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发布时间:2020-10-31    来源:亚州城登录21517


Google’s big bet on computers that can teach themselves is about to face its most significant押注计算机可以自律自学的赌局,将要面对最根本性的考验。Machine learning has brought artificial intelligence (AI) back into the technology mainstream which, for Google, means using its computing resources to analyse mountains of data to identify patterns and make predictions, from calculating the adverts users are likely to find relevant to whether a digital image shows a cat or a dog.机器学习把人工智能(AI)带上返回科技主流中,对谷歌而言,这意味著利用它的计算能力来分析海量数据以识别模式并做出预测,从计算出来用户有可能实在涉及的广告,到一幅数字图像表明的是猫还是狗。It’s now solving problems we don’t know how to solve in any other way, said Jeff Dean, the engineer who has spearheaded Google’s efforts since it began to focus on the area nearly five years ago. 它现在正在解决问题我们几乎不告诉如何解决问题的问题,自谷歌在近5年前开始探讨该领域以来仍然引导研究的工程师杰夫迪恩(Jeff Dean)回应。About 100 product teams at Google now apply the technology, he added. 他补足称之为,谷歌如今大约有100个产品团队正在应用于这项技术。

The latest — and most visible — product of the push is an intelligent digital assistant, intended to usher in a more natural and intelligent form of human-computer interaction, based on the use of everyday language. 近期(也最醒目)的产品是一个智能数字助理,目的打开一个更加大自然、更加智能的嵌入式模式,基于日常语言的用于。The feature — called Assistant — is due to appear, in different guises, in a range of Google products and services in the coming weeks.被称作助手(Assistant)的这项功能将于未来几周以有所不同形式经常出现在谷歌一系列产品和服务中。

That will give it a central place in the company’s efforts to steal users away from some of its rivals’ most successful recent ventures. 它将有助谷歌从某些竞争对手最顺利的新项目夺回用户。These include Amazon’s voice-activated home device, Echo; Apple’s smart assistant, Siri; and Facebook’s messaging services, Messenger and WhatsApp.这些还包括亚马逊(Amazon)的家庭声控设备Echo;苹果(Apple)的智能助手Siri;以及Facebook的通讯服务——Messenger和WhatsApp。

But even for a company with Google’s massive computing power and engineering brains, teaching computers to act more naturally and intelligently has required it to confront some of the most intractable computer science problems.但是,即使是对于像谷歌那样享有可观计算能力和工程设计人才的公司来说,教会计算机更加大自然更加智能地行动,也必须面临一些最棘手的计算机科学问题。Google certainly has the bench strength to make a dent in this problem but no one has cracked the code yet, said Tim Tuttle, chief executive of MindMeld, an AI start-up that is building its own platform for conversational computing.谷歌当然享有充足强劲的人才实力来挑战这个问题,但是目前为止还没有人能几乎密码,AI初创企业MindMeld的首席执行官蒂姆塔特尔(Tim Tuttle)回应。该公司正在打造出自己的对话式计算出来平台。Many experts in the AI field credit Google with having edged ahead of its main rivals in machine learning.AI领域的很多专家否认,谷歌在机器学习方面领先于其主要竞争对手。


It has been showing leading edge results in the field, said Oren Etzioni, head of artificial intelligence at the research institute of Microsoft co-founder Paul Allen. 在微软公司(Microsoft)联合创始人保罗艾伦(Paul Allen)的研究所负责管理AI研究的奥伦埃齐奥尼(Oren Etzioni)称之为,谷歌在该领域展现出了前沿成果。He credits it with taking a more open approach than rivals, publishing its research and making its technologies freely available. 他指出,这是由于谷歌采行了比输掉更加对外开放的姿态,公开发表研究结果,并使其技术可以免费取得。This open-sourcing has helped it build a wider ecosystem around its approach. 这种开源模式协助它环绕自己的方法创建了一个更大的生态系统。

Amazon has adopted a much more closed model and is playing catch-up in machine learning, said Mr Etzioni. The people that they have attracted are not at the same level.亚马逊使用了更加堵塞的模式,在机器学习领域于是以追上谷歌,埃齐奥尼称之为,他们更有到的人才不是同一水平的。All of this has served to raise expectations that Google’s Assistant will reach new standards in understanding language and supplying more intelligent guidance, from answering direct questions to steering users through tasks such as finding a restaurant for dinner or arranging a flight. 所有这一切都起着了提升期望值的起到,即谷歌Assistant在解读语音和获取更加智能的提示上将超过新的水平,从问必要的问题,到指导用户已完成找寻餐厅或决定航班等任务。But the heightened expectations have also greatly elevated the risks. 但是,期望值提升也大大提高了风险。Users are often quick to impute high levels of intelligence to computers that appear to understand language, leaving plenty of room for disappointment when the results fall short.用户往往迅速指出或许解读语言的计算机具备高智能,当结果不尽人意时会十分沮丧。

Google first disclosed its plans for Assistant at its annual developer conference in May. 谷歌于今年5月在年度开发者大会上首次透漏了Assistant计划。The technology will take different forms, depending on the device or service where it is used. 该技术将根据用于的设备或服务而采行有所不同形式。It is set to be used in a product called Home, a voice-activated gadget modelled on Amazon’s breakthrough Echo. 预计将用作一款被称作Home的语音工具产品(效仿亚马逊的Echo)。

Google also said in May that it would power a text-based intelligent service to appear inside Allo, an app launched yesterday (see below) that is intended to propel Google, belatedly, into messaging.谷歌5月时还回应,该技术将用作在应用软件Allo中驱动基于文本的智能服务。近日已公布的Allo目的推展谷歌转入即时信息领域。


