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This doesn't match what I've seen of usage of the term AGI since ~2010. I think we've "solved" chatbots more than was imagined at the time, and that involves be

This doesn't match what I've seen of usage of the term AGI since ~2010. I think we've "solved" chatbots more than was imagined at the time, and that involves being able to produce readable and arguably useful answers about a range of topics, but we haven't got game playing sorted yet, we don't have proactive models, and there's nothing in these models for movement or robotics (which until recently has been considered an important necessary step). We have taken a noticeable step forwards towards AGI in the last few years, but AGI is still a long way off.

lucubratory 3y ago
"there's nothing in these models for movement or robotics" You should read the article. It talks about exactly this use case, using an LLM as part of robotics control systems.
BlueTemplar 3y ago
But at that point neural networks started to dominate AI research already to the point that "AI" started to become synonymous with them... what about 1950(?)-2010 ?
famouswaffles 3y ago
It's not just about language. https://general-pattern-machines.github.io/ https://general-pattern-machines.github.io/ >but we haven't got game playing sorted yet 4 can play chess, Minecraft fine. So I imagine a lot of games fall down to data. >and there's nothing in these models for movement or robotics The point is that there doesn't need to be. There are many projects using LLMs to pilot robots off text prediction ability. https://tidybot.cs.princeton.edu/ https://tidybot.cs.princeton.edu/ https://innermonologue.github.io/ https://innermonologue.github.io/ https://www.deepmind.com/blog/rt-2-new-model-translates-vision-and-language-into-action https://www.deepmind.com/blog/rt-2-new-model-translates-visi... I think most from the 2000s would be calling what we have today AGI.
- dr-detroit 3y ago
  [dead]
atemerev 3y ago
Games are solved since AlphaZero. Just set up an adversarial model, and voila. Any game, any conditions. Proactive models are simple — just generate the “internal monologue” periodically from the system prompt, mix it with the compressed state, then feed it to another model (the outputs are used as state updates). I think this is how human agency works as well. Movement is a different story (LLMs do not work here, except as planners), but it pretty much solved too. Robot hardware is too expensive, though, and it is not clear how to power it autonomously.
- danpalmer 3y ago
  AlphaZero is amazing, but it only plays 2D games with well defined win conditions.
  - atemerev 3y ago
    Yes, like military strategy.
    - danpalmer 3y ago
      Indeed, this is something that neither AlphaZero nor anything else has managed to do at anything approaching human level.
      - lucubratory 3y ago
        You really shouldn't say that so confidently. I know for a fact that at least in the US military (well, DoD civilian analysts), they're using models like AlphaZero for theatre-win condition modelling. It's probably being used because it allows analysts to find better solutions and they probably started using it after winning wargames with it - both guesses on my part, all I know for sure is that they are using the tech to model westpac.
  - deleted 3y ago
    [deleted]
- 3y ago

lucubratory 3y ago

"there's nothing in these models for movement or robotics" You should read the article. It talks about exactly this use case, using an LLM as part of robotics control systems.

BlueTemplar 3y ago

But at that point neural networks started to dominate AI research already to the point that "AI" started to become synonymous with them... what about 1950(?)-2010 ?

famouswaffles 3y ago

It's not just about language. https://general-pattern-machines.github.io/ https://general-pattern-machines.github.io/ >but we haven't got game playing sorted yet 4 can play chess, Minecraft fine. So I imagine a lot of games fall down to data. >and there's nothing in these models for movement or robotics The point is that there doesn't need to be. There are many projects using LLMs to pilot robots off text prediction ability. https://tidybot.cs.princeton.edu/ https://tidybot.cs.princeton.edu/ https://innermonologue.github.io/ https://innermonologue.github.io/ https://www.deepmind.com/blog/rt-2-new-model-translates-vision-and-language-into-action https://www.deepmind.com/blog/rt-2-new-model-translates-visi... I think most from the 2000s would be calling what we have today AGI.

dr-detroit 3y ago
[dead]

atemerev 3y ago

Games are solved since AlphaZero. Just set up an adversarial model, and voila. Any game, any conditions. Proactive models are simple — just generate the “internal monologue” periodically from the system prompt, mix it with the compressed state, then feed it to another model (the outputs are used as state updates). I think this is how human agency works as well. Movement is a different story (LLMs do not work here, except as planners), but it pretty much solved too. Robot hardware is too expensive, though, and it is not clear how to power it autonomously.

danpalmer 3y ago
AlphaZero is amazing, but it only plays 2D games with well defined win conditions.
- atemerev 3y ago
  Yes, like military strategy.
  - danpalmer 3y ago
    Indeed, this is something that neither AlphaZero nor anything else has managed to do at anything approaching human level.
    - lucubratory 3y ago
      You really shouldn't say that so confidently. I know for a fact that at least in the US military (well, DoD civilian analysts), they're using models like AlphaZero for theatre-win condition modelling. It's probably being used because it allows analysts to find better solutions and they probably started using it after winning wargames with it - both guesses on my part, all I know for sure is that they are using the tech to model westpac.
- deleted 3y ago
  [deleted]
3y ago