最近，特斯拉汽車公司CEO埃隆?穆斯克和其他科技行業領軍人物，共同投入10億美元研究人工智能。他們的研究結果將供全世界使用。人工智能具有無限可能。比如，它可以檢測細胞圖像中的異常以發現癌癥，幫助機器人與人類互動，構建幫助兒童學習的程序，以更個性化的方式按照孩子的學習進度進行授課等。

這筆讓人“感覺不錯”的投資，讓我們有機會一窺硅谷大佬最關心的問題。此外，我們也可以借此了解人工智能（即人們常說的機器學習技術）如何像上世紀90年代中期的網絡那樣顛覆科技行業。

人工智能引發的擔憂不斷見諸報端。媒體大肆宣揚人工智能將加速人類滅絕——隨著智能設備變得比人類更聰明，它們會消滅我們，當然并非出于仇恨，而是因為我們妨礙了它們實現自己的目標。最樂觀的人則關注，將來是否會出現有對話能力的性愛機器人。

但事實上，人工智能已經存在了十多年。在一些我們認為理所當然的技術中，人工智能一直在發揮重要作用，例如蘋果Siri語音助手，曾在《危機邊緣》中戰勝人類的IBM沃森超級電腦，甚至還包括特斯拉今年早些時候推出的自動駕駛功能。

在人工智能毀滅人類或者提供性滿足之前，它需要變得更好，需要更大幅度的改進。非盈利研究中心OpenAI耗資10億美元，其成立將讓我們有機會了解計算機科學與商業領域的偉大思想家們眼中的機遇和挑戰。

首先，正如分析師本?湯普森在網站Stratechery撰文指出的那樣，OpenAI的成立可以看做是一則宣言，一份面向優秀研究人才的招聘廣告。

OpenAI的博客表示，要確保商業利益不會綁架人工智能研究的前途。但湯普森透過這些空話看到了本質。他關注的是OpenAI簡介第三段的最后一句話：“我們希望，這是業內最優秀的人才們最關心的事情。”

這家新機構擔心的是，谷歌、Facebook和中國搜索引擎百度，正在用銷售說辭吸引所有機器學習人才加入他們的公司。這些公司宣稱，他們聘用的員工可以解決當今時代最復雜的社會問題。每一家公司都在利用海量的數據，幫助訓練復雜的機器學習算法。

數據是人工智能的生命線。要訓練計算機像人類一樣學習，你必須給它們提供數以萬計的示例。比如照片、地圖或詞語等。如果你希望得到不同的結果，你就需要提供不同的示例。計算機會嘗試理解這些示例的哪些要素決定了一張圖片中的貓是貓，或者哪些要素賦予了某個單詞意義。之后，算法會生成每一次猜測的統計權重，幫助計算機“學習”什么才是正確的答案。在這個過程中，計算機科學家通過提供反饋和更多示例，幫助訓練算法。

正是因為這個原因，沒有哪家公司打算放棄數據。這些數據遲早可以用于人工智能訓練。這就是為什么使用特斯拉汽車的數據生成算法的承諾，可能足以吸引研究人員去OpenAI工作，而不是去谷歌。

OpenAI聯席董事長山姆?阿爾特曼告訴《財富》雜志，特斯拉的數據將提供給OpenAI的研究人員使用。作為創業孵化器Y Combinator的領導者，他還將盡可能地為OpenAI研究人員提供該項目旗下的初創公司生成的數據。

阿爾特曼表示：“互聯網上還有海量公開數據。”研究人員可以利用這些數據生成新的工具和算法，促進人工智能的發展。

OpenAI用于吸引人才的第二個要素是其非營利性質，以及對開放性的承諾。當然，這并不是說Facebook和其他公司在研究方面不夠開放。他們也會迅速公開研究進度。雖然谷歌往往會等到其新發現獲得顯著的戰略優勢之后，才對外公布，但至少，它最終還是會公開。

本月早些時候，Facebook人工智能研究項目總監瑟爾坎?皮安蒂諾在公司新服務器首次亮相之前的電話會議上，強調了開放的重要性。Facebook的新服務器專為訓練計算機學習而設計。Facebook的工程師們希望他們的工作成果能夠回饋給開源社區。因此，Facebook將代碼分享給社區，很大程度上也是為了討好這些有公民意識的工程師。

但爭奪人才并非OpenAI存在的唯一原因。真正的人工智能的發展，將顛覆軟件業。每一家公司都希望參與到這一巨變當中。

人工智能安全初創企業Spark Cognition公司CEO阿米爾?侯賽因表示：“今天，軟件正在吞噬整個世界，未來，人工智能也會對軟件做同樣的事情。”這家公司位于德克薩斯州奧斯丁市。

他解釋說，許多取代紙質文件和檔案柜的商業軟件，最終將變成全新格式。由于人工智能在背后的努力工作，這種格式將變得更人性化。

侯賽因說：“所有分類將被打破，并重新劃分，因此，這一領域有著巨大的經濟潛力。這就好像回到了僅有一個人了解HTML語言的1995年。”

