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          Facebook首席科技官:新員工要做好挨批的準備

          Jonathan Vanian 2019年10月10日

          在這個動蕩的時代,在Facebook工作會遇到各種隱私崩潰問題、信息誤傳問題,以及各類其他不愉快的事情。

          當Facebook的首席科技官邁克·施洛普弗歡迎新招聘工程人員加入這家社交網絡公司時,他首先談到的是公司在過去幾年中遭到的鋪天蓋地的批評。

          施洛普弗對《財富》雜志說:“就像是,‘嗨,歡迎加入Facebook,我先向大家介紹一下有關批評Facebook的一些頭條新聞。’我對所有人說,挨批是必然的。”

          在這個動蕩的時代,在Facebook工作會遇到各種隱私崩潰問題、信息誤傳問題,以及各類其他不愉快的事情。這些事情都會迫使施洛普弗思考公司科技可能會造成的意外后果,以及工程師保護Facebook這樣的平臺免受惡人侵害的職責。

          施洛普弗在談到那些試圖利用社交網絡實現其政治或經濟目的的人時表示:“由于平臺由樂觀主義者和技術人員搭建,因此他們不大會用惡意去揣度別人,而這正是你們必須做的事情,也就是防范這類惡意。”

          施羅普弗說自己曾經告誡新招聘員工:“我們的業務規模非常大,因此每個人肩負的責任也是十分重大。人們會仔細審視你所做的每件事情,而我們的工作就是確保通過這類審查。要做到這一點,我們必須付出大量的努力。”

          過去幾年讓施羅普弗發生了改變,今年夏天早些時候接受《紐約時報》采訪時激烈的措辭便說明了這一點,而這些措辭也引起了一些人的抵觸。Facebook高管對此的反應是:“沒事。”

          他說:“我正在努力保持自己的樂觀情緒,同時也對可能出現危害的事實有了更加深刻的認識。”

          人工智能專家施羅普弗最近也在招兵買馬,因為除了他自己打造可過濾虛假新聞的人工智能系統的工作之外,Facebook后續還將推出一系列項目。以下是Facebook正在研究的一些新項目:

          虛擬現實手部動作跟蹤

          Facebook即將發布的更新能夠讓其Oculus Quest虛擬現實頭戴設備跟蹤手部動作,要實現這一目標則需要大量的人工智能技術作為支撐。盡管Quest設備配備了可識別人手的攝像頭,然而人們在虛擬世界中移動人手時,這些攝像頭無法從各個角度捕捉人手的動作。為了解決這個問題,Facebook不得不組建一個人工智能模型,以識別手部動作,從而幫助攝像頭解決這個問題。

          人工智能芯片

          當前涌現出的一大批初創企業都在打造用于協助人工智能相關任務的計算機芯片。施羅普弗說:“從硬件層面來講,現在真是個好時候。”按照他的話說,原因在于“摩爾定律已經失效了。”按照該定義,計算機芯片晶體管數量每兩年會翻一番。

          如今,越來越多的企業都試圖打造新一代的顛覆性半導體。施羅普弗對圖形處理芯片(GPU)制造商英偉達表示了贊賞,早在2004年,該公司的芯片便可以在優化視頻游戲的同時用于處理其他任務。英偉達的GPU自那之后成為了用于培訓神經網絡的首要計算機芯片。

          老當益壯的CPU

          施羅普弗表示,盡管Facebook使用大量的GPU來培訓眾多的人工智能系統,但公司依然會使用傳統的CPU來執行一些重負荷任務。為了培訓擅長“點擊預測”的龐大神經網絡,Facebook使用了“非常龐大的CPU集群”,從而讓公司能夠更加高效地處理各類信息,即便是處理能力高達32GB的最強GPU也只能甘拜下風。

          應對深度偽造的崛起

          Facebook最近表示將贊助一項賽事。賽事期間,研究人員將開發用于偵測所謂深度偽造的最佳方式。這些視頻的內容與看起來與現實無異,其目的是欺騙或誤導觀眾。作為這個競賽的一部分,Facebook表示,公司將打造一個深度偽造視頻數據庫,來幫助研究人員開發辨別真偽的技術。

          湊巧的時,谷歌在9月下旬表示,公司也將開展這方面的舉措,向人工智能研究人員公布其自有的深度偽造視頻海量數據組,來打擊深度偽造的崛起。在談到谷歌深度偽造數據組時,施羅普弗對《財富》雜志說,他希望將數據組進行整合,這樣,這場由Facebook贊助、非營利性機構Partnership on AI監管的競賽可以有更多的偽造視頻可供分析。

