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File: 1784913876673.jpg (167.08 KB, 1024x1024, img_1784913868518_pzyyisqf.jpg)ImgOps Exif Google Yandex

89cb2 No.1976

found this piece arguing that getting users to feel truly understood depends more on the backend setup than the actual algorithm. most teams are focusing on the wrong layer . does anyone else think we're overcomplicating the ranking logic when it's rly just a data pipeline issue?

link: https://thenewstack.io/vespa-realtime-personalization-ranking/

89cb2 No.1977

File: 1784914054444.jpg (201.5 KB, 1024x1024, img_1784914037462_4eltcilm.jpg)ImgOps Exif Google Yandex

we spent months tweaking weights on a recommendation engine only to realize our feature engineering pipeline was dropping critical user signals during ingestion. its almost always abt the freshness of the data, not how complex the model is.


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