這也是被OpenAI排除在外的硅谷大公司和其他公司，紛紛想在這個領域占據一席之地的原因之一。IBM院士、IBM沃森集團副總裁兼首席技術官羅伯?海伊解釋說，這家計算業巨頭很有興趣深入了解和參與OpenAI。

與所有人一樣，IBM也是在最近才知曉OpenAI成立的消息。IBM有一個長達數十年，通過沃森研究人工智能的計劃。IBM希望人工智能可以幫助該公司應對從基于網絡的軟件轉向人工智能相關的新服務這一趨勢。

此外，IBM還在研發一種利用人工智能模仿人類大腦的全新芯片：神經突觸計算機芯片。就面向人工智能的硬件而言，IBM絕對是最認真的公司。

其次是英偉達。這家公司生產的圖形處理器，是目前訓練計算機學習的首選芯片。

讓我們再回到OpenAI，看看這家非營利機構有什么規劃。阿爾特曼表示，短期目標是生成工具和算法，并向公眾分享。而從長期而言，要創建行為與人類更相似的人工智能，必須有更出色的硬件支持。

阿爾特曼說道：“要想創建更好的人工智能和更逼真地模仿人腦，必須加大硬件研究，開發出更出色的硬件，這非常重要。但這并不是我們當下的重點。”

這或許可以解釋，為什么阿爾特曼會說，OpenAI只是非常隨意地與IBM沃森業務部門的某個人聊了聊，并沒有通過正式渠道邀請IBM參與進來。（IBM竟然沒有找到OpenAI與該公司聯系的記錄。）又或許是，在硅谷將涉及人工智能的一切都稱為機器學習的做法，與其在新品發布中推銷人工智能之間，存在一道分水嶺。IBM一直以沃森和認知計算的名義宣傳其人工智能工作，這或許在公眾當中造成了誤解。

其他許多公司也在開展人工智能研究。例如，蘋果也曾聘用研究人員，但據報道，它發現專家招聘并不順利。這在很大程度上是因為公司不希望分享研究成果。值得一提的是，微軟也在進行人工智能研究，研究方向包括針對其Skype翻譯業務的自然語言和計算機識別。

這是一種成本更低的解決辦法，與亞馬遜的作法更為類似。除了規模龐大的科技公司，初創公司、工業巨頭和研究機構也在使用人工智能進行試驗。如果OpenAI真的能夠創造出可廣泛使用的工具，這將有助于推動人類科技的進步。

阿爾特曼表示，現在確定OpenAI的研究重點還為時尚早。它將開發工具和算法，但具體的重點研究領域尚未確定。不過，他表示，如果該機構能在一年內發表“幾篇原創性論文，推動當前工藝水平的進步”，那也算是一種成功。

不過，很顯然，支持該項目的技術專家和其他人工智能研究者，都有更加宏大的目標。（財富中文網）

譯者：劉進龍/汪皓

審校：任文科

Last week, Tesla CEO Elon Musk and fellow tech kingpins committed $1 billion to researching artificial intelligence. The group’s findings would be made available for the world. The possibilities where AI might help include the ability to detect anomalies in images of cells to detect cancer, programming robots that can interact with humans, and building programs that could help teach kids at their pace of learning in a more individual style.

Behind this feel-good effort is a hint at the priorities of some of the biggest names in Silicon Valley. It also provides an understanding of how AI or machine learning, as the technology is often called, has the potential to remake the tech world in the same way the web did in the mid-’90s.

Worries about artificial intelligence have sparked headlines exclaiming that AI could bring about the death of humanity as smart machines become so much smarter than us they wipe us out, not out of malice, but because we’re simply in the way of their own goals. The most optimistic ones focused on the possibility of sex robots that can carry on conversations.

But in reality, AI has existed for over a decade. It already plays a big role in technologies that we take for granted like Apple’s Siri personal assistant, IBM’s Watson Jeopardy-winning computer, and even the autopilot feature that Teslarolled out in its cars earlier this year.

And before AI can destroy humanity, or provide sexual satisfaction, it has to get better. Much better. And the launch of OpenAI, the billion-dollar nonprofit research center announced this week, opens a window into what some of the big thinkers in computer science and business consider as opportunities and challenges.

First, as analyst Ben Thompson, who writes over at the site Stratechery, pointed out in an essay about the topic, OpenAI’s creation can be read as a manifesto, or as a recruiting ad for top research talent.

Thompson looked past the do-gooder language of the OpenAI blog post, which talks about ensuring that commercial interests don’t hijack the promise of artificial intelligence research. Instead, he focused on the final line of the third paragraph of the introduction, which reads “We hope this is what matters most to the best in the field.”

