Meta
Hyperscaler
Social media giant, open-source AI leader (Llama models).
Recent activity
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Exploring 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 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 Op
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Modernizing 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 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 Met
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Meta’s AI Storage Blueprint at Scale
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 .
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10 Years of Meta’s Commitment to Python
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 .
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Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study
  Privacy controls — systems that enforce retention, access, allowed-purpose, downstream-sharing, or anonymization policies — require a reliable understanding of data to function. Before such a control can operate effectively, it must know exactly what it is looking at. This can be complex, as demonstrated by a field simply named “age“: In one context, it [...] Read More... The post Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study appeared fi
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How Meta Engineered Ultra-Narrow Batteries for AI Glasses
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. But it all has to fit into the glasses’ temple arms. So how do you place a battery with enough power to run a pair of smart glasses [...] Read More... The post How Meta Engineered Ultra-Narrow Batteries for AI Glasses appeared first on Engineering at Meta .
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Adopting AV1 for Real-Time Communication (RTC) at Scale
Adopting AV1 for real-time communication at Meta has been a multi-year effort spanning codec selection, device eligibility, rate control, and error resilience. We’re sharing the technical and operational challenges while deploying AV1 and expanding coverage, and how we addressed them for real-time communication. We’re presenting several technologies for improving AV1 call quality, including rate control [...] Read More... The post Adopting AV1 for Real-Time Communication (RTC) at Scale appeared
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Lights Out, Systems On: Validating Instant Power Loss Readiness
We’re introducing Instantaneous PowerLoss Storm, a new testing paradigm within Meta’s infrastructure for handling and mitigating instant or zero-notice power loss in our data centers. We’re sharing: how we built readiness to tolerate instant failures into our existing systems with defense-in-depth strategies; tradeoffs made in implementing it, and how we validated our readiness. Disaster preparedness [...] Read More... The post Lights Out, Systems On: Validating Instant Power Loss Readiness appe
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SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems
We’re introducing SilverTorch, a reimagining of recommendation systems that unifies all retrieval components for user generated content under a unified architecture. SilverTorch shows up to 23.7x higher throughput compared to the state-of-the-art approaches. It’s also showing 20.9x more compute cost efficiency compared to a CPU-based solution while also improving accuracy. Our research paper, “SilverTorch: A [...] Read More... The post SilverTorch: Index as Model — A New Retrieval Paradigm for R
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