Meta has begun deploying Media over QUIC (MoQ), an emerging open protocol for real-time video streaming at scale. MoQ will ...
We’ve previously written about building a more accurate time service at Meta scale – migrating from ntpd to chrony, going from 10 milliseconds to 100 microseconds, and opening time.meta.com to ...
Zoomer: Powering AI Performance at Meta's Scale Through Intelligent Debugging and Optimization ...
Meta believes in building community through open source technology. Explore our latest projects in Artificial Intelligence, Data Infrastructure, Development Tools, Front End, Languages, Platforms, ...
Meta believes in building community through open source technology. Explore our latest projects in Artificial Intelligence, Data Infrastructure, Development Tools, Front End, Languages, Platforms, ...
We’re introducing ZGateway, the proxy we are using to unify traffic through ZippyDB, Meta’s most widely-used key value store. As a bonus, it also enables admission control, load balancing, ...
In the examples above, the first two rows show a precise match of religions in the source and the sink values, thus belonging to the high confidence match-set. The third row depicts a transformed data ...
We’re sharing details about Glean, Meta’s open source system for collecting, deriving, and working with facts about source code. In this blog post we’ll talk about why a system like Glean is important ...
We are inspired by the possibilities of AI to help people be more creative, productive, and stay closely connected on WhatsApp, so we set out to build a new technology that allows our users around the ...
We developed a new static analysis tool called Nullsafe that is used at Meta to detect NullPointerException (NPE) errors in Java code. Interoperability with legacy code and gradual deployment model ...
In this post, we explore how Instagram has successfully scaled its algorithm to include over 1000 ML models without sacrificing recommendation quality or reliability. We delve into the intricacies of ...
Purpose limitation, a core data protection principle, is about ensuring data is only processed for explicitly stated purposes. A crucial aspect of purpose limitation is managing data as it flows ...