          施羅普弗說,盡管深度偽造這個問題在平臺上還不是很嚴重,但“如果要問我在過去三年中都學會了什么,那就是我不希望打沒有準備的仗。”

          他說:“我寧愿帶著我不需要的工具,隨時做好戰斗的準備,而不是在某一天,特別是在例如2020年美國大選期間,當深度偽造成為一種問題的時候,我卻沒有投資相應的技術來應對這個問題。”

          譯者:馮豐

          審校:夏林

          When Facebook chief technology officer Mike Schroepfer welcomes new engineering recruits to the social network, the first thing he talks about is the massive criticism facing the company over the past few years.

          “It’s like, ‘Hi, welcome to Facebook, let me show you a bunch of news headlines of people criticizing us,” Schroepfer tells Fortune. “And what I tell everyone is the criticism is warranted.”

          Working at Facebook during this tumultuous time has included multiple privacy debacles, the spread of misinformation, and various other unpleasantries that have caused Schroepfer to consider the potential unintended consequences of the company's technology—and the role of engineers to safeguard platforms like Facebook from people with bad intentions.

          “As optimists and technologists building, it’s hard to assume bad intent, and that’s exactly what you have to do to plan for these things,” Schroepfer says referring to people who are trying to exploit the social network for political or economic gain.

          “We’re operating something on massive scale, you bear a huge responsibility—people should scrutinize everything you do, and our job is to prevail in the face of that scrutiny and that requires us to do a lot of hard work,” Schroepfer says he tells his hires.

          These past few years have changed Schroepfer, as he revealed in an emotional interview earlier this summer in The New York Times, which prompted some backlash. The Facebook executive's response: “That’s fine.”

          “I’m fighting hard to retain my optimism while coupling with a much deeper sense of sort of realism about the harms that can happen,” he says.

          Schroepfer, an artificial intelligence expert, has been staffing up recently to because Facebook has on an array of projects in its pipleline, in addition to his work building A.I. systems that can filter fake news. Here are some of the things the company is working on:

          Virtual reality hand-tracking

          Facebook’s forthcoming update that enables its Oculus Quest virtual reality headsets to track hand movements has required a lot of artificial intelligence to make it possible. Although the Quest device has cameras to help it recognize a person’s hands, it’s not possible for the cameras to capture all of the various angles when someone moves their hands around in a virtual world. To accommodate, Facebook had to build an A.I. model that could recognize hand movements to help the cameras out.

          Artificial intelligence chips

          Regarding the current boom in startups creating computer chips designed for to aid A.I.-related tasks, Schroepfer says “it’s a really interesting time for hardware.” This is because, he says, “Moore’s Law is dead,” referring to the notion that the number of transistors on a computer chip doubles every two years.

          Now there's an increasing amount of players trying to create the next game-changing semiconductor. Schroepfer commends Nvidia, the maker of the graphical processing units (GPUs,) for recognizing as early as 2004 that its chips could be used for other tasks besides making video games look prettier. Nvidia’s GPUs have since become the leading computer chips used to train neural networks.

          Good ol' CPUs

          Although Facebook uses tons of GPUs to train it many A.I. systems, it also uses conventional CPUs for some heavy-duty tasks, Schroepfer says. To train giant neural networks that are good at “click predicting,” Facebook uses “very large fleets of CPUs” that allow it to crunch information more efficiently than even the beefiest GPUs that top out at 32 GBs.

          Combating the rise of deep fakes

          Facebook recently said it would fund a competition in which researchers would develop the best ways to detect so-called deepfakes, which are realistic looking videos intended to fool or mislead people. As part of the competition, Facebook said it would create a database of deepfake videos to help researchers develop techniques to detect what’s real and what’s not.

          Coincidentally, at late September, Google said it would also contribute to efforts to combat the rise of deepfakes by releasing its own giant dataset of deepfake videos to A.I. researchers. Regarding the Google deepfake datasets, Schroepfer tells Fortune his hope is to merge the datasets so the Facebook-funded competition, overseen by the non-profit Partnership on AI, will have more fake videos to analyze.

          While deepfakes are not a clear issue on the platform today, Schroepfer says, “if I’ve learned anything in the last three years, I don’t want to be unprepared for something.”

          “I’d rather be ready to go with tools that I don’t need to use, than be in a situation especially with—say, the 2020 U.S. elections—where it becomes an issue and I haven’t invested in the technology to defend against it,” he says.

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