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 ...
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, ...
WhatsApp is committed to helping people stay safe while protecting the privacy of their messages. As scam tactics evolve — from impersonation to social engineering to AI-generated lures — we’re always ...
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We’re sharing how we’ve enabled Dolby Vision and ambient viewing environment (amve) on the Instagram iOS app to enhance the video viewing experience. HDR videos created on iPhones contain unique Dolby ...
Disaggregated Schedule Fabric (DSF) is Meta’s next-generation network fabric technology for AI training networks that addresses the challenges of existing Clos-based networks. We’re sharing the ...
Hardware faults can have a significant impact on AI training and inference. Silent data corruptions (SDCs), undetected data errors caused by hardware, can be particularly harmful for AI systems that ...
Have you ever worked is legacy code? Are you curious what it takes to modernize systems at a massive scale? Pascal Hartig is joined on the latest Meta Tech Podcast by Elaine and Buping, two software ...
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 ...
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’re sharing how Meta built support for data logs, which provide people with additional data about how they use our products. Here we explore initial system designs we considered, an overview of the ...
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 ...
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