當(dāng)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(wǎng)絡(luò)公司時(shí),，他首先談到的是公司在過(guò)去幾年中遭到的鋪天蓋地的批評(píng),。

施洛普弗對(duì)《財(cái)富》雜志說(shuō)：“就像是，‘嗨,，歡迎加入Facebook，我先向大家介紹一下有關(guān)批評(píng)Facebook的一些頭條新聞,?！覍?duì)所有人說(shuō)，挨批是必然的,?！?/p>

在這個(gè)動(dòng)蕩的時(shí)代，在Facebook工作會(huì)遇到各種隱私崩潰問(wèn)題,、信息誤傳問(wèn)題,，以及各類(lèi)其他不愉快的事情。這些事情都會(huì)迫使施洛普弗思考公司科技可能會(huì)造成的意外后果,，以及工程師保護(hù)Facebook這樣的平臺(tái)免受惡人侵害的職責(zé),。

施洛普弗在談到那些試圖利用社交網(wǎng)絡(luò)實(shí)現(xiàn)其政治或經(jīng)濟(jì)目的的人時(shí)表示：“由于平臺(tái)由樂(lè)觀主義者和技術(shù)人員搭建,，因此他們不大會(huì)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(lèi)惡意,。”

施羅普弗說(shuō)自己曾經(jīng)告誡新招聘員工：“我們的業(yè)務(wù)規(guī)模非常大,，因此每個(gè)人肩負(fù)的責(zé)任也是十分重大,。人們會(huì)仔細(xì)審視你所做的每件事情，而我們的工作就是確保通過(guò)這類(lèi)審查,。要做到這一點(diǎn),，我們必須付出大量的努力?！?/p>

過(guò)去幾年讓施羅普弗發(fā)生了改變,，今年夏天早些時(shí)候接受《紐約時(shí)報(bào)》采訪時(shí)激烈的措辭便說(shuō)明了這一點(diǎn)，而這些措辭也引起了一些人的抵觸,。Facebook高管對(duì)此的反應(yīng)是：“沒(méi)事,。”

他說(shuō)：“我正在努力保持自己的樂(lè)觀情緒,，同時(shí)也對(duì)可能出現(xiàn)危害的事實(shí)有了更加深刻的認(rèn)識(shí),。”

人工智能專(zhuān)家施羅普弗最近也在招兵買(mǎi)馬,，因?yàn)槌怂约捍蛟炜蛇^(guò)濾虛假新聞的人工智能系統(tǒng)的工作之外,，F(xiàn)acebook后續(xù)還將推出一系列項(xiàng)目。以下是Facebook正在研究的一些新項(xiàng)目：

虛擬現(xiàn)實(shí)手部動(dòng)作跟蹤

Facebook即將發(fā)布的更新能夠讓其Oculus Quest虛擬現(xiàn)實(shí)頭戴設(shè)備跟蹤手部動(dòng)作,，要實(shí)現(xiàn)這一目標(biāo)則需要大量的人工智能技術(shù)作為支撐,。盡管Quest設(shè)備配備了可識(shí)別人手的攝像頭，然而人們?cè)谔摂M世界中移動(dòng)人手時(shí),，這些攝像頭無(wú)法從各個(gè)角度捕捉人手的動(dòng)作,。為了解決這個(gè)問(wèn)題，F(xiàn)acebook不得不組建一個(gè)人工智能模型,，以識(shí)別手部動(dòng)作,，從而幫助攝像頭解決這個(gè)問(wèn)題。

人工智能芯片

當(dāng)前涌現(xiàn)出的一大批初創(chuàng)企業(yè)都在打造用于協(xié)助人工智能相關(guān)任務(wù)的計(jì)算機(jī)芯片,。施羅普弗說(shuō)：“從硬件層面來(lái)講,，現(xiàn)在真是個(gè)好時(shí)候?！卑凑账脑?huà)說(shuō),，原因在于“摩爾定律已經(jīng)失效了?！卑凑赵摱x,，計(jì)算機(jī)芯片晶體管數(shù)量每?jī)赡陼?huì)翻一番,。

如今，越來(lái)越多的企業(yè)都試圖打造新一代的顛覆性半導(dǎo)體,。施羅普弗對(duì)圖形處理芯片（GPU）制造商英偉達(dá)表示了贊賞,，早在2004年，該公司的芯片便可以在優(yōu)化視頻游戲的同時(shí)用于處理其他任務(wù),。英偉達(dá)的GPU自那之后成為了用于培訓(xùn)神經(jīng)網(wǎng)絡(luò)的首要計(jì)算機(jī)芯片,。

老當(dāng)益壯的CPU

施羅普弗表示，盡管Facebook使用大量的GPU來(lái)培訓(xùn)眾多的人工智能系統(tǒng),，但公司依然會(huì)使用傳統(tǒng)的CPU來(lái)執(zhí)行一些重負(fù)荷任務(wù),。為了培訓(xùn)擅長(zhǎng)“點(diǎn)擊預(yù)測(cè)”的龐大神經(jīng)網(wǎng)絡(luò)，F(xiàn)acebook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(lèi)信息,，即便是處理能力高達(dá)32GB的最強(qiáng)GPU也只能甘拜下風(fēng)。

應(yīng)對(duì)深度偽造的崛起

Facebook最近表示將贊助一項(xiàng)賽事,。賽事期間,，研究人員將開(kāi)發(fā)用于偵測(cè)所謂深度偽造的最佳方式。這些視頻的內(nèi)容與看起來(lái)與現(xiàn)實(shí)無(wú)異,，其目的是欺騙或誤導(dǎo)觀眾,。作為這個(gè)競(jìng)賽的一部分，F(xiàn)acebook表示,，公司將打造一個(gè)深度偽造視頻數(shù)據(jù)庫(kù),，來(lái)幫助研究人員開(kāi)發(fā)辨別真?zhèn)蔚募夹g(shù)。

湊巧的時(shí),，谷歌在9月下旬表示,，公司也將開(kāi)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(shù)據(jù)組,，來(lái)打擊深度偽造的崛起,。在談到谷歌深度偽造數(shù)據(jù)組時(shí)，施羅普弗對(duì)《財(cái)富》雜志說(shuō),，他希望將數(shù)據(jù)組進(jìn)行整合,，這樣，這場(chǎng)由Facebook贊助,、非營(yíng)利性機(jī)構(gòu)Partnership on AI監(jiān)管的競(jìng)賽可以有更多的偽造視頻可供分析。

施羅普弗說(shuō),，盡管深度偽造這個(gè)問(wèn)題在平臺(tái)上還不是很?chē)?yán)重,，但“如果要問(wèn)我在過(guò)去三年中都學(xué)會(huì)了什么，那就是我不希望打沒(méi)有準(zhǔn)備的仗,?！?/p>

他說(shuō)：“我寧愿帶著我不需要的工具,，隨時(shí)做好戰(zhàn)斗的準(zhǔn)備，而不是在某一天,，特別是在例如2020年美國(guó)大選期間,，當(dāng)深度偽造成為一種問(wèn)題的時(shí)候，我卻沒(méi)有投資相應(yīng)的技術(shù)來(lái)應(yīng)對(duì)這個(gè)問(wèn)題,?！?/p>

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.