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Every year or so we get another huge advance... Well, more accurately, something comes along to benchmark the state of AI research against a human activity. Th

by ctoth 8y ago

Every year or so we get another huge advance... Well, more accurately, something comes along to benchmark the state of AI research against a human activity. Then come the HN comments. For Alpha Go: Oh this is impressive but can't generalize. Wake me up when it doesn't have to have information precoded/doesn't learn from human players For alpha go 0: So this is cool but not amazing because they're all perfect information games. And now here we have this, and people who haven't even watched the presentation are yammering about stuff like the APM, or how this isn't impressive because of ... Well, something? If I believed in a terminator scenario, I would point out that a robot, too, will presumably have higher APM than all of us desk warriors. It really feels like there are just some people who are religiously attached to being the only known intelligent entities on the planet, to the point where, when presented with evidence that hey, this is actually a thing, they will stick their fingers in their ears and shout about how unreal/unfair it all is. I invite you to have a look back at the other announcement threads from Deepmind and OpenAI. I decided not to directly quote people as I don't want this to get personal, but I couldn't just sit here and watch the same old story play out again without at least mentioning that these same people have been wrong, and wrong, and wrong, and will presumably continue to be wrong. Exponential curves are unintuitive.

noir_lord 8y ago
I've heard what you said more pithily put as "true AI is anything we can't make a computer do right now".
scarmig 8y ago
What does it matter, at this point? The proof is in the pudding, and we are making more and more pudding everyday. Instead of caring about naysayers, we need to be working under the assumption AI is here to stay and rapidly expanding in scope, and we need to build the social and political structures to be able to handle it.
- setr 8y ago
  >we need to build the social and political structures to be able to handle it. This would be a massive waste of resources depending on how far you misinterpret the nature of the “AI thats here to stay”. There is little to support that we’re near-approaching a general purpose, “true” AI, the kind of superintelligent, creative, potentially world-ending and self-improving thinking machine that brings us to the singularity. Its much fairer to characterize current technologies as an algorithm that excels in certain fields, with distinct limitations that we’re still exploring, and have some idea but not perfect of where those limits are. Functionally, they just find probabilities matrixes for a certain sequence of actions, and can search the problem space much faster than we did before, by simulating the event indefinitely. And they come with the issue that anything that can’t be well-simulated and quickly can’t be “AI’d”, as well as the common issue of catastrophically failing due to not actually understanding the object in total (eg change a picture of a cat to an ostrich by editing key pixels). And afaik, they’ve shown no ability to “change the problem”, a key component of creativity (if you can’t find a good answer to something, consider changing the question; our “AI”s do not.) And this is naturally why they excel at games (almost by definition a repeatedable simulation) that typically have a very well-defined question. But at the same time, we don’t expect current AI to be capable of taking its “strategies” forward to the next update of starcraft (the problem changes) without re-searching a lot of the problem space (there exist algorithms for training future networks; I don’t know how much progress they’ve made), because they don’t really have strategies in the first place, or a real model for how things interact (they struggle to predict new interactions without sinulating them, or rather, “experiencing” them). Which is also why its difficult to imagine AI’s will ever truly be driving cars around with the current tech — rather, they’ll succeed likely as an awkward combination of nueral networks, expert systems, hueristics and safeguards. We’d naturally expect most sci-fi usecases of AI to be the same — eg political decision making. And they’ll be limited to the extent that we can render simulations. And if we pretend these distinctly limited algorithms are in fact the predecessors to our post-singularity successors, simply because they’re able to do a few things we weren’t really expecting (just as computers have proved to be a whole lot more capable than the 60’s general population thought, but far less than what 60’s scifi thought), we’ll do a whole lot of work for quite a bit of nothing. The fact that its called AI doesn’t mean we’re quickly approaching star trek’s Data AI. It didn’t mean it in the last few AI hype cycles either.
- chronial 8y ago
  The saying is actually "The proof of the pudding is in the eating". I don't quite understand what "the proof is in the pudding" is supposed to mean and how that relates to making a lot of pudding ^^.
b_tterc_p 8y ago
It’s more so that the purpose of these tests is to see if the computer can strategize well. The result seems to be... not really, not yet at least. To take a terminator situation, sure the robot will be a lot better at gun fighting, but if we can kite it with trivial attacks to make it walk into an obvious trap (not really that different from what happens in Starcraft today) then it’s not so threatening. Nobody denies that machines are better at small tasks that are founded on reaction time, precise inputs, and wide span of attention. But the thing we’re trying to actually get them better at is strategic planning.
dilap 8y ago
It's extremely impressive, but at the same time it's still an interesting and fair question to say, "can we make an AI that beats humans while playing in a 'human like' fashion?", or alternatively, could we make an AI that would win if we put it inside a human body and made it play through those physical input restrictions? (I do agree though that HN is way too negative overall. Partly it's just because, negative comments are more interesting. "Hey, this is cool!" doesn't have too much content. Nitpicks give you something to talk about.) (Still, I've imagined a site where commenting is explicitly broken into two columns: Positive comments and critical comments. Then you could self-select to bask in the positivity for a bit before diving into the nitpicks.)
- kowdermeister 8y ago
  > "can we make an AI that beats humans while playing in a 'human like' fashion?" Yes, now. From the article: “I was impressed to see AlphaStar pull off advanced moves and different strategies across almost every game, using a very human style of gameplay I wouldn’t have expected,” he said. “I’ve realised how much my gameplay relies on forcing mistakes and being able to exploit human reactions, so this has put the game in a whole new light for me. We’re all excited to see what comes next.”
  - Buttons840 8y ago
    It was performing over 1000 pixel perfect (presumably) and meaningful actions a minute during fights. That's super-human.
andreyk 8y ago
Note that this approach is very dissimilar to Alpha Go or Alpha Go 0. So it's true that they did not generalize...
gambler 8y ago
When your algorithm needs to be changed to generalize, it does not generalize. If people stopped moving the goalposts and spreading baseless hype, actual AI research would be much father along right now.
- keerthiko 8y ago
  I don't think the algorithm is changing. The infrastructure, engineering, practice regimens and environments, the training data, the selection of metrics for success, are changing. One can say broadly they are part of the algorithm, but these are learnings for curators of AI that can easily be transferred to other spaces to "generalize" as well.
asdgionio2345 8y ago
I was impressed with DeepMind's work on Go and Chess. It seemed to truly grasp the strategy and "understand" the games better than any human, which is in stark contrast to previous engines that relied on brute-force tactical brilliance. AlphaStar plays like I'd expect a computer to play. It makes some very stupid decisions that suggest a lack of real "understanding" or strategic thinking, such as its wacky unit compositions, the packs of five observers moving around together, and its miserable response to the immortal drop in the last game. It won through superhuman multitasking and micro, which is where I'd expect it to shine. AlphaStar is, in some respects, awful at SC2.
- red75prime 8y ago
  We tend to think in hierarchical terms: tactics, strategy, and the like. It allows us to quickly create imperfect viable solutions. AlphaStar is probably lacking such distinction and sees the game as a sequence of actions. So it takes a lot more time for it to learn behavior patterns that we call strategy. I think after training for maybe 20 thousand in-game years it will have decent strategy, while still lacking a real "understanding" of what a strategy is. We probably will not see humanlike learning speed and adaptability before development of methods for learning hierarchical representations.

