3 ms·

Gato is definitely cool, but it's worth remembering it was based on supervised learning with data from a bunch of tasks, so data availability is a strong bottle

Gato is definitely cool, but it's worth remembering it was based on supervised learning with data from a bunch of tasks, so data availability is a strong bottleneck with that approach. Still, I'd agree the past year or two have made me more optimistic about HLAI (if not scary AGI).

sigmoid10 4y ago
Yeah, I'm definitely not saying this is already the ultimate solution. But if you look at their scaling experiments and extrapolate the results, it roughly shows how a model with number of parameters on the same order of magnitude as the human brain could more or less achieve overall human level performance. Of course that doesn't mean the architecture has to extrapolate, but it's definitely a path worth walking unless someone proves it's a dead end. In that case I'd replace "end of decade" with 10 to 20 years in my above statement.
- godelski 4y ago
  Except it is pretty naive to extrapolate like that. A high order polynomial looks flat if you zoom in enough. You can't extrapolate far beyond what you have empirical data for without potentially running into huge problems.
  - sigmoid10 4y ago
    How do you know what the function looks like? Unless someone shows that this scaling behaviour breaks down, it is definitely worth pursuing, since the possible benefits are obvious. Everyone who just says it will break down eventually is almost certainly right, but this is also a completely trivial and worthless prediction by itself. The important distinction is that noone knows where the breakdown happens. And from what we can tell today, it's not even close.
    - godelski 4y ago
      I think your viewpoint is the more naive one and I think you have the burden of proof to argue why local trends are representative of global trends. This is because the non-local argument accepts a wider range of possibilities and the local argument is the the more specific one. Think of it this way, I'm saying that every function looks linear given the right perspective and you're arguing that a particular function _is_ linear. I'm arguing that we don't know that. The burden of proof would be on you to prove that this function were linear beyond what we have data for. (Path towards HLI doesn't have to be linear, exponential, nor logarithmic but you do have to make a pretty strong argument to convince others that the local trend is generalizable).
      - sigmoid10 4y ago
        You are arguing completely beside the original point. Gato was just meant as one surprising example out of many to show how much more the architectures we already have today are capable of. Whether you believe how the scaling curve for this very particular model will work in detail is totally irrelevant to me or anyone else and I'm not trying to convince you of anything. I was just pointing out that there is a clear direction for future research and if you think people like Carmack are on the wrong path - so be it. You don't have to pursue it as well. But I don't care and he certainly doesn't either.
        godelski 4y ago
        I understood your argument, in the context of the discussion we've been having, that Gato was a good example of us being on a good path towards building intelligent machines. I do not think Gato demonstrates that.
  - idontpost 4y ago
    You're missing the point. The point isn't that we can or cannot extrapolate. The point is that it is worth investigating to see if the trend line holds up.
    - godelski 4y ago
      I think it is pretty disingenuous to read my comments as not wanting to investigate. I definitely do. I did say I'm an ML researcher and I do want to see HLI in my lifetime. But I also think we should invest in other directions as well.

sigmoid10 4y ago

Yeah, I'm definitely not saying this is already the ultimate solution. But if you look at their scaling experiments and extrapolate the results, it roughly shows how a model with number of parameters on the same order of magnitude as the human brain could more or less achieve overall human level performance. Of course that doesn't mean the architecture has to extrapolate, but it's definitely a path worth walking unless someone proves it's a dead end. In that case I'd replace "end of decade" with 10 to 20 years in my above statement.

godelski 4y ago
Except it is pretty naive to extrapolate like that. A high order polynomial looks flat if you zoom in enough. You can't extrapolate far beyond what you have empirical data for without potentially running into huge problems.
- sigmoid10 4y ago
  How do you know what the function looks like? Unless someone shows that this scaling behaviour breaks down, it is definitely worth pursuing, since the possible benefits are obvious. Everyone who just says it will break down eventually is almost certainly right, but this is also a completely trivial and worthless prediction by itself. The important distinction is that noone knows where the breakdown happens. And from what we can tell today, it's not even close.
  - godelski 4y ago
    I think your viewpoint is the more naive one and I think you have the burden of proof to argue why local trends are representative of global trends. This is because the non-local argument accepts a wider range of possibilities and the local argument is the the more specific one. Think of it this way, I'm saying that every function looks linear given the right perspective and you're arguing that a particular function _is_ linear. I'm arguing that we don't know that. The burden of proof would be on you to prove that this function were linear beyond what we have data for. (Path towards HLI doesn't have to be linear, exponential, nor logarithmic but you do have to make a pretty strong argument to convince others that the local trend is generalizable).
    - sigmoid10 4y ago
      You are arguing completely beside the original point. Gato was just meant as one surprising example out of many to show how much more the architectures we already have today are capable of. Whether you believe how the scaling curve for this very particular model will work in detail is totally irrelevant to me or anyone else and I'm not trying to convince you of anything. I was just pointing out that there is a clear direction for future research and if you think people like Carmack are on the wrong path - so be it. You don't have to pursue it as well. But I don't care and he certainly doesn't either.
      - godelski 4y ago
        I understood your argument, in the context of the discussion we've been having, that Gato was a good example of us being on a good path towards building intelligent machines. I do not think Gato demonstrates that.
- idontpost 4y ago
  You're missing the point. The point isn't that we can or cannot extrapolate. The point is that it is worth investigating to see if the trend line holds up.
  - godelski 4y ago
    I think it is pretty disingenuous to read my comments as not wanting to investigate. I definitely do. I did say I'm an ML researcher and I do want to see HLI in my lifetime. But I also think we should invest in other directions as well.