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I know it has been mentioned a lot the past few days, but since the articles keep flowing about it I'll mention it again: It's a great feat and kudos to the op

I know it has been mentioned a lot the past few days, but since the articles keep flowing about it I'll mention it again: It's a great feat and kudos to the openai team, but it is VERY unfair for the human players who rely on a sensory interface vs a direct API connection. That's unlike chess or go where the interface isn't important. The really impressive feat will be an AI that uses the same sensory information to make decisions (and I really hope that's where the openai will head next)

hobofan 9y ago
And the response as I've seen it on other threads: It probably doesn't make a big difference, and will outperform humans there too, and it would be a huge waste of computing power to train it that way. I think OpenAI should show that the AI can derive (a close aproximation of) the API data from videos, but I don't think that building a closed training loop would add much value here.
- lvoudour 9y ago
  >And the response as I've seen it on other threads: It probably doesn't make a big difference, and will outperform humans there too, and it would be a huge waste of computing power to train it that way. Well they may be right about the "outperform" part but they are dead wrong about the waste of time/effort/energy part. I mean if (at least human-like) real-time video/audio recognition and decision making is not an impressive AI feat, I don't know what is. I'm no expert in the field but claiming that plugging into an API and crunching numbers is more important than sensory-based decision making, just doesn't sound right
  - radarsat1 9y ago
    It's their long-term goal: https://blog.openai.com/universe/ https://blog.openai.com/universe/
  - hobofan 9y ago
    > sensory-based decision making You can pretty cleanly split that up into two different problems: "sensory-based data extraction" and "data-based decision making" Though I haven't worked in the field of self-driving cars, I am fairly confident that they employ a similar split: One part that takes in all the (pre-processed) data from LIDAR, cameras, etc. and maps that to a simplified model of the surroundings, and another part that makes the driving decisions based on the simplified model. Sensory->data mapping doesn't raise a lot of eyebrows anymore if you can generate as much sensory information as you want to explore all possible states, as it is possible with Dota.
    - lvoudour 9y ago
      To me though as an outside observer it seems that the dota problem is harder than the car problem. There's too much action going on, too many visual/aural cues to keep track of, team cooperation/coordination, fog of war, etc. Car AI is important because there are real life-or-death consequences, but the problem (again to my limited experience) seems more tractable: path choices are limited, action is rare, there's no team element and there's no competition. Even for human drivers driving a car in a city or motorway is a tedious, mostly repetitive task. Now, competitive driving raises the stakes and we haven't seen any self-driving car tackling that problem yet (which will definitely raise a lot of eyebrows)
      - hobofan 9y ago
        > there's no team element and there's no competition I don't think that this is true, considering all the other humans on/near the road, that can influence the system by making actions of their own. > There's too much action going on, too many visual/aural cues to keep track of, team cooperation/coordination, fog of war, etc. I dont see how this is different from a car at all. - too many visual/aural cues to keep track of -> everything you can see, car horns, etc. - team cooperation/coordination -> as I said everyone else on/near the road - fog of war -> blind spots & people hidden behind objects From some experience in the AI world, I can say that I've seen systems that are good enough that they should be able to solve most of those subproblems in the limited system that is Dota. Yes, fog of war might also be interesting given that you have an agressive opponent. The real novel things lie at the strategy level, like picking a hero, buying items, etc., because, like AlphaGo, they demonstrate reasoning in systems with a large action space and delayed payoff.
- hacker_9 9y ago
  Depends what the aim is, to create general AI? Or just a good DOTA bot? If the goal is the former, then vision will play a huge part.
- haeffin 9y ago
  You can't get the things you get from the API from videos alone. If a player wants to see the amount of mana an enemy has, he has to click on the enemy, you don't see it usually. Same for items. There is an active component in information gathering in Dota (and those actions take time/clicks away from other things you could do at the same time).
fridek 9y ago
Exactly my thoughts after Elon Musk's tweet: https://twitter.com/elonmusk/status/896163163581825025 https://twitter.com/elonmusk/status/896163163581825025 Unless AI is constrained to pro player max pointer move delta, click rate, and vision latency, I don't really see much difference between AI and a team of kids running with aimbot shouting "cyka cyka".
- hobofan 9y ago
  > Actions accessible by the bot API, chosen at a frequency comparable to humans I would guess that this already includes all the delays you are asking for.
  - thewhitetulip 9y ago
    No, there is a difference. The human player has to see, react and then shot. The computer has a direct API. gun.shoot() as opposed to image of a gun falls on the retina process the info sent by the eye synapses fired etc :)
    - hobofan 9y ago
