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ZGateway: Learnings from Putting a Proxy in Front of ZippyDB

Meta EngineeringLabsZGateway: 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 ri

An Organizational Second Brain: Building an AI That Learns From Experts

Meta EngineeringLabsAn 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 t

MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet

Meta EngineeringLabsMetaRoCE: 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 transpor

MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines

Meta EngineeringLabsMTIA 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 com

How We’re Building Scam Alert on WhatsApp With End-to-End Encryption and Verifiability Guarantees

Meta EngineeringLabsHow 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, s

From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking

Meta EngineeringLabsFrom 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 sequ

GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model

Meta EngineeringLabsGEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model 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 i

Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization

Meta EngineeringLabsExploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization 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 embeddi

Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler

Meta EngineeringLabsModernizing the Meta Ads Service With an Open-Source Kernel Scheduler 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

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予定 · Conferences and launch events, this week's stories from each corner of the industry, and what its press is covering — in English

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About

Accept All is a magazine, a radar and a diary about artificial intelligence and the craft of code — read from Tokyo, for people who build.

The name is the button. Code is written by agents now and reviewed by a human thumb that hovers over Accept all a hundred times a day; the whole question of this decade is what, exactly, you just accepted. So we read the diff. A magazine, because every week one model, one tool or one idea is worth reading about slowly. A radar, because we count what the labs, the Valley, GitHub and the chip makers are talking about — releases, agents, open weights, compute, funding, rules — and show it as it moves. A diary, because a seal is set each day in that day's colour, and the days add up.

We read the research labs' own posts, the American and European tech press, the Japanese and Chinese developer sites and the newsletters people actually forward, and bring it together in English and Japanese. Everything here links back to the people who wrote it; the images belong to their authors.

Accept All will keep changing. New sources, new signals, new ways of looking — a little better each week, never finished. If something here made you open a terminal, that is enough.

Thank you for reading. ありがとうございます。