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It's because the people actually working on AI, including OpenAI, finally knocked some sense into Elon Musk. He finally realized how far behind AI is (it is a g

It's because the people actually working on AI, including OpenAI, finally knocked some sense into Elon Musk. He finally realized how far behind AI is (it is a glorified linear regression) and we won't be seeing general AI for at least another 40 years. Source: Am an AI research scientist.

computerex 9y ago
Would be interested to know how you reached that 40 years number. I don't think we are even remotely close to AGI, 40 years to me seems extremely optimistic. That's within my lifetime.
- adrianN 9y ago
  They're a scientist: https://xkcd.com/678/ https://xkcd.com/678/
  - eli_gottlieb 9y ago
    That's a little sadder now that I've had the "fourth quarter next year" thing happen to me personally.
- ewjordan 9y ago
  Probably the same way everyone does, by pulling it out of thin air as a guess. When nobody even knows what theoretical breakthroughs are necessary, you'll always end up with a scattershot all over the place, even amongst experts. Try asking working mathematicians how long until the Riemann hypothesis is resolved one way or another, or look at what people were saying about Fermat's Last Theorem up until it was solved. What we do know is that current techniques won't get us close to AGI, so something new is needed (or perhaps like backprop, something old will work once we have enough compute power). Personally I'm bullish on AGI because I have strikingly low faith in the ability of evolution to operate very effectively as a tool for algorithm discovery, so I suspect that once we've hit the compute threshold we'll find that many different algorithms can do the trick, and 40 years is probably not out of the question for us to hit that point (or 10, or 100), depending who you talk to about what the compute threshold might be. I'd caution against putting too much weight in what experts say, though, since with a tiny few set of exceptions anyone working on "AI" today is actually just working on narrow AI, which is, as someone put it, just glorified linear regression. Those tools will almost certainly be part of the solution, but only in the sense that the classical theory of Diophantine equations was part of Weil's proof of Fermat's Last Theorem - they are not the core of the theoretical approach.
  - evc123 9y ago
    Evolution has been running ~10^19 experiments in parallel for billions of years: http://reducing-suffering.org/how-many-wild-animals-are-there/ http://reducing-suffering.org/how-many-wild-animals-are-ther... Evolution is a slow algorithm, but it had access to an absurd amount of compute (all neuronal organic matter on Earth) and environment simulation (all of physical reality on Earth) when discovering us; so the discovery of the algorithms/architectures/principles in our heads shouldn't be viewed as trivial.
    - backpropaganda 9y ago
      The massive compute/time advantage evolution has makes me bearish about AGI. We really need to fix our compute capabilities before we can start overruning evolution. The math dictates it'll happen, but exponentially slowly if we don't innovate in compute.
      - espadrine 9y ago
        There's more to the story, too: advances on top of CRISP may give us better tools to self-improve the species, accelerating evolution. Personally, I'm bearish about AGI because I believe we will eventually realize that the brain is a glorified linear regression too, with a custom wiring to help learn language and vision.
        computerex 9y ago
        What do you mean when you say that the brain is a glorified linear regression?
  - eli_gottlieb 9y ago
    >What we do know is that current techniques won't get us close to AGI, so something new is needed (or perhaps like backprop, something old will work once we have enough compute power). With backprop we didn't just need bigger machines, we needed better algorithms, palliatives for the exploding-gradient problem that made values exceed our numerical representations, and then hardware specifically designed for doing the matrix-ops involved. If I saw something capable of speeding up probabilistic program inference the way GPUs sped up backprop, I'd start saying we should expect to see powerful AI applications quite soon.
- deleted 9y ago
  [deleted]
- Houshalter 9y ago
  40 years is very pessimistic. The median estimate given by AI experts is in the 2040s. Moore's law will surpass the human brain before then.
aerovistae 9y ago
So when you say "It's because...", are you in touch with people working there, or are you just guessing that this transpired because it seems like a reasonable assumption to you?
rspeer 9y ago
I'd be interested in hearing more background here. Last time I heard Musk say anything about AI, he was still on the hype train to crazy-town, talking about the world-conquering things it would do in the coming decades that have nothing to do with what anyone's researching right now. The idea that OpenAI could talk him down is pretty impressive, and if true I would significantly positively update my impression of OpenAI. (I thought OpenAI was funded by people on this hype train.)
- Houshalter 9y ago
  Musk didn't say that AGI was close or that current research was particularly dangerous. He was worried about what might be possible in many decades.
bravura 9y ago
I got my PhD in machine learning and NLP and did a 3-yr postdoc on deep learning. My advisor shared the following wisdom with me: "When the experts in your field say that saying can be done, they are probably right. When the experts in your field say that something cannot be done, they are not necessarily right."
- _delirium 9y ago
  > When the experts in your field say that saying can be done, they are probably right. Generally yes, but they may be significantly off on the timeframe. One famous example is that once alpha-beta search was invented (in the late 1950s), Herb Simon predicted that "within ten years a digital computer will be the world's chess champion". That did eventually happen, using techniques not even all that different from alpha-beta search, but it took 40 years rather than 10. Many of the 1980s neural nets claims turned out to be eventually vindicated too, but it took 30 years, which was quiet a bit longer than the optimistic portion of 1980s "connectionists" expected. That's the type of skepticism I usually have with claims today too. When people say "there will be fully autonomous self-driving cars on the road by 2020", I don't doubt it'll happen, but whether it'll happen in less than 3 years I have more doubts about. You could argue AI researchers have gotten better at accurately predicting the timeframes of advances than they were in the early days of AI, but I'm not sure there is solid evidence of that (would be interesting if someone has studied it).
  - Houshalter 9y ago
    It can happen the other way around too though. Few people predicted the massive jump in AI ability the last few years. Notable AI researchers said it would take decades to get to human accuracy on imagenet, and they were wrong within a few years. I recall reading the first deep learning Go papers around 2015 and thinking that superhuman Go AI was inevitable in a few years. And when I discussed it with other people they were very skeptical and thought it was unlikely. And then AlphaGo came out...
    - rspeer 9y ago
      > Few people predicted the massive jump in AI ability the last few years. I'm guessing you work in image recognition, or mostly hear from people who work in image recognition. There is more to AI, and not all of it is instantly improved by a convolutional neural net.
Voloskaya 9y ago
Universe is purposedly being abandonned (a specific training framework) not OpenAI... But thank you for your valuable insight, we all know being an AI research scientists gives you a direct connection to Elon's brain. Edit: And seems like you are wrong anyway, see top comment.
eli_gottlieb 9y ago
Oh good, they're finally getting it. Now we can maybe have a nice AI winter for deep learning and clear the stage for the next few things.

