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aientity · one source so far

nanobind

for ml engineers

Steadystackoverflow
Signal score
18
Live items
1
Trajectory
↓ Cooling
7-day est. ~10

Why this scored 18

every term, weighted
Velocity+0.0 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+11.6 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+7.8 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty−0.9 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite18.5

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Outlook

low confidence · estimate, not a guarantee

7-day

~10

range 0–22

14-day

~0

range 0–14

30-day

~0

range 0–19

Signal history

7-day window (free)
1073

projected trajectory (estimate, not a guarantee)

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.

  1. 1
    18

    JAX FFI handler does not find my CUDA function exported with nanobind

    JAX FFI cannot locate CUDA functions exported via nanobind, blocking GPU acceleration. · for ml engineers

    stackoverflowSteadyai3d ago