谷歌全新AI搜索引擎讓你暢快查文獻(xiàn)

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.

谷歌研究院正在讓我們得以一瞥，人工智能領(lǐng)域的自然語言處理技術(shù)已經(jīng)取得了多大的進(jìn)展。山景城(谷歌位于加州的總部)的研究部門推出了幾個(gè)網(wǎng)站，被稱為Semantic Experiences(語義體驗(yàn))，這些網(wǎng)站有一些有趣的活動(dòng)，活動(dòng)展現(xiàn)出人工智能有理解我們語言的能力。

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.

大眾可以享受兩種技術(shù)體驗(yàn)，而第三種是針對(duì)開發(fā)者的，可以幫助他們開發(fā)屬于自己的“體驗(yàn)”。前兩種體驗(yàn)中，一個(gè)被稱作“Talk to Books”，使用這一技術(shù)，用戶可以探索與書籍交流的新方式，另一個(gè)是“Semantris”，人們?cè)谶@一部分可以玩到由語義研究提供支持的單詞聯(lián)想游戲。

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.”

這兩個(gè)公開實(shí)驗(yàn)中的第一個(gè)被稱作“Talk to Books”，毫不夸張地說，它可以讓你與機(jī)器學(xué)習(xí)訓(xùn)練型算法進(jìn)行交流，該算法通過人工文本的相關(guān)段落來回答問題。正如庫茲韋爾(谷歌的技術(shù)總監(jiān))和伯恩斯坦(谷歌的產(chǎn)品經(jīng)理)所說，“Talk to Books”讓你可以“陳述一件事情或是提出一個(gè)問題，該工具可以在書中找到回應(yīng)的語句，而不依賴于關(guān)鍵詞匹配。”

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.”

二人還補(bǔ)充說：“從某種意義上來說，你是在與書籍交談，從機(jī)器那里得到的回應(yīng)可以幫助你確定是否有興趣進(jìn)一步閱讀這些書。”

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.

如果你問一個(gè)問題，諸如“為什么天是藍(lán)色的?”，你會(huì)從這一主題的相關(guān)書籍中得到許多不同的答案，答案會(huì)以清晰的文本形式展示給你，例如“隨著波長(zhǎng)的降低，光在大氣中分子的瑞利散射會(huì)變得更強(qiáng)”。但是，與使用標(biāo)準(zhǔn)的谷歌搜索不同，你不必再去點(diǎn)擊鏈接，解析一篇文章或是網(wǎng)頁，“Talk To Books”的算法為你完成了這一工作。

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)."

詞向量的發(fā)展促使了過去幾年中自然語言處理技術(shù)的進(jìn)步與提升，這是一種人工智能訓(xùn)練模型，使算法能夠根據(jù)實(shí)際的語言使用情況來學(xué)習(xí)單詞之間的關(guān)聯(lián)。庫茲韋爾和伯恩斯坦表示，這些網(wǎng)站展示了人工智能的“新功能如何去推動(dòng)以前不可能實(shí)現(xiàn)的應(yīng)用”。他們表示還有一些其他潛在的應(yīng)用，包括“分類、語義相似性、語義聚類、白名單(從眾多選擇中選取正確答案)和語義搜索(其中‘Talk to Books’就是一個(gè)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.

谷歌還發(fā)布了一個(gè)TensorFlow 模塊供其他研究人員和開發(fā)者使用，如此一來，這家科技巨頭公司可能會(huì)引領(lǐng)更多人工智能應(yīng)用的出現(xiàn)，這些應(yīng)用能夠比過去更好地理解我們對(duì)語言的使用。

“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.”

“驅(qū)動(dòng)這個(gè)實(shí)驗(yàn)的模型接受了10億個(gè)類似對(duì)話句子的訓(xùn)練，來學(xué)習(xí)如何作出更好的回應(yīng)，” 庫茲韋爾和伯恩斯坦解釋說， “當(dāng)用戶提出問題(或者做出陳述)時(shí)，這些工具就會(huì)搜索超過10萬本書籍中的所有句子，根據(jù)句子級(jí)別的語義找出那些可以回應(yīng)用戶輸入的句子;而且不會(huì)有預(yù)定義的規(guī)則來限制用戶輸入的內(nèi)容和得到的結(jié)果之間的關(guān)系。”

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

谷歌的CEO桑達(dá)爾·皮查伊一直以來都在人工智能和機(jī)器學(xué)習(xí)方面“壓下重注”。

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類正在研究的最具深遠(yuǎn)意義的一件事，并將人工智能的重要性與基礎(chǔ)公共設(shè)施作比較。皮查伊還表示，人工智能在未來可以用來幫助解決氣候變化問題或是治愈癌癥。