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aientity · one source so far

coreml

for edge AI engineers

Steadygithub
Signal score
15
Live items
1
Trajectory
Steady
7-day est. ~34

Why this scored 15

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 penalty4.1 / 30

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

Composite15.3

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

~34

range 047

14-day

~35

range 051

30-day

~35

range 057

Signal history

7-day window (free)
451

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
    33

    Laya on Mac M4 CoreML Offline

    Laya runs offline on Mac M4 using CoreML, enabling local inference without cloud. · for mobile AI engineers

    hackernewsSteady 3 · layaai3d ago
  2. 2
    13

    laya-coreml — Local Laya typed decisions on Apple Core ML and Neural Engine. Validated ports, ~5 ms short decisions on M3 Max, reproducible

    laya-coreml achieves ~5 ms decisions on M3 Max via Apple Neural Engine for fast local inference. · for edge AI engineers

    githubSteadyai5 saturated2d ago