<ul data-eligibleForWebStory="true"><li>Companies like Discord, Netflix, and Meta are reassessing their technological strategies.</li><li>Instagram's recommendation system operates over 1,000 machine learning models for different aspects of the user experience.</li><li>Meta engineers introduced a central model registry to document each model's role, criticality, and technical metadata.</li><li>The model registry improved operational triage and enabled policy enforcement and automation.</li><li>Instagram introduced model stability as a core health metric to address inaccuracy issues.</li><li>The launch pipeline at Instagram has been automated end-to-end, reducing launch time significantly.</li><li>Meta created virtual capacity pools for teams at Instagram to manage resource allocation better.</li><li>The changes at Instagram highlight the complexities of operating with over 1,000 machine learning models.</li><li>The process ensures that important models don't become unstable, improving user experience.</li><li>The article gives insights into the technology behind Instagram's user experience and machine learning models.</li></ul>

What Happens Behind the Scenes Every Time You Scroll Instagram

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