UPDATED 00:57 EST / DECEMBER 11 2015

zdnet-facebook-ai-hardware-open-source NEWS

Facebook open-sources its Big Sur machine learning server specs

Facebook has announced it’s contributing its special server designs for machine learning software to the open-source community, which means others will be able to build similar systems.

The reference design, dubbed “Big Sur”, is being contributed to the Facebook-led Open Compute Project (OCP). It uses eight high-performance CPUs packed with up to 300 watts each in an air-cooled rack, and sits nicely with existing data center designs in the OCP.

Facebook uses Big Sur to power its machine learning programs, which are special algorithms that “learn” and improve their ability to solve certain tasks over time, Computerworld reports. One of the most common applications for machine learning is image recognition, wherein a computer program studies images or videos and learns to identify which objects are in that frame. Alternative uses including fraud detection and email spam filtering, among other use cases.

“We want to make it a lot easier for AI researchers to share techniques and technologies,” Facebook’s AI Research Team wrote in a blog post. “As with all hardware systems that are released into the open, it’s our hope that others will be able to work with us to improve it.”

The idea is that by open-sourcing its servers, others will be able to copy them and build their own machine learning systems. Through collaboration, Facebook hopes we’ll get “one step closer to building complex AI systems that bring this kind of innovation to our users and, ultimately, help us build a more open and connected world.”

The move to open up Big Sur follows Facebook’s decision to open-source its Torch machine learning algorithm. The team said that Big Sur allows Torch to run twice as fast as other servers can, because it scales up to eight CPUs, allowing for the development of larger and faster neural networks.

Facebook’s design is powered by Nvidia Corp.’s GPUs, although the team says it’s open to using a “wide range of PCI-e cards.”

“Deep learning has started a new era in computing,” said Ian Buck, veep of accelerated computing at Nvidia. “Enabled by big data and powerful GPUs, deep learning algorithms can solve problems never possible before. Huge industries from web services and retail to healthcare and cars will be revolutionized.”

Facebook hasn’t said exactly when it’s planning to release Big Sur to the OCP, only that it intends to do so soon. What with the next OCP Summit taking place in March 2016, we’d wager it’s likely Facebook will tell us more either before, or on that date.

Since you’re here …

Show your support for our mission with our one-click subscription to our YouTube channel (below). The more subscribers we have, the more YouTube will suggest relevant enterprise and emerging technology content to you. Thanks!

Support our mission:    >>>>>>  SUBSCRIBE NOW >>>>>>  to our YouTube channel.

… We’d also like to tell you about our mission and how you can help us fulfill it. SiliconANGLE Media Inc.’s business model is based on the intrinsic value of the content, not advertising. Unlike many online publications, we don’t have a paywall or run banner advertising, because we want to keep our journalism open, without influence or the need to chase traffic.The journalism, reporting and commentary on SiliconANGLE — along with live, unscripted video from our Silicon Valley studio and globe-trotting video teams at theCUBE — take a lot of hard work, time and money. Keeping the quality high requires the support of sponsors who are aligned with our vision of ad-free journalism content.

If you like the reporting, video interviews and other ad-free content here, please take a moment to check out a sample of the video content supported by our sponsors, tweet your support, and keep coming back to SiliconANGLE.