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>there are no longer any well-defined tasks that a human can outperform a computer in. If by "well-defined" you mean "complete information", then yes. If by we

>there are no longer any well-defined tasks that a human can outperform a computer in. If by "well-defined" you mean "complete information", then yes. If by well-defined you mean... well-defined, then no. Humans are better at a lot of things still, including video games for example. OpenAI has been working for years on a DotA AI, and while very technologically interesting, it still can only play (well) with and against a fraction of heroes and mechanics, and even within those limitations humans have quickly been able to find weaknesses and outmaneuver it. AI really hasn't over the last 5 years (and probably won't during the next 5) changed the world that much. There are some problem domains that saw big interesting leaps (mainly image recognition, image reconstruction and game AI), but that's about it. Self-driving cars, if they ever come to market properly, will be the biggest change. And that's certainly a big change, but it's not really the "software industry revolutionizing" change that some people seem to expect.

roenxi 7y ago
I'm surprised by your example; OpenAI has basically shown that humans can't compete at DotA. The bot outperformed humans in an unusual but reasonable restricted version of the game and it is obvious that it would do just as well at the full game excepting that OpenAI didn't have the stomach to try and tackle the engineering challenge for no reward. They weren't even trying to abuse the reaction time of the computer, or train one agent to coordinate a team as one entity. There isn't really a question; if humans needed to win games of DotA for some reason we'd send machines. It just happens that DotA is a spectator sport and that would be boring. Exploiting the AI ... maybe? The experience with AlphaGo is that peak computer performance is just going to be better than peak human performance. Dota isn't fundamentally more complicated than Go. A few orders of magnitude harder to engineer, but OpenAI's work suggests they're about 20% of the way through a 10 year process and they've covered the interesting parts - so they stopped. With more resourcing that could be solved quickly but it isn't enough of a challenge any more. There isn't anything left to prove in DotA. Bots can play the game really well and would crush humans if it was important to anyone. Nobody cares enough to actually finish the project but if there was money on the line it is obvious how it would play out.
- pingyong 7y ago
  >it is obvious that it would do just as well at the full game excepting that OpenAI didn't have the stomach to try and tackle the engineering challenge for no reward. That's an interesting interpretation. My interpretation is that they simply weren't able to do it yet (not for a lack of trying though), and so they gave up. It's not obvious at all to me that there is a way to simply scale their approach to the real game. I mean, certainly there is a way with infinite computing power, but it's not clear to me that even with all the computing power on earth currently this approach would work. 18 out of 117 heroes does reduce complexity quite a lot, especially when you pick ones with less complex mechanics. >They weren't even trying to abuse the reaction time of the computer They introduced a constant reaction time, but they still "abused" the interface they are provided. If this was a task in the real world, the AI would have the same interface as humans: The screen. They would have to move the screen and run object recognition algorithms on the rendered values, and they would have to "click" on units (not physically) instead of being able to internally select them. This would introduce completely different (and more realistic) reaction time parameters, because if a hero starts an animation it might not be immediately clear which animation it is in the first 5 frames, but the API will provide the value immediately. AlphaStar's strength dropped considerably for example when they realized that the AI being able to perceive the entire map at once was an unfair advantage and restricted it so that it had to move the camera around. But still even AlphaStar is using an API instead of just the rendered output, which enables things like selecting units that are hidden behind other units, which for a human player is literally impossible without moving it out of the way first. I think for AI to be able to claim that it is better at a game than humans, the AI ought to be playing the actual game, and use the same interface. (Not necessarily physically, you don't need a camera and a robot, but the AI's input should be the rendered output of the game, and the AI's output should be mouse movement / key strokes.) You might think that would be a trivial and useless exercise (like it would be in Chess/Go), but I'm really not convinced of that for video games. There are a lot of examples where even playing a frame-by-frame recording of a fight you just can't tell what exactly is going on in a fight until a couple frames later, but the API will always provide floating-point accurate data of everything. This is a huge advantage that just doesn't translate into real world tasks when the AI has to use cameras and sensors to make sense of the world (in automated driving for example) just like we have to.

roenxi 7y ago

I'm surprised by your example; OpenAI has basically shown that humans can't compete at DotA. The bot outperformed humans in an unusual but reasonable restricted version of the game and it is obvious that it would do just as well at the full game excepting that OpenAI didn't have the stomach to try and tackle the engineering challenge for no reward. They weren't even trying to abuse the reaction time of the computer, or train one agent to coordinate a team as one entity. There isn't really a question; if humans needed to win games of DotA for some reason we'd send machines. It just happens that DotA is a spectator sport and that would be boring. Exploiting the AI ... maybe? The experience with AlphaGo is that peak computer performance is just going to be better than peak human performance. Dota isn't fundamentally more complicated than Go. A few orders of magnitude harder to engineer, but OpenAI's work suggests they're about 20% of the way through a 10 year process and they've covered the interesting parts - so they stopped. With more resourcing that could be solved quickly but it isn't enough of a challenge any more. There isn't anything left to prove in DotA. Bots can play the game really well and would crush humans if it was important to anyone. Nobody cares enough to actually finish the project but if there was money on the line it is obvious how it would play out.

pingyong 7y ago
>it is obvious that it would do just as well at the full game excepting that OpenAI didn't have the stomach to try and tackle the engineering challenge for no reward. That's an interesting interpretation. My interpretation is that they simply weren't able to do it yet (not for a lack of trying though), and so they gave up. It's not obvious at all to me that there is a way to simply scale their approach to the real game. I mean, certainly there is a way with infinite computing power, but it's not clear to me that even with all the computing power on earth currently this approach would work. 18 out of 117 heroes does reduce complexity quite a lot, especially when you pick ones with less complex mechanics. >They weren't even trying to abuse the reaction time of the computer They introduced a constant reaction time, but they still "abused" the interface they are provided. If this was a task in the real world, the AI would have the same interface as humans: The screen. They would have to move the screen and run object recognition algorithms on the rendered values, and they would have to "click" on units (not physically) instead of being able to internally select them. This would introduce completely different (and more realistic) reaction time parameters, because if a hero starts an animation it might not be immediately clear which animation it is in the first 5 frames, but the API will provide the value immediately. AlphaStar's strength dropped considerably for example when they realized that the AI being able to perceive the entire map at once was an unfair advantage and restricted it so that it had to move the camera around. But still even AlphaStar is using an API instead of just the rendered output, which enables things like selecting units that are hidden behind other units, which for a human player is literally impossible without moving it out of the way first. I think for AI to be able to claim that it is better at a game than humans, the AI ought to be playing the actual game, and use the same interface. (Not necessarily physically, you don't need a camera and a robot, but the AI's input should be the rendered output of the game, and the AI's output should be mouse movement / key strokes.) You might think that would be a trivial and useless exercise (like it would be in Chess/Go), but I'm really not convinced of that for video games. There are a lot of examples where even playing a frame-by-frame recording of a fight you just can't tell what exactly is going on in a fight until a couple frames later, but the API will always provide floating-point accurate data of everything. This is a huge advantage that just doesn't translate into real world tasks when the AI has to use cameras and sensors to make sense of the world (in automated driving for example) just like we have to.