Episode 178 – L33T Learning Siri

 

Just say no to enabling autonomous bots & drones with the ability to apply lethal force.  Following on last week’s episode 177, Michael & Michael start off with a continuation of the discussion on the Pandora’s Box of armed robots.

Moving on to a happier topic, while still staying on the machine learning concept, the pair talks about how Siri and other voice interactive systems have been improved with deep learning.  Not just recorded scripts, but actual intelligence, and more natural interaction is apparent when you listen to how far things have come since the earliest days of Siri — listen to the examples from the Apple Machine Learning Journal article, and we think you’ll agree.

Understanding that you’re talking with a bot vs a human is important to help avoid the uncanny valley where the interaction becomes weird vs expected — perhaps this is why Michael R preferred the Australian accent reminiscent of J.A.R.V.I.S, and how in Star Trek and other science fiction, interaction with the computer was prefaced with “computer!” before issuing a request.

Feedback loops getting faster & faster, which is really evident in machine learning examples applied to games.  When the machine — the program — is experimenting with the game to learn, and figure out what is rewarded, what is not rewarded, and determine a heuristic model for playing the game, which for a human is for fun and for the machine learning example is to maximize the outcome.  The example from the O’Reilly article was particularly intriguing to Michael M who wondered why the AI playing the game did not scoop up each and every present while playing the game.  Michael R made the interesting point that if the machine learning algorithms assume that there’s an infinite number of presents ahead, it makes more sense to quickly move forward and grab the presents because there are more ahead of you than behind.  The screenshot above is from a machine learning model playing Super Mario Kart, where it is easy to see how machine learning quickly gets better and better with successive plays of the game.

Closing out this episode, Michael and Michael include David Ma’s videos of food imagined in the style of  famous directors, a funny song about waffles and a discussion on Zork.  Hope you enjoy these tasty treats!

Selected links 

last week’s show, E177 — What could possibly go wrong? — http://gamesatwork.biz/2017/08/31/episode-177-what-could-possibly-go-wrong/

An open letter to the United Nations Convention on Certain Conventional Weapons — https://futureoflife.org/autonomous-weapons-open-letter-2017

We don’t have long to act — https://qz.com/1058280/we-do-not-have-long-to-act-teslas-tsla-elon-musk-and-others-warn-the-un-about-autonomous-weapons

Six Colors article:  Deep Learning Improves Siri’s voice — https://sixcolors.com/link/2017/08/deep-learning-improves-siris-voice/

Apple’s Machine Learning Journal:  Deep Learning for Siri’s Voice: On-device Deep Mixture Density Networks for Hybrid Unit Selection Synthesis — https://machinelearning.apple.com/2017/08/06/siri-voices.html

Uncanny Valley — https://en.wikipedia.org/wiki/Uncanny_valley

J.A.R.V.I.S. — https://en.wikipedia.org/wiki/Edwin_Jarvis#J.A.R.V.I.S.

O’Reilly article:  Bringing gaming to life with AI and deep learning — https://www.oreilly.com/ideas/bringing-gaming-to-life-with-ai-and-deep-learning

YouTube:  Super MarI/O Kart Commentary — https://www.youtube.com/watch?v=S9Y_I9vY8Qw

Food by Favorite Directors (Sort Of) — https://www.subtraction.com/2017/08/14/food-by-famous-directors-sort-of/

YouTube:  What if Alfonso Cuaron made pancakes?  — https://www.youtube.com/watch?v=6_hpJHNt4IE

Do You Like Waffles?  By Parry Gripp — https://itunes.apple.com/us/album/do-you-like-waffles/id468568946?i=468568983

MIT Technology Review — The Enduring Legacy of Zork — https://www.technologyreview.com/s/608670/the-enduring-legacy-of-zork/

MIT Technology Review article:  Siri for Business — https://www.technologyreview.com/s/600990/siri-for-business/

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Crossy Road for the new AppleTV

Crossy Roads for AppleTV

with the new AppleTV released on Friday, one of the most exciting games I was looking forward to playing was multiplayer Crossy Road, partially because of my memory of playing competitive Mario Brothers on the Apple ][ and partially because my kids just love playing the game and unlocking new characters.  It was with great anticipation for my kids to get the AppleTV set up — which was very easy to do with the iPhone, as was the installation of the app from the AppleTV store.  What proved to be more challenging was getting the iOS device to be recognized by the AppleTV for the second player to control their Crossy Road character.  Looking on the web for help, there were some good articles, such as the one from iMore, however there was one important tip that the Crossy Road app itself pointed out, but in our zeal to play, we had ignored.

in order for the AppleTV to recognize the iOS device, they both need to be on the same WiFi network.  in our home setup, I have the AppleTV hardwired with an ethernet connection to the router so as to help with bringing down movies in the absolute fastest possible way, and because the AppleTV was smart enough to recognize the ethernet wire, it did not enable a wireless connection.  Then, once we had rebooted the AppleTV on WiFi, restarted Crossy Road and selected two player, the iOS device was recognized, and as they say, hilarity ensued.  the kids proceeded to play, pushing one another’s characters into oncoming trucks and the water, giggling and laughing.

 

 

Episode 102 – I’ve got Plastisity

New GamesAtWork.BiZ Recording Studio

New GamesAtWork.BiZ Recording Studio


Phaedra, Michael and Michael get together for a detailed review of the economics of digital games for 2014. We continue to see the transition from Pay to Play to Free to Play games, and discuss how this is changing the game play of many MMOs. We also take issue with a recent report on how Gamificiation is failing health care. The issue is not gamification, but bad design. As more and more people jump into the hype of gamificaiton we are seeing the same patterns as other technologies, where people are trying to just use the term, without understanding the appropriate way of doing this. You can just use “blanket approaches” to gamifiction, you need to identify the correct success metrics, and build your game around ensuring the appropriate behavior and outcomes.

We end the episode with a discussion on how different generations engage with same game. Do you play games with your kids, or parents? Do you enjoy it in the same way? Do you enjoy watching others play games more than playing the game yourself?

Show Links:
Digital Games Year in review
Maple Story
World of Warcraft competes in a freemium world
Lord of the Rings Online goes Free to Play
Star Wars the Old Republic goes Free to Play
Why Gamification is failing in Healthcare
Amazon buys Twitch TV

Games we are playing:
Michael M. – Disco Zoo, Crossy Road, and Game Dev Story
Phaedra – Portal 2, Checkers, Chess, and Words with Strangers
Michael R. – Space Age

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