40 ms·

AlphaGo's next move

285 points by bjin 9y ago

ipsum2 9y ago
Congratulations to Deepmind and Google for this tremendous achievement. However, it is disappointing that the code and model will not be released publicly after Alphago finishes competitive play. It's one thing to say that an apple, once dropped, will fall to the ground, but another to describe its motion as 1/2at^2 + vt.
- tux3 9y ago
  They did announce that they would release a teaching tool which will show AlphaGo's analysis of Go positions, as well as the paper explaining how to build your own. Not only do you have the principle and the formula behind it, but also a little physics simulator tool! At this point, it is hard to complain.
  - gwern 9y ago
    > At this point, it is hard to complain. Actually, it's very easy to complain. If they released the model, people could generate arbitrarily many self-play games instead of depending on DM to release 50, could create arbitrarily many tools using the model instead of depending on DM to create and maintain a single tool, and could verify the results of training a clone based on even sketchy descriptions of the methods instead of depending on DM releasing a detailed enough whitepaper and then guessing at whether a reimplementation is competitive or not. DM is only being 'generous' if you ignore how releasing the model is easier for them and superior for us in every way.
    - espadrine 9y ago
      > people could generate arbitrarily many self-play games I have doubts. Their TPU design may be a large factor into making matches at this level within the time limits. And at this point, some implementation details might hook into Google-specific libraries that require the ability to spawn processes in thousands of servers, which past blog posts[0] have hinted at. [0]: https://deepmind.com/blog/decoupled-neural-networks-using-synthetic-gradients/ https://deepmind.com/blog/decoupled-neural-networks-using-sy...
      - gwern 9y ago
        There might be some hard to release infrastructure code for the MCTS part, certainly, but the model on its own should be a standard TF CNN model and highly competitive (and people can write their own MCTS wrapper, it's not that complex an algorithm). Nothing in the AG paper or statements since has hinted at using anything as exotic as synthetic gradients* and there is no reason to use synthetic gradients in AG. (In RL applications the NNs are generally small because there's so little supervision from the rewards so a large NN would overfit grossly; a NN so large as to require synthetic gradients to be split across GPUs would be simply catastrophicly bad. Plus, the input of a 19x19 board, a few planes of metadata, and other details encapsulating the state is small compared to many applications like image labeling, further reducing the benefits of size. Silver has said AG is now 40 layers but that's not much compared to the 1000-layer Resnet monsters and even those 40 layers are probably going to be thin layers, since it's the depth which provides more serial computation equivalence, not width, making for a model with relatively few parameters overall.) * I find synthetic gradients super cool and I've been reading DM papers closely for hints of its use anywhere and have been disappointed how the idea doesn't appear to be going anywhere. The only followup so far has been https://arxiv.org/abs/1703.00522 https://arxiv.org/abs/1703.00522 which is more of a dissection and further explanation of the original paper than an extension or application.
      - visarga 9y ago
        They could just release the trained nets and let us re-scale the code. Even without a large MCTS it is still powerful.
    - rojobuffalo 9y ago
      DeepMind's mission is to build AGI. I think it's probably good if they have a buffered lead on all other efforts. That concern probably weighs on decisions about releasing code. The rationale for why a buffer would be good is described by Demis Hassabis here: https://youtu.be/h0962biiZa4?t=11m24s https://youtu.be/h0962biiZa4?t=11m24s ...the main points are: there may be safety considerations along the way that are costly. More "capitalistic" organizations may decide to shortcut those costs because of the winner-take-all scenario. DeepMind is at least nominally very committed to safety. Releasing AlphaGo's source code would probably reduce DeepMind's buffer, which in theory, would also reduce safety.
      - gwern 9y ago
        That would require some radically inconsistent thinking on their part. DM does occasionally release source code and trained models for other things, and the arms race logic (https://www.fhi.ox.ac.uk/wp-content/uploads/Racing-to-the-precipice-a-model-of-artificial-intelligence-development.pdf https://www.fhi.ox.ac.uk/wp-content/uploads/Racing-to-the-pr...) would even more strongly argue for not releasing anything, even research (they're privately owned, they don't have to publish squat), and especially not running stunts like the AlphaGo tournament which cost millions of dollars in order to terrify and impress competitors and heat up the arms race. A more parsimonious explanation is simply that it's great PR to maintain rigid control over the family jewels and dribble out occasional sample games and bits and pieces while pretending to be generous. (No one has ever accused Hassabis of being bad at PR or not knowing how to milk the media.)
