201.07207.pdf
  - sullyj3 5y ago
    Here's an example of an extended language model operating in a real world environment: https://www.youtube.com/watch?v=ysFav0b472w https://www.youtube.com/watch?v=ysFav0b472w
  - FeepingCreature 5y ago
    They have a complex external environment just as much as we do: the physical world generates their inputs. Just because their inputs are prefiltered through human language doesn't mean they're not exposed to its full complexity just as much as we are, after having it prefiltered through our eyeball and optic nerve. And predicting human statements implicitly requires modeling agents with goals - see the joke explanations.
    - visarga 5y ago
      But LM's can't do causal interventions to separate correlation from causation unless they have access to the real environment. Would a scientist that can't run experiments be able to advance the field by just reading past papers? Even babies need to try causality laws by letting objects fall and observing what happens, we learn by interacting with our environment.