Deciding with Jev AI

Hassan El Mghari's post on X, curated on eChai

  • Triage and classification

    Curated from X →

    Hassan again, on a larger set: 1,018 AI papers summarised by DeepSeek V4 Flash and then filed into 24 topics by Jev for eight cents in total, at 256 ms median per paper. The result is live at 1kpapers.com.

    Hassan El Mghari Hassan El Mghari

    I used Jev to classify 1,018 AI research papers.

    The result: $0.08 total cost and 256ms median end-to-end latency per paper.

    The pipeline was:

    1. Summarize each paper with DeepSeek V4 Flash
    2. Send the title + summary + 24 possible topics to Jev
    3. Use Jev to classify each paper
    4. Visualize everything on http://1kpapers.com

    The summaries cost $3.99 on @togethercompute. The classifications cost $0.08 on @typesafeai.

    So for just over $4 of inference, I ended up with a pretty useful way to explore the top AI research papers from the past year.

    I think this is where things are heading: different models for different parts of the workflow, instead of using one model for everything.

    I’m running evals on the Jev classifications before replacing the current ones, but the site is already live:

    1kpapers.com 1kpapers
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