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Protein folding is a well modeled math problem. The alpha fold solution is extremely good at pruning (aka guessing) folding chain structure possibilities. I am

Protein folding is a well modeled math problem. The alpha fold solution is extremely good at pruning (aka guessing) folding chain structure possibilities. I am Impressed and this is a difficult problem but this is extremely different from AGI as this is a well scoped easily modelable problem that is basically a chain of 26 inputs types of links of arbitrary length. I am not trying to take away that the protein folding is incredible but AGI is extremely different. AGI is literally having a model that can both do alpha fold and self driving cars, as well as the ability to generate novel models to solve new well scopes problems. RL can do 0 to 1, the 1 to n (generalizeability) is the extremely difficult part.

ackbar03 5y ago
I may be really only speaking for myself here but I have very sincere doubts that anyone who has done any moderately serious work on "AI" and wrangled with the nitty gritty details of it all is really having any huge expectations for AGI. I mean if it comes during my lifetime, hurrah! But personally I'm not gonna sit around waiting for it or depend on it for anything. That being said, is the current AI tech as we have it useless? Of course not. Things like protein folding and alphago are still huge leaps forward in tech, it'd be kind of silly to treat AGI as the only thing worth achieving
tinco 5y ago
It is entirely not necessary for an AGI to be able to drive a car. Frankly, after seeing AlphaZero and AlphaFold I'm surprised they didn't declare AGI right there and then. People assume that when AGI happens, computers can suddenly outsmart humans in every way and solve every problem imaginable. The reality is just that it could in theory given enough time and resources. It is like quantum computing. In theory it can instantly factor and break our nice cryptographic primes. In reality the largest number it factored is 21.
- croon 5y ago
  > It is entirely not necessary for an AGI to be able to drive a car. "Artificial general intelligence (AGI) is the hypothetical[1] ability of an intelligent agent to understand or learn any intellectual task that a human being can." What definition are you using?
  - tinco 5y ago
    The same, that they understand and can learn how to drive a car doesn't mean they would actually be able to do it in the real world. You can read a book on how to hit a ball with a baseball bat, you can even practice and get good at it, but that still doesn't mean you would actually be able to hit a ball thrown by a professional pitcher.
    - croon 5y ago
      The interface to the car is a solved problem. > You can read a book on how to hit a ball with a baseball bat, you can even practice and get good at it, but that still doesn't mean you would actually be able to hit a ball thrown by a professional pitcher. If I hade incredibly fast reflexes and actuators I could.
      - tinco 5y ago
        Similarly, DeepMind's software might be able to drive a car, would it have a similar neuron count, connectivity, perception systems and training you received. Or maybe it couldn't, because the software is not as efficient as the organisation of your brain is. Or because there's hardcoded routines evolved in your brain that it lacks. What I'm saying is that just that because an AGI can't drive a car, it doesn't mean it's an AGI. For the same reason there's loads of people out there that are generally intelligent that can't drive cars for all sorts of physical reasons.
        croon 5y ago
        > Similarly, DeepMind's software might be able to drive a car, would it have a similar neuron count, connectivity, perception systems and training you received. Admittedly I'm a layman in this area, but could it? AFAICT it would only work on trained set data and whatever generalizations can be made on that and not infer unseen scenarios like humans do readily. > What I'm saying is that just that because an AGI can't drive a car, it doesn't mean it's an AGI. I understood what you meant from your first post, I'm simply disagreeing on account of the very definition of AGI. You can't have an ameoba level AGI and still call it (a limited) AGI. Either it can understand/learn any human task, or it can't. The definition is made for a reason. Watering it down for any specific generation of AI serves no benefit.
- qsort 5y ago
  > it could in theory given enough time and resources. In theory given enough time and resources, anyone can defeat any grandmaster in Chess: just compute the extended tree form of the game and run the minimax algorithm. The "given enough time and resources" clause makes everything that follows meaningless, unless a reasonable algorithm is presented. > It is like quantum computing. It is absolutely not like quantum computing. Shor's algorithm is something you can look up right now. It is precise and well-defined. The problems we are facing with quantum computation are related to the fact that we can't really build reliable hardware. But we know that given such machines the algorithm would work. We have precise bounds and requirements on those machines. As far as AGI goes, we have absolutely no idea. There's lively debate on whether anything we have done even counts as significant advancement towards AGI.
  - tinco 5y ago
    > In theory given enough time and resources, anyone can defeat any grandmaster in Chess: just compute the extended tree form of the game and run the minimax algorithm. Yes, that's why we're considered to be generally intelligent. It is exactly the point, and not at all meaningless. Right now there's no machine that can come up with the idea to run an extended tree form of the game and minimax the algorithm. If there was such a machine, then that machine would be considered AGI. > It is absolutely not like quantum computing. I meant in the sense that just that it has actually been achieved, it doesn't mean it's as powerful as we have described in the theory. In theory you can use Shor's algorithm to break encryption, in practice the devices we have today have trouble with 2 digit numbers. The same principle goes for AGI. If someone releases an AGI system today, it doesn't mean that tomorrow we'll see a Boston Dynamics robot hop on a bicycle to his day job as a Disney movie art director. The world would most likely not change at all, at least not for a while, many people would not recognise the significance and many people might not even recognise the fact that it is in fact AGI. > As far as AGI goes, we have absolutely no idea. There's lively debate on whether anything we have done even counts as significant advancement towards AGI. You might think that, and that says something about what side of the debate you're on. We're commenting here on the thread of an article about DeepMind asseting that reinforcement learning is enough to reach general AI. If that's true (and I think it is), then we've probably reached general AI already.
- deleted 5y ago
  [deleted]