        johnsmith21006 9y ago
        I am constantly amazed what Google shares. They are a company with shareholders to be fair.
- adyavanapalli 9y ago
  "We plan to publish one final academic paper later this year that will detail the extensive set of improvements we made to the algorithms’ efficiency and potential to be generalised across a broader set of problems." Should be enough, no?
  - lossolo 9y ago
    Depends what you look for. Most of ML papers do not disclose weights/models that they used or all details needed to make fully reproducible solution. Doesn't seem like this will change this time.
    - skybrian 9y ago
      There are other Go playing programs and they've apparently improved a lot by applying ideas from the original AlphaGo paper. It seems reasonable to assume they will improve more based on ideas from the new paper too, and probably surpass AlphaGo before too long. (Similarly, Deep Blue was dismantled but chess engines continued to evolve.)
- chillydawg 9y ago
  They're also publishing later in the year with all the details.
  - Radim 9y ago
    Publications never have "all the details".
- tim333 9y ago
  Though if they released the code Tencent would incorporate it in their rival so I can see the argument for delaying a bit.
  - cjbprime 9y ago
    If it's retired from competitive play, it no longer has a rival.
binarymax 9y ago
I remember vividly in 1997 when Deep Blue defeated Kasparov, and I was a competitive chess player. The mystique of the game was immediately lost for me, and I never found the passion for the game that I once had. My heart goes out to the sea of Go players now searching for meaning in the game. At the very least we can take this signal as a true indicator that our world is close to being completely upheaved by intelligent machines, in all areas of intellectual pursuit.
- blazespin 9y ago
  Bit hyperbolic. Go at it's heart is a pretty basic game, just tricky combinatorics. The fact that you can do unsupervised learning simplifies it even more. I think there are much better true indicators, such as better translation, speech to text, auto driving, etc.
  - jacquesm 9y ago
    > Go at it's heart is a pretty basic game, just tricky combinatorics. This goes for every turn based game and a lot of card games as well. If you just had perfect memory you'd be a formidable chess and cards player.
    - gabrielgoh 9y ago
      in a way, life is just a simple game with tricky combinatorics, and fairly trivial to attack with the tools of unsupervised learning.
      - panic 9y ago
        Life isn't simple in the way these games are. The choices you have in life aren't clear, and neither is what will happen once you make them.
        Tar90 9y ago
        Plus, these games are deterministic, whereas everything in life is a stochastic process.
candiodari 9y ago
It's scary how coverage of this match in China, which is extensive, actually manages to censor the association between Deepmind and Google.
- oska 9y ago
  The microphones used in the post match discussion featured the name “Google” quite prominently. I imagine that was a negotiated detail.
  - candiodari 9y ago
    There's different post match discussions.
placebo 9y ago
I find it interesting that AlphaGo improves its play by playing against itself. I wonder what the limits of this are.
- paulsutter 9y ago
  In RL you have two modes, "explore" and "exploit". In explore mode it doesn't always select the best known move, instead it selects a promising move for which it has less experience. This is how the surprising new strategies are discovered, in self play there's no shame in losing.
wiz21c 9y ago
The gift Google makes to the community (some games AlphaGo,played ) is nothing. The super tricky thing with neural networks is that you can't reverse engineer them. Once the information is coded into the parameters, you can't base anything useful on them. So it's a super good intellectual property protection... Therefore one more nail in the coffin of knowledge sharing as we know it...
- yeukhon 9y ago
  Most importanly, it is almost inevitable they must run on a fam of computers basically mean it becomes a service. Can we ever create a robot who can self-learn but with the super brain power locally without having to call a service for an answer?
  - wiz21c 9y ago
    This raises a question for me : is there currently some public infrastructure that can rival with AlphaGo ?
    - yeukhon 9y ago
      Public means API? AlphaGo is very specialized in solving Go game. Google, Amazon and IBM have services for various services like image recongition and speech recongition. Startups like Clarifi also exists in that space. The closest to a generalized AI service would probably be Watson from IBM (but I don't have experiment with it sadly so I am not sure about the usage experience).
