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.
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.
Each chapter starts with a character's name, just like Martin's actual books.
和马丁本人撰写的小说一样，每章打头的文字都是一个角色的名字。
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.
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。
[attach]21329[/attach]
作者: kobe 时间: 2017-9-3 23:14
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."
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。
A recurrent neural network is a specific subclass, which works best when it comes to processing long sequences of data, such as lengthy text from five previous books.
一个循环神经网络是一个特定的子集，最擅长处理长的数据序列，比如《冰与火之歌》前5部冗长的文本。
In theory, Thoutt's algorithm should be able to create a true sequel to Martin's existing work, based off things that have already happened in the novels.
理论上，图特的算法应该能基于书中已经出现的剧情创作出《冰与火之歌》真正的续集。
But in practice, the writing is clumsy and, most of the time, nonsensical. And it also references characters that have already died.
但实际上，这个算法的写作能力还很低级，大部分内容都不知所云，还会提到已经死掉的角色。
Still, some of the lines sound fairly prophetic:
不过，有些台词还是有一定预言性的：
"Arya saw Jon holding spears. Your grace," he said to an urgent maid, afraid. "The crow's eye would join you.
他对一个焦急的女仆说，“陛下，艾莉亚看到雪诺拿着长矛。乌鸦的眼睛会跟着你。”
"A perfect model would take everything that has happened in the books into account and not write about characters being alive when they died two books ago," Thoutt told Motherboard.
"The reality, though, is that the model isn't good enough to do that. If the model were that good authors might be in trouble ... but it makes a lot of mistakes because the technology to train a perfect text generator that can remember complex plots over millions of words doesn't exist yet."
One of the main limitations here is the fact that the books just don't contain enough data for an algorithm.
最主要的局限之一是书中包含的数据对一个算法而言是不够的。
Although anyone who's read them will testify that they're pretty damn long, they actually represent quite a small data set for a neural network to learn from.
虽然《冰与火之歌》的读者都认为这部小说太长了，但是对于神经网络要学习的数据集来说，这些内容太少了。
But at the same time they contain a whole lot of unique words, nouns, and adjectives which aren't reused, which makes it very hard for the neural network to learn patterns.|
