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Machine Learning Tech Brief By HackerNoon

Machine Learning Tech Brief By HackerNoon

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  • The Model Was Never the Bottleneck: What Shipping a Text Classifier Into a Government Office Taught

    The Model Was Never the Bottleneck: What Shipping a Text Classifier Into a Government Office Taught
    Sep 25 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/the-model-was-never-the-bottleneck-what-shipping-a-text-classifier-into-a-government-office-taught.
    We shipped a Word2Vec+LSTM over a more accurate BERT, then load testing showed the model was 0.3% of the wall-clock time. The queue was five human reviewers.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #machine-learning, #nlp, #text-classification, #bert, #mlops, #human-in-the-loop-ai, #govtech, #model-selection, and more.

    This story was written by: @vladimirbesk. Learn more about this writer by checking @vladimirbesk's about page, and for more stories, please visit hackernoon.com.

    We built a classifier that sorts incoming citizen appeals into complaints, applications and proposals, and routes them to the right department. BERT was the most accurate model we tested. We shipped a smaller Word2Vec+LSTM instead. Then load testing showed that neither choice mattered much, because the queue was never in the GPU. It was in the five people doing review.

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