等不及馬丁新作,人工智能續寫《冰與火之歌》！
Artificial intelligence is attempting to write the next 'Game of Thrones' book
為了給苦苦等待的粉絲們找點樂趣,軟件工程師扎克·圖特（Zack Thoutt）讓循環神經網絡人工智能技術學習該劇原著《冰與火之歌》前五部的內容,然后續寫五章劇情.這些人工智能創作的情節與粉絲早前的一些推測部分吻合,比如,詹姆最終殺死了瑟曦,囧雪成了龍騎士,而瓦里斯毒死了龍母.如果你感興趣,可以在GitHub的主頁上查看所有章節.
下面來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.
軟件工程師扎克·圖特讓一種名為循環神經網絡的人工智能技術學習了《冰與火之歌》前五部近5000頁的內容,然后利用該算法預測接下來的情節.
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.
根據人工智能的預測,一些粉絲早前的推測的確出現了.在該算法目前撰寫的五章內容中,詹姆最終殺死了瑟曦,囧雪成了龍騎士,而瓦里斯毒死了龍母.
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.
不過,我們也不要太過興奮,因為除了存在很多人已經預測會發生的劇情外,這個人工智能算法還引入了一些令人意外的情節,它們絕對不會出現在電視劇或馬丁的小說中.
For example, in the algorithm's first chapter, written from Tyrion's perspective, Sansa turns out to be a Baratheon.
例如,算法編寫的第一章從小惡魔的視角寫道,珊莎其實屬于拜拉席恩家族.
There's also the introduction of a strange, pirate-like new character called Greenbeard.
書中還出現了一個名叫Greenbeard的怪咖,這個新角色的身份和海盜類似.
"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."
圖特在接受Motherboard采訪時告訴山姆•希爾,"這個算法顯然并不完美,它不能編寫長篇故事,語法也有問題.但是神經網絡可以自學英語的基本語言知識以及馬丁的文風結構."
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.
神經網絡是一種機器學習算法,設計靈感來自于人腦的記憶能力、遵循指令的能力以及從過去經驗學習的能力.