With these new approaches, the search company is betting that many people are ready to try new ways of interacting with digital devices. 凭借这些新方法,这家搜寻公司押注很多人都已准备好尝试与数字化设备交互的新方式。Around 20 per cent of searches on Android devices in the US are already conducted by voice, according to Google.据谷歌回应,在美国,Android设备上展开的搜寻大约20%通过语音已完成。Advances in the quality of techniques like speech recognition have brought the technology to a stage where it is ready for a mass market, said Mr Dean. 迪恩称之为,语音辨识等技术的变革,使得AI超过了可以面向大众市场的阶段。

For instance, Google says its error rate in understanding spoken words, even in a noisy room, has fallen to 8 per cent.例如,谷歌称之为其解读口语单词的错误率(即使是在喧闹的房间内)已降到8%。The company has done a remarkable job in areas such as speech recognition and the text-to-speech feature that turns search results into spoken answers, said Mr Tuttle.塔特尔称之为,该公司还在语音辨识和文本切换语音(将搜寻结果切换为语音问)等领域获得了出众的展现出。Each of these draws on Google’s roots in internet search, which supplies it with mountains of data about general language usage to fuel its core language engines. 这一切顺利都利用了谷歌在互联网搜寻方面的根基,后者使其可以利用有关一般语言用法的海量数据来推展其核心语言引擎。

In these contexts, Google has an advantage, says Mr Tuttle.在这些方面,谷歌具备优势,塔特尔回应。However, understanding language at the deeper level involves grasping the context of a statement, which is often not obvious, or being able to follow a sequence of comments that follow human but not computer logic. 然而,若要在加深层面上解读语言,就必定牵涉到掌控一句话的背景(往往不显著)或是需要解读一系列遵循人类(而非计算机)逻辑的评论。These are things that trip up general-purpose tools such as Assistant, said Mr Tuttle.塔特尔称之为,这些任务不会使Assistant等标准化工具错误。

In taking on the more intractable challenges, Google is looking to draw on deep learning, the most advanced form of machine learning. 为了应付更加棘手的挑战,谷歌正在谋求利用深度自学——机器学习的最高级形式。Patterned on the workings of the human brain, deep learning systems use multiple processing layers, like artificial neural networks, to filter data to reach their results. 深度自学系统糅合人类大脑的工作方式,利用多个处置层(就像人工神经网络那样)来过滤器数据以获得结果。The technology is particularly well suited to things that computers have traditionally found impossible, such as image recognition, and has been applied most strikingly in Google’s Photos app to automatically identify people or objects in users’ albums.这项技术尤其适合于处置传统电脑不有可能已完成的任务,比如图像识别。

该技术目前为止最引人瞩目的应用于是在谷歌Blogger(Photos)的用户相簿中自动识别人或物体。According to Mr Dean, the sort of breakthroughs made in image recognition are now beginning to be seen in language, divining context and meaning where other programs have foundered. 据迪恩回应,图像识别上的这种突破,如今早已开始经常出现在语音、语境和语意推断方面;在这些方面,其他程序已告终。What’s happened recently is the deep learning approaches have started showing an ability to understand language for many different tasks, he said.最近经常出现的情况是,深度自学方法开始在很多有所不同的任务中展现出出有了解读语言的能力,他称之为。


He concedes, though, that Google’s computers are still far from matching human levels of language comprehension, or replicating the broad understanding of the world that people draw on when holding a conversation. 尽管如此,他否认谷歌的计算机距离人类语言理解能力、或者人类在对话时利用很深背景科学知识的程度依然很近。We have a pretty good ability to understand shorter sentences or utterances, said Mr Dean. But we don’t have the ability in long-range context, or the deep background models a human has from other areas when you are talking.我们在解读较短的句子或传达时享有非常出众的能力,迪恩称之为,但是我们无法解读长程语境和人类在说出时来自其他方面的深层背景模式。

A further challenge will be to restrict the situations in which Assistant can handle tasks automatically, limiting it to areas where there is little chance of it making a mistake. 还有一个挑战将容许Assistant自动处置任务的情形,把它容许在受罚几率较小的领域。It is one thing to unleash a deep learning program to identify pictures of cats, said Mr Dean, but it is another to set the same program free to make changes to your travel itinerary, where a slight misunderstanding would cause deep inconvenience.迪恩称之为,获释一款深度自学程序来辨识猫咪照片是一其实,而回头让某种程度的程序来变更你的行程则是另一回事。

在后面一种情形中,微小的误会都会导致很大的不便。As a result, the packaging of the new Assistant technology — finding a useful set of tasks that it can do well, without over-promising or disappointing — is likely to be as important to its success as the underlying technical achievements themselves. 其结果是,新的Assistant技术的纸盒——在不过度允诺或让人沮丧的情况下,寻找一套它可以顺利完成的任务——可能会和它本身作为根本性技术成就的顺利某种程度最重要。

The best technologies don’t always translate to the best product or the winner in the market place, said Mr Etzioni. Google has already seen Amazon steal a march with the groundbreaking Echo, and Apple catch the popular imagination with Siri. With Assistant, it is time to get back into the conversation.最差的技术并不总是转化成为最篮的产品或市场上的赢家,埃齐奥尼称之为。在眼见着亚马逊以开创性的Echo先声夺人、苹果以Siri逃跑大众想象力之后,谷歌是时候在Assistant的协助下新的沦为注目焦点。



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