computerex 9y ago

Would be interested to know how you reached that 40 years number. I don't think we are even remotely close to AGI, 40 years to me seems extremely optimistic. That's within my lifetime.

adrianN 9y ago
They're a scientist: https://xkcd.com/678/ https://xkcd.com/678/
- eli_gottlieb 9y ago
  That's a little sadder now that I've had the "fourth quarter next year" thing happen to me personally.
ewjordan 9y ago
Probably the same way everyone does, by pulling it out of thin air as a guess. When nobody even knows what theoretical breakthroughs are necessary, you'll always end up with a scattershot all over the place, even amongst experts. Try asking working mathematicians how long until the Riemann hypothesis is resolved one way or another, or look at what people were saying about Fermat's Last Theorem up until it was solved. What we do know is that current techniques won't get us close to AGI, so something new is needed (or perhaps like backprop, something old will work once we have enough compute power). Personally I'm bullish on AGI because I have strikingly low faith in the ability of evolution to operate very effectively as a tool for algorithm discovery, so I suspect that once we've hit the compute threshold we'll find that many different algorithms can do the trick, and 40 years is probably not out of the question for us to hit that point (or 10, or 100), depending who you talk to about what the compute threshold might be. I'd caution against putting too much weight in what experts say, though, since with a tiny few set of exceptions anyone working on "AI" today is actually just working on narrow AI, which is, as someone put it, just glorified linear regression. Those tools will almost certainly be part of the solution, but only in the sense that the classical theory of Diophantine equations was part of Weil's proof of Fermat's Last Theorem - they are not the core of the theoretical approach.
- evc123 9y ago
  Evolution has been running ~10^19 experiments in parallel for billions of years: http://reducing-suffering.org/how-many-wild-animals-are-there/ http://reducing-suffering.org/how-many-wild-animals-are-ther... Evolution is a slow algorithm, but it had access to an absurd amount of compute (all neuronal organic matter on Earth) and environment simulation (all of physical reality on Earth) when discovering us; so the discovery of the algorithms/architectures/principles in our heads shouldn't be viewed as trivial.
  - backpropaganda 9y ago
    The massive compute/time advantage evolution has makes me bearish about AGI. We really need to fix our compute capabilities before we can start overruning evolution. The math dictates it'll happen, but exponentially slowly if we don't innovate in compute.
    - espadrine 9y ago
      There's more to the story, too: advances on top of CRISP may give us better tools to self-improve the species, accelerating evolution. Personally, I'm bearish about AGI because I believe we will eventually realize that the brain is a glorified linear regression too, with a custom wiring to help learn language and vision.
      - computerex 9y ago
        What do you mean when you say that the brain is a glorified linear regression?
- eli_gottlieb 9y ago
  >What we do know is that current techniques won't get us close to AGI, so something new is needed (or perhaps like backprop, something old will work once we have enough compute power). With backprop we didn't just need bigger machines, we needed better algorithms, palliatives for the exploding-gradient problem that made values exceed our numerical representations, and then hardware specifically designed for doing the matrix-ops involved. If I saw something capable of speeding up probabilistic program inference the way GPUs sped up backprop, I'd start saying we should expect to see powerful AI applications quite soon.
deleted 9y ago
[deleted]
Houshalter 9y ago
40 years is very pessimistic. The median estimate given by AI experts is in the 2040s. Moore's law will surpass the human brain before then.

