Facebook to Publish Designs for `Big Sur' AI Computer Hardware

  • Company to open-source artificial intelligence server plans
  • Decision follows Google releasing TensorFlow software.

Facebook Inc.’s use of artificial intelligence, which ranges from tools for image recognition to the filtering of the news feeds for its social network, demands special computing infrastructure. The company recently began building custom servers for its artificial intelligence workload and Thursday announced it would release the designs for that powerful hardware to the world -- for free.

The company said the plan to open-source the blueprints of the servers -- called “Big Sur” -- would help other companies and researchers benefit from the incessant tweaking of Facebook’s developers. This follows Alphabet Inc.-subsidiary Google’s release last month of a software tool for building AI systems named TensorFlow. Microsoft Corp., International Business Machines Corp., and Samsung Electronics Co. also have released their own software tools.

The servers are built around graphical processing units from Nvidia Corp. GPUs are widely used in artificial intelligence because the chips have far more individual processing cores on them than traditional processors produced by Intel Corp., making them adept at the dumb-but-numerous calculations required by AI software.

The hardware designs will be made available as part of the Open Compute Project, an initiative Facebook Chief Executive Officer Mark Zuckerberg started in 2011 to share the secrets of the Menlo Park, California-based company’s data centers. Other companies, ranging from IT suppliers like Hewlett Packard, to buyers like Goldman Sachs Group Inc., adopted the technology.

Goldman Sachs said in 2012 that using the OCP designs saved its computing costs by as much as 30 percent. Zuckerberg in January 2014 said the usage of these systems had saved Facebook about $1.2 billion.

Potential Advantages

For Facebook, releasing its designs has potent benefits: the openness can be a major incentive for top talent to join the company; firms that use the equipment may contribute their improvements back to the community, letting Facebook outsource some of its research and development costs; and if enough people buy the equipment, then economies of scale will ultimately lower the price Facebook pays for its computer hardware, Serkan Piantino, the engineering director of Facebook’s AI group, said in an briefing with reporters.

“Often the things we open-source become standards in the community and it makes it easier and cheaper for us to acquire the things later because we put them out there,” Piantino said.

Perhaps the greatest incentive for Facebook’s decision may be the way AI researchers like to work -- in the open and rapidly. Companies that are more secretive, such as Apple Inc., have faced difficulties hiring people into their own closed environments. Facebook’s researchers, by comparison, have published academic papers that reference breakthroughs made at Google, and vice versa.

“We really like opening up the things that we’re doing,” Piantino said.

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