      I considered that, and I don't think there is. The frequency of the actions is already a result of the "actual time it takes to executr the action" + "all human delays". If you limit the bot to that frequency, everything is accounted for. ---- EDIT: On second thought, there might be a difference, in that this leaves the bot with more time to think, unless you limit the time of that. Not sure if that would dramatically influence the performance though.
      - thewhitetulip 9y ago
        The thing is, every human has a different response time, but the bot doesn't have one. The day a bot will play the game like humans, a physical robot holding a console remote etc then maybe it'd be cancelling out the API advantage that the bot has. but this doesn't undermine the achievement that they have made. It is phenomenal that an AI can play a complex game like DOTA.
BaronSamedi 9y ago
I completely disagree. An API is software's natural input mechanism just like the senses are a human's natural input mechanism. Having the AI use human senses unfairly handicaps it. More importantly, however, is that this is not the key problem. The key problem is teaching the AI strategy and tactics. What heroes to pick? Where to lane them? When to rotate? What items to buy? What spells to level up? What enemies to target with which spells and in which order? These are the hard problems and they are very hard indeed. A 5v5 AI will have to become expert at risk calculation, Pareto optimization, basic military principles, and many more things. Compared to these problems, the choice of input mechanism is trivial.
- lvoudour 9y ago
  >Compared to these problems, the choice of input mechanism is trivial I don't know why you think the visual/aural problem is trivial. The biggest achievement of AIs so far in this field is classification of static images
  - bingojess 9y ago
    Trivial may not be the best word but what they were trying to get the AI to do was learn dota strategy and tactics. It's like teaching alphaGo to play go with a camera.
    - mirceal 9y ago
      I disagree. The representation of state is hard for machines. Go/Chess are very simple state wise when compared to Dota. By giving it API access you have eliminated guesswork/approximations from the overall picture
  - BaronSamedi 9y ago
    I apologize if my statement was misleading. I do not think the visual problem itself is trivial. I think the choice of input mechanism is tangential to the hard problems actually faced by the AI designers: strategy and tactics.
- 9y ago
madez 9y ago
> The really impressive feat will be an AI that uses the same sensory information to make decisions (and I really hope that's where the openai will head next) Impressive? Yes. Interesting? Not as much. We consider AI important not because it can play Dota. We consider stronger AI important for making our lives easier by solving problems. For AI to solve our problems we will not unnecessarily restrict it to our sensory information.
Houshalter 9y ago
The goal of this project is to make progress in reinforcement learning. Having an AI plan and learn strategies to play a game. This is a separate problem from machine vision, which is being worked on by tons of other people. Adding a machine vision requirement wouldn't help them with their goal and would take 100x more computing resources. OpenAI could probably afford to do it, but it no smaller researchers or hobbyists would be able to compete.
- motoboi 9y ago
  You forgot to mention the people working on physical robots, waiting for software to get better.
Fnoord 9y ago
The comparison goes indeed moot, for a myriad of reasons. Interface is one of the many. If we look at a game such as WoW we can observe the fights in group content (dungeons and raids) have become more difficult over time. The WoW development team cites a few reasons for that: 1) players have become better so the difficulty has gone up, and 2) boss mods (software) have become better. This software aids the user in observing/notifying (sensing actions) , and executing (processing information and deciding upon it) mechanics on a fight and are available thanks to the LUA engine and API. Ironically, even without such software, that game has improved majorly in communicating mechanics to the player over the years (WoW is from 2004). Hence aspects like the UI and API are going to affect the quality of gameplay of humans as well. For AI it would only be API. Furthermore, there is network lag, interface lag, input lag, and cognitive lag. Only the latter seems fair game to me.
dumbmatter 9y ago
Yeah, it's like Watson on Jeopardy. It could buzz in faster than a human, so it got to answer every question that it thought it knew, which was most of them. Problem is, the human competitors surely also knew most of them (maybe even more than Watson) but they couldn't buzz in fast enough.
hossbeast 9y ago
Until they ditch the API, I don't want to read about them claiming to have "beaten" a human opponent. It's nonsense. I'm sure your AI is impressive, but you're not even playing the same game.
autokad 9y ago
one thing AI bots can be good for is testing to see if games are balanced. For instance, I am a zerg player and I bought star craft 2, but it was immediately clear to me that the game was heavily unbalanced. I quit playing. whether you agree protos was over-powered or not, I think we can all agree that game developers can benefit from AI with human limitations. it can help them design better games

hobofan 9y ago

And the response as I've seen it on other threads: It probably doesn't make a big difference, and will outperform humans there too, and it would be a huge waste of computing power to train it that way. I think OpenAI should show that the AI can derive (a close aproximation of) the API data from videos, but I don't think that building a closed training loop would add much value here.

