4 ms·

Makes me think of Carmacks remark (from the lex fridman interview) that he 'almost count anyone out' that tries to make AGI happen through real life humanoid-is

by naillo 4y ago

Makes me think of Carmacks remark (from the lex fridman interview) that he 'almost count anyone out' that tries to make AGI happen through real life humanoid-ish machines. (Meaning simulated worlds that can do e.g. 1000x real time is much more efficinent.)

raghavtoshniwal 4y ago
Geohot has some bias to believe AGI would have to exist in meatspace, he has invested years into cracking self driving cars and dealing with the messy real world. He does plug open pilot at the end.
- krick 4y ago
  I'm not gonna take anyone's side here, just to point out that "bias" goes both ways. Carmack is a life-long game-developer (always more focused on "technical" aspects of gamedev, like graphics), and now basically a rich celebrity, who can indulge himself by something as grand and abstract as "working on AGI" (since 2019). While Hotz is probably best known for his exploits, he still is a legit machine learning professional, and comma.ai is legit business actually focused on "AI-kinda -stuff". Now, AGI is that thing from the joke about "teenage sex". Everyone has some opinion, but we don't really take it too seriously when LeCun, or Karpathy, or Hinton express their opinions on that, because everyone (except for Musk fans, obviously) knows, that no one knows. And as I've said, I'm not gonna take anyone's side here, but unlike Hotz, Carmack has almost as much clue about that stuff as some random FE-developer out there. So you can as well replace "bias" with "experience" here, and it would be as true, but the whole meaning would be quite different.
  - cma 4y ago
    > Carmack is a life-long game-developer (always more focused on "technical" aspects of gamedev, like graphics), and now basically a rich celebrity, who can indulge himself by something as grand and abstract as "working on AGI" (since 2019). He also started a rocket company and was a big part of making VR workable with reprojection techniques and other innovations (some of them may have had precedent but so did Doom, he and others got it all working in useable form this time, like Doom (Ultima Underworld was a bit slow and had to be run in a much smaller fraction of the screen)). Beyond just pure rendering, he also created the first usable megatexturing/virtual texturing, now used about everywhere, which is almost more of a data management problem. It maybe wasn't that great until SSDs, but he knew that and put out an early mindblowing iphone version using the solid state storage and integrated cpu/gpu memory as well.
mattmee 4y ago
george talks about "A banana peel? Did you put all those things in your simulator?" -- it doesn't matter if it's in the simulation yet, the generalization of your algorithm is what matters... once it's ready to act with new objects by itself, put it in there to see if it can generalize around it. Humans dont know what a banana peel is until they've been exposed to it, and they work with it. smart of carmack to say "almost anyone", clearly smart people are working via the humanoid aspect and I'd guess they'll have some discoveries before the simulation people, but not necessarily because they're going from the humanoid approach
- liuliu 4y ago
  At certain point, training / inference difference will be blur. Is GPT-3's prompt some kind of "learning" or just a different way to poke the model? For RL, things like domain randomization, particularly, the way to train "teacher-student" network (like in MIT Cheetah running paper), when inference, it recovers physic parameters of the body, does that count as "learning"? The simulation may not have "banana peel", but for a multi-modality model, it is not hard to imagine it has encountered an object with similar physic parameters before and "other models" in the system, after "fall over", can recover such parameters and won't be tricked again. Does that count as "learning"?
  - mattmee 4y ago
    It all depends on how you define "learning". I was just saying that I think George is wrong to say "The only way forward is on device learning." Especially his use of the word "only". I think in order to interact in the real world, you will have to learn in the real world to some extent, but like pilots do in training, something/someone can learn a lot from simulations. Something to consider is that living creatures in general have hundreds of millions (billions?) of years and (insert very, very large number) of variations of trail and error in the real world. Intelligence and learning came way before humans.
    - liuliu 4y ago
      Oh, I am totally in the camp of "simulation is enough". My reply is a convoluted way to argue that once learned enough in simulation, adaptation in real-world should just work (if you treat adaptation as a way of learning).

by naillo 4y ago

raghavtoshniwal 4y ago

Geohot has some bias to believe AGI would have to exist in meatspace, he has invested years into cracking self driving cars and dealing with the messy real world. He does plug open pilot at the end.

krick 4y ago
I'm not gonna take anyone's side here, just to point out that "bias" goes both ways. Carmack is a life-long game-developer (always more focused on "technical" aspects of gamedev, like graphics), and now basically a rich celebrity, who can indulge himself by something as grand and abstract as "working on AGI" (since 2019). While Hotz is probably best known for his exploits, he still is a legit machine learning professional, and comma.ai is legit business actually focused on "AI-kinda -stuff". Now, AGI is that thing from the joke about "teenage sex". Everyone has some opinion, but we don't really take it too seriously when LeCun, or Karpathy, or Hinton express their opinions on that, because everyone (except for Musk fans, obviously) knows, that no one knows. And as I've said, I'm not gonna take anyone's side here, but unlike Hotz, Carmack has almost as much clue about that stuff as some random FE-developer out there. So you can as well replace "bias" with "experience" here, and it would be as true, but the whole meaning would be quite different.
- cma 4y ago
  > Carmack is a life-long game-developer (always more focused on "technical" aspects of gamedev, like graphics), and now basically a rich celebrity, who can indulge himself by something as grand and abstract as "working on AGI" (since 2019). He also started a rocket company and was a big part of making VR workable with reprojection techniques and other innovations (some of them may have had precedent but so did Doom, he and others got it all working in useable form this time, like Doom (Ultima Underworld was a bit slow and had to be run in a much smaller fraction of the screen)). Beyond just pure rendering, he also created the first usable megatexturing/virtual texturing, now used about everywhere, which is almost more of a data management problem. It maybe wasn't that great until SSDs, but he knew that and put out an early mindblowing iphone version using the solid state storage and integrated cpu/gpu memory as well.

mattmee 4y ago

george talks about "A banana peel? Did you put all those things in your simulator?" -- it doesn't matter if it's in the simulation yet, the generalization of your algorithm is what matters... once it's ready to act with new objects by itself, put it in there to see if it can generalize around it. Humans dont know what a banana peel is until they've been exposed to it, and they work with it. smart of carmack to say "almost anyone", clearly smart people are working via the humanoid aspect and I'd guess they'll have some discoveries before the simulation people, but not necessarily because they're going from the humanoid approach

liuliu 4y ago
At certain point, training / inference difference will be blur. Is GPT-3's prompt some kind of "learning" or just a different way to poke the model? For RL, things like domain randomization, particularly, the way to train "teacher-student" network (like in MIT Cheetah running paper), when inference, it recovers physic parameters of the body, does that count as "learning"? The simulation may not have "banana peel", but for a multi-modality model, it is not hard to imagine it has encountered an object with similar physic parameters before and "other models" in the system, after "fall over", can recover such parameters and won't be tricked again. Does that count as "learning"?
- mattmee 4y ago
  It all depends on how you define "learning". I was just saying that I think George is wrong to say "The only way forward is on device learning." Especially his use of the word "only". I think in order to interact in the real world, you will have to learn in the real world to some extent, but like pilots do in training, something/someone can learn a lot from simulations. Something to consider is that living creatures in general have hundreds of millions (billions?) of years and (insert very, very large number) of variations of trail and error in the real world. Intelligence and learning came way before humans.
  - liuliu 4y ago
    Oh, I am totally in the camp of "simulation is enough". My reply is a convoluted way to argue that once learned enough in simulation, adaptation in real-world should just work (if you treat adaptation as a way of learning).