Meta
We track 18 posts about Meta from 8 engineering blogs. Most active: Facebook, Discord, Facebook. Latest post: Oct 15, 2026.
Companies writing about Meta
Recent posts
How Meta Built Forum With AI-Native Engineering (opens on the source site)
Facebook ·
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.
Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI (opens on the source site)
Facebook ·
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.
Shipping Media Over QUIC at Meta Scale for Instagram Live Ingest (opens on the source site)
Facebook ·
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.
What Is Meta Muse? A Plain-English Guide to Meta's New AI (opens on the source site)
Meta recently released their new personal AI agent named Meta Muse. However, behind this name isn’t just “one thing”. Meta also uses the Muse name for an upcoming pocket gadget and for the AI models that programmers use to build apps. By the end of this tutorial, you’ll understand which Muse is which and whether it’s worth trying. No coding experience required. To see which part of Muse fits you, find your situation in the table below: Your situation Recommendation Want an assistant that answers questions and handles errands like shopping or booking travel The Muse app Want a pocket-sized…
NTS: Authenticated Time at Meta (opens on the source site)
Facebook ·
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.
A new, bespoke static site generator to replace Jekyll (opens on the source site)
My blog began as a blosxom (Perl) site running on a VPS. In 2011 I moved to the new GitHub Pages, with the site generated statically by Jekyll (Ruby) on a GitHub server. It was a no-brainer: easier, faster, and cheaper, better in every way. After 15 years of Jekyll, this week I replaced it with a new, custom-built static site generator, dubbed ssg, in “C with templates” C++20. The ~8KLoC source closely follows my personal coding style including templated arenas and slices, zero dependencies, and a libc-free core. It’s wicked fast, and a complete, cold generation of my blog takes 150ms on my…
Bringing Private Processing to Meta AI Glasses (opens on the source site)
Facebook ·
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.
MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines (opens on the source site)
Facebook ·
MTIA 300 is the first of Meta’s family of in-house training and inference accelerators optimized for training ranking and recommendation models. We’re sharing how MTIA 300’s built-in NIC chiplets allow it to meet the communication needs associated with training recommendation models with superior performance over general-purpose GPUs. By co-designing MTIA’s communication library, HCCL, alongside the [...] Read More... The post MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines appeared first on Engineering at Meta.
Muse Code: Meta's Terminal Coding Agent — Setup, Pricing Tiers, and First Look (opens on the source site)
Meta launched Muse Code on August 5, 2026 — terminal-native coding agent powered by Muse Spark 1.2 with 1M-token context, subagent orchestration, worktrees, and event-logged crash recovery. Developers debating Standard vs Contributor pricing tiers. Most coverage missing a clear setup walkthrough explaining .museignore and MUSE_CODE.md workflows. Continue reading Muse Code: Meta's Terminal Coding Agent — Setup, Pricing Tiers, and First Look on SitePoint.
From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking (opens on the source site)
Facebook ·
Every 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 modeling the order and timing of user actions (rather than relying on static, manually engineered sparse features) [...] Read More... The post From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking appeared first on Engineering at Meta.
GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model (opens on the source site)
Facebook ·
Meta’s Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs. This post goes into the details on how we achieved: doubling end-to-end (E2E) training efficiency to 20–25% Model FLOPs Utilization (MFU) while scaling training FLOPs 4x in [...] Read More... The post GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model appeared first on Engineering at Meta.
Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization (opens on the source site)
Facebook ·
Hierarchical Interest Representation is a research area for Meta Ads. We’re exploring an upstream representation layer over the universe of Ads entities – users, advertisers, products, services – learning unified embeddings that connect users’ inferred interests with the breadth of what advertisers offer in their deep funnel ads. The innovations in Hierarchical Interest Representation are [...] Read More... The post Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization appeared first on Engineering at Meta.
Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler (opens on the source site)
Facebook ·
TL; DR At Meta’s scale, a few milliseconds of latency degradation can have a significant negative impact on ads performance. When a Linux kernel upgrade risked regressing latency across Meta’s ad serving fleet, we turned to sched_ext — the upstream, BPF-based extensible scheduling framework — to build a scheduling policy customized to the Ads delivery [...] Read More... The post Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler appeared first on Engineering at Meta.
Meta’s AI Storage Blueprint at Scale (opens on the source site)
Facebook ·
Over the past several years, model capabilities and training dataset sizes have experienced exponential growth. During the past year or so, the time between new-frontier-model releases has gone down from months to weeks. Reliable and fast access to storage is important to both the speed and computational cost of this AI innovation. If AI is [...] Read More... The post Meta’s AI Storage Blueprint at Scale appeared first on Engineering at Meta.
10 Years of Meta’s Commitment to Python (opens on the source site)
Facebook ·
This year marks Meta’s 10th consecutive year as a sponsor of the Python Software Foundation (PSF), the charitable organization dedicated to advancing, supporting, and protecting the open-source Python programming language and the community that sustains it. Python is one of the world’s most influential programming languages, and we use it across our engineering stack, from [...] Read More... The post 10 Years of Meta’s Commitment to Python appeared first on Engineering at Meta.
Discord is Now on Meta Quest: Reach Out to Your Servers While in VR (opens on the source site)
Discord ·
Starting today, Discord is now available to download directly from Meta’s Horizon App Store. No more sideloading. No more using the web app. Grab it using the link in this blog, or at discord.com/download.
The OEIS meta sequence and subway stations (opens on the source site)
A051070 is a sequence about OEIS sequences. a(n) is the n-th term in sequence A_n (or -1 if A_n doesn’t have enough terms). So the first term in A051070 is 1 because A000001 is the number of groups of order n, and that sequence has 1 as its entry in index 1. A000002 is the Kolakoski sequence (what? For another time) and has value 2 in entry 2. The sequence continues: 1, 2, 1, 0, 2, 3, 0, 7, 8, 4, 63, 1, 316, …
Category definition for Meta (opens on the source site)
system: Discussion about this forum system: and how we can improve it. Some Categories on this Blog include a Category definition or an About topic, while some others do not. My first suggestion is to give each category either an About topic or a Category definition. Here are some of the topics that do not currently have one: linux blogging My second suggestion is for some of the Category definitions and the About topics that currently do not have a definition (it is the default format*) to be replaced with what the topic is actually for. Here is a list of some of the topics that have…
Related topics
This page is generated automatically from the engineering blogs we follow. Every post links to its source, where it was published. See all sources.