The fear is that Google, Facebook, and Chinese search engine Baiduare luring all of the machine learning talent to their companies using a sales pitch that hires can work on some of the most complex social problems of our era. Each company uses huge pools of data to help train sophisticated machine learning algorithms.

Data is the lifeblood of AI. To train computers to learn more like humans, you have to feed them tens of thousands of examples of something. Depending on what type of outcome you are hoping for, the examples can be photos, maps, or words. The computers try to understand what elements of those examples define what makes a cat a cat in an image or what gives meaning to a certain word. The algorithm then gives a statistical weight to each guess that helps the computer “learn” what the right answer is. The computer scientist helps train the algorithm by giving feedback and more examples along the way.

That’s why none of these companies ever wants to throw away data. It may come in handy for AI training someday. And that’s why the promise of using something like Tesla’s car data for building algorithms might be enough to get a researcher excited to work with OpenAI instead of Google.

Sam Altman, a co-chair at OpenAI, tells Fortune that data from Tesla would be made available to researchers working at OpenAI. He said he would also work to make data from startups that go through Y Combinator, the accelerator program he leads, available for researchers at OpenAI as well.

“There are also plenty of publicly available data sets on the Internet,” Altman said. Researchers could use those to come up with new tools and algorithms that will advance AI as well.

The second element designed to attract talent to OpenAI is its nonprofit status and its pledge of openness. It’s not that Facebook and others aren’t open with their research. They publish their research fairly quickly. Google, however, tends to wait until it has gained a significant strategic advantage from a new findings before publishing. But it is still made public.

SerkanPiantino, director of Facebook’s AI research program, emphasized the importance of openness in a conference call ahead of premiering his company’s new servers designed especially for training computers to learn earlier this month. Facebook’s engineers expect the work they do to be contributed back to the open source community. Thus, Facebook contributes code to the community in part because that keeps its civic-minded engineers happy.

But the race for talent isn’t the only reason OpenAI exists. The development of true artificial intelligence is going to remake software. And every business wants to be part of that shift.

“The way software is eating the world today, well, AI will do that to software,” says Amir Husain, CEO of Spark Cognition, an AI security startup in Austin, Texas.

He explained that many kinds of business software that replaced paper documents and in filing cabinets will eventually be transformed into a new format. And that format will likely be more user-friendly because of hard work done by artificial intelligence behind the scenes.

“All of these categories will be destroyed and remade, so there’s a lot of economic potential locked up in this,” says Husain. “It’s sort of like being the only guy in 1995 who knows HTML.”

And that, more than anything, is why the big brains in Silicon Valley and at other companies left out of the OpenAI effort are hustling to stake a claim in this space. Rob High, an IBM Fellow, and VP and CTO of IBM’s Watson Group, explained that the computing giant is interested in learning more about the organization and getting involved.

IBM, which learned about the OpenAI group on Friday like nearly everyone else, has a decades-long program in artificial intelligence through Watson. The company hopes that it will help it weather the shift from web-based software to new A.I.-related services.

But IBMis also building an entirely new type of chip designed for artificial intelligence modeled on the human brain, called a synaptic chip. As far as hardware for AI goes, IBM is the most serious player in the space.

Following is Nvidia, which makes graphics processors that are actually the preferred chip used today for training computers to learn.

That gets us back to Altman, from OpenAI, and the plans for the nonprofit. The short-term goals, he said are to build tools and algorithms that will be shared publicly. But in the long term, better hardware is needed to build AI that can perform more like a human.

“If you think about building better AI and modeling it after the human brain, more hardware research and better hardware will be important,” Altman says. “But today that is not our primary focus.”

That might be why Altman says OpenAI only spoke very casually with a person who was involved with Watson at IBM, instead of going through formal channels to try to get Big Blue involved with the project. (And why IBM found no record of someone from OpenAI contacting it at all). Or perhaps there’s simply a divide between the Silicon Valley practice of calling anything with machine learning involved AI and promoting its involvement in new product launches. Meanwhile, IBM, which brands all of its AI efforts under Watson and cognitive computing, may have confused the public.

Plenty of other companies have their own efforts in artificial intelligence. For example, Apple has hired researchers, but has reportedly found it to be tough to recruit experts. In part, it’s because the company doesn’t want to share the research results. Microsoft MSFT 1.29% also has AI research in natural language for its Skype translation efforts and computer recognition that are worth mentioning as well.

This is a cheaper way to solve the problem and more Amazon-like. Outside of the giant tech firms, startups, industrial giants, researchers and more are all experimenting with using AI. If OpenAI really does build broadly useful tools, that could help advance science for everyone.

Altman says it’s too soon to list OpenAI’s research priorities. It will work on tools and algorithms, but the specific areas where it will focus are unsure. But he said he would consider it a success if the organization, within one year, publishes “some seminal paper that drives the state of the art forward.”

However, it’s clear that technologists supporting the project and those working on AI in general, have much larger goals.