AI News: Meta Engineering (ML) https://ai-news.ypetit.net/sources/meta-engineering-ml/ Latest publications from Meta Engineering (ML), aggregated by AI News from the official source. en Fri, 23 Oct 2026 19:08:30 GMT Meta Engineering (ML): GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabularyhttps://engineering.fb.com/2026/10/19/ml-applications/genrecs-tokenization-transforming-ads-recommendation-at-meta-with-stable-model-vocabulary/https://engineering.fb.com/?p=24783Mon, 19 Oct 2026 16:00:47 GMTblogGenerative 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 intelligen… Meta Engineering (ML): The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Dohttps://engineering.fb.com/2026/10/19/ml-applications/thin-orchestrator-ai-agent-architecture/https://engineering.fb.com/?p=24724Mon, 19 Oct 2026 15:30:37 GMTblogSometimes, 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 chec… Meta Engineering (ML): Inside Prometheus: Meta’s Journey to a Gigawatt-Scale Superclusterhttps://engineering.fb.com/2026/10/19/data-center-engineering/inside-prometheus-meta-gigawatt-scale-supercluster/https://engineering.fb.com/?p=24763Mon, 19 Oct 2026 13:00:10 GMTblogWith 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 ~… Meta Engineering (ML): How Meta Built Forum With AI-Native Engineeringhttps://engineering.fb.com/2026/10/15/ml-applications/how-meta-built-forum-ai-native-engineering/https://engineering.fb.com/?p=24709Thu, 15 Oct 2026 19:00:03 GMTblogMeta’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 bui… Meta Engineering (ML): Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AIhttps://engineering.fb.com/2026/10/13/ml-applications/generative-ads-model-gem-scaling-frontier-ads-ai/https://engineering.fb.com/?p=24641Tue, 13 Oct 2026 16:01:00 GMTblogLast 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… Meta Engineering (ML): OCP Summit 2026: Powering AI with Open Innovations in Scale-Up, Scale-Out, and Scale-Across Networkshttps://engineering.fb.com/2026/10/12/open-source/ocp-summit-2026-powering-ai-with-open-innovations-in-scale-up-scale-out-and-scale-across-networks/https://engineering.fb.com/?p=24657Mon, 12 Oct 2026 21:19:18 GMTblogAt 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… Meta Engineering (ML): Turning Opportunistic AI Inference Capacity Into Better Ads Recommendationshttps://engineering.fb.com/2026/10/12/ml-applications/turning-opportunistic-ai-inference-capacity-into-better-ads-recommendations/https://engineering.fb.com/?p=24593Mon, 12 Oct 2026 16:00:50 GMTblogAt Meta, we’ve built a system that enhances ads recommendations by leveraging idle inference capacity in our fleet. Two elasticity levers in the system allow ads recommendation work to expand across opportunistic capacity, without compromising baseline performance. This post d… Meta Engineering (ML): An Organizational Second Brain: Building an AI That Learns From Expertshttps://engineering.fb.com/2026/09/02/ml-applications/organizational-second-brain-ai-learns-from-experts/https://engineering.fb.com/?p=24419Wed, 02 Sep 2026 09:00:29 GMTblogWe’ve built an AI agent that acts as a secondary expert for a given domain, making deep specialist knowledge readily available and preserved for anyone in an organization to access, share, and build upon. This is not a typical domain-specific agent. Its novelty comes from inte… Meta Engineering (ML): From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Rankinghttps://engineering.fb.com/2026/08/05/ml-applications/from-user-sequences-to-scaling-laws-a-multi-stage-architecture-for-metas-ads-ranking/https://engineering.fb.com/?p=23996Wed, 05 Aug 2026 19:20:20 GMTblogEvery day, Meta’s recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. In our 2024 post on sequence learning for ads recommendations, we showed how mode…