As ‘Game of Thrones’ fans eagerly wait to find out who will finally sit on the Iron Throne, researchers have developed artificial intelligence (AI) algorithms to predict the survival chances of each of the characters in the last season of the hit HBO show. The new algorithms developed at the Technical University of Munich (TUM) in Germany predict that Daenerys Targaryen has the highest chance (99 per cent) of surviving the harrowing world of ‘Game of Thrones.
The popular Tyrion Lannister also has a promising 97 per cent survival rate, researchers said. An application scours the web for data about the show, then crunches the numbers using the algorithms to predict which character has the best chance to sit the coveted Iron Throne.
Back in 2016 and just before the airing of Season 6, students attending a computer science seminar at TUM created an algorithm that accurately predicted Jon Snow’s resurrection. Survival rates are predicted using longevity analysis — a technique similar to scientific studies that examine the effects of treatments and complications on cancer patients.
Savvy GoT fans can get an in-depth look into the main reasons for the algorithm’s predictions. For instance, being born in Winterfell to the House of Stark as well as only being married seems to increase the chances of Sansa Stark to be eliminated in the upcoming season; her predicted likelihood of death is 73 per cent.
Fans interested in exploring the differences between the plot of the TV show and the story told by the books underlying the TV series, can find a side by side comparison of details about characters, including age, status (dead vs alive) and longevity prospects.
“While the task of predicting survival chances for Game of Thrones characters relies on data taken from the world of fantasy, the exact same Artificial Intelligence techniques are used in the real world and are having a powerful impact on our everyday lives,” lead mentor of the class Guy Yachdav said in a statement.
“The combination of passion and teaching is a brilliant way to create new tools that matter,” said Professor Burkhard Rost heading the Chair for Bioinformatics at TUM’s Informatics faculty. “In our course at TUM we found a fun way to teach students how to use this technology and prepare them to build the next big thing once they graduate,” Rost said.
If you have an interesting article / experience / case study to share, please get in touch with us at [email protected]