ackbar03 5y ago

I may be really only speaking for myself here but I have very sincere doubts that anyone who has done any moderately serious work on "AI" and wrangled with the nitty gritty details of it all is really having any huge expectations for AGI. I mean if it comes during my lifetime, hurrah! But personally I'm not gonna sit around waiting for it or depend on it for anything. That being said, is the current AI tech as we have it useless? Of course not. Things like protein folding and alphago are still huge leaps forward in tech, it'd be kind of silly to treat AGI as the only thing worth achieving

tinco 5y ago

It is entirely not necessary for an AGI to be able to drive a car. Frankly, after seeing AlphaZero and AlphaFold I'm surprised they didn't declare AGI right there and then. People assume that when AGI happens, computers can suddenly outsmart humans in every way and solve every problem imaginable. The reality is just that it could in theory given enough time and resources. It is like quantum computing. In theory it can instantly factor and break our nice cryptographic primes. In reality the largest number it factored is 21.

croon 5y ago
> It is entirely not necessary for an AGI to be able to drive a car. "Artificial general intelligence (AGI) is the hypothetical[1] ability of an intelligent agent to understand or learn any intellectual task that a human being can." What definition are you using?
- tinco 5y ago
  The same, that they understand and can learn how to drive a car doesn't mean they would actually be able to do it in the real world. You can read a book on how to hit a ball with a baseball bat, you can even practice and get good at it, but that still doesn't mean you would actually be able to hit a ball thrown by a professional pitcher.
  - croon 5y ago
    The interface to the car is a solved problem. > You can read a book on how to hit a ball with a baseball bat, you can even practice and get good at it, but that still doesn't mean you would actually be able to hit a ball thrown by a professional pitcher. If I hade incredibly fast reflexes and actuators I could.
    - tinco 5y ago
      Similarly, DeepMind's software might be able to drive a car, would it have a similar neuron count, connectivity, perception systems and training you received. Or maybe it couldn't, because the software is not as efficient as the organisation of your brain is. Or because there's hardcoded routines evolved in your brain that it lacks. What I'm saying is that just that because an AGI can't drive a car, it doesn't mean it's an AGI. For the same reason there's loads of people out there that are generally intelligent that can't drive cars for all sorts of physical reasons.
      - croon 5y ago
        > Similarly, DeepMind's software might be able to drive a car, would it have a similar neuron count, connectivity, perception systems and training you received. Admittedly I'm a layman in this area, but could it? AFAICT it would only work on trained set data and whatever generalizations can be made on that and not infer unseen scenarios like humans do readily. > What I'm saying is that just that because an AGI can't drive a car, it doesn't mean it's an AGI. I understood what you meant from your first post, I'm simply disagreeing on account of the very definition of AGI. You can't have an ameoba level AGI and still call it (a limited) AGI. Either it can understand/learn any human task, or it can't. The definition is made for a reason. Watering it down for any specific generation of AI serves no benefit.
qsort 5y ago
> it could in theory given enough time and resources. In theory given enough time and resources, anyone can defeat any grandmaster in Chess: just compute the extended tree form of the game and run the minimax algorithm. The "given enough time and resources" clause makes everything that follows meaningless, unless a reasonable algorithm is presented. > It is like quantum computing. It is absolutely not like quantum computing. Shor's algorithm is something you can look up right now. It is precise and well-defined. The problems we are facing with quantum computation are related to the fact that we can't really build reliable hardware. But we know that given such machines the algorithm would work. We have precise bounds and requirements on those machines. As far as AGI goes, we have absolutely no idea. There's lively debate on whether anything we have done even counts as significant advancement towards AGI.
- tinco 5y ago
  > In theory given enough time and resources, anyone can defeat any grandmaster in Chess: just compute the extended tree form of the game and run the minimax algorithm. Yes, that's why we're considered to be generally intelligent. It is exactly the point, and not at all meaningless. Right now there's no machine that can come up with the idea to run an extended tree form of the game and minimax the algorithm. If there was such a machine, then that machine would be considered AGI. > It is absolutely not like quantum computing. I meant in the sense that just that it has actually been achieved, it doesn't mean it's as powerful as we have described in the theory. In theory you can use Shor's algorithm to break encryption, in practice the devices we have today have trouble with 2 digit numbers. The same principle goes for AGI. If someone releases an AGI system today, it doesn't mean that tomorrow we'll see a Boston Dynamics robot hop on a bicycle to his day job as a Disney movie art director. The world would most likely not change at all, at least not for a while, many people would not recognise the significance and many people might not even recognise the fact that it is in fact AGI. > As far as AGI goes, we have absolutely no idea. There's lively debate on whether anything we have done even counts as significant advancement towards AGI. You might think that, and that says something about what side of the debate you're on. We're commenting here on the thread of an article about DeepMind asseting that reinforcement learning is enough to reach general AI. If that's true (and I think it is), then we've probably reached general AI already.
deleted 5y ago
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