等不及马丁新作,人工智能续写《冰与火之歌》！
Artificial intelligence is attempting to write the next 'Game of Thrones' book
为了给苦苦等待的粉丝们找点乐趣,软件工程师扎克·图特（Zack Thoutt）让循环神经网络人工智能技术学习该剧原著《冰与火之歌》前五部的内容,然后续写五章剧情.这些人工智能创作的情节与粉丝早前的一些推测部分吻合,比如,詹姆最终杀死了瑟曦,囧雪成了龙骑士,而瓦里斯毒死了龙母.如果你感兴趣,可以在GitHub的主页上查看所有章节.
下面来了解一下人工智能是如何做到的：
After feeding a type of AI known as a recurrent neural network the roughly 5,000 pages of Martin's five previous books, software engineer Zack Thoutt has used the algorithm to predict what will happen next.
软件工程师扎克·图特让一种名为循环神经网络的人工智能技术学习了《冰与火之歌》前五部近5000页的内容,然后利用该算法预测接下来的情节.
According to the AI's predictions, some long-held fan theories do play out - in the five chapters generated by the algorithm so far, Jaime ends up killing Cersei, Jon rides a dragon, and Varys poisons Daenerys.
根据人工智能的预测,一些粉丝早前的推测的确出现了.在该算法目前撰写的五章内容中,詹姆最终杀死了瑟曦,囧雪成了龙骑士,而瓦里斯毒死了龙母.
Each chapter starts with a character's name, just like Martin's actual books.But in addition to backing up what many of us already suspect will happen, the AI also introduces some fairly unexpected plot turns that we're pretty sure aren't going to be mirrored in either the TV show or Martin's books, so we wouldn't get too excited just yet.
不过,我们也不要太过兴奋,因为除了存在很多人已经预测会发生的剧情外,这个人工智能算法还引入了一些令人意外的情节,它们绝对不会出现在电视剧或马丁的小说中.
For example, in the algorithm's first chapter, written from Tyrion's perspective, Sansa turns out to be a Baratheon.
例如,算法编写的第一章从小恶魔的视角写道,珊莎其实属于拜拉席恩家族.
There's also the introduction of a strange, pirate-like new character called Greenbeard.
书中还出现了一个名叫Greenbeard的怪咖,这个新角色的身份和海盗类似.
"It's obviously not perfect," Thoutt told Sam Hill over at Motherboard. "It isn't building a long-term story and the grammar isn't perfect. But the network is able to learn the basics of the English language and structure of George R.R. Martin's style on its own."
图特在接受Motherboard采访时告诉山姆•希尔,"这个算法显然并不完美,它不能编写长篇故事,语法也有问题.但是神经网络可以自学英语的基本语言知识以及马丁的文风结构."
Neural networks are a type of machine learning algorithm that are inspired by the human brain's ability to not just memorize and follow instructions, but actually learn from past experiences.
神经网络是一种机器学习算法,设计灵感来自于人脑的记忆能力、遵循指令的能力以及从过去经验学习的能力.
