Xiaoyang Yang, Head of Data AI Security and IT over at Second Dinner Studios, explains how Second Dinner navigates the issue of excess data with intention and discover the metrics that go deeper than the surface to measure the quality of competition, balance, and fairness within gaming. Xiaoyang also describes the difference between AI and gaming AI and shows us how each can be used to enhance the other. Listen to today’s episode for a careful look at how AI can be used to improve player experience and how gaming can act as a testing ground to improve AI in everyday life. 

Key Points From This Episode:

Introducing Xiaoyang Yang, head of Data AI Security and IT at Second Dinner Studios.His recently launched video game, MARVEL SNAP.How he uses data as a tool to listen to players before translating it into insights.The role of scale and how it changes the parameters around which players you attract.The discrepancy between how different players experience the same feature.Xiaoyang’s background in theoretical physics, machine learning, and gaming.How an internship at Blizzard helped him enter a new industry.His time working on World of Warcraft and with Riot Games.Second Dinner’s partnership with Marvel to create MARVEL SNAP.Xiaoyang’s aim to use data to make the game accessible to a wider audience who hasn’t tried collectible card games before. The issue of excess data and how Second Dinner combats this with careful intention.Data metrics that go deeper to enhance design and balance.Competition, fairness, and balance as indicators for how fun a game will be for players.How AI can be used to test fairness and balance in gaming.How game AI differs from AI in general and how each can be used to inform the other. The competitive experience you can have with gaming AI due to different skill levels.The new experience you can offer users today that has been facilitated by AI. 

Tweetables:

“We try to really listen to what our players are saying. One way to do that is through data. We use data as a tool.” — Xiaoyang Yang [0:02:28]

“When you see the scale, you begin to really understand that different players have different desires. Sometimes, different players see the same feature or the same experience in a very different type of way.” — Xiaoyang Yang [0:04:46]

“We see a lot of opportunities to use technology data AI to make MARVEL SNAP approachable to a wide audience of players and, hopefully, some players who have never tried the genre of collectible card games.” — Xiaoyang Yang [0:11:25]

“We want to make sure that there are different sets of cards you can use to have fun and still be competitive in the game. That's not an easy task.” — Xiaoyang Yang [0:19:25]

Links Mentioned in Today’s Episode:

Xiaoyang Yang on LinkedIn

Second Dinner Studios

MARVEL SNAP

Blizzard

Riot Games

How AI Happens

Sama