      - nl 9y ago
        > The closest to a generalized AI service would probably be Watson from IBM Ha ha ha!
        doktrin 9y ago
        >> The closest to a generalized AI service would probably be Watson from IBM > Ha ha ha! can you expand on that for those of us who don't know much about the field?
mark_l_watson 9y ago
The 10 AlphaGo vs. AlphaGo games are a nice gift! I have always liked playing through great games, both Chess (using the book The Golden Dozen) and Go (modern games and the ancient Shogun Castle games). I have some history with computer Go. In the late 1970s I wrote a Go playing program in UCSD Pascal that I sold for the Apple II, and also for a lot more money I sold the source code to a few people who wanted to experiment with it. DeepMind's AlphaGo is a great intellectual and technological triumph and I agree that it is an example of future AIs teaching us and working with us. A little off topic, but Peter Norvig gave a nice talk a few weeks ago at the NYC Lisp Users Group where he talked about the future of collaboration with AIs and also that the ability to work effectively with AIs, adding human insights, will be an important future job skill.
- oska 9y ago
  Do you know if there's video or audio of Peter's talk online? I just did a bit of a search but couldn't find it.
  - mark_l_watson 9y ago
    https://vimeo.com/215418110 https://vimeo.com/215418110 Enjoy!
codecamper 9y ago
"We have always believed in the potential for AI to help society discover new knowledge and benefit from it" Get real. You do this for your own intellectual gain. Google does it for financial gain. Meanwhile, Antarctica may crumble. How about putting effort into solving THAT problem, with all your technology & knowhow Google?
- deleted 9y ago
  [deleted]
- sowbug 9y ago
  https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/155/Relative-Privation https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFalla...
Entangled 9y ago
I'd like to see public competitions between two AI giants like Google and IBM. Now that would be an interesting ongoing race for AI superiority.
fiatjaf 9y ago
If your AI is so great you should do some deep learning thing to explain the AlphaGo moves.
nopinsight 9y ago
One common comment from Go players at all levels up to 9-dan pros is that they don't understand many of the moves. The same will happen as more and more advanced AIs are used in the real world. Yes, we do not completely understand the workings of current advanced neural networks either but the effects are still contained as they are not general enough to cause unintended impact outside their domains. This could have started to change: a recent Google paper, AutoML, allows the machines to design themselves to suit each task. [1] A future advance could allow the machines to pick and learn to do new tasks that are helpful to accomplish a given high level mission. Therefore, chances of unintended consequences become much greater. With human involvement only at the meta level, deep understanding of the generated implementations becomes more challenging and, in highly complex domains, perhaps impossible. The major issue is, without a moral core that closely aligns with humanity's evolved morality, there will be moves that advanced AIs come up with that we deem abhorrent, and sometimes unforeseeable, yet they perform them innocently and we only find out the consequences once it is too late. [1] https://research.googleblog.com/2017/05/using-machine-learning-to-explore.html https://research.googleblog.com/2017/05/using-machine-learni...
- m3kw9 9y ago
  They don't understand the move probably the AI has a memory depth that is way beyond any human, some of those moves are the best possible look aheads for that situation
- skybrian 9y ago
  They don't fully understand the moves but on the other hand, the live commentary on the games suggests it's not completely mysterious. Good moves still tend to look good to them, in retrospect at least. The games are apparently very interesting to study.
  - AndyNemmity 9y ago
    Against a human, the games look fairly straight forward. From what they've released against itself, the games look like a different game. Especially at times, Game 2 in the current crop for example.
temp_12345 9y ago
So, a question bordering on the philosophical : What can be done to prepare for the end of human supremacy, and quite likely human civilization? For instance, as a software developer it feels almost pointless to continue improving at my craft if AI systems will surpass me within 2-4 years (even if the pessimists are right about it taking 5-10 years, that's still an awfully small timeframe). Likewise, it feels a little pointless to work on any endeavor - technical or otherwise - including but not limited to AI research itself. From a purely practical standpoint just getting up to speed on AI research will take a solid 5+ years, and from a moral vantage point I'm not sure that's even a defensible career given the obvious and hugely negative implications that field will have for human civilization. Even in artistic endeavors, humans will soon be second fiddle to our own creations - so it's not like there's any "point" to starting down that path either. Is it time to just engage in a hedonistic, nihilistic, fest of gluttony and "fun" while that's still possible? Honestly, news like this just makes me consider ending it all : it feels like none of us will have much of a future before long.