aerovistae 9y ago

So when you say "It's because...", are you in touch with people working there, or are you just guessing that this transpired because it seems like a reasonable assumption to you?

rspeer 9y ago

I'd be interested in hearing more background here. Last time I heard Musk say anything about AI, he was still on the hype train to crazy-town, talking about the world-conquering things it would do in the coming decades that have nothing to do with what anyone's researching right now. The idea that OpenAI could talk him down is pretty impressive, and if true I would significantly positively update my impression of OpenAI. (I thought OpenAI was funded by people on this hype train.)

Houshalter 9y ago
Musk didn't say that AGI was close or that current research was particularly dangerous. He was worried about what might be possible in many decades.

bravura 9y ago

I got my PhD in machine learning and NLP and did a 3-yr postdoc on deep learning. My advisor shared the following wisdom with me: "When the experts in your field say that saying can be done, they are probably right. When the experts in your field say that something cannot be done, they are not necessarily right."

_delirium 9y ago
> When the experts in your field say that saying can be done, they are probably right. Generally yes, but they may be significantly off on the timeframe. One famous example is that once alpha-beta search was invented (in the late 1950s), Herb Simon predicted that "within ten years a digital computer will be the world's chess champion". That did eventually happen, using techniques not even all that different from alpha-beta search, but it took 40 years rather than 10. Many of the 1980s neural nets claims turned out to be eventually vindicated too, but it took 30 years, which was quiet a bit longer than the optimistic portion of 1980s "connectionists" expected. That's the type of skepticism I usually have with claims today too. When people say "there will be fully autonomous self-driving cars on the road by 2020", I don't doubt it'll happen, but whether it'll happen in less than 3 years I have more doubts about. You could argue AI researchers have gotten better at accurately predicting the timeframes of advances than they were in the early days of AI, but I'm not sure there is solid evidence of that (would be interesting if someone has studied it).
- Houshalter 9y ago
  It can happen the other way around too though. Few people predicted the massive jump in AI ability the last few years. Notable AI researchers said it would take decades to get to human accuracy on imagenet, and they were wrong within a few years. I recall reading the first deep learning Go papers around 2015 and thinking that superhuman Go AI was inevitable in a few years. And when I discussed it with other people they were very skeptical and thought it was unlikely. And then AlphaGo came out...
  - rspeer 9y ago
    > Few people predicted the massive jump in AI ability the last few years. I'm guessing you work in image recognition, or mostly hear from people who work in image recognition. There is more to AI, and not all of it is instantly improved by a convolutional neural net.

Voloskaya 9y ago

Universe is purposedly being abandonned (a specific training framework) not OpenAI... But thank you for your valuable insight, we all know being an AI research scientists gives you a direct connection to Elon's brain. Edit: And seems like you are wrong anyway, see top comment.

eli_gottlieb 9y ago

Oh good, they're finally getting it. Now we can maybe have a nice AI winter for deep learning and clear the stage for the next few things.