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Smerity's profile
Smerity
Smerity
Smerity
@Smerity

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Smerity

@Smerity

gcc startup.c -o ./startup. Focused on machine learning & society. Previously @Salesforce Research via @MetaMindIO. @Harvard '14, @Sydney_Uni '11. 🇦🇺 in SF.

San Francisco, CA
smerity.com
Joined July 2008

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    Smerity‏ @Smerity 25 Jun 2018

    Smerity Retweeted OpenAI

    The @OpenAI team have done amazing work and really opened my eyes towards many of AI's possibilities, the vast majority positive. Instead of discussing my opinion of the nitty gritty, I'll try to stay at the highest levels of abstraction as to how this has impacted my thinking.https://twitter.com/OpenAI/status/1011248482735177729 …

    Smerity added,

    OpenAIVerified account @OpenAI
    Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams (including a semi-pro team) at Dota 2: https://blog.openai.com/openai-five/ 
    1:10 PM - 25 Jun 2018
    • 137 Retweets
    • 413 Likes
    • Chenoe Hart Isaac Almanza Poppy Living Toronto! RAY Alex Sherstinsky Goku Mohandas Victor Akinwande Seungho Yang
    11 replies 137 retweets 413 likes
      1. New conversation
      2. Smerity‏ @Smerity 25 Jun 2018

        I want to wax poetic about the models (LSTM+PPO pushed far beyond what people likely thought possible, mirroring @Smerity et al + @GaborMelis et al in LSTM language modeling), the game (DotA as a complex test-bed), or the stupendous compute (180 years of gaming per day), but ...pic.twitter.com/cgUJ4w39G0

        Blurry photo of Smerity in the foreground of the OpenAI 5v5 DotA tournament
        1 reply 0 retweets 31 likes
        Show this thread
      3. Smerity‏ @Smerity 25 Jun 2018

        ... the real focus should be on how these bots are better team players than humans. Humans pride themselves on this. Every darn Disney film focuses on this. Society is based on this. Yet these "dumb" bots used self play and coarse objectives to learn better team work than humans.

        4 replies 23 retweets 92 likes
        Show this thread
      4. Smerity‏ @Smerity 25 Jun 2018

        For me this registered as a distinctly different beast as to what ML/AI is traditionally superhuman at. I was a heavy DotA player (started WC3 era and have played 830 hours of Dota 2) and these bot games are best described "restricted gameplay but with a sophisticated team plot".

        1 reply 1 retweet 33 likes
        Show this thread
      5. Smerity‏ @Smerity 25 Jun 2018

        I honestly believe the "restricted gameplay" part is irrelevant as I see no major obstacles (other than immense engineering which @OpenAI are well equipped) that would prevent near bot perfection. It's the team work angle that is distinctly unique and the new addition for me.

        2 replies 0 retweets 31 likes
        Show this thread
      6. Smerity‏ @Smerity 25 Jun 2018

        The bots knew when to take the fall to set their team up, when to waive their local reward for the team's global reward, and had no sense of a hero complex (I'm going to attack as I have a time limited Double Damage rune even though my team isn't ready!).

        1 reply 3 retweets 49 likes
        Show this thread
      7. Smerity‏ @Smerity 25 Jun 2018

        Humans can't learn this properly. At the amateur level, amateurs can't rely on their team mates. At the professional level, there are only so many hours in a day to perfect co-operation and players suffer from rage quits / going full tilt / ... even at the highest tier of sports.

        1 reply 2 retweets 27 likes
        Show this thread
      8. Smerity‏ @Smerity 25 Jun 2018

        This is an iterated prisoner's dilemma but humans will never spend enough time in this jail to work out how to optimally play the game through team work and collaboration. Conversely, we can happily lock our friendly @OpenAI Five team into hundreds of years of gameplay per day.

        1 reply 5 retweets 42 likes
        Show this thread
      9. Smerity‏ @Smerity 25 Jun 2018

        Why is this exciting for me? This has implications far beyond DotA. These bots never see traditional human strategies, they only play the game as the rules and objectives dictate it should be played. If there's a positive sum way to play a "human" zero sum game, it'll find it.