lvoudour 9y ago
>And the response as I've seen it on other threads: It probably doesn't make a big difference, and will outperform humans there too, and it would be a huge waste of computing power to train it that way. Well they may be right about the "outperform" part but they are dead wrong about the waste of time/effort/energy part. I mean if (at least human-like) real-time video/audio recognition and decision making is not an impressive AI feat, I don't know what is. I'm no expert in the field but claiming that plugging into an API and crunching numbers is more important than sensory-based decision making, just doesn't sound right
- radarsat1 9y ago
  It's their long-term goal: https://blog.openai.com/universe/ https://blog.openai.com/universe/
- hobofan 9y ago
  > sensory-based decision making You can pretty cleanly split that up into two different problems: "sensory-based data extraction" and "data-based decision making" Though I haven't worked in the field of self-driving cars, I am fairly confident that they employ a similar split: One part that takes in all the (pre-processed) data from LIDAR, cameras, etc. and maps that to a simplified model of the surroundings, and another part that makes the driving decisions based on the simplified model. Sensory->data mapping doesn't raise a lot of eyebrows anymore if you can generate as much sensory information as you want to explore all possible states, as it is possible with Dota.
  - lvoudour 9y ago
    To me though as an outside observer it seems that the dota problem is harder than the car problem. There's too much action going on, too many visual/aural cues to keep track of, team cooperation/coordination, fog of war, etc. Car AI is important because there are real life-or-death consequences, but the problem (again to my limited experience) seems more tractable: path choices are limited, action is rare, there's no team element and there's no competition. Even for human drivers driving a car in a city or motorway is a tedious, mostly repetitive task. Now, competitive driving raises the stakes and we haven't seen any self-driving car tackling that problem yet (which will definitely raise a lot of eyebrows)
    - hobofan 9y ago
      > there's no team element and there's no competition I don't think that this is true, considering all the other humans on/near the road, that can influence the system by making actions of their own. > There's too much action going on, too many visual/aural cues to keep track of, team cooperation/coordination, fog of war, etc. I dont see how this is different from a car at all. - too many visual/aural cues to keep track of -> everything you can see, car horns, etc. - team cooperation/coordination -> as I said everyone else on/near the road - fog of war -> blind spots & people hidden behind objects From some experience in the AI world, I can say that I've seen systems that are good enough that they should be able to solve most of those subproblems in the limited system that is Dota. Yes, fog of war might also be interesting given that you have an agressive opponent. The real novel things lie at the strategy level, like picking a hero, buying items, etc., because, like AlphaGo, they demonstrate reasoning in systems with a large action space and delayed payoff.
hacker_9 9y ago
Depends what the aim is, to create general AI? Or just a good DOTA bot? If the goal is the former, then vision will play a huge part.
haeffin 9y ago
You can't get the things you get from the API from videos alone. If a player wants to see the amount of mana an enemy has, he has to click on the enemy, you don't see it usually. Same for items. There is an active component in information gathering in Dota (and those actions take time/clicks away from other things you could do at the same time).

fridek 9y ago

Exactly my thoughts after Elon Musk's tweet: https://twitter.com/elonmusk/status/896163163581825025 https://twitter.com/elonmusk/status/896163163581825025 Unless AI is constrained to pro player max pointer move delta, click rate, and vision latency, I don't really see much difference between AI and a team of kids running with aimbot shouting "cyka cyka".

hobofan 9y ago
> Actions accessible by the bot API, chosen at a frequency comparable to humans I would guess that this already includes all the delays you are asking for.
- thewhitetulip 9y ago
  No, there is a difference. The human player has to see, react and then shot. The computer has a direct API. gun.shoot() as opposed to image of a gun falls on the retina process the info sent by the eye synapses fired etc :)
  - hobofan 9y ago
    I considered that, and I don't think there is. The frequency of the actions is already a result of the "actual time it takes to executr the action" + "all human delays". If you limit the bot to that frequency, everything is accounted for. ---- EDIT: On second thought, there might be a difference, in that this leaves the bot with more time to think, unless you limit the time of that. Not sure if that would dramatically influence the performance though.
    - thewhitetulip 9y ago
      The thing is, every human has a different response time, but the bot doesn't have one. The day a bot will play the game like humans, a physical robot holding a console remote etc then maybe it'd be cancelling out the API advantage that the bot has. but this doesn't undermine the achievement that they have made. It is phenomenal that an AI can play a complex game like DOTA.

