{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "AI News: Meta Engineering (ML)",
  "home_page_url": "https://ai-news.ypetit.net/sources/meta-engineering-ml/",
  "feed_url": "https://ai-news.ypetit.net/feed/source/meta-engineering-ml.json",
  "description": "Latest publications from Meta Engineering (ML), aggregated by AI News from the official source.",
  "language": "en",
  "items": [
    {
      "id": "https://engineering.fb.com/?p=24926",
      "url": "https://engineering.fb.com/2026/11/03/ml-applications/f3-lightning-how-meta-accelerates-ads-ml-features-to-production/",
      "title": "Meta Engineering (ML): F3 Lightning: How Meta Accelerates Ads ML Features to Production at Scale",
      "summary": "Facebook Feature Framework (F3) is Meta’s framework for authoring, compiling, and serving the machine learning features underlying ads ranking models, where a single request can require more than 20,000 features. We first presented F3 at AI @ Scale 2020. F3 reduced execution c…",
      "date_published": "2026-11-03T17:00:35.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24907",
      "url": "https://engineering.fb.com/2026/10/29/security/catching-bugs-before-they-land-jittestings-human-on-the-loop-approach-at-full-scale/",
      "title": "Meta Engineering (ML): Catching Bugs Before They Land: JiTTesting’s Human-on-the-Loop Approach at Full Scale",
      "summary": "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 produc…",
      "date_published": "2026-10-29T16:00:12.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24890",
      "url": "https://engineering.fb.com/2026/10/28/ml-applications/meta-andromeda-next-gen-ads-retrieval-gpu-co-design/",
      "title": "Meta Engineering (ML): Meta Andromeda: Powering the Next Generation of Ads Retrieval Through Model-System Co-Design",
      "summary": "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 ranki…",
      "date_published": "2026-10-28T16:00:01.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24851",
      "url": "https://engineering.fb.com/2026/10/27/security/privacylib/",
      "title": "Meta Engineering (ML): PrivacyLib: Privacy Controls at the Data Access Boundary",
      "summary": "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…",
      "date_published": "2026-10-27T16:00:12.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24816",
      "url": "https://engineering.fb.com/2026/10/26/open-source/ocp-summit-2026-meta-networking-talks/",
      "title": "Meta Engineering (ML): Meta Networking at the 2026 OCP Global Summit: Open Innovation for Scale-Up, Scale-Out, and Scale-Across AI Networks",
      "summary": "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-co…",
      "date_published": "2026-10-26T16:00:07.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24783",
      "url": "https://engineering.fb.com/2026/10/19/ml-applications/genrecs-tokenization-transforming-ads-recommendation-at-meta-with-stable-model-vocabulary/",
      "title": "Meta Engineering (ML): GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabulary",
      "summary": "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 intelligen…",
      "date_published": "2026-10-19T16:00:47.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24724",
      "url": "https://engineering.fb.com/2026/10/19/ml-applications/thin-orchestrator-ai-agent-architecture/",
      "title": "Meta Engineering (ML): The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do",
      "summary": "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 chec…",
      "date_published": "2026-10-19T15:30:37.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24763",
      "url": "https://engineering.fb.com/2026/10/19/data-center-engineering/inside-prometheus-meta-gigawatt-scale-supercluster/",
      "title": "Meta Engineering (ML): Inside Prometheus: Meta’s Journey to a Gigawatt-Scale Supercluster",
      "summary": "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 ~…",
      "date_published": "2026-10-19T13:00:10.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    },
    {
      "id": "https://engineering.fb.com/?p=24709",
      "url": "https://engineering.fb.com/2026/10/15/ml-applications/how-meta-built-forum-ai-native-engineering/",
      "title": "Meta Engineering (ML): How Meta Built Forum With AI-Native Engineering",
      "summary": "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 bui…",
      "date_published": "2026-10-15T19:00:03.000Z",
      "tags": [
        "blog",
        "Meta Engineering (ML)"
      ],
      "authors": [
        {
          "name": "Meta Engineering (ML)"
        }
      ]
    }
  ]
}