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Meta Engineering AI news
The latest from Meta Engineering, listed as it is published. Headlines link to the original on engineering.fb.com.
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Intelligent Delivery: Making Every Unit of Compute Serve Better Ads
Ads ranking models are growing toward LLM scale faster than the hardware to run them can keep up. An extra unit of compute has more impact on some ad requests, models, and chips than on others. The challenge is deciding where to allocate…
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Your Algorithm: Giving People More Ways to Personalize Facebook Recommendations
Your algorithm is a suite of AI-powered tools that makes Facebook recommendations more transparent and steerable, with a single editable view of the interests that shape Feed and Reels. We’re sharing how Your algorithm turns people’s…
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F3 Lightning: How Meta Accelerates Ads ML Features to Production at Scale
Facebook Feature Framework (F3) is Meta’s framework for authoring, compiling, and serving the machine learning features underlying ads ranking models, where a single request can require more than 20,000 features. We first presented F3 at…
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Catching Bugs Before They Land: JiTTesting’s Human-on-the-Loop Approach at Full Scale
Over the last year we’ve been sharing our work leveraging large language models to catch bugs on the fly — a novel approach we call Catching Just-in-Time Tests (JiTTests). Now, we’re sharing the results and positive impact we’ve seen with…
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Python Typing Survey 2026: AI Tools and the Shifting Checker Landscape
The 2026 Python Typing Survey received 1,794 responses. Type hint use changed little across three years, but checker selection changed sharply. Among respondents who reported which checkers they use, half selected more than one, and…