Built with the aid of Nvidia, the social network’s state-of-the-art server, codenamed Big Sur, can run the latest AI algorithms, and comes wielding a huge number of GPUs — built with the aid of Nvidia. At Facebook, the “deep learning” technology helps identify faces in user photos, curates the news feed, and even powers parts of the company’s upcoming “M” personal assistant, reports Wired.
But why are the likes of Google, Microsoft, and now Facebook so keen for the tech industry to get their hands on their hardware? It’s mainly due to the fact that all three companies currently don’t have the manpower to grow the technology at the pace they would like. It also doesn’t help that the entire field of deep learning researchers is still fairly small.
Facebook is hoping that by submitting its AI hardware to the Open Compute Project — a group through which it shares the designs of its computer infrastructure with other tech giants including Microsoft and Apple — it can attract more industry talent into its fold.
Yann LeCun, the man in charge of Facebook’s AI research group, believes that opening up Big Sur can help unlock design ideas for the newly created server, reports MIT Technology Review. “Companies like us actually thrive on fast progress; the faster the progress can be made, the better it is for us,” says LeCun.
In the increasingly competitive field of AI research, the recruitment process is the new battlefront for companies such as Facebook and Google. Although Google beat it to the punch by sharing its AI hardware last month, Facebook’s inception of the Open Commute Project established it as the frontrunner in open-sourcing technology. Facebook claims that this approach helps drive down costs and accelerate the growth of technology.