- tim333 9y ago
  Well, firstly AI outdoing us in software development is going to take a while, probably >10 years. Secondly you're looking mostly at the negatives but not positives of AI advancing. Some of those: We will likely use AI to enhance ourselves rather than just have it take over. Such merging may lead to the end of death. At the moment sure you can develop away then age and die - the AI thing may be jollier. Robots at some stage will be able to do the work so you should be able to have a hedonistic gluttony fest it that's your thing.
  - visarga 9y ago
    Also, we'll get to use amazing AI tools in our projects. That should create a lot work opportunity, even for non-AI experts.
- rubidium 9y ago
  You need to get out of whatever bubble you're living in. Human civilization is doing fine. Machine learning will do some stuff but not major changes at the civilization level in the next 40 years. Walk into any real world business today. There's a huge amount of need for humans, because fundamentally business is about trust not productivity.
deleted 9y ago
[deleted]
cocktailpeanuts 9y ago
There was a time not too far back when people used to be considered a "genius" for their ability to memorize things well. Nowadays nobody thinks of them as geniuses. Also, people used to be considered geniuses for knowing a lot of things. Nowadays information is just a Google search away, so knowing a lot doesn't really mean as much as it used to. What matters more nowadays is your ability to learn synthesize the things you know to come up with creative solutions to things. Basically the "memory" part of human brains have become commoditized without us even realizing. It's still very early but I do think there have been some subtle but significant step forward in the last couple of years. The most important being: machines are capable of doing certain things better in ways humans can't comprehend easily. I think this is a glimpse into the future where the "creativity" aspect of our brains will become commoditized, also without us realizing. This doesn't mean machines will take over, just like machines didn't take over the world because they have better memory. But I think this will result in many humans taking advantage of this aspect to exert influence on rest of the humanity.
- abhi3 9y ago
  >Nowadays information is just a Google search away Knowing what is credible and what is not on the internet is a skill in itself. If you don't have that skill you'd likely be telling people all about how Bush did 9/11 or how hillary killed a DNC employee.
  - rcpt 9y ago
    That part can be automated to. See https://fullfact.org/blog/2016/aug/automated-factchecking/ https://fullfact.org/blog/2016/aug/automated-factchecking/ for example
- andrepd 9y ago
  > Also, people used to be considered geniuses for knowing a lot of things. This is still true, and in the eagerness to dismiss "memorization" as a thing of the past you overlook the obvious. For example, anything you care to know about, say, C++ programming or quantum field theory is available to you on the internet. But does that mean you can write a C++ program as if you had already learned it? What if you want to write a C++ program and you have to look up everything? You will do a very poor job if at all, and you will take a lot of time. So yeah, until looking up stuff in the internet is as quick as effective as looking stuff up in your brain (the quick may happen but the effective I don't think so), then it still is a very worthy skill.
theptip 9y ago
> We plan to publish one final academic paper later this year that will detail the extensive set of improvements we made to the algorithms’ efficiency and potential to be generalised across a broader set of problems. I'm fascinated to see what the next step for this AI is. Anyone care to speculate what a system like this could most readily be applied to?
Houshalter 9y ago
My browser just shows me a blank page.
yters 9y ago
The problem is an AI that is good at Go is not at all transferable to any other game. However, a human prodigy can apply their genius to many domains.
- reckoner2 9y ago
  > However, a human prodigy can apply their genius to many domains I'm not sure how true this is. It's pretty rare to find someone who is a genius in more than one domain. Einstein was famously offered the presidency of Israel. Sure, he could probably do well in other sciences, but he was smart enough to know he could not apply his genius to unrelated domains.
  - yters 9y ago
    Of course there is domain knowledge that needs to be learned, along with non intelligence related characteristics, such as personality. But general intelligence appears to be widely applicable.