        2 replies 16 retweets 87 likes
        Show this thread
      10. Smerity‏ @Smerity 25 Jun 2018

        I would argue humans have forced themselves into a corner in many places due to our limits - slowly evolving rules that have high overheard to set up and poor interpretability. Ex: Loop holes are ~when laws aren't updated to account for changed context or adversarial intentions.

        3 replies 0 retweets 43 likes
        Show this thread
      11. Smerity‏ @Smerity 25 Jun 2018

        These bots weren't perfect at most of the skills humans optimize for. In a million ways they appear to have suboptimal behaviour to humans (getting gold (last hitting, jungling, farming, ...), strategy (creep blocking, pushing towers, ...), ...) - but that really didn't matter.

        1 reply 2 retweets 27 likes
        Show this thread
      12. Smerity‏ @Smerity 25 Jun 2018

        The bots, working as a team, saw the objective pipeline and optimized for the parts that mattered. They don't get all the gold+items if it means their team members are underpowered. They don't get the ultra-quadruple-mega-kill for glory when it'll make your team lose the game.

        2 replies 1 retweet 29 likes
        Show this thread
      13. Smerity‏ @Smerity 25 Jun 2018

        We could see a future where many of society's patchwork forced complexities fall away as these automated systems reveal the premature optimizations we've tricked ourselves into and the obvious blindspots we've missed that until now are only visible with hindsight.

        1 reply 17 retweets 79 likes
        Show this thread
      14. Smerity‏ @Smerity 25 Jun 2018

        We as humans aren't smart enough to see through that fog of complexity and complex interaction - but the systems we write might be. They might help us achieve the objectives which we've been lossily and haphazardly walking towards for hundreds of years.

        9 replies 15 retweets 108 likes
        Show this thread
      15. End of conversation
      1. New conversation
      2. Kim Barrington‏ @kimbrotoo 25 Jun 2018
        Replying to @Smerity @ceobillionaire @OpenAI

        Wondering who is judging this? Any humans that are women?

        1 reply 0 retweets 0 likes
      3. Smerity‏ @Smerity 25 Jun 2018
        Replying to @kimbrotoo @ceobillionaire @OpenAI

        To clarify, what aspect are you referring to that is being judged? In terms of the team behind the @OpenAI Dota bot project, the full team member list at the bottom of their blog post includes many brilliantly talented women doing the research and engineering.

        0 replies 0 retweets 5 likes
      4. End of conversation
      1. Evan Hennis‏ @TheNurl 25 Jun 2018
        Replying to @Smerity @OpenAI

        Once I got into ML at grad school I thought one amazing aspect was what you mentioned here. The machine learning something that humans can't see because of bias, etc. Is there a better way to do something common?

        0 replies 0 retweets 3 likes
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      1. murat k.‏ @muratk3n 26 Jun 2018
        Replying to @Smerity @OpenAI

        We should learn from the machines to optimize ourselves IMO. Great thread.

        0 replies 0 retweets 2 likes
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      1. Prashanth Rao‏ @tech_optimist 25 Jun 2018
        Replying to @Smerity @OpenAI

        I really see promise in this system coming up with massive real world applications. It's still early days, but imagine the good that a well-implemented system could help with governance and societal change, the possibilities are endless! Can't wait to see the next phase :)

        0 replies 0 retweets 2 likes
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      1. Maximilian‏ @MaxiIgl 29 Jun 2018
        Replying to @Smerity @OpenAI

        @Smerity As expert both in Dota2 and RL, what are your thoughts on the role of partial observability in the game? In particular: To what extend must the strategy be adapted based on only partially observed/inferred actions of the enemy team? (SC or poker being extreme cases here)

        0 replies 0 retweets 1 like
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      1. James  ☀️‏ @jamesaSYD 26 Jun 2018
        Replying to @Smerity @OpenAI

        Great thread @smerity and work @OpenAI team 🙌 looking forward to more announcements.

        0 replies 0 retweets 1 like
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