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> Google Lambda and Bing/Sydney are not at least incrementally closer to evidence? No, in the same way that boiling water in a kettle is not incrementally clos

> Google Lambda and Bing/Sydney are not at least incrementally closer to evidence? No, in the same way that boiling water in a kettle is not incrementally closer to inventing the fuel for a rocket ship. You can, in hidsight do a linear connection of water boiling -> steam engine -> fuel engine -> aeronautics -> space travel But the first time someone boiled water, if you said that got you closer to being on the moon I think you would be mad. There is a non trivial chance that all our current work in AI is functionally useless in terms of creating AGI, it might take a complete breakthrough in ML, tech not invented yet, or it might not be possible at all.

SturgeonsLaw 4y ago
Except, in your example, boiling water did get us closer to the moon :)
- Arkhaine_kupo 4y ago
  Yep, and there was a much mre promissing science on checking Ether, and the magical qualities of gravity defying physics. Who is to say that our current ML models are not Ether studies and utterly useless. If we crack AGI in 10 years, maybe our current models are the fuel engine. But if they are not even close, we might be boiling water. Or perhaps be wrong all together, thats why I said your observation of us getting closer thanks to those proyects is not right, at least not yet.
CuriouslyC 4y ago
We have lots of examples of generally intelligent systems, they're common and they evolve by themselves, so the idea that it might not be possible at all just seems ridiculous. Large language models might not be capable of general intelligence by themselves, but a model network that includes a LLM as part of a generalized game playing model would certainly have the potential to get there.
- RandomLensman 4y ago
  I think it is fair to say that "not at all possible" is perhaps too strong. On the potential of certain approaches I am less certain we have or know what we need. But we also have examples of things all around us we cannot make ourselves (e.g., a simple animal or lifeform from scratch).
  - CuriouslyC 4y ago
    Except that we've already created synthetic genomes: https://www.nytimes.com/2019/05/15/science/synthetic-genome-bacteria.html https://www.nytimes.com/2019/05/15/science/synthetic-genome-... If we can define what "generally intelligent" means in concrete terms, we can absolutely create it. The problem is that we don't have a good understanding/shared idea of what we're trying to achieve. We can create models that can learn to play many different games using the same weights, solve IQ/logic tests and pass the Turing test consistently, but people are going to move the goalposts and say those are just complex mashups of autocomplete and flowcharts. To be honest I don't think AI skeptics are ever going to believe until there's a Skynet trying to exterminate them.
    - RandomLensman 4y ago
      I don't share the view that all that is holding us back from creating AGI is a definition. Btw., that synthetic genome is a long way from making even something like an little nematode. I rather think AGI "idealists" (maybe there is a better word) will forever hold out (any) algorithmic advances as a sign of the immanent creation of AGI proper.

SturgeonsLaw 4y ago

Except, in your example, boiling water did get us closer to the moon :)

Arkhaine_kupo 4y ago
Yep, and there was a much mre promissing science on checking Ether, and the magical qualities of gravity defying physics. Who is to say that our current ML models are not Ether studies and utterly useless. If we crack AGI in 10 years, maybe our current models are the fuel engine. But if they are not even close, we might be boiling water. Or perhaps be wrong all together, thats why I said your observation of us getting closer thanks to those proyects is not right, at least not yet.

CuriouslyC 4y ago

We have lots of examples of generally intelligent systems, they're common and they evolve by themselves, so the idea that it might not be possible at all just seems ridiculous. Large language models might not be capable of general intelligence by themselves, but a model network that includes a LLM as part of a generalized game playing model would certainly have the potential to get there.

RandomLensman 4y ago
I think it is fair to say that "not at all possible" is perhaps too strong. On the potential of certain approaches I am less certain we have or know what we need. But we also have examples of things all around us we cannot make ourselves (e.g., a simple animal or lifeform from scratch).
- CuriouslyC 4y ago
  Except that we've already created synthetic genomes: https://www.nytimes.com/2019/05/15/science/synthetic-genome-bacteria.html https://www.nytimes.com/2019/05/15/science/synthetic-genome-... If we can define what "generally intelligent" means in concrete terms, we can absolutely create it. The problem is that we don't have a good understanding/shared idea of what we're trying to achieve. We can create models that can learn to play many different games using the same weights, solve IQ/logic tests and pass the Turing test consistently, but people are going to move the goalposts and say those are just complex mashups of autocomplete and flowcharts. To be honest I don't think AI skeptics are ever going to believe until there's a Skynet trying to exterminate them.
  - RandomLensman 4y ago
    I don't share the view that all that is holding us back from creating AGI is a definition. Btw., that synthetic genome is a long way from making even something like an little nematode. I rather think AGI "idealists" (maybe there is a better word) will forever hold out (any) algorithmic advances as a sign of the immanent creation of AGI proper.