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IBM最新人工智能技术助力美国电视节目

IBM最新人工智能技术助力美国电视节目

Jeremy Kahn 2020年10月18日
该技术对节目中的数万条评论进行了归纳总结。

重新分配财富的时间是不是到了?

这是两位前政府官员在电视辩论节目中将要探讨的话题,期间,IBM最新的人工智能软件也贡献了自己的绵薄之力。这两位一位是希腊财政部的前部长,另一位是一名研究员,他们曾经对卖淫经济学(Economics of Prostitution)进行过研究。

这场辩论于美国纽约时间晚间在彭博有线电视频道播出,是系列节目《大有可辩》(That’s Debatable)的首秀剧集。每一集将围绕不同的主题展开辩论。该剧集由媒体和活动公司Intelligence Squared与Bloomberg共同打造,由Big Blue赞助。艾美奖得主记者约翰·唐文将担任该节目的主持人,他自2008年以来一直担任Intelligence Squared辩论的主持人。

第一期辩论节目将邀请四位知名经济学家助阵,他们是美国财政部前部长、哈佛大学前校长拉里·萨默斯,美国劳工部前部长罗伯特·赖克,直言不讳的希腊财政部前部长雅尼斯·瓦鲁法基斯,以及曼哈顿研究所高级研究员艾利森·希拉格(因其2019年的书作《从经济学角度来看待妓院:有助于理解风险的意外之地》而闻名)。

然而毫无疑问,IBM希望其Watson人工智能软件至少能够在一定程度上大出风头。特别值得一提的是,该节目将凸显Watson最新功能:对数千条甚至数万条个人评论和意见进行分类和总结,并将其归纳为一系列要点。

这一称之为“要点分析”的功能源于IBM对“Project Debater”项目的研究,由该公司位于以色列的人工智能实验室团队主导,涉及打造可以成功与人类辩论的人工智能软件,并帮助人类从各种信息来源中寻找强有力的论点。

IBM希望将这种技术出售给各大工作,从而将其作为一种开展市场调研、从雇员和客户中征求意见的新方式。IBM还认为,政府亦能够使用这一技术来更好地理解市民的意见。

IBM的首席人工智能建构师达科西·阿古拉沃尔说:“话题收集和论点生成这类功能来自于Debater项目,而且已经得到了部分客户的使用。”他称,要点分析将允许各大企业“搜集数万个数据点,并在提炼后助力制定数据驱动型决策。”

小屏幕上的深蓝

在过去三年中,IBM推出了一系列“大挑战”公共活动,以展示基于人工智能的技术,《大有可辩》电视节目便是其新近参加的一项活动。

电视节目采用的要点总结工具可分析用户针对某个问题通过网站提交的数千条评论。在这个节目中,这个问题就是辩题:重新分配财富的时候到了。

通过使用自然语言处理(可以分析并在一定程度上理解语言的人工智能技术),IBM系统会根据关联性对这些评论打分,去除那些与主题无关的评论。然后,该工具将把剩余评论分为两个大组:辩题正方与反方。

然后,它会使用其语言处理算法,总结每一个要点的精华,进一步将每一个组别的评论归纳为几个要点,同时避免生成使用不同语言表达同样观点的重复要点。

软件还会让用户知道所提交评论提到每个要点的频率。率领Project Debater团队的IBM工程师诺亚姆·斯隆尼姆说:“精准地告知数据中每个要点的相关性对决策者来说十分重要。”

“离题万里”

《大有可辩》的主持人唐文称,对比他以及其他辩论主持人在过去采用的常用做法——仅仅是随机让感兴趣进行评论的观众成员参与其中,该技术能够更好地让观众参与辩论。

他说:“在我看来,如果我随机叫人举手向辩手提问,观众的问题可能会让人摸不着头脑。说实话,我得筛选掉大量的问题,因为他们有的重复性很高,有的离题万里,有的存在表述问题。这项技术可以帮助应对这一挑战。”

Intelligence Squared的首席执行官克里·科纳称,要点分析人工智能能够让公司从更广泛、更多元化的人群吸取观点。它还可以借此让世界各地的人士通过网页页面提交意见。她说:“这一创新真的有助于我们了解更广泛人群对这一问题的真正看法,可能会达到数万人,而不是局限于此前在现场参加活动的400至600名观众。”斯隆尼姆称,他认为这项技术甚至可能会被用于提升未来美国总统辩论的参与性。

为了培训人工智能系统能够按照质量给论点打分,IBM不得不创建了一个涵盖3万人立场的数据库,其中涉及广泛的话题,随后,这些话题将交由10至15人的小规模人员讨论组进行评估。培训的结果随后被用于指导人工智能如何辨别清晰、强有力的论点。

要点分析功能是IBM一项技术的提炼,该公司将该技术称为“众论”,于去年11月在英格兰剑桥大学剑桥联盟俱乐部举办的一场辩论赛中首次亮相。

总结大量文本并归纳要点的能力是人工智能研究的活跃领域,拥有巨大的商用潜力。仅在过去三个月中,由埃隆·马斯克联合创建、微软参与注资的旧金山研究公司OpenAI公司以及旧金山另一家初创公司Primer,推出了能够对长文本文件进行归纳总结的工具。与此同时,Facebook的研究人员也在开发这类功能。(财富中文网)

译者:冯丰

审校:夏林

重新分配财富的时间是不是到了?

