Meta
Hyperscaler
Social media giant, open-source AI leader (Llama models).
Recent activity
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Over the last year we’ve been sharing our work leveraging large language models to catch bugs on the fly — a novel approach we call Catching Just-in-Time Tests (JiTTests). Now, we’re sharing the results and positive impact we’ve seen with Catching JiTTests deployed into production. Our paper, “Just-in-Time Catching Test Generation at Meta,” fully details [...] Read More... The post Catching Bugs Before They Land: JiTTesting’s Human-on-the-Loop Approach at Full Scale appeared first on Engineering
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This post describes the next generation of Meta Andromeda, Meta’s personalized ads retrieval engine, and how co-designing the model, system, and GPU hardware unlocks a new efficiency frontier for ads retrieval. In production, the system scores every eligible ad with near ranking-level model performance at retrieval scale and surfaces the top candidates at over one [...] Read More... The post Meta Andromeda: Powering the Next Generation of Ads Retrieval Through Model-System Co-Design appeared fir
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This latest deep dive into Meta’s Privacy Aware Infrastructure (PAI) takes a look at PrivacyLib. A privacy requirement must hold as data moves through Meta’s diverse data and processing systems. Historically, supporting a new requirement meant implementing the same enforcement logic separately in each system. PrivacyLib replaces this with a common library that runs inside [...] Read More... The post PrivacyLib: Privacy Controls at the Data Access Boundary appeared first on Engineering at Meta .
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The 2026 Python Typing Survey received 1,794 responses. Type hint use changed little across three years, but checker selection changed sharply. Among respondents who reported which checkers they use, half selected more than one, and missing library type information was the most common difficulty. For the third consecutive year, we asked Python developers how they [...] Read More... The post Python Typing Survey 2026: AI Tools and the Shifting Checker Landscape appeared first on Engineering at Me
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At the 2026 Open Compute Project (OCP) Global Summit, Meta shared the networking innovations that are directly supporting our latest AI models, including Muse Wonder and Muse Spark, and our gigawatt-scale Prometheus cluster. Highlights IcePack & IceCube: Meta’s first liquid-cooled network rack with 102.4T switch blades (128×800G, Broadcom Tomahawk 6C and NVIDIA Spectrum-6 variants), running [...] Read More... The post Meta Networking at the 2026 OCP Global Summit: Open Innovation for Scale-Up, S
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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
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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 Engine
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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 .
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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 .
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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 .
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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 .
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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
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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
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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 .
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At 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 describes how we designed and now operate the system at Meta’s scale and how it drives [...] Read More... The post Turning Opportunistic AI Inference Capacity Into Better Ads Recommendations appeared first on Engineering at
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Meta’s public time service now speaks NTS (Network Time Security, RFC 8915) at nts.meta.com. Packets are authenticated, so a device can verify the time came from us and was not modified on the way. Our NTS servers hold no per-client state. Cookie keys are derived, not stored and not replicated. We’ve open sourced everything, including [...] Read More... The post NTS: Authenticated Time at Meta appeared first on Engineering at Meta .
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We believe glasses are the best form factor for having AI help throughout your day. They can understand your personal context better than other kinds of devices and keep you present without picking up a mobile phone. Most of the time, glasses are helping you see well, protecting your eyes and complementing your look, and [...] Read More... The post Bringing Private Processing to Meta AI Glasses appeared first on Engineering at Meta .
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We’re open-sourcing Rebalancer, the assignment-problem solver that has been used to solve resource allocation problems throughout Meta for over nine years. Rebalancer separates several related concerns: how to specify an assignment problem, how to store it efficiently in memory, how to solve it, and how to debug it. This separation of concerns is crucial to [...] Read More... The post Open-Sourcing Rebalancer: A Generic, High-Performance Library for Solving Assignment Problems appeared first on
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Petal, the next step in Meta’s subsea innovation, will be the first subsea cable to deliver petabit capacity at transoceanic distances, connecting France and the United States over approximately 7,000 km (4,300 mi). Expected to enter service in 2029, it will be the first subsea cable system to deploy multi-core fiber technology at scale, doubling [...] Read More... The post Inside Petal: Building the World’s First Petabit-Class Transoceanic Subsea Cable appeared first on Engineering at Meta .
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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, cross-region resilience, and richer operations. ZippyDB is the most widely used key value store at Meta, backing product metadata, counters, and configuration, and can serve billions [...] Read More... The post ZGateway: Learnings from Putting a Proxy in Front of ZippyDB appeared first on Engineering at Meta .
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