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Bostrom is in no way in charge of people who happen to agree with him wrt ai risk. For the book he mostly collected and organized a lot of existing thought on a

by nohat 9y ago

Bostrom is in no way in charge of people who happen to agree with him wrt ai risk. For the book he mostly collected and organized a lot of existing thought on ai risk (not that he hasn't made his own novel contributions). That's very valuable, largely because it makes for a good reference point to contextualize discussion on the topic. Unfortunately the critics don't seem to have read it because (in my experience) they repeat the same objections without reference to the existing responses to those objections. People do sometimes overblow alphago/ dqn playing Atari, but it's not meaningless. These systems (and other deep learning based systems) can truly learn from scratch on a decent variety of environments. One of the most important unknowns is exactly how difficult various cognitive tasks will prove to be for a machine. Each task accomplished is another data point.

rspeer 9y ago
I wouldn't say that DeepMind learns Atari games "from scratch" any more than Deep Blue learned chess from scratch. It learns to play Atari games because it's a machine designed to learn to play Atari games.
- Elrac 9y ago
  I strongly disagree. You don't seem to be aware of the difference in approach between Deep Blue and DeepMind. Deep Blue was hand-led directly and specifically to solve the problem of chess: It was provided with a library of opening moves, some sophisticated tactical algorithms relevant to the problem of chess, a library of strategies for chess, and so on. Many actual human masters of chess were consulted, directly or indirectly, to help with developing Deep Blue's approach to the problem. DeepMind, on the other hand, was created as a "blank slate" with no more hard-wired instruction than "create optimal algorithms to achieve the winning state, given the inputs." Critically, its learning phase is completely self-directed. Essentially, the box is given access to the controls and the video screen content and then sent on its way. It's instructive to note that this is pretty much exactly how, very generally speaking, evolution and intelligence solve the problem of survival: every organism has controls and a glimpse of "game state" and has to learn (collectively as a species, individually as an organism) to play the game successfully.
  - Ngunyan 9y ago
    > DeepMind, on the other hand, was created as a "blank slate" with no more hard-wired instruction than "create optimal algorithms to achieve the winning state, given the inputs." Critically, its learning phase is completely self-directed. Essentially, the box is given access to the controls and the video screen content and then sent on its way. Have you seen DeepMind algorithm to be able to say this ? Are there other people outside of Google who have seen the algorithm and can confirm Google's press release?
    - Elrac 9y ago
      Maybe you have some legitimate concern about Googles' claim as per their press release and my comment. Who knows, maybe they have some reason to lie about what they did! But then I wonder why you aren't asking the same question of my parent poster. Has he viewed the DeepMind code, is he qualified to tell us it works the same as chess code? Having made that claim backed on even less evidence than I made mine, I'd say his burden of proof is somewhat greater.
      - rspeer 9y ago
        I think there's a heavy dose of press release to what Google is saying. Most people wouldn't call PR puff "lying", but only because standards are low. I don't think Google has fundamentally different deep-learning technology than everyone else. In fact, TensorFlow indicates that they have the same kind of deep-learning technology as everyone else and they just want to do it more cleanly. Deep learning is parameter optimization. There are more parameters now, and they optimize more things, but don't get caught up in wild visions of machines designing themselves. Would you consider the bzip2 algorithm to be "self-directed learning"? What's the difference, besides the number of parameters? The PR people, when they say "blank slate", are discounting all the programming that went into the system because it sounds more impressive that way. This is unfortunate. It has happened in AI for decades. To be a responsible consumer of AI press releases, you need to understand this.
        Elrac 9y ago

by nohat 9y ago

rspeer 9y ago

I wouldn't say that DeepMind learns Atari games "from scratch" any more than Deep Blue learned chess from scratch. It learns to play Atari games because it's a machine designed to learn to play Atari games.

Elrac 9y ago
I strongly disagree. You don't seem to be aware of the difference in approach between Deep Blue and DeepMind. Deep Blue was hand-led directly and specifically to solve the problem of chess: It was provided with a library of opening moves, some sophisticated tactical algorithms relevant to the problem of chess, a library of strategies for chess, and so on. Many actual human masters of chess were consulted, directly or indirectly, to help with developing Deep Blue's approach to the problem. DeepMind, on the other hand, was created as a "blank slate" with no more hard-wired instruction than "create optimal algorithms to achieve the winning state, given the inputs." Critically, its learning phase is completely self-directed. Essentially, the box is given access to the controls and the video screen content and then sent on its way. It's instructive to note that this is pretty much exactly how, very generally speaking, evolution and intelligence solve the problem of survival: every organism has controls and a glimpse of "game state" and has to learn (collectively as a species, individually as an organism) to play the game successfully.
- Ngunyan 9y ago
  > DeepMind, on the other hand, was created as a "blank slate" with no more hard-wired instruction than "create optimal algorithms to achieve the winning state, given the inputs." Critically, its learning phase is completely self-directed. Essentially, the box is given access to the controls and the video screen content and then sent on its way. Have you seen DeepMind algorithm to be able to say this ? Are there other people outside of Google who have seen the algorithm and can confirm Google's press release?
  - Elrac 9y ago
    Maybe you have some legitimate concern about Googles' claim as per their press release and my comment. Who knows, maybe they have some reason to lie about what they did! But then I wonder why you aren't asking the same question of my parent poster. Has he viewed the DeepMind code, is he qualified to tell us it works the same as chess code? Having made that claim backed on even less evidence than I made mine, I'd say his burden of proof is somewhat greater.
    - rspeer 9y ago
      I think there's a heavy dose of press release to what Google is saying. Most people wouldn't call PR puff "lying", but only because standards are low. I don't think Google has fundamentally different deep-learning technology than everyone else. In fact, TensorFlow indicates that they have the same kind of deep-learning technology as everyone else and they just want to do it more cleanly. Deep learning is parameter optimization. There are more parameters now, and they optimize more things, but don't get caught up in wild visions of machines designing themselves. Would you consider the bzip2 algorithm to be "self-directed learning"? What's the difference, besides the number of parameters? The PR people, when they say "blank slate", are discounting all the programming that went into the system because it sounds more impressive that way. This is unfortunate. It has happened in AI for decades. To be a responsible consumer of AI press releases, you need to understand this.
      - Elrac 9y ago