这是两位前政府官员在电视辩论节目中将要探讨的话题,期间,IBM最新的人工智能软件也贡献了自己的绵薄之力。这两位一位是希腊财政部的前部长,另一位是一名研究员,他们曾经对卖淫经济学(Economics of Prostitution)进行过研究。

这场辩论于美国纽约时间晚间在彭博有线电视频道播出,是系列节目《大有可辩》(That’s Debatable)的首秀剧集。每一集将围绕不同的主题展开辩论。该剧集由媒体和活动公司Intelligence Squared与Bloomberg共同打造,由Big Blue赞助。艾美奖得主记者约翰·唐文将担任该节目的主持人,他自2008年以来一直担任Intelligence Squared辩论的主持人。

第一期辩论节目将邀请四位知名经济学家助阵,他们是美国财政部前部长、哈佛大学前校长拉里·萨默斯,美国劳工部前部长罗伯特·赖克,直言不讳的希腊财政部前部长雅尼斯·瓦鲁法基斯,以及曼哈顿研究所高级研究员艾利森·希拉格(因其2019年的书作《从经济学角度来看待妓院:有助于理解风险的意外之地》而闻名)。

然而毫无疑问,IBM希望其Watson人工智能软件至少能够在一定程度上大出风头。特别值得一提的是,该节目将凸显Watson最新功能:对数千条甚至数万条个人评论和意见进行分类和总结,并将其归纳为一系列要点。

这一称之为“要点分析”的功能源于IBM对“Project Debater”项目的研究,由该公司位于以色列的人工智能实验室团队主导,涉及打造可以成功与人类辩论的人工智能软件,并帮助人类从各种信息来源中寻找强有力的论点。

IBM希望将这种技术出售给各大工作,从而将其作为一种开展市场调研、从雇员和客户中征求意见的新方式。IBM还认为,政府亦能够使用这一技术来更好地理解市民的意见。

IBM的首席人工智能建构师达科西·阿古拉沃尔说:“话题收集和论点生成这类功能来自于Debater项目,而且已经得到了部分客户的使用。”他称,要点分析将允许各大企业“搜集数万个数据点,并在提炼后助力制定数据驱动型决策。”

小屏幕上的深蓝

在过去三年中,IBM推出了一系列“大挑战”公共活动,以展示基于人工智能的技术,《大有可辩》电视节目便是其新近参加的一项活动。

电视节目采用的要点总结工具可分析用户针对某个问题通过网站提交的数千条评论。在这个节目中,这个问题就是辩题:重新分配财富的时候到了。

通过使用自然语言处理(可以分析并在一定程度上理解语言的人工智能技术),IBM系统会根据关联性对这些评论打分,去除那些与主题无关的评论。然后,该工具将把剩余评论分为两个大组:辩题正方与反方。

然后,它会使用其语言处理算法,总结每一个要点的精华,进一步将每一个组别的评论归纳为几个要点,同时避免生成使用不同语言表达同样观点的重复要点。

软件还会让用户知道所提交评论提到每个要点的频率。率领Project Debater团队的IBM工程师诺亚姆·斯隆尼姆说:“精准地告知数据中每个要点的相关性对决策者来说十分重要。”

“离题万里”

《大有可辩》的主持人唐文称,对比他以及其他辩论主持人在过去采用的常用做法——仅仅是随机让感兴趣进行评论的观众成员参与其中,该技术能够更好地让观众参与辩论。

他说:“在我看来,如果我随机叫人举手向辩手提问,观众的问题可能会让人摸不着头脑。说实话,我得筛选掉大量的问题,因为他们有的重复性很高,有的离题万里,有的存在表述问题。这项技术可以帮助应对这一挑战。”

Intelligence Squared的首席执行官克里·科纳称,要点分析人工智能能够让公司从更广泛、更多元化的人群吸取观点。它还可以借此让世界各地的人士通过网页页面提交意见。她说:“这一创新真的有助于我们了解更广泛人群对这一问题的真正看法,可能会达到数万人,而不是局限于此前在现场参加活动的400至600名观众。”斯隆尼姆称,他认为这项技术甚至可能会被用于提升未来美国总统辩论的参与性。

为了培训人工智能系统能够按照质量给论点打分,IBM不得不创建了一个涵盖3万人立场的数据库,其中涉及广泛的话题,随后,这些话题将交由10至15人的小规模人员讨论组进行评估。培训的结果随后被用于指导人工智能如何辨别清晰、强有力的论点。

要点分析功能是IBM一项技术的提炼,该公司将该技术称为“众论”,于去年11月在英格兰剑桥大学剑桥联盟俱乐部举办的一场辩论赛中首次亮相。

总结大量文本并归纳要点的能力是人工智能研究的活跃领域,拥有巨大的商用潜力。仅在过去三个月中,由埃隆·马斯克联合创建、微软参与注资的旧金山研究公司OpenAI公司以及旧金山另一家初创公司Primer,推出了能够对长文本文件进行归纳总结的工具。与此同时,Facebook的研究人员也在开发这类功能。(财富中文网)

译者:冯丰

审校:夏林

Is it time to redistribute the wealth?