285 points by bjin 9y ago

Congratulations to Deepmind and Google for this tremendous achievement. However, it is disappointing that the code and model will not be released publicly after Alphago finishes competitive play. It's one thing to say that an apple, once dropped, will fall to the ground, but another to describe its motion as 1/2at^2 + vt.

tux3 9y ago
They did announce that they would release a teaching tool which will show AlphaGo's analysis of Go positions, as well as the paper explaining how to build your own. Not only do you have the principle and the formula behind it, but also a little physics simulator tool! At this point, it is hard to complain.
- gwern 9y ago
  > At this point, it is hard to complain. Actually, it's very easy to complain. If they released the model, people could generate arbitrarily many self-play games instead of depending on DM to release 50, could create arbitrarily many tools using the model instead of depending on DM to create and maintain a single tool, and could verify the results of training a clone based on even sketchy descriptions of the methods instead of depending on DM releasing a detailed enough whitepaper and then guessing at whether a reimplementation is competitive or not. DM is only being 'generous' if you ignore how releasing the model is easier for them and superior for us in every way.
  - espadrine 9y ago
    > people could generate arbitrarily many self-play games I have doubts. Their TPU design may be a large factor into making matches at this level within the time limits. And at this point, some implementation details might hook into Google-specific libraries that require the ability to spawn processes in thousands of servers, which past blog posts[0] have hinted at. [0]: https://deepmind.com/blog/decoupled-neural-networks-using-synthetic-gradients/ https://deepmind.com/blog/decoupled-neural-networks-using-sy...
    - gwern 9y ago
      There might be some hard to release infrastructure code for the MCTS part, certainly, but the model on its own should be a standard TF CNN model and highly competitive (and people can write their own MCTS wrapper, it's not that complex an algorithm). Nothing in the AG paper or statements since has hinted at using anything as exotic as synthetic gradients* and there is no reason to use synthetic gradients in AG. (In RL applications the NNs are generally small because there's so little supervision from the rewards so a large NN would overfit grossly; a NN so large as to require synthetic gradients to be split across GPUs would be simply catastrophicly bad. Plus, the input of a 19x19 board, a few planes of metadata, and other details encapsulating the state is small compared to many applications like image labeling, further reducing the benefits of size. Silver has said AG is now 40 layers but that's not much compared to the 1000-layer Resnet monsters and even those 40 layers are probably going to be thin layers, since it's the depth which provides more serial computation equivalence, not width, making for a model with relatively few parameters overall.) * I find synthetic gradients super cool and I've been reading DM papers closely for hints of its use anywhere and have been disappointed how the idea doesn't appear to be going anywhere. The only followup so far has been https://arxiv.org/abs/1703.00522 https://arxiv.org/abs/1703.00522 which is more of a dissection and further explanation of the original paper than an extension or application.
    - visarga 9y ago
      They could just release the trained nets and let us re-scale the code. Even without a large MCTS it is still powerful.
  - rojobuffalo 9y ago
    DeepMind's mission is to build AGI. I think it's probably good if they have a buffered lead on all other efforts. That concern probably weighs on decisions about releasing code. The rationale for why a buffer would be good is described by Demis Hassabis here: https://youtu.be/h0962biiZa4?t=11m24s https://youtu.be/h0962biiZa4?t=11m24s ...the main points are: there may be safety considerations along the way that are costly. More "capitalistic" organizations may decide to shortcut those costs because of the winner-take-all scenario. DeepMind is at least nominally very committed to safety. Releasing AlphaGo's source code would probably reduce DeepMind's buffer, which in theory, would also reduce safety.
    - gwern 9y ago
      That would require some radically inconsistent thinking on their part. DM does occasionally release source code and trained models for other things, and the arms race logic (https://www.fhi.ox.ac.uk/wp-content/uploads/Racing-to-the-precipice-a-model-of-artificial-intelligence-development.pdf https://www.fhi.ox.ac.uk/wp-content/uploads/Racing-to-the-pr...) would even more strongly argue for not releasing anything, even research (they're privately owned, they don't have to publish squat), and especially not running stunts like the AlphaGo tournament which cost millions of dollars in order to terrify and impress competitors and heat up the arms race. A more parsimonious explanation is simply that it's great PR to maintain rigid control over the family jewels and dribble out occasional sample games and bits and pieces while pretending to be generous. (No one has ever accused Hassabis of being bad at PR or not knowing how to milk the media.)
      - johnsmith21006 9y ago
        I am constantly amazed what Google shares. They are a company with shareholders to be fair.
adyavanapalli 9y ago
"We plan to publish one final academic paper later this year that will detail the extensive set of improvements we made to the algorithms’ efficiency and potential to be generalised across a broader set of problems." Should be enough, no?
- lossolo 9y ago
  Depends what you look for. Most of ML papers do not disclose weights/models that they used or all details needed to make fully reproducible solution. Doesn't seem like this will change this time.
  - skybrian 9y ago
    There are other Go playing programs and they've apparently improved a lot by applying ideas from the original AlphaGo paper. It seems reasonable to assume they will improve more based on ideas from the new paper too, and probably surpass AlphaGo before too long. (Similarly, Deep Blue was dismantled but chess engines continued to evolve.)
chillydawg 9y ago
They're also publishing later in the year with all the details.
- Radim 9y ago
  Publications never have "all the details".
tim333 9y ago
Though if they released the code Tencent would incorporate it in their rival so I can see the argument for delaying a bit.
- cjbprime 9y ago
  If it's retired from competitive play, it no longer has a rival.

