5 ms·

> Some program that self learned a (admittedly impressive) number of reactions based on seeing/playing a huge number of simulations is not intelligence so not A

• trabant00 6y ago
  > Is this really that different than what humans do? Yes, we have built in mechanism that react to situations we never encountered before. You will never be able to simply sit calmly while something is damaging you for example.
  • phaemon 6y ago
    Reacting to damage is something you learned in previous generations. You've encountered that situation billions of times (you just don't remember them).
• 1123581321 6y ago
  We are quite different as we can evaluate new situations based on our understanding of the principles behind something like a build order in Starcraft.
• Retric 6y ago
  Clearly it can surpass peak human skill at StarCraft, but it’s important to understand what Deep Mind is doing differently. One example is memory. Deep mind doesn’t update it’s strategy when playing the same player repeatedly or even over the same game. It can operate at near peak human performance indefinitely, but it avoids being exploited via deep understanding of the exact rules in play. It was also playing on the ladder under random names to avoid people developing specific counters.
  • chmod775 6y ago
    > One example is memory. Deep mind doesn’t update it’s strategy when playing the same player repeatedly or even over the same game. It can operate at near peak human performance indefinitely but it avoids being exploited via deep understanding of the exact rules in play. It was also playing on the ladder under random names to avoid people developing specific counters. This is because many games without perfect information have "rock-paper-scissor" situations. An AI designed without this in mind, lacking a source of randomness (or memory of the last encounter fed into the next game), is going to pick "rock" every time and start losing to the human who realizes and exploits this.
• eternalban 6y ago
  Imagination plays a significant role for us humans. We also are capable of maintaining incomplete conceptual mental models. Some of us experience epiphanies. Etc. Pattern matching and search are brute force approximation of actual “intelligence”.
  • gwd 6y ago
    As far as I understand, AlphaZero had three main components: 1. A model of how Go worked, constructed by humans 2. A neural net for generating interesting moves, and a neural net for evaluating game positions. 3. A Markov search algorithm that used 1+2 to do pattern patching and search. I will say that so far, #1 -- constructing mental models which can then be searched -- is something I haven't seen an AI do yet. But looking at the actual work that I do -- from coding to deciding what to cook for dinner to deciding how to lay out my extension -- I'm pretty sure that behind the scenes it's exactly the same as 1+2+3 above; and that if I could download my mental model and my utility evaluator into a program, it could (with training) do all of the above faster and more consistently.
    • RiversHaveWings 6y ago
      After AlphaZero, DeepMind went on to develop MuZero (https://en.wikipedia.org/wiki/MuZero https://en.wikipedia.org/wiki/MuZero, paper: https://arxiv.org/abs/1911.08265 https://arxiv.org/abs/1911.08265), which is able to learn to play games without being provided an explicit model of their rules. "When evaluated on Go, chess and shogi, without any knowledge of the game rules, MuZero matched the superhuman performance of the AlphaZero algorithm that was supplied with the game rules."
• iEchoic 6y ago
  > A lot of it comes down to the same kind of thing. "Send your first overlord to scout their natural. If they haven't expanded to their natural, build one -- ONE -- spine crawler in your natural." I think your general question is still a good one, but it's worth noting that from a human perspective, Starcraft matches only start off this way. Very quickly, the game state becomes complex enough that decision trees break down and intuition becomes the driving process for high-level human players. The extent to which AI can begin to compete with this sort of intuitive human processing is most interesting to me. As it relates to this article, I think it matters a great deal if the experiment has constrained the system to the degree that it ceases to operate in that intuitive realm that high-level Starcraft matches operate in.
  • gwd 6y ago
    > Very quickly, the game state becomes complex enough that decision trees break down and intuition becomes the driving process for high-level human players. The extent to which AI can begin to compete with this sort of intuitive human processing is most interesting to me. As far as I can tell, we're already there. Go is a game where search + explicit rules work really poorly, and intuition is a heavy factor in how humans play. AlphaGo was the first major success where neural nets were able to replicate this "intuition", and actually become far better at it than humans. You can definitely see this "intuition" factor if you watch the AlphaStar games. Basically, if you have two armies with "middle of the road" units, AlphaStar always knows when to take a fight. You can sometimes see it take its army up to a defensive line, then turn around and go home; but if it decides to attack up that ramp, it always wins, even in a situation where a human would be less sure. The exception is with unusual unit compositions; for example, it seems in training to have only encountered 1-2 battle cruisers at a time. So there are games where over and over again it throws an expensive army full-throttle into a group of 10 battle cruisers, and over and over gets slaughtered. But again, I think this "intuition" factor, even in humans, is not much more than a sophisticated pattern matching, perhaps with background search.
    • heylook 6y ago
      > The exception is with unusual unit compositions Could be wrong, but I believe this is actually a case-in-point moment for the other side. AI as it exists now is flummoxed by unfamiliar input, whereas a human expert is more likely to be able to react in a way that is at least directionally correct. Put another way, if AlphaStar is confronted with a Terran opponent that can build Zerg units, how likely would it be to win the game? How likely would an expert human be to win that game?
• rytill 6y ago
  The “one” spine crawler thing is a bit overstated in the context of an actual game. It’s not like it’s 100% necessary to build it, build it in your natural, or only build one depending on what you’ve scouted, the opponent’s race, and who you’re playing against. Like the sibling said, the game begins like a decision tree but quickly falls outside that purview.
  • gwd 6y ago
    Well you have to remember who he's talking to. You can sort of tell that lots of people, if they think they're about to be rushed, would make loads of spine crawlers as a defense; the emphasis on "ONE spine crawler" to delay an attacking army just long enough that you can build your own army in response (assuming you see it when it starts to cross the map) with the minimal impact on your economy. And my point is that basically what he does in the series is start with a super simple set of rules, and then slowly add more subtleties and sub-clauses. That's obviously at some level how he works when he's actually playing -- he has a general plan, then a whole load of patterns that he matches on in how to respond. I'd be willing to bet that he rarely encounters a genuinely new situation for which there is absolutely zero precedent -- absolutely nothing in his experience which is similar enough for him to take an existing response and adapt it for that purpose. How is that different to what AlphaStar is doing? The main difference is likely to be in how they learn afterwards. If he encounters a new situation in a game, afterwards he will use his model of the game to try to come up with new responses. AlphaStar will most likely have to do something much closer to brute force to find an appropriate response.