Computing

Facebook Joins Stampede of Tech Giants Giving Away Artificial Intelligence Technology

Leading computing companies are helping both themselves and others by open-sourcing AI tools.

Facebook is releasing for free the designs of a powerful new computer server it crafted to put more power behind artificial-intelligence software. Serkan Piantino, an engineering director in Facebook’s AI Research group, says the new servers are twice as fast as those Facebook used before. “We will discover more things in machine learning and AI as a result,” he says.

Facebook designed this server to put new power behind the simulated neurons that enable software to do smart things like recognize speech or the content of photos.

The social network’s giveaway is the latest in a recent flurry of announcements by tech giants that are open-sourcing artificial-intelligence technology, which is becoming vital to consumer and business-computing services. Opening up the technology is seen as a way to accelerate progress in the broader field, while also helping tech companies to boost their reputations and make key hires.

In November, Google opened up software called TensorFlow, used to power the company’s speech recognition and image search (see “Here’s What Developers Are Doing with Google’s AI Brain”). Just three days later Microsoft released software that distributes machine-learning software across multiple machines to make it more powerful. Not long after, IBM announced the fruition of an earlier promise to open-source SystemML, originally developed to use machine learning to find useful patterns in corporate databanks.

Facebook’s new server design, dubbed Big Sur, was created to power deep-learning software, which processes data using roughly simulated neurons (see “Teaching Computers to Understand Us”). The invention of ways to put more power behind deep learning, using graphics processors, or GPUs, was crucial to recent leaps in the ability of computers to understand speech, images, and language. Facebook worked closely with Nvidia, a leading manufacturer of GPUs, on its new server designs, which have been stripped down to cram in more of the chips. The hardware can be used to run Google’s TensorFlow software.

Yann LeCun, director of Facebook’s AI Research group, says that one reason to open up the Big Sur designs is that the social network is well placed to slurp up any new ideas it can unlock. “Companies like us actually thrive on fast progress; the faster the progress can be made, the better it is for us,” says LeCun. Facebook open-sourced deep-learning software of its own in February of this year.

LeCun says that opening up Facebook’s technology also helps attract leading talent. A company can benefit by being seen as benevolent, and also by encouraging people to become familiar with a particular way of working and thinking. As Google, Facebook, and other companies have increased their investments in artificial intelligence, competition to hire experts in the technology has intensified (see “Is Google Cornering the Market in Deep Learning?”).

Derek Schoettle, general manager of IBM Cloud Data Services unit, which offers tools to help companies analyze data, says that machine-learning technology has to be opened up for it to become widespread. Open-source projects have played a major role in establishing large-scale databases and data analysis as the bedrock of modern computing companies large and small, he says. Real value tends to lie in what companies can do with the tools, not the tools themselves.

“What’s going to be interesting and valuable is the data that’s moving in that system and the ways people can find value in that data,” he says. Late last month, IBM transferred its SystemML machine-learning software, designed around techniques other than deep learning, to the Apache Software Foundation, which supports several major open-source projects.

Facebook’s Big Sur server design will be submitted to the Open Compute Project, a group started by the social network through which companies including Apple and Microsoft share designs of computing infrastructure to drive down costs (see “Inside Facebook’s Not-So-Secret New Data Center”).

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