by ctoth 8y ago

noir_lord 8y ago

I've heard what you said more pithily put as "true AI is anything we can't make a computer do right now".

scarmig 8y ago

What does it matter, at this point? The proof is in the pudding, and we are making more and more pudding everyday. Instead of caring about naysayers, we need to be working under the assumption AI is here to stay and rapidly expanding in scope, and we need to build the social and political structures to be able to handle it.

setr 8y ago
>we need to build the social and political structures to be able to handle it. This would be a massive waste of resources depending on how far you misinterpret the nature of the “AI thats here to stay”. There is little to support that we’re near-approaching a general purpose, “true” AI, the kind of superintelligent, creative, potentially world-ending and self-improving thinking machine that brings us to the singularity. Its much fairer to characterize current technologies as an algorithm that excels in certain fields, with distinct limitations that we’re still exploring, and have some idea but not perfect of where those limits are. Functionally, they just find probabilities matrixes for a certain sequence of actions, and can search the problem space much faster than we did before, by simulating the event indefinitely. And they come with the issue that anything that can’t be well-simulated and quickly can’t be “AI’d”, as well as the common issue of catastrophically failing due to not actually understanding the object in total (eg change a picture of a cat to an ostrich by editing key pixels). And afaik, they’ve shown no ability to “change the problem”, a key component of creativity (if you can’t find a good answer to something, consider changing the question; our “AI”s do not.) And this is naturally why they excel at games (almost by definition a repeatedable simulation) that typically have a very well-defined question. But at the same time, we don’t expect current AI to be capable of taking its “strategies” forward to the next update of starcraft (the problem changes) without re-searching a lot of the problem space (there exist algorithms for training future networks; I don’t know how much progress they’ve made), because they don’t really have strategies in the first place, or a real model for how things interact (they struggle to predict new interactions without sinulating them, or rather, “experiencing” them). Which is also why its difficult to imagine AI’s will ever truly be driving cars around with the current tech — rather, they’ll succeed likely as an awkward combination of nueral networks, expert systems, hueristics and safeguards. We’d naturally expect most sci-fi usecases of AI to be the same — eg political decision making. And they’ll be limited to the extent that we can render simulations. And if we pretend these distinctly limited algorithms are in fact the predecessors to our post-singularity successors, simply because they’re able to do a few things we weren’t really expecting (just as computers have proved to be a whole lot more capable than the 60’s general population thought, but far less than what 60’s scifi thought), we’ll do a whole lot of work for quite a bit of nothing. The fact that its called AI doesn’t mean we’re quickly approaching star trek’s Data AI. It didn’t mean it in the last few AI hype cycles either.
chronial 8y ago
The saying is actually "The proof of the pudding is in the eating". I don't quite understand what "the proof is in the pudding" is supposed to mean and how that relates to making a lot of pudding ^^.

