Engineering at MetaCompany/Startup Blogs6 min read
GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabulary
Generative Recommenders (GenRecs) represent a paradigm shift from scoring every ad to reasoning about ad content and user preferences together in order to predict the best outcome for advertisers. Leveraging the world knowledge built into LLMs makes ad matching more intelligent and precise, compounding gains for advertisers. GenRecs Tokenization is the foundational data representation that [...] Read More... The post GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabulary appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs7 min read
The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do
Sometimes, giving an AI agent all of the knowledge it needs is the wrong approach. At Meta, we’ve seen notable improvements in efficiency and accuracy by keeping the orchestration layer of our data pipeline agents deliberately thin: It routes work and enforces reliability checks, while specialized agents do the domain reasoning. We’re sharing our own [...] Read More... The post The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs16 min read
Inside Prometheus: Meta’s Journey to a Gigawatt-Scale Supercluster
With the recent release of the Muse family of foundational models, we want to take you inside the infrastructure that has made it all possible. The first phase of Prometheus, our gigawatt-scale supercluster, is already complete and we’re working toward scaling it to comprise ~1 million GPUs. Prometheus also features technologies like closed-loop liquid cooling [...] Read More... The post Inside Prometheus: Meta’s Journey to a Gigawatt-Scale Supercluster appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs8 min read
How Meta Built Forum With AI-Native Engineering
Meta’s newest app, Forum, is for anyone who wants to go deeper into the conversations in their Facebook groups. To build Forum, Meta engineers adopted a whole new way of working by bringing an AI agent into the development cycle. We’re sharing insights into what it took to build Forum with agentic AI: how we [...] Read More... The post How Meta Built Forum With AI-Native Engineering appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs4 min read
2026 World Cup: Breaking Records, Spiky Charts and Reliability at Scale
Every four years, the World Cup becomes the largest planned stress test of our infrastructure. This year it also set an all-time record! There are a few moments throughout the year, like New Years Eve, that really let us see the collective impact of everything we’ve built — but none are bigger than the quadrennial [...] Read More... The post 2026 World Cup: Breaking Records, Spiky Charts and Reliability at Scale appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs2 min read
Sapienz Receives ISSTA 2026 Impact Paper Award
Ke Mao, Mark Harman, and Yue Jia have been recognized with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2026 Most Influential Paper Award for their 2016 research, “Sapienz: multi-objective automated testing for Android applications.” The recognition celebrates a decade of impact from work that began at University College London and went [...] Read More... The post Sapienz Receives ISSTA 2026 Impact Paper Award appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs15 min read
Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI
Last year, we introduced GEM, the industry’s largest recommendation system (RecSys) foundation model. GEM established Meta’s first LLM-inspired paradigm for ads recommendation, driving major performance gains. Building on this foundation, our next goal is to further scale both compute and intelligence transfer with next-generation hardware, and expand this capability across Meta’s entire ads ecosystem. This [...] Read More... The post Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs11 min read
OCP Summit 2026: Powering AI with Open Innovations in Scale-Up, Scale-Out, and Scale-Across Networks
At the 2026 Open Compute Project Global Summit, Meta is sharing the next generation of open networking infrastructure, including: Our first liquid-cooled network rack (IcePack), and 102.4T switch platform (IceCube). Flattened Planar Fabric (FPF), a multiplane backend scale-out fabric that fundamentally changes how GPUs connect to the network MetaRoCE, our open-source AI transport protocol. Launching [...] Read More... The post OCP Summit 2026: Powering AI with Open Innovations in Scale-Up, Scale-Out, and Scale-Across Networks appeared first on Engineering at Meta .
Engineering at MetaCompany/Startup Blogs8 min read
Shipping Media Over QUIC at Meta Scale for Instagram Live Ingest
Meta has begun deploying Media over QUIC (MoQ), an emerging open protocol for real-time video streaming at scale. MoQ will help simplify our protocol stack for live streaming video and enhance overall user experience for live video. We’re sharing how we shipped MoQ on Instagram Live ingest, and what the future looks like from here. [...] Read More... The post Shipping Media Over QUIC at Meta Scale for Instagram Live Ingest appeared first on Engineering at Meta .