Until April, Microsoft boasted of having the largest collection of faces that anyone could use to train facial-recognition algorithms. Since then, the once publicly-available dataset has quietly disappeared.
直到四月,微软都吹嘘拥有最大的人脸数据库,任何人都可以使用它来训练面部识别算法。而那之后,曾经公开可用的数据集已经悄然消失。
As the Financial Times reports, Microsoft quietly deleted the dataset after the paper called attention to privacy and ethical issues, including use of the dataset by military researcherss.
正如英国《金融时报》报道的那样,在该报引发了关于隐私和道德问题的关注之后(包括军事研究人员和中国监管公司使用数据集),微软悄然删除了数据集。
Microsoft did not immediately respond to a request for comment from Fortune. But it told the Financial Times: “The site was intended for academic purposes. It was run by an employee that is no longer with Microsoft and has since been removed.”
微软没有立即回复《财富》杂志的评论请求。但它告诉英国《金融时报》:“该网站是为了学术目的设立的。它由一名不再受雇于微软的员工运营,并且已经被删除。”
The now-deleted dataset contained more than 10 million faces culled from websites like Flickr, which host photographs uploaded under a Creative Commons license—meaning many can be used free of copyright concerns.
现已删除的数据集中包含超过1000万张面孔,这些面孔来自Flickr等网站,这些网站储存的是根据知识共享许可上传的照片——这意味着许多都可以免费,但可能有版权问题。
The name of the Microsoft dataset, MS Celeb, was chosen because many of the images it contains are famous people who live public lives. Many of the other faces in the set, however, belong to people who are not celebrities—including journalists and privacy researchers—and who were not aware their images had been included.
这个微软的数据集叫MS Celeb,之所以选择这个名称,是因为它包含的许多图像都是过着公开生活的名人。然而,该集中的许多其他面孔属于不是名人的人——包括记者和隐私研究人员——并且他们不知道他们的图像被包括在内。
Microsoft is hardly the only company to assemble large datasets by scraping photos from the open Internet. In January, IBM announced it was sharing a collection of 1 million faces in the name of promoting more diversity in artificial intelligence. Meanwhile, a website called Megapixels identifies several other massive collections as part of a bid to halt what it describes as a “growing crisis of authoritarian biometric surveillance.”
微软并不是唯一一家通过从开放的互联网上抓取照片来组装大型数据集的公司。今年1月,IBM宣布它正在以促进人工智能更多样化的名义共享100万张面孔。与此同时,一个名为Megapixels的网站确定了另外几个大型集合,以此来阻止它所谓的“威胁性的生物识别监视危机”。
While many of the facial recognition sets are culled from public websites like Flickr, that is not the only way companies obtain pictures of faces. As a recent Fortune investigation revealed, startups have been using photo collection apps to surreptitiously collect millions of faces, while other companies have been scanning public collections of mug shots.
虽然像Flickr这样的公共网站很多都剔除了面部识别装置,但这并不是公司获取面部图片的唯一方式。最近《财富》调查显示,创业公司一直在使用照片收集应用程序暗中收集数百万张面孔,而其他公司则一直在扫描大量的大头照。
雅思听力:考生如何避免考场失误
雅思听力长段子精听技巧
雅思听力考试如何获得高分
雅思听力复习四步走
雅思听力听不懂怎么办
雅思听力:边听边锁定出题点
雅思听力场景词汇及解析:相貌篇
雅思听力高分4step晋级法
Bottom-Up听力复习法 轻松拿下雅思听力
雅思听力走神问题如何解决
雅思听力需注意的冷门知识点
浅谈雅思听力和雅思口语的备考方法
揭秘雅思听力备考新方向
雅思听力攻略:解析8大失分点
雅思听力训练首先要解决生词的问题
雅思听力:如何发现段落主题
雅思听力考试为什么审题时会容易犯错误
雅思听力精听方法步骤介绍
雅思听力:配对题应考技巧
雅思听力选择题——雾里如何看花
解读雅思听力的“游戏规则”
雅思听力考点解读:相貌场景的考点及词汇
听力练习:“肥皂剧”比题海战术更好
关于雅思听力9个问题的解答
需要避免的十大雅思听力问题
雅思听力技巧:如何发现段落主题
四点攻克雅思听力表格题
总结:雅思听力完成句五项答题要领
如何才能有效的提高雅思听力水平
雅思听力训练:生词问题
| 不限 |
| 英语教案 |
| 英语课件 |
| 英语试题 |
| 不限 |
| 不限 |
| 上册 |
| 下册 |
| 不限 |