Google Research is giving us a glimpse of how far natural language processing in artificial intelligence has come. Mountain View’s research division has rolled out a couple of what it calls Semantic Experiences, which are websites with interesting activities that demonstrate AIs’ ability to understand how we speak.

　　谷歌研究院正在让我们得以一瞥，人工智能领域的自然语言处理技术已经取得了多大的进展。山景城(谷歌位于加州的总部)的研究部门推出了几个网站，被称为Semantic Experiences(语义体验)，这些网站有一些有趣的活动，活动展现出人工智能有理解我们语言的能力。

　　It has two experiences to enjoy and the third one is for developers to help them create their own experience. The first two experiences are called "Talk to Books" in which users can explore a new way to interact with books, and "Semantris" where people can play word association games powered by semantic search.

　　大众可以享受两种技术体验，而第三种是针对开发者的，可以帮助他们开发属于自己的“体验”。前两种体验中，一个被称作“Talk to Books”，使用这一技术，用户可以探索与书籍交流的新方式，另一个是“Semantris”，人们在这一部分可以玩到由语义研究提供支持的单词联想游戏。

　　The first of the two publicly available experiments is called Talk to Books, and it quite literally lets you converse with a machine learning-trained algorithm that surfaces answers to questions with relevant passages from human-written text. As described by Kurzweil and Bernstein, Talk to Books lets you “make a statement or ask a question, and the tool finds sentences in books that respond, with no dependence on keyword matching.”

　　这两个公开实验中的第一个被称作“Talk to Books”，毫不夸张地说，它可以让你与机器学习训练型算法进行交流，该算法通过人工文本的相关段落来回答问题。正如库兹韦尔(谷歌的技术总监)和伯恩斯坦(谷歌的产品经理)所说，“Talk to Books”让你可以“陈述一件事情或是提出一个问题，该工具可以在书中找到回应的语句，而不依赖于关键词匹配。”

　　The duo add that, “In a sense you are talking to the books, getting responses which can help you determine if you’re interested in reading them or not.”

　　二人还补充说：“从某种意义上来说，你是在与书籍交谈，从机器那里得到的回应可以帮助你确定是否有兴趣进一步阅读这些书。”

　　Ask it a question like “why is the sky blue?” and you’ll get a number of different answers displayed in clear text, sourced from books on the subject, like, “The Rayleigh scattering of light by molecules in the atmosphere gets stronger as the wavelength decreases.” But, as opposed to using standard Google Search and having to click a link and parse an article or webpage, the Talk To Books algorithm does that work for you.

　　如果你问一个问题，诸如“为什么天是蓝色的?”，你会从这一主题的相关书籍中得到许多不同的答案，答案会以清晰的文本形式展示给你，例如“随着波长的降低，光在大气中分子的瑞利散射会变得更强”。但是，与使用标准的谷歌搜索不同，你不必再去点击链接，解析一篇文章或是网页，“Talk To Books”的算法为你完成了这一工作。

　　The development in word vector, an AI-training model that enables algorithms to learn relationships between words based on actual language usage, led to the advancement in natural language processing over the past few years. According to Kurzweil and Bernstein, these websites show how AIs’ "new capabilities can drive applications that weren’t possible before." They said other potential applications include "classification, semantic similarity, semantic clustering, whitelist applications (selecting the right response from many alternatives) and semantic search (of which Talk to Books is an example)."

　　词向量的发展促使了过去几年中自然语言处理技术的进步与提升，这是一种人工智能训练模型，使算法能够根据实际的语言使用情况来学习单词之间的关联。库兹韦尔和伯恩斯坦表示，这些网站展示了人工智能的“新功能如何去推动以前不可能实现的应用”。他们表示还有一些其他潜在的应用，包括“分类、语义相似性、语义聚类、白名单(从众多选择中选取正确答案)和语义搜索(其中‘Talk to Books’就是一个例子)”。

　　Google has released a module on TensorFlow other researchers and developers can use, so the tech giant’s work could lead to more AI-powered applications that can understand how we wield words better than their older counterparts can.

　　谷歌还发布了一个TensorFlow 模块供其他研究人员和开发者使用，如此一来，这家科技巨头公司可能会引领更多人工智能应用的出现，这些应用能够比过去更好地理解我们对语言的使用。

　　“The models driving this experience were trained on a billion conversation-like pairs of sentences, learning to identify what a good response might look like,” Kurzweil and Berstein explain. “Once you ask your question (or make a statement), the tools searches all the sentences in over 100,000 books to find the ones that respond to your input based on semantic meaning at the sentence level; there are no predefined rules bounding the relationship between what you put in and the results you get.”

　　“驱动这个实验的模型接受了10亿个类似对话句子的训练，来学习如何作出更好的回应，” 库兹韦尔和伯恩斯坦解释说， “当用户提出问题(或者做出陈述)时，这些工具就会搜索超过10万本书籍中的所有句子，根据句子级别的语义找出那些可以回应用户输入的句子;而且不会有预定义的规则来限制用户输入的内容和得到的结果之间的关系。”

　　Google CEO Sundar Pichai has been "betting big" on advances in AI and machine learning.

　　谷歌的CEO桑达尔·皮查伊一直以来都在人工智能和机器学习方面“压下重注”。

　　Earlier this year, Pichai said that AI is one of the most profound things that humanity is working on right now and compared it to basic utilities in terms of its importance. Pichai also said that AI could be used to help solve climate change issues or to cure cancer in the future.

　　今年年初，皮查伊表示人工智能是人类正在研究的最具深远意义的一件事，并将人工智能的重要性与基础公共设施作比较。皮查伊还表示，人工智能在未来可以用来帮助解决气候变化问题或是治愈癌症。