全部/科技/实时热榜

Meta Engineering · 实时热榜

7小时前更新
HISTORY近 30 天历史柱高表示当天去重热搜数量
906907908910911912913914915916917918920102110229231024925926927928929930901903904905
09/06—10/05 有历史数据
  • 01
    Bringing Private Processing to Meta AI Glasses
    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 .
  • 02
    Open-Sourcing Rebalancer: A Generic, High-Performance Library for Solving Assignment Problems
    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
  • 03
    Inside Petal: Building the World’s First Petabit-Class Transoceanic Subsea Cable
    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 .
  • 04
    ZGateway: Learnings from Putting a Proxy in Front of ZippyDB
    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 .
  • 05
    An Organizational Second Brain: Building an AI That Learns From Experts
    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 build upon. This is not a typical domain-specific agent. Its novelty comes from integrating two layers: A structured, auditable knowledge architecture separates what [...] Read More... The post An Organizational Second Brain: Building an AI That Learns From Experts appeared first on Engineering at Meta .
  • 06
    MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet
    Training and serving frontier AI models depends on fast, reliable networks that move data between GPUs without wasting compute cycles. To meet this challenge at scale, Meta designed MetaRoCE – a clean-sheet RDMA transport protocol purpose-built for AI workloads on commodity Ethernet. We’re releasing the MetaRoCE specification, a reference software implementation and a compliance test [...] Read More... The post MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet appeared first on Engineer
  • 07
    MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines
    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 Communica
  • 08
    How We’re Building Scam Alert on WhatsApp With End-to-End Encryption and Verifiability Guarantees
    WhatsApp is committed to helping people stay safe while protecting the privacy of their messages. As scam tactics evolve — from impersonation to social engineering to AI-generated lures — we’re always evolving as well, so that our protections stay ahead of scammers while protecting people’s personal messages with end-to-end encryption. Today, we’re sharing an early [...] Read More... The post How We’re Building Scam Alert on WhatsApp With End-to-End Encryption and Verifiability Guarantees appear
  • 09
    From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking
    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 Ranki