binarymax 9y ago

I remember vividly in 1997 when Deep Blue defeated Kasparov, and I was a competitive chess player. The mystique of the game was immediately lost for me, and I never found the passion for the game that I once had. My heart goes out to the sea of Go players now searching for meaning in the game. At the very least we can take this signal as a true indicator that our world is close to being completely upheaved by intelligent machines, in all areas of intellectual pursuit.

blazespin 9y ago
Bit hyperbolic. Go at it's heart is a pretty basic game, just tricky combinatorics. The fact that you can do unsupervised learning simplifies it even more. I think there are much better true indicators, such as better translation, speech to text, auto driving, etc.
- jacquesm 9y ago
  > Go at it's heart is a pretty basic game, just tricky combinatorics. This goes for every turn based game and a lot of card games as well. If you just had perfect memory you'd be a formidable chess and cards player.
  - gabrielgoh 9y ago
    in a way, life is just a simple game with tricky combinatorics, and fairly trivial to attack with the tools of unsupervised learning.
    - panic 9y ago
      Life isn't simple in the way these games are. The choices you have in life aren't clear, and neither is what will happen once you make them.
      - Tar90 9y ago
        Plus, these games are deterministic, whereas everything in life is a stochastic process.

candiodari 9y ago

It's scary how coverage of this match in China, which is extensive, actually manages to censor the association between Deepmind and Google.

oska 9y ago
The microphones used in the post match discussion featured the name “Google” quite prominently. I imagine that was a negotiated detail.
- candiodari 9y ago
  There's different post match discussions.

placebo 9y ago

I find it interesting that AlphaGo improves its play by playing against itself. I wonder what the limits of this are.

paulsutter 9y ago
In RL you have two modes, "explore" and "exploit". In explore mode it doesn't always select the best known move, instead it selects a promising move for which it has less experience. This is how the surprising new strategies are discovered, in self play there's no shame in losing.

wiz21c 9y ago

The gift Google makes to the community (some games AlphaGo,played ) is nothing. The super tricky thing with neural networks is that you can't reverse engineer them. Once the information is coded into the parameters, you can't base anything useful on them. So it's a super good intellectual property protection... Therefore one more nail in the coffin of knowledge sharing as we know it...

yeukhon 9y ago
Most importanly, it is almost inevitable they must run on a fam of computers basically mean it becomes a service. Can we ever create a robot who can self-learn but with the super brain power locally without having to call a service for an answer?
- wiz21c 9y ago
  This raises a question for me : is there currently some public infrastructure that can rival with AlphaGo ?
  - yeukhon 9y ago
    Public means API? AlphaGo is very specialized in solving Go game. Google, Amazon and IBM have services for various services like image recongition and speech recongition. Startups like Clarifi also exists in that space. The closest to a generalized AI service would probably be Watson from IBM (but I don't have experiment with it sadly so I am not sure about the usage experience).
    - nl 9y ago
      > The closest to a generalized AI service would probably be Watson from IBM Ha ha ha!
      - doktrin 9y ago
        >> The closest to a generalized AI service would probably be Watson from IBM > Ha ha ha! can you expand on that for those of us who don't know much about the field?

