硅谷大佬为什么都在豪赌人工智能

最近，特斯拉汽车公司CEO埃隆•穆斯克和其他科技行业领军人物，共同投入10亿美元研究人工智能。他们的研究结果将供全世界使用。人工智能具有无限可能。比如，它可以检测细胞图像中的异常以发现癌症，帮助机器人与人类互动，构建帮助儿童学习的程序，以更个性化的方式按照孩子的学习进度进行授课等。

这笔让人“感觉不错”的投资，让我们有机会一窥硅谷大佬最关心的问题。此外，我们也可以借此了解人工智能（即人们常说的机器学习技术）如何像上世纪90年代中期的网络那样颠覆科技行业。

人工智能引发的担忧不断见诸报端。媒体大肆宣扬人工智能将加速人类灭绝——随着智能设备变得比人类更聪明，它们会消灭我们，当然并非出于仇恨，而是因为我们妨碍了它们实现自己的目标。最乐观的人则关注，将来是否会出现有对话能力的性爱机器人。

但事实上，人工智能已经存在了十多年。在一些我们认为理所当然的技术中，人工智能一直在发挥重要作用，例如苹果Siri语音助手，曾在《危机边缘》中战胜人类的IBM沃森超级电脑，甚至还包括特斯拉今年早些时候推出的自动驾驶功能。

在人工智能毁灭人类或者提供性满足之前，它需要变得更好，需要更大幅度的改进。非盈利研究中心OpenAI耗资10亿美元，其成立将让我们有机会了解计算机科学与商业领域的伟大思想家们眼中的机遇和挑战。

首先，正如分析师本•汤普森在网站Stratechery撰文指出的那样，OpenAI的成立可以看做是一则宣言，一份面向优秀研究人才的招聘广告。

OpenAI的博客表示，要确保商业利益不会绑架人工智能研究的前途。但汤普森透过这些空话看到了本质。他关注的是OpenAI简介第三段的最后一句话：“我们希望，这是业内最优秀的人才们最关心的事情。”

这家新机构担心的是，谷歌、Facebook和中国搜索引擎百度，正在用销售说辞吸引所有机器学习人才加入他们的公司。这些公司宣称，他们聘用的员工可以解决当今时代最复杂的社会问题。每一家公司都在利用海量的数据，帮助训练复杂的机器学习算法。

数据是人工智能的生命线。要训练计算机像人类一样学习，你必须给它们提供数以万计的示例。比如照片、地图或词语等。如果你希望得到不同的结果，你就需要提供不同的示例。计算机会尝试理解这些示例的哪些要素决定了一张图片中的猫是猫，或者哪些要素赋予了某个单词意义。之后，算法会生成每一次猜测的统计权重，帮助计算机“学习”什么才是正确的答案。在这个过程中，计算机科学家通过提供反馈和更多示例，帮助训练算法。

正是因为这个原因，没有哪家公司打算放弃数据。这些数据迟早可以用于人工智能训练。这就是为什么使用特斯拉汽车的数据生成算法的承诺，可能足以吸引研究人员去OpenAI工作，而不是去谷歌。

OpenAI联席董事长山姆•阿尔特曼告诉《财富》杂志，特斯拉的数据将提供给OpenAI的研究人员使用。作为创业孵化器Y Combinator的领导者，他还将尽可能地为OpenAI研究人员提供该项目旗下的初创公司生成的数据。

阿尔特曼表示：“互联网上还有海量公开数据。”研究人员可以利用这些数据生成新的工具和算法，促进人工智能的发展。

OpenAI用于吸引人才的第二个要素是其非营利性质，以及对开放性的承诺。当然，这并不是说Facebook和其他公司在研究方面不够开放。他们也会迅速公开研究进度。虽然谷歌往往会等到其新发现获得显著的战略优势之后，才对外公布，但至少，它最终还是会公开。

