Applied machine learning at Facebook: a datacenter infrastructure perspective
Applied machine learning at Facebook: a datacenter infrastructure perspective Hazelwood et al., _HPCA’18 _
This is a wonderful glimpse into what it’s like when machine learning comes to pervade nearly every part of a business, with implications top-to-bottom through the whole stack. It’s amazing to step back and think just how fundamentally software systems have changed over the last decade in this regard.
Just how pervasive is machine learning at Facebook?
- “At Facebook, machine learning provides key capabilities in driving nearly all aspects of user experience… Machine learning is applied pervasively across nearly all services.”
- “Facebook funnels a large fraction of all stored data through machine learning pipelines, and this fraction is increasing over time to improve model quality.”
- “Looking forward, Facebook expects rapid growth in machine learning across existing and new services…. Over time, most services indicate a trend toward leveraging increased amounts of user data.. the training data sets are trending towards continued and sometimes dramatic growth.”
The modern user-experience is increasingly powered by machine learning models, and the quality of those models depends directly on the volume and quality of the data powering them: “For many machine learning models Continue reading



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