mark_l_watson 9y ago

The 10 AlphaGo vs. AlphaGo games are a nice gift! I have always liked playing through great games, both Chess (using the book The Golden Dozen) and Go (modern games and the ancient Shogun Castle games). I have some history with computer Go. In the late 1970s I wrote a Go playing program in UCSD Pascal that I sold for the Apple II, and also for a lot more money I sold the source code to a few people who wanted to experiment with it. DeepMind's AlphaGo is a great intellectual and technological triumph and I agree that it is an example of future AIs teaching us and working with us. A little off topic, but Peter Norvig gave a nice talk a few weeks ago at the NYC Lisp Users Group where he talked about the future of collaboration with AIs and also that the ability to work effectively with AIs, adding human insights, will be an important future job skill.

oska 9y ago
Do you know if there's video or audio of Peter's talk online? I just did a bit of a search but couldn't find it.
- mark_l_watson 9y ago
  https://vimeo.com/215418110 https://vimeo.com/215418110 Enjoy!

codecamper 9y ago

"We have always believed in the potential for AI to help society discover new knowledge and benefit from it" Get real. You do this for your own intellectual gain. Google does it for financial gain. Meanwhile, Antarctica may crumble. How about putting effort into solving THAT problem, with all your technology & knowhow Google?

deleted 9y ago
[deleted]
sowbug 9y ago
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/155/Relative-Privation https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFalla...

Entangled 9y ago

I'd like to see public competitions between two AI giants like Google and IBM. Now that would be an interesting ongoing race for AI superiority.

fiatjaf 9y ago

If your AI is so great you should do some deep learning thing to explain the AlphaGo moves.

nopinsight 9y ago

One common comment from Go players at all levels up to 9-dan pros is that they don't understand many of the moves. The same will happen as more and more advanced AIs are used in the real world. Yes, we do not completely understand the workings of current advanced neural networks either but the effects are still contained as they are not general enough to cause unintended impact outside their domains. This could have started to change: a recent Google paper, AutoML, allows the machines to design themselves to suit each task. [1] A future advance could allow the machines to pick and learn to do new tasks that are helpful to accomplish a given high level mission. Therefore, chances of unintended consequences become much greater. With human involvement only at the meta level, deep understanding of the generated implementations becomes more challenging and, in highly complex domains, perhaps impossible. The major issue is, without a moral core that closely aligns with humanity's evolved morality, there will be moves that advanced AIs come up with that we deem abhorrent, and sometimes unforeseeable, yet they perform them innocently and we only find out the consequences once it is too late. [1] https://research.googleblog.com/2017/05/using-machine-learning-to-explore.html https://research.googleblog.com/2017/05/using-machine-learni...

m3kw9 9y ago
They don't understand the move probably the AI has a memory depth that is way beyond any human, some of those moves are the best possible look aheads for that situation
skybrian 9y ago
They don't fully understand the moves but on the other hand, the live commentary on the games suggests it's not completely mysterious. Good moves still tend to look good to them, in retrospect at least. The games are apparently very interesting to study.
- AndyNemmity 9y ago
  Against a human, the games look fairly straight forward. From what they've released against itself, the games look like a different game. Especially at times, Game 2 in the current crop for example.

temp_12345 9y ago

So, a question bordering on the philosophical : What can be done to prepare for the end of human supremacy, and quite likely human civilization? For instance, as a software developer it feels almost pointless to continue improving at my craft if AI systems will surpass me within 2-4 years (even if the pessimists are right about it taking 5-10 years, that's still an awfully small timeframe). Likewise, it feels a little pointless to work on any endeavor - technical or otherwise - including but not limited to AI research itself. From a purely practical standpoint just getting up to speed on AI research will take a solid 5+ years, and from a moral vantage point I'm not sure that's even a defensible career given the obvious and hugely negative implications that field will have for human civilization. Even in artistic endeavors, humans will soon be second fiddle to our own creations - so it's not like there's any "point" to starting down that path either. Is it time to just engage in a hedonistic, nihilistic, fest of gluttony and "fun" while that's still possible? Honestly, news like this just makes me consider ending it all : it feels like none of us will have much of a future before long.