本月早些时候，Facebook人工智能研究项目总监瑟尔坎•皮安蒂诺在公司新服务器首次亮相之前的电话会议上，强调了开放的重要性。Facebook的新服务器专为训练计算机学习而设计。Facebook的工程师们希望他们的工作成果能够回馈给开源社区。因此，Facebook将代码分享给社区，很大程度上也是为了讨好这些有公民意识的工程师。

但争夺人才并非OpenAI存在的唯一原因。真正的人工智能的发展，将颠覆软件业。每一家公司都希望参与到这一巨变当中。

人工智能安全初创企业Spark Cognition公司CEO阿米尔•侯赛因表示：“今天，软件正在吞噬整个世界，未来，人工智能也会对软件做同样的事情。”这家公司位于德克萨斯州奥斯丁市。

他解释说，许多取代纸质文件和档案柜的商业软件，最终将变成全新格式。由于人工智能在背后的努力工作，这种格式将变得更人性化。

侯赛因说：“所有分类将被打破，并重新划分，因此，这一领域有着巨大的经济潜力。这就好像回到了仅有一个人了解HTML语言的1995年。”

这也是被OpenAI排除在外的硅谷大公司和其他公司，纷纷想在这个领域占据一席之地的原因之一。IBM院士、IBM沃森集团副总裁兼首席技术官罗伯•海伊解释说，这家计算业巨头很有兴趣深入了解和参与OpenAI。

与所有人一样，IBM也是在最近才知晓OpenAI成立的消息。IBM有一个长达数十年，通过沃森研究人工智能的计划。IBM希望人工智能可以帮助该公司应对从基于网络的软件转向人工智能相关的新服务这一趋势。

此外，IBM还在研发一种利用人工智能模仿人类大脑的全新芯片：神经突触计算机芯片。就面向人工智能的硬件而言，IBM绝对是最认真的公司。

其次是英伟达。这家公司生产的图形处理器，是目前训练计算机学习的首选芯片。

让我们再回到OpenAI，看看这家非营利机构有什么规划。阿尔特曼表示，短期目标是生成工具和算法，并向公众分享。而从长期而言，要创建行为与人类更相似的人工智能，必须有更出色的硬件支持。

阿尔特曼说道：“要想创建更好的人工智能和更逼真地模仿人脑，必须加大硬件研究，开发出更出色的硬件，这非常重要。但这并不是我们当下的重点。”

这或许可以解释，为什么阿尔特曼会说，OpenAI只是非常随意地与IBM沃森业务部门的某个人聊了聊，并没有通过正式渠道邀请IBM参与进来。（IBM竟然没有找到OpenAI与该公司联系的记录。）又或许是，在硅谷将涉及人工智能的一切都称为机器学习的做法，与其在新品发布中推销人工智能之间，存在一道分水岭。IBM一直以沃森和认知计算的名义宣传其人工智能工作，这或许在公众当中造成了误解。

其他许多公司也在开展人工智能研究。例如，苹果也曾聘用研究人员，但据报道，它发现专家招聘并不顺利。这在很大程度上是因为公司不希望分享研究成果。值得一提的是，微软也在进行人工智能研究，研究方向包括针对其Skype翻译业务的自然语言和计算机识别。

这是一种成本更低的解决办法，与亚马逊的作法更为类似。除了规模庞大的科技公司，初创公司、工业巨头和研究机构也在使用人工智能进行试验。如果OpenAI真的能够创造出可广泛使用的工具，这将有助于推动人类科技的进步。

阿尔特曼表示，现在确定OpenAI的研究重点还为时尚早。它将开发工具和算法，但具体的重点研究领域尚未确定。不过，他表示，如果该机构能在一年内发表“几篇原创性论文，推动当前工艺水平的进步”，那也算是一种成功。

不过，很显然，支持该项目的技术专家和其他人工智能研究者，都有更加宏大的目标。（财富中文网）

译者：刘进龙/汪皓

审校：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.