That's the topic two former Clinton administration officials, a former Greek finance minister and a researcher who has studied the economics of prostitution, explored in a televised debate—with a little help from IBM's latest artificial intelligence software.

The debate, which aired on Bloomberg's cable television channel in the U.S. New York time, is the debut episode of a series called "That's Debatable." Each episode will feature a debate on a different topic. The show is produced by the media and events company Intelligence Squared and Bloomberg, with sponsorship from Big Blue. John Donvan, an Emmy-winning journalist who has moderated debates for Intelligence Squared since 2008, is serving as the show's host and moderator.

The first debate featured four esteemed economists: Larry Summers, the former U.S. Treasury secretary and former president of Harvard University, Robert Reich, the former U.S. Labor secretary, Yanis Varoufakis, the outspoken former Greek finance minister, and Allison Shrager, a senior fellow at the Manhattan Institute known for her 2019 book, An Economist Walks Into a Brothel: And Other Unexpected Places to Understand Risk.

But IBM is no doubt hoping that, at least to some extent, its Watson A.I. software will have stolen the show. In particular, the television program highlights one of Watson's newest capabilities: categorizing and summarizing thousands, or even hundreds of thousands, of individual comments and opinions, and distilling them down to a handful of key points.

Called "key point analysis," the capability has grown out of IBM's "Project Debater" research, spearheaded by a team in its A.I. lab in Israel, which has involved building A.I. software capable of successfully debating humans—and helping humans surface strong arguments from a variety of different types of sources.

IBM hopes that it will be able to sell the technology to companies as a new way to conduct market research and solicit views from both employees and customers. The company also thinks the technology could be used by governments to better understand the views of citizens.

"Topic clustering and argument generation, those capabilities came from Debater and these are now being used with select customers," Dakshi Agrawal, IBM's chief architect for AI, said. He said key point analysis will allow businesses to "collect tens fo thousands of data points and distill them down to make more data-driven decisions."

Big Blue on the small screen

The company has staged a series of "grand challenge" public events in the past three years designed to showcase the A.I.-based technology, of which the "It's Debatable" T.V. program is the latest.

The key point summarization tool being featured in the television show can analyze thousands of comments that users submit through a website in response to a question, in this case, the debate proposition: "It is time to redistribute the wealth."

Using natural language processing—the kind of A.I. that can analyze and to some extent "understand" language—the IBM system scores these comments for relevancy, discarding those it sees as not being germane to the topic. Then it groups the remaining ones into two broad categories: those that support the proposition, and those that oppose it.

It then further groups the comments in each camp into a handful of key points, using its language processing algorithm to summarize the essence of each point and avoiding repetition of points that are simply expressing the same idea using different language.

The software also tells a user know how often each key point was mentioned by those submitting comments. "Actually conveying the prevalence of each keypoint in the data, this is important for decision-makers," Noam Slonim, the IBM engineer who leads the Project Debater team, said.

“Off in outer space”

Donvan, the "It's Debatable" host, said that the technology was a much better way to allow the audience to participate in the debate compared to what he and other debate moderators have typically done in the past, which is to simply call on audience members interested in making a comment more or less at random.

"Audiences can be very tricky for me in that I randomly call on people to raise their hands and ask a question of the debaters, and to be honest I have to throw out a large number of the questions because they are repetitive, or they off in outer space, or they are just not well articulated," he said. "This helps with that challenge."

Clea Conner, Intelligence Squared's chief executive officer, said the key point analysis A.I. allowed the company to incorporate views from a much broader and diverse group of people. It does so by enabling people anywhere in the world to submit opinions via a Web page. "This innovation is really helping us understand what a much larger group of people than the four or six hundred that could attend the event live previously, in this case thousands of people, where they really stand on the issue," she said. Slonim said he thought the technology could even be used to make future U.S. Presidential Debates more participatory.

To train an A.I. system to score arguments for quality, IBM had to create a database of 30,000 human-generated positions on a wide variety of topics which were then assessed by small human focus groups of 10 to 15 individuals, Slonim said. The results of this exercise were then used to teach the A.I. what constituted a coherent, strong argument.

The key point analysis feature is a refinement of a technology, which IBM called "speech by crowd," that it unveiled last November in a debate held at the Cambridge Union debating club at Cambridge University in England.

The ability to summarize large amounts of text and pull out key points is an active area of A.I. research with big potential commercial applications. In just the past three months, both OpenAI, the San Francisco research company that was co-founded by Elon Musk and has received funding from Microsoft, and Primer, another startup in San Francisco, have unveiled tools that can summarize long text documents. Researchers at Facebook have also been pursuing this capability too.

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