b_tterc_p 8y ago

It’s more so that the purpose of these tests is to see if the computer can strategize well. The result seems to be... not really, not yet at least. To take a terminator situation, sure the robot will be a lot better at gun fighting, but if we can kite it with trivial attacks to make it walk into an obvious trap (not really that different from what happens in Starcraft today) then it’s not so threatening. Nobody denies that machines are better at small tasks that are founded on reaction time, precise inputs, and wide span of attention. But the thing we’re trying to actually get them better at is strategic planning.

dilap 8y ago

It's extremely impressive, but at the same time it's still an interesting and fair question to say, "can we make an AI that beats humans while playing in a 'human like' fashion?", or alternatively, could we make an AI that would win if we put it inside a human body and made it play through those physical input restrictions? (I do agree though that HN is way too negative overall. Partly it's just because, negative comments are more interesting. "Hey, this is cool!" doesn't have too much content. Nitpicks give you something to talk about.) (Still, I've imagined a site where commenting is explicitly broken into two columns: Positive comments and critical comments. Then you could self-select to bask in the positivity for a bit before diving into the nitpicks.)

kowdermeister 8y ago
> "can we make an AI that beats humans while playing in a 'human like' fashion?" Yes, now. From the article: “I was impressed to see AlphaStar pull off advanced moves and different strategies across almost every game, using a very human style of gameplay I wouldn’t have expected,” he said. “I’ve realised how much my gameplay relies on forcing mistakes and being able to exploit human reactions, so this has put the game in a whole new light for me. We’re all excited to see what comes next.”
- Buttons840 8y ago
  It was performing over 1000 pixel perfect (presumably) and meaningful actions a minute during fights. That's super-human.

andreyk 8y ago

Note that this approach is very dissimilar to Alpha Go or Alpha Go 0. So it's true that they did not generalize...

gambler 8y ago

When your algorithm needs to be changed to generalize, it does not generalize. If people stopped moving the goalposts and spreading baseless hype, actual AI research would be much father along right now.

keerthiko 8y ago
I don't think the algorithm is changing. The infrastructure, engineering, practice regimens and environments, the training data, the selection of metrics for success, are changing. One can say broadly they are part of the algorithm, but these are learnings for curators of AI that can easily be transferred to other spaces to "generalize" as well.

asdgionio2345 8y ago

I was impressed with DeepMind's work on Go and Chess. It seemed to truly grasp the strategy and "understand" the games better than any human, which is in stark contrast to previous engines that relied on brute-force tactical brilliance. AlphaStar plays like I'd expect a computer to play. It makes some very stupid decisions that suggest a lack of real "understanding" or strategic thinking, such as its wacky unit compositions, the packs of five observers moving around together, and its miserable response to the immortal drop in the last game. It won through superhuman multitasking and micro, which is where I'd expect it to shine. AlphaStar is, in some respects, awful at SC2.

red75prime 8y ago
We tend to think in hierarchical terms: tactics, strategy, and the like. It allows us to quickly create imperfect viable solutions. AlphaStar is probably lacking such distinction and sees the game as a sequence of actions. So it takes a lot more time for it to learn behavior patterns that we call strategy. I think after training for maybe 20 thousand in-game years it will have decent strategy, while still lacking a real "understanding" of what a strategy is. We probably will not see humanlike learning speed and adaptability before development of methods for learning hierarchical representations.