NTS: Authenticated Time at Meta
Engineering at Metaby Oleg Obleukhov·3d ago
- 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...
Bringing Private Processing to Meta AI Glasses
Engineering at Metaby Pritam Shah; Oskar Linde·16d ago
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...
Open-Sourcing Rebalancer: A Generic, High-Performance Library for Solving Assignment Problems
Engineering at Metaby Richard Barnes; Neeraj Kumar; Pol Mauri Ruiz·18d ago
- We’re open-sourcing Rebalancer, the assignment-problem solver that has been used to solve resource allocation problems throughout Meta for over nine years.
Inside Petal: Building the World’s First Petabit-Class Transoceanic Subsea Cable
Engineering at Metaby Elizabeth Rivera Hartling; Pascal Pecci; Matthew Mitchell·18d ago
- 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...
ZGateway: Learnings from Putting a Proxy in Front of ZippyDB
Engineering at Metaby Rittik Banik; Yunhao Cao·3 Sept 2026
- We’re introducing ZGateway, the proxy we are using to unify traffic through ZippyDB, Meta’s most widely-used key value store.
An Organizational Second Brain: Building an AI That Learns From Experts
Engineering at Metaby Shaurya Sengar; Jason Nawrocki; Jay Shah; Prashant Kommireddi·2 Sept 2026
- We’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...
MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet
Engineering at Metaby Arvind Srinivasan; Neil Spring; Omar Baldonado; Rajiv Krishnamurthy·24 Aug 2026
- Training and serving frontier AI models depends on fast, reliable networks that move data between GPUs without wasting compute cycles.
MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines
Engineering at Metaby Rajiv Krishnamurthy; Wes Bland·24 Aug 2026
- MTIA 300 is the first of Meta’s family of in-house training and inference accelerators optimized for training ranking and recommendation models.
How We’re Building Scam Alert on WhatsApp With End-to-End Encryption and Verifiability Guarantees
Engineering at Metaby Chris Wiltz·12 Aug 2026
WhatsApp is committed to helping people stay safe while protecting the privacy of their messages.
From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking
Engineering at Metaby Steven De Gryze; Parshva Doshi; Sean O'Byrne; Arnold Overwijk; Dinesh Ramasamy; Lee Xiong·5 Aug 2026
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.
Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization
Engineering at Metaby Yuhui Ouyang; Di Wang; Sreedal Menon; Jie Tian·15 Jul 2026
- 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 –...
Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler
Engineering at Metaby Blaise Sanouillet; Sunyi Shao; Jeff Song; Gosh Arzumanyan; Shawn Wu; Tejun Heo; Praveen Sampath; GP Musumeci·13 Jul 2026
TL; DR - At Meta’s scale, a few milliseconds of latency degradation can have a significant negative impact on ads performance.
Meta’s AI Storage Blueprint at Scale
Engineering at Metaby Sidharth Bajaj; Venkatraghavan Srinivasan·1 Jul 2026
Over the past several years, model capabilities and training dataset sizes have experienced exponential growth.
Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study
Engineering at Metaby Rituraj Kirti; Vasileios Lakafosis·25 Jun 2026
Privacy controls — systems that enforce retention, access, allowed-purpose, downstream-sharing, or anonymization policies — require a reliable understanding of data to function.
How Meta Engineered Ultra-Narrow Batteries for AI Glasses
Engineering at Metaby Pascal Hartig·23 Jun 2026
Smart glasses like the Ray-Ban Meta and Oakley Meta Vanguards need to pack enough energy to power features like cameras, speakers, AI workloads, and even a display.
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