tim333 9y ago
Well, firstly AI outdoing us in software development is going to take a while, probably >10 years. Secondly you're looking mostly at the negatives but not positives of AI advancing. Some of those: We will likely use AI to enhance ourselves rather than just have it take over. Such merging may lead to the end of death. At the moment sure you can develop away then age and die - the AI thing may be jollier. Robots at some stage will be able to do the work so you should be able to have a hedonistic gluttony fest it that's your thing.
- visarga 9y ago
  Also, we'll get to use amazing AI tools in our projects. That should create a lot work opportunity, even for non-AI experts.
rubidium 9y ago
You need to get out of whatever bubble you're living in. Human civilization is doing fine. Machine learning will do some stuff but not major changes at the civilization level in the next 40 years. Walk into any real world business today. There's a huge amount of need for humans, because fundamentally business is about trust not productivity.

deleted 9y ago

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cocktailpeanuts 9y ago

There was a time not too far back when people used to be considered a "genius" for their ability to memorize things well. Nowadays nobody thinks of them as geniuses. Also, people used to be considered geniuses for knowing a lot of things. Nowadays information is just a Google search away, so knowing a lot doesn't really mean as much as it used to. What matters more nowadays is your ability to learn synthesize the things you know to come up with creative solutions to things. Basically the "memory" part of human brains have become commoditized without us even realizing. It's still very early but I do think there have been some subtle but significant step forward in the last couple of years. The most important being: machines are capable of doing certain things better in ways humans can't comprehend easily. I think this is a glimpse into the future where the "creativity" aspect of our brains will become commoditized, also without us realizing. This doesn't mean machines will take over, just like machines didn't take over the world because they have better memory. But I think this will result in many humans taking advantage of this aspect to exert influence on rest of the humanity.

abhi3 9y ago
>Nowadays information is just a Google search away Knowing what is credible and what is not on the internet is a skill in itself. If you don't have that skill you'd likely be telling people all about how Bush did 9/11 or how hillary killed a DNC employee.
- rcpt 9y ago
  That part can be automated to. See https://fullfact.org/blog/2016/aug/automated-factchecking/ https://fullfact.org/blog/2016/aug/automated-factchecking/ for example
andrepd 9y ago
> Also, people used to be considered geniuses for knowing a lot of things. This is still true, and in the eagerness to dismiss "memorization" as a thing of the past you overlook the obvious. For example, anything you care to know about, say, C++ programming or quantum field theory is available to you on the internet. But does that mean you can write a C++ program as if you had already learned it? What if you want to write a C++ program and you have to look up everything? You will do a very poor job if at all, and you will take a lot of time. So yeah, until looking up stuff in the internet is as quick as effective as looking stuff up in your brain (the quick may happen but the effective I don't think so), then it still is a very worthy skill.

theptip 9y ago

> We plan to publish one final academic paper later this year that will detail the extensive set of improvements we made to the algorithms’ efficiency and potential to be generalised across a broader set of problems. I'm fascinated to see what the next step for this AI is. Anyone care to speculate what a system like this could most readily be applied to?

Houshalter 9y ago

My browser just shows me a blank page.

yters 9y ago

The problem is an AI that is good at Go is not at all transferable to any other game. However, a human prodigy can apply their genius to many domains.

reckoner2 9y ago
> However, a human prodigy can apply their genius to many domains I'm not sure how true this is. It's pretty rare to find someone who is a genius in more than one domain. Einstein was famously offered the presidency of Israel. Sure, he could probably do well in other sciences, but he was smart enough to know he could not apply his genius to unrelated domains.
- yters 9y ago
  Of course there is domain knowledge that needs to be learned, along with non intelligence related characteristics, such as personality. But general intelligence appears to be widely applicable.