BaronSamedi 9y ago

I completely disagree. An API is software's natural input mechanism just like the senses are a human's natural input mechanism. Having the AI use human senses unfairly handicaps it. More importantly, however, is that this is not the key problem. The key problem is teaching the AI strategy and tactics. What heroes to pick? Where to lane them? When to rotate? What items to buy? What spells to level up? What enemies to target with which spells and in which order? These are the hard problems and they are very hard indeed. A 5v5 AI will have to become expert at risk calculation, Pareto optimization, basic military principles, and many more things. Compared to these problems, the choice of input mechanism is trivial.

lvoudour 9y ago
>Compared to these problems, the choice of input mechanism is trivial I don't know why you think the visual/aural problem is trivial. The biggest achievement of AIs so far in this field is classification of static images
- bingojess 9y ago
  Trivial may not be the best word but what they were trying to get the AI to do was learn dota strategy and tactics. It's like teaching alphaGo to play go with a camera.
  - mirceal 9y ago
    I disagree. The representation of state is hard for machines. Go/Chess are very simple state wise when compared to Dota. By giving it API access you have eliminated guesswork/approximations from the overall picture
- BaronSamedi 9y ago
  I apologize if my statement was misleading. I do not think the visual problem itself is trivial. I think the choice of input mechanism is tangential to the hard problems actually faced by the AI designers: strategy and tactics.
9y ago

madez 9y ago

> The really impressive feat will be an AI that uses the same sensory information to make decisions (and I really hope that's where the openai will head next) Impressive? Yes. Interesting? Not as much. We consider AI important not because it can play Dota. We consider stronger AI important for making our lives easier by solving problems. For AI to solve our problems we will not unnecessarily restrict it to our sensory information.

Houshalter 9y ago

The goal of this project is to make progress in reinforcement learning. Having an AI plan and learn strategies to play a game. This is a separate problem from machine vision, which is being worked on by tons of other people. Adding a machine vision requirement wouldn't help them with their goal and would take 100x more computing resources. OpenAI could probably afford to do it, but it no smaller researchers or hobbyists would be able to compete.

motoboi 9y ago
You forgot to mention the people working on physical robots, waiting for software to get better.

Fnoord 9y ago

The comparison goes indeed moot, for a myriad of reasons. Interface is one of the many. If we look at a game such as WoW we can observe the fights in group content (dungeons and raids) have become more difficult over time. The WoW development team cites a few reasons for that: 1) players have become better so the difficulty has gone up, and 2) boss mods (software) have become better. This software aids the user in observing/notifying (sensing actions) , and executing (processing information and deciding upon it) mechanics on a fight and are available thanks to the LUA engine and API. Ironically, even without such software, that game has improved majorly in communicating mechanics to the player over the years (WoW is from 2004). Hence aspects like the UI and API are going to affect the quality of gameplay of humans as well. For AI it would only be API. Furthermore, there is network lag, interface lag, input lag, and cognitive lag. Only the latter seems fair game to me.

dumbmatter 9y ago

Yeah, it's like Watson on Jeopardy. It could buzz in faster than a human, so it got to answer every question that it thought it knew, which was most of them. Problem is, the human competitors surely also knew most of them (maybe even more than Watson) but they couldn't buzz in fast enough.

hossbeast 9y ago

Until they ditch the API, I don't want to read about them claiming to have "beaten" a human opponent. It's nonsense. I'm sure your AI is impressive, but you're not even playing the same game.

autokad 9y ago

one thing AI bots can be good for is testing to see if games are balanced. For instance, I am a zerg player and I bought star craft 2, but it was immediately clear to me that the game was heavily unbalanced. I quit playing. whether you agree protos was over-powered or not, I think we can all agree that game developers can benefit from